January 1, 2023

15 min read

New Human Metabolism Research Upends Conventional Wisdom about How We Burn Calories

Metabolism studies reveal surprising insights into how we burn calories—and how cooperative food production helped Homo sapiens flourish

By Herman Pontzer

Art concept of researchers examining a human stomach.

Eva Vázquez

It was my daughter Clara's seventh birthday party, a scene at once familiar and bizarre. The celebration was an American take on a classic script: a shared meal of pizza and picnic food, a few close COVID-compliant friends and family, a beaming kid blowing out candles on a heavily iced cake. With roughly 380,000 boys and girls around the world turning seven each day, it was a ritual no doubt repeated by many, the world's most prolific primate singing “Happy Birthday” in an unbroken global chorus.

Such a wholesome setting seems an unlikely place for rampant rule breaking. But as an evolutionary anthropologist, I can't help but notice the blatant disregard our species shows for the natural order. Nearly every aspect of our modern lives marks a cheerfully outrageous departure from the laws that govern every other species on the planet, and this birthday party was no exception. Aside from the fresh veggies left wilting in the sun, none of the food was recognizable as a product of nature. The cake was a heat-treated amalgam of pulverized grass seed, chicken eggs, cow milk and extracted beet sugar. The raw materials for the snacks and drinks would take a forensic chemist years to reconstruct. It was a calorie bonanza that animals foraging in the wild could only dream about, and we were giving it away to people who didn't even share our genes. All this to celebrate some obscure astronomical alignment, the moment our planet swept through the same position relative to its star as on the day my daughter was born. At seven years old, most mammals are grandparents if they're lucky enough to be alive. Clara was still a kid, dependent on us for food and shelter and years away from independence.

Humans weren't always such scofflaws. We come from a good Family. The living apes, our closest relatives, are well-behaved primates, eating fruit and leaves straight from the tree and nibbling on the occasional meal of insects or small game. Like every other mammal, apes learn early to fend for themselves, foraging on their own as soon as they're weaned, and they know better than to give their hard-earned food away. Fossils from deep in the human lineage, the first four million years after we broke from the other apes, indicate our early ancestors played by the same ecological rules.

Around 2.5 million years ago things took an unlikely turn. Early populations of the genus Homo stumbled onto a new way of making a living, something unprecedented in the history of life. Instead of pursuing a career as a plant eater, carnivore or generalist, they tried a strange, dual strategy: some would hunt, others would gather, and they'd share whatever they acquired. This cooperative approach placed a premium on intelligence, and over millennia brain size began to increase. Our Paleolithic ancestors learned to knap delicate blades from round stone cobbles, hunt large game and cook their food. They built hearths and homes and began changing the landscape, developing an ecological mastery that led eventually to farming.

These evolutionary shifts reverberate today. The cooperative foraging that pushed our hunting, gathering and farming ancestors to flout long-established ecological rules didn't just change the foods we eat. It altered fundamental aspects of our biology, including our metabolism. The same unlikely series of events that gave us birthday cake has also shaped the way we eat it—and how we use the calories.

For all the talk about metabolism in the exercise and dieting worlds, you would think the science was settled. In reality, we've been embarrassingly short on hard data about the calories we burn each day and how we evolved to obtain them. But recently my colleagues and I have made important strides in understanding how our bodies use energy. Our findings have overturned much of the received wisdom about the ways human energy requirements change over the course of a lifetime. And, as we've discovered in a parallel effort, our energy needs are deeply intertwined with the evolution of our food-production strategies: foraging and farming. Together these studies provide the clearest picture yet of the inner workings of the human engine—and how our strategy for earning, burning and sharing calories underpins our extraordinary success as a species.

Energy Budgets

Our bodies are wonders of coordinated chaos. Every second of every day, each of your 37 trillion cells is hard at work, pulling in nutrients, building new proteins and doing the myriad other tasks that keep you alive. All of this work takes energy. Our metabolism is the energy we expend (or the calories we burn) each day. That energy comes from the food we eat, and so our metabolism also sets our energy requirements. Calories in, calories out.

Evolutionary biologists often think about metabolism as an organism's energy budget. Life's essential tasks, including growth, reproduction and bodily maintenance, require energy. And every organism must balance its books.

Humans are a striking example of this evolutionary bookkeeping in action. The traits that distinguish us from the other apes, including our huge brains, big babies and long lives, all require a lot of energy. We pay for some of these costs by spending less on our digestive system, having evolved a shorter intestinal tract and smaller liver. But we have also increased our metabolic rate and the size of our energy budget. For our body size, humans consume and burn more calories each day than any of the other apes. Our cells have evolved to work harder.

The work our bodies do changes as we age, the activities of our cells waxing and waning in a choreographed dance from growth to adulthood to senescence. Tracking those changes through our metabolism could provide a better understanding of the work our cells do at each age as well as our changing calorie needs. But a clear audit of our metabolism over the human life span has been hard to obtain.

It's obvious that adults need more calories than infants—bigger people have more cells doing more work, so they burn more energy. We also know that elderly people tend to eat less, although that's often accompanied by a loss of body weight, particularly muscle mass. But if we want to know how active our cells are and whether metabolism gets faster or slower as we grow up and grow old, we need to separate the effects of age and size, which is not easy. You need a large sample with people of all ages, measured with the same methods. Ideally, you'd want measures of total daily energy expenditure, a full tally of the calories used each day.

Researchers have been measuring metabolic rates at rest for more than a century, with some evidence for faster metabolism in children and slower metabolism among the elderly. Yet resting metabolism accounts for only 60 percent or so of the calories we burn over 24 hours and doesn't include the energy we spend on exercise and other physical activity. Online calorie calculators purport to include activity costs, but they're really just a guess based on your self-reported weight and physical activity. In the absence of solid evidence, a kind of folk wisdom has developed, cheered on and cultivated by charismatic hucksters selling metabolic boosters and other snake oil. We're often told our metabolism speeds up at puberty and slows down in middle age, particularly with menopause, and that men have faster metabolisms than women. None of these claims is based on real science.

One chart plots total daily energy use against fat-free body mass; another plots relative daily energy use against age.

A Metabolic Database

My colleagues and I have begun to fill that gap in scientific understanding. In 2014 John Speakman, a researcher in metabolism with laboratories at the University of Aberdeen in Scotland and the Chinese Academy of Sciences in Shenzhen, organized an international effort to develop a large metabolic database. Crucially, this database would focus on total daily energy expenditure measured using the doubly labeled water method, an isotope-tracking technique that measures the carbon dioxide produced by the body (and thus the calories burned) over one to two weeks. Doubly labeled water is the gold standard for measuring daily energy expenditures, but it's costly, and you need a specialized lab for the isotope analyses. So although the technique has been around for decades, studies are typically small. Led by Speakman, my lab joined a dozen others around the world in pooling decades of data. We ended up with more than 6,400 measurements of people ranging from babies just eight days old to men and women in their 90s.

In 2021, after years of collaborative effort, we published the first comprehensive study investigating the effects of age and body size on daily energy expenditure. As expected, we found that metabolic rates increase with body size: bigger people burn more calories. In particular, fat-free mass (the muscles and other organs) is the single strongest predictor of daily energy expenditure. This makes good sense. Fat cells aren't as active as those in the liver, brain, or other tissues, and they don't contribute much to your daily expenditure. More important, with the relation between mass and metabolic rate clearly established from thousands of measurements, we could finally test whether metabolism at each age was faster or slower than we'd expect from size.

The results were a revelation, the first clear road map of metabolism over the human life span. We found that, metabolically, babies are born like tiny adults, reflecting their development as part of their mom's energy budget. But metabolism skyrockets over the first year of life, so that by their first birthday children are burning 50 percent more energy than we'd expect for their size. Their cells are far busier than adults' cells, hard at work on growth and development. Earlier studies measuring glucose uptake in the brain during childhood suggest some of this work is neuronal growth and synapse development. Maturation in other systems no doubt contributes as well. Metabolism stays elevated through childhood, slowly decelerating through adolescence to land at adult levels around age 20. Boys decline more slowly than girls, consistent with boys' slower development, but there's no bump at puberty in males or females.

Perhaps the biggest surprise was the stability of our metabolism through middle age. Daily energy expenditures hold remarkably steady from age 20 to 60. No middle age slowdown, no change with menopause. The weight gain so many of us experience in adulthood cannot be blamed on a declining metabolism. As a man in my 40s, I had sort of believed the folk wisdom that metabolism slowed as we aged. My body definitely feels different than it did 10 or 20 years ago. But like hunting some metabolic Sasquatch, when you actually look there's nothing there. Same for the much touted metabolic differences between men and women. Women have lower daily energy expenditures on average, but that is only because women tend to be smaller and carry more of their weight as fat. Compare men and women with the same body weight and body fat percentage, and the metabolic difference disappears.

We did find a decline in metabolism with age, but it doesn't kick in until we hit 60. After 60, metabolism slows by around 7 percent per decade. By the time men and women are in their 90s, their daily expenditures are 20 to 25 percent lower, on average, than those of adults in their 50s. That's after we account for body size and composition. Weight loss with old age, especially diminished muscle mass, compounds the decline in expenditure. As with all age groups, there's a good amount of individual variability. Maintaining a younger, faster metabolism into old age might be a sign of aging well, or perhaps it is even protective against heart disease, dementia and other age-related disease. We can now start to investigate these connections. Guided by our metabolic road map, we have a new world of research ahead of us.

What is already apparent, however, is that a bite of birthday cake does different things for a seven-year-old girl, her middle-aged dad and her elderly grandmother. Clara's bite is likely to be gobbled up by busy cells, fueling development. Mine might go to maintenance, repairing all the little bits of damage accrued through the course of the day. As for Grandma, her aging cells might be slow to use the calories at all, storing them instead as glycogen or fat. Indeed, for any of us, the cake will end up as fat if we eat more calories than we burn.

The road map also highlights a major conundrum of the human condition. Whether they're born into a hunter-gatherer camp, a farming village or an industrial megacity, human youngsters need a lot of help getting food. Other apes learn to forage for themselves by the time they stop nursing, around the age of three or four. Our children are wholly dependent on others for food for years and aren't self-sufficient until their teens. And those least able to fend for themselves have the greatest energy needs. Not only has our species evolved a faster metabolic rate and greater energy demands than other apes, but we must also provision each costly offspring for more than a decade. Where do we get all those calories? Recently my colleagues and I worked out this part of the human energy equation, too.

Costly Kids

The question of calories looms largest in hunter-gatherer and farming communities, where daily life revolves around food production. For most of our species' history, as for most species, there was no other line of work. Every kid knew what they were going to be when they grew up. As late as the mid-1800s, more than half of the American workforce was made up of farmers.

For the past decade I've been working with colleagues to understand the calorie economy in the Hadza community of northern Tanzania. The Hadza are a small population of 1,000 or so, and about half of them maintain a traditional hunting-and-gathering way of life, foraging on the savanna landscape they call home. No population alive today is a perfect model of the past, but groups like the Hadza, who continue these traditions, provide a living example of how these systems work. Men spend most days hunting with bow and arrow or chopping into hollow tree limbs to pillage honey from beehives. Women gather berries and other plant foods or dig for wild tubers in the rocky soil. Hadza camps, small collections of grass houses tucked among the acacia trees, are alive all day with kids being kids, running around, laughing, playing—and waiting for adults to bring them food.

We've measured Hadza energy budgets using doubly labeled water, giving us a clear idea of the calories men and women consume and expend each day. We've also lugged portable respirometry equipment into the bush, a metabolic lab in a briefcase, to measure the energy costs of foraging activities such as walking, climbing, digging tubers and chopping trees. And we've got years of careful observation recording the hours spent each day on different foraging tasks and the amount of food acquired. After more than a decade of work, we've got a complete accounting of the Hadza energy economy: the calories spent to get food, the calories acquired, the proportions shared and consumed.

Tom Kraft of the University of Utah led our team's effort to compare the energy budgets of the Hadza population with similar data from other human groups and from other species of apes. It was a massive project, with researchers poring over old ethnographic accounts of hunter-gatherer and farming groups and combing through ecological studies and doubly labeled water measurements in apes to reconstruct their foraging economies. But when we were finished, what emerged was a new understanding of the energetic foundation for our species' success. We could finally see where all those calories come from, the energy needed to fuel expensive human metabolisms and provision helpless kids.

Clever Cooperators

It turns out humans' unique, cooperative foraging strategy, combined with our clever brains and tools, makes hunting and gathering extremely productive. Even in the harsh, dry savanna of northern Tanzania, Hadza men and women acquire 500 to 1,000 kilocalories of food an hour, on average. Ethnographic records from other groups around the world suggest these rates are typical for hunter-gatherers. Five hours of hunting and gathering can reliably bring in 3,000 to 5,000 kilocalories of food, enough to meet a forager's daily needs and provision the camps' children.

It's the positive feedback engine that propelled the human species to new heights. Hunting and gathering is so productive that it creates an energy surplus. Those extra calories are channeled to offspring, meaning they can take longer to develop, learning skills that make them effective foragers. Reaching adulthood, they'll do just as their parents did, acquiring extra food and plowing those calories into the next generation. Over evolutionary time childhood grows longer as foraging strategies grow more complex. Life spans get extended, too, with natural selection favoring additional years of productive foraging to support children and grandchildren. Grandparents, once rare, become a fixture of the social network.

Apes in the wild are not nearly as productive in gathering food. A forensic accounting of the energy budgets for chimpanzees, gorillas and orangutans shows that males and females get around 200 to 300 kilocalories an hour. It takes them seven hours of foraging just to meet their own needs each day. No wonder they don't share.

Our hyperproductive foraging isn't cheap. People in hunter-gatherer communities expend more than twice as much energy to acquire food as apes in the wild. Surprisingly, human technology and smarts don't make us very energy-efficient. Hadza men and women achieve the same paltry ratio of energy acquired to energy expended that we find in wild apes. Cooperation and culture enable human foragers to be incredibly time-efficient, acquiring lots of calories an hour, but our unique foraging strategies are still energetically demanding. Hunting and gathering is hard work.

Farming isn't any easier, but our analyses found it can be even more productive. When we compared the energy budgets for the Hadza and other hunter-gatherer populations with those of traditional farming groups, we found that farmers typically produce far more calories an hour. The Tsimane community, a population in the Amazonian rain forest of Bolivia, provides a useful point of comparison. The Tsimane get most of their calories from farming, but they also hunt, fish and collect wild plants. With farmed foods as their energy staple, they produce nearly twice as many calories an hour as the Hadza. They're more energy-efficient as well, getting more food from every calorie they spend foraging and farming.

Those extra calories are embodied in the children running around Tsimane villages. More food and faster production mean a lighter workload for mothers because others in the community can more easily share the time and energy costs of caring for kids. As with many subsistence farming communities, Tsimane families tend to be large. Women have an average of nine children over the course of their lives. Compare that with the average fertility rate of six children per mother in the Hadza community, and the impact of that extra energy is inescapable. And it's not just the Tsimane. Farming communities tend to have higher fertility rates than hunter-gatherer communities. Increased fertility is an important reason farming overtook hunting and gathering in the Neolithic age, the time spanning roughly 12,000 to 6,500 years ago. Archaeological sites across Eurasia and the Americas document a rising tide of children and adolescents following the development of agriculture.

Having Our Cake

From this perspective, a kid's birthday party is more than a personal milestone. It's a celebration of our improbable evolutionary story. There's the food, of course. We get the flour and sugar for the cake from our farming ancestors, the fire to bake it from the Paleolithic era. The milk and eggs come from animals that we've completely transformed from species we once hunted, shaped to our will over generations of careful husbandry. And there's the calendar we use to mark our days and measure our years, an invention of agriculturalists who needed to know precisely when to reap and sow. Hunter-gatherers track the seasons and lunar cycles but have little use for accurate annual calendars. There are no birthdays in a Hadza camp.

But the key element of any celebration is the community of friends and relatives, multiple generations gathering to eat and laugh and sing. Our evolved social contract—to hunt, gather and farm collectively—tied us together, gave us our childhood and extended our golden years. Cooperative foraging also helped to fuel the cultural complexity and innovation that make birthdays and other rituals so fantastical and diverse. And at the center of it all is the universal commitment to share.

With eight billion humans on the planet today, one might begin to worry that we've taken things a bit too far. We've learned to turbocharge our energy budgets by tapping into climate-changing fossil fuels and flooding our world with cheap food. Calories are so easy to produce that very few of us spend our days foraging, a first in the history of life. This massive shift has been a boon to our collective creativity, enabling many to spend their lives as artists, doctors, teachers, scientists—a range of careers outside of food production. Having carved out our own strange niche, far removed from the laws that govern the rest of the natural world, we have only ourselves to look to for guidance. With a little luck and a lot of cooperation, we just might secure the human lineage another couple million birthdays. Make a wish.

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Illustration by Philip Lay.

Burn, baby, burn: the new science of metabolism

Losing weight may be tough, but keeping it off, research tells us, is tougher – just not for the reasons you might think

A s the director of the Energy Metabolism Laboratory at the USDA Nutrition Center Tufts University, Massachusetts, Susan Roberts has spent much of the past two decades studying ways to fight the obesity epidemic that continues to plague much of the western world.

But time and again, Roberts and other obesity experts around the globe have found themselves faced with a recurring problem. While getting overweight individuals to commit to shedding pounds is often relatively straightforward in the short term, preventing them from regaining the lost weight is much more challenging.

According to the University of Michigan , about 90% of people who lose significant amounts of weight, whether through diets, structured programmes or even drastic steps such as gastric surgery, ultimately regain just about all of it.

Why is this? Scientists believe that the answer lies in the workings of our metabolism, the complex set of chemical reactions in our cells, which convert the calories we eat into the energy our body requires for breathing, maintaining organ functions, and generally keeping us alive.

When someone begins a new diet, we know that metabolism initially drops – because we are suddenly consuming fewer calories, the body responds by burning them at a slower pace, perhaps an evolutionary response to prevent starvation – but what then happens over the following weeks, months, and years, is less clear.

“Does metabolism continue to go down, more than it should,” asks Roberts, “or does it initially go down, and then bounce back? This is an enormously controversial topic, and one that we’re looking to address.”

Over the next three to four years, we may get some answers. Roberts is co-leading a new study, funded by the National Institutes of Health in the US, which will follow 100 individuals over the course of many months as they first lose and then regain weight, measuring everything from energy expenditure to changes in the blood, brain and muscle physiology, to try to see what happens.

The implications for how we tackle obesity could be enormous. If metabolism drops and continues to stay low during weight loss, it could imply that dieting triggers innate biological changes that eventually compel us to eat more. If it rebounds to normal levels, this suggests that weight regain is due to the recurrence of past bad habits, with social and cultural factors tempting us to go back to overeating.

Scales and a measuring tape

“If someone’s metabolism really drops during weight loss and doesn’t recover, it shows we have to put all of our money on preventing weight gain in the first place,” says Roberts. “Because once it’s happened, you’re doomed. If metabolism rebounds, it means that the lessons about eating less because you’ve now got a smaller body haven’t been learned effectively. So we might need to encourage people who have lost weight to see psychologists to work on habit formation. These are such different conclusions that we really need to get it right.”

This is just one of many ways in which our understanding of metabolism is evolving. In recent years, many of the traditional assumptions, which had long been accepted as truth – that exercise can ramp up metabolism, that metabolism follows a steady decline from your 20s onwards – have been challenged. For scientists at the forefront of this field, these answers could go on to change many aspects of public health.

The age myth

In mid-August, a paper emerged in the journal Science that appeared to challenge one of metabolism’s universal truths. For decades, scientists have accepted that metabolism begins to slow down in early adulthood, initiating a steady descent that continues through middle age and later life, inevitably resulting in the phenomenon known as “middle-aged spread”.

But this may not actually be true. Over the past few years, Herman Pontzer, an associate professor of evolutionary anthropology at Duke University, North Carolina, and more than 80 other scientists have compiled data from more than 6,400 individuals – from eight days to 95 years old – that shows something very different.

It appears that between the ages of 20 and 60 our metabolism stays almost completely stable, even during major hormonal shifts such as pregnancy and menopause. Based on the new data, a woman of 50 will burn calories just as effectively as a woman of 20.

Instead, there are just two major life shifts in our metabolism, with the first occurring between one and 15 months old. The Science study showed that infants burn energy at such a rate to support their development that their metabolism at one year old is more than 50% higher than an adult’s. The second transition takes place at about the age of 60, when our metabolism begins to drop again, continuing to do so until we die.

“For much of your life, your body’s kind of chugging along on a trajectory for how busy your cells are going to be,” says Pontzer. “Your cells are following a roadmap, and it’s very hard to bump them off that roadmap.”

So what does this mean? Much of the ageing process, and the commonly observed middle-aged weight gain, is not because of declining metabolism but genetics, hormone changes and lifestyle factors such as stress, sleep, smoking and, perhaps most crucially, diet. Pontzer argues that if the calories we burn stay largely the same throughout life, then the real source of obesity has to be the amount we’re eating, and particularly the heavy consumption of highly processed foods.

Over the years, one of the main marketing tools used to promote different exercise regimes and wellness supplements has been claims that they boost your metabolism. Pontzer says that this is mostly nonsense.

Studies that have compared indigenous tribes of hunter-gatherers in northern Tanzania – who walk an average of 19,000 steps a day – with sedentary populations in Europe and the US have found that their total number of calories burned is largely the same. Other studies looking at whether metabolism changes if you put a mouse on an exercise regime , or comparing non-human primates living in a zoo or the rainforest, have found a similar pattern.

Some scientists believe that this is because the body is programmed to keep its average daily energy expenditure within a defined range. While there are day-to-day fluctuations, the body still burns the same number of calories overall, but it adjusts how they are used, depending on our lifestyle. To explain the theory, Pontzer gives the example of a keen amateur cyclist who takes part in 100km bike rides at weekends. Overall, that individual still won’t burn more calories on average than a sedentary person, but their average energy expenditure will be skewed towards providing fuel for the muscles. The sedentary person will burn a similar number of calories, but on background bodily functions which we do not notice, including less healthy outlets such as producing inflammation and stress.

A keen cyclist may not burn as many calories as they think.

“I think there is a deep evolutionary reason to this,” says Pontzer. “In the industrialised world, burning more energy than you eat would be great, but in the wild, that’s a bad strategy. The reason we’re gaining weight is not only because there’s more food available than we have evolved to expect, but because they’re modern, industrialised foods, designed to be overeaten. So you’ve got this perfect storm for making people obese.”

But these new findings on metabolism are not only changing our understanding of how to tackle obesity: they have ramifications across the world of medicine. Given that metabolism slows markedly beyond the age of 60, doctors now need to know whether older adults should receive slightly different medicinal doses, while the research will prompt questions about the connection between a slower metabolism and the onset of chronic disease in older adults.

Individual differences

While the Science paper illustrated general population trends for metabolism across the age spectrum, we still know relatively little about individual differences, and what they might represent. Do babies with a particularly rapid metabolism develop quicker and in a better way? And do variations in the environment in which they grow up, such as social deprivation, mean that they have a slightly slower metabolism than their peers?

This is all speculation for now, but scientists know that metabolism can still vary significantly from one person to another, even after you account for factors such as size and body composition. We still don’t know exactly why this variation occurs, but there are thought to be a whole range of factors, from genetics to organ sizes, the immune system, and even the species of bacteria in their gut microbiome.

Even with the latest digital technologies, it is very difficult for people to track their own metabolic rate. Pontzer says this is because none of the current apps on the market can account for individual differences in resting metabolic rate.

Herman Pontzer

However, one of the key questions is whether these variations can confer susceptibility to disease, especially illnesses linked to metabolic dysfunction such as cancer and type 2 diabetes. “There are so many metabolic health conditions,” says Eric Ravussin, director of the Nutrition Obesity Research Center at the Pennington Biomedical Research Centre in Baton Rouge, Louisiana. “These are influenced by your diet and your weight. As you gain weight, you’re more likely to have hypertension, you’re more likely to have inflammation.”

A whole variety of startups around the world are now investigating ways of using our knowledge of metabolism to assist with developing personalised treatment programmes. Because our gut microbes play such a crucial role in energy metabolism, by breaking down the food we eat, dysfunctional imbalances in the gut microbiome have been linked to the development of a number of metabolic illnesses.

Oslo-based Bio-Me is profiling the gut microbiomes of patients with type 2 diabetes, coeliac disease, inflammatory bowel disease and certain types of cancer, using DNA sequencing of faecal samples to identify the exact species of bacteria present in their intestines. It can then compare that information with existing microbiome data on that group of patients, available in population biobanks, and use this to predict dietary regimes or treatment interventions that could be particularly beneficial for those individuals.

Bio-Me CEO Morten Isaksen says that this can be used to predict whether common medications, such as the diabetes drug metformin, will work well for that particular patient. “It was discovered that metformin only works because the gut bacteria change the medicine into its active form,” says Isaksen. “So if you don’t have the right bacteria in the gut, the medicine won’t work. So knowing which bacteria are present is really important for identifying the right treatments.”

Because dysfunctional cell metabolism is central to cancer, determining how tumours form, as well as how fast they grow and spread, indications of metabolic dysfunction could be used for early diagnosis of certain cancers. The Stockholm-based biotech firm Elypta is trialling a system that detects small molecules, known as metabolites, which are produced by kidney cancer cells. In future, this could be used as part of a liquid biopsy for the disease.

“Once cancer cells begin to proliferate, what really changes is the metabolic requirements, compared with healthy cells,” says Francesco Gatto, co-founder of Elypta. “So we think we can use this layer of information from metabolism, to help identify multiple types of cancer early in a non-invasive manner.”

Pontzer is now planning to follow up the Science study by delving further into the extremes of metabolism, both in the young and the old. “We’re going to try to look at that variability both in very young children and the over-60s,” he says. “We want to try to understand whether in people whose metabolism is changing more or less, or faster or slower, does that predict anything about their health or how their bodies develop? Or maybe it’s not related at all. So we’re going to try to find out these things.”

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Why Everything You Thought About Middle-Aged Metabolism May Be Wrong

A new, large-scale study upends traditional thinking on midlife weight gain and more.

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We've all heard the conventional wisdom on metabolism, and it goes something like this: During your 20s your metabolism is firing on all cylinders, zapping enough calories to let you scarf down second helpings and extra slices of late-night pizza with few consequences on the scale. Then midlife and/or menopause come along, jamming up the works on your body's energy-burning engine and leading to middle-aged spread.

While all of this may sound all-too-familiar, a major new study has upended the story about how our metabolism changes as we grow older. That middle-aged slowdown? The idea that calorie burning crests in your 20s — or slumps with menopause? Not true, this new research says. Instead, its evidence shows that age 60 is when metabolism starts to dip — far later than previously believed.

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“If you're gaining weight it's easy to say, ‘Oh, that's my metabolism.’ It's almost like a scapegoat. Now that we know it's not metabolism, we can focus on some of those other factors.”

"This is an incredibly important study for people who study metabolism across the lifespan,” says Anthony Ferrante Jr., M.D., a professor of medicine and chief of preventive medicine and nutrition at Columbia University Irving Medical Center. “These data will help frame how people approach metabolic health going forward."

What makes the study so groundbreaking is its scale: It analyzed things like energy expenditure from more than 6,400 people across 29 countries — from 1-week-old newborns to people in their 90s. To capture such information, researchers used something called the “doubly labeled water” method to determine how many calories the subjects burned each day. Considered the scientific gold standard, it involves having people drink water that has been chemically modified to allow scientists to measure how quickly molecules are flushed through the digestive system. The method has been around since the 1980s, but it's complicated and expensive, and as a result most previous studies — unlike this new one — have included only a small number of participants.

What's more, the global team of researchers measured not only how much energy is used to perform basic functions (breathing, healing wounds, pumping blood through your veins), but also the energy used for daily activities like jogging, brushing your teeth — even thinking. To further zoom in on the effects of age and gender, they adjusted the data to account for body size (a smaller person naturally burns fewer calories than a bigger person) and body composition (muscle tissue burns more calories than fat).

What they discovered? In a nutshell:

  • There are four metabolic life stages, but they don't necessarily line up with big milestones like puberty, pregnancy or menopause.
  • Metabolism peaks much earlier — and starts slowing down much later, around age 60 — than formerly believed.
  • Controlling for body fat and muscle percentage, women's metabolisms were essentially the same as men's.
  • Within the larger population-based trends, individual metabolic rates varied significantly: Some subjects had rates 25 percent above average for their age, while others had rates 25 percent below average.

But the complete story is full of other interesting details. When infants are first born, for instance, their metabolism mirrors that of their mothers. Then, about a month after they enter the world, their metabolic rate begins to rev up — a lot. Adjusting for weight, a 1-year-old burns calories about 50 percent faster than an adult. In fact, toddlerhood — not the teen years or early adulthood — is when human metabolism peaks. After the initial acceleration, your metabolic rate slides about 3 percent every year until age 20, when it plateaus. From there metabolism holds steady until that magic (average) age of 60, and then declines at a rate of .7 percent a year indefinitely.

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That was a surprise to Herman Pontzer, the study's lead author and associate professor of evolutionary anthropology at Duke University. “I'm in my 40s, so I expected to see some evidence to back up my subjective experience that my metabolism is slowing down. It feels that way to me! But it's not really what's happening,” he says.

So what's really behind middle-aged weight gain?

Of course, that doesn't mean that the dreaded middle-aged spread is all in our heads, he notes. (Research shows the average U.S. adult gains one to two pounds a year from early to middle adulthood.) It just means there are contributing factors other than metabolism. “Your stress level, your schedule, your hormone levels, your energy levels are different in your 40s or 50s compared to your 20s,” says Pontzer, who is also the author of  Burn , a new book about the science of metabolism. “If you're gaining weight it's easy to say, ‘Oh, that's my metabolism.’ It's almost like a scapegoat. Now that we know it's not metabolism, we can focus on some of those other factors.”

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Research has also shown that metabolism and weight aren't always as closely linked as you imagine. “It's not about how many calories you burn, it's about whether you're burning more than you're eating,” says Pontzer. “Just because you have a high metabolism doesn't mean you're better at matching your intake to your output."

How findings could affect drug dosing, cancer treatment

Experts say these new understandings on metabolism will have implications beyond just weight control. For example, there may be applications for drug dosing as it relates to the rate at which your body breaks down medication. It might also change the way we treat diseases such as cancer, says Pontzer. “Tumor cells metabolize energy as they grow and divide,” he says. “So cancer may progress differently in younger people with faster metabolisms compared to older people with slower metabolisms."

The study also sheds new light on the aging process, specifically how cell activity changes as you grow older. “There's an age-related decline that happens across the body's systems,” says Pontzer. “One of the exciting things from the study is now we have a map of how this change is happening at the metabolic level — because metabolism is a reflection of how busy your body is.”

If scientists can develop a better understanding of what's changing in cells as they age, it could provide new insight into how to reduce disease vulnerability in older adults, says Rozalyn Anderson, professor at the University of Wisconsin School of Medicine and Public Health Anderson, who studies the biology of aging.

"Around age 60 is when we start to see the emergence and increased risk for age-related conditions like cancer, cardiovascular disease or neurodegenerative diseases,” she says. “When I saw this data, I was immediately struck by the fact that there's also an intrinsic change in innate metabolism that begins at the same time."

Future research could drill down past the first layer of population data, perhaps categorizing study subjects based on their individual metabolisms and seeing if there are differences in their disease outcomes. “How much does your individual metabolism before age 60 dictate the pace of change after age 60?” asks Anderson. “As metabolism slopes downward in older adulthood, is a steeper rate of decline associated with a higher incidence of disease?"

Ferrante says the research provides solid ground for scientists to launch numerous other studies. “This is an incredibly important observational study, but it doesn't get at the whys,” he says. “Now we can begin to answer those questions."

Jennifer Rainey Marquez is an Atlanta-based freelance journalist specializing in health and wellness. Her writing has appeared in Atlanta magazine, Garden & Gun and Women's Health , among other publications. 

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What We Think We Know About Metabolism May Be Wrong

A new study challenges assumptions about energy expenditure by people, including the idea that metabolism slows at middle age.

new research on metabolism

By Gina Kolata

Everyone knows conventional wisdom about metabolism: People put pounds on year after year from their 20s onward because their metabolisms slow down, especially around middle age. Women have slower metabolisms than men. That’s why they have a harder time controlling their weight. Menopause only makes things worse, slowing women’s metabolisms even more.

All wrong, according to a paper published Thursday in Science . Using data from nearly 6,500 people, ranging in age from 8 days to 95 years, researchers discovered that there are four distinct periods of life, as far as metabolism goes. They also found that there are no real differences between the metabolic rates of men and women after controlling for other factors.

The findings from the research are likely to reshape the science of human physiology and could also have implications for some medical practices, like determining appropriate drug doses for children and older people.

“It will be in textbooks,” predicted Leanne Redman, an energy balance physiologist at Pennington Biomedical Research Institute in Baton Rouge, La., who also called it “a pivotal paper.”

Rozalyn Anderson, a professor of medicine at the University of Wisconsin-Madison, who studies aging, wrote a perspective accompanying the paper. In an interview, she said she was “blown away” by its findings. “We will have to revise some of our ideas,” she added.

But the findings’ implications for public health, diet and nutrition are limited for the moment because the study gives “a 30,000-foot view of energy metabolism,” said Dr. Samuel Klein, who was not involved in the study and is director of the Center for Human Nutrition at the Washington University School of Medicine in St. Louis. He added, “I don’t think you can make any new clinical statements” for an individual. When it comes to weight gain, he says, the issue is the same as it has always been: People are eating more calories than they are burning.

Metabolic research is expensive, and so most published studies have had very few participants. But the new study’s principal investigator, Herman Pontzer, an evolutionary anthropologist at Duke University, said that the project’s participating researchers agreed to share their data. There are more than 80 co-authors on the study. By combining efforts from a half dozen labs collected over 40 years, they had sufficient information to ask general questions about changes in metabolism over a lifetime.

All of the research centers involved in the project were studying metabolic rates with a method considered the gold standard — doubly labeled water. It involves measuring calories burned by tracking the amount of carbon dioxide a person exhales during daily activities.

The investigators also had participants’ heights and weights and percent body fat, which allowed them to look at fundamental metabolic rates. A smaller person will burn fewer calories than a bigger person, of course, but correcting for size and percent fat, the group asked: Were their metabolisms different?

“It was really clear that we didn’t have a good handle on how body size affects metabolism or how aging affects metabolism,” Dr. Pontzer said. “These are basic fundamental things you’d think would have been answered 100 years ago.”

Central to their findings was that metabolism differs for all people across four distinct stages of life.

There’s infancy, up until age 1, when calorie burning is at its peak, accelerating until it is 50 percent above the adult rate.

Then, from age 1 to about age 20, metabolism gradually slows by about 3 percent a year.

From age 20 to 60, it holds steady.

And, after age 60, it declines by about 0.7 percent a year.

Once the researchers controlled for body size and the amount of muscle people have, they also found no differences between men and women.

As might be expected, while the metabolic rate patterns hold for the population, individuals vary. Some have metabolic rates 25 percent below the average for their age and others have rates 25 percent higher than expected. But these outliers do not change the general pattern, reflected in graphs showing trajectory of metabolic rates over the years.

The four periods of metabolic life depicted in the new paper show “there isn’t a constant rate of energy expenditure per pound,” Dr. Redman noted. The rate depends on age. That runs counter to the longstanding assumptions she and others in nutrition science held.

The trajectories of metabolism over the course of a lifetime and the individuals who are outliers will open a number of research questions. For instance, what are the characteristics of people whose metabolisms are higher or lower than expected, and is there a relationship with obesity?

One of the findings that most surprised Dr. Pontzer was the metabolism of infants. He expected, for example, that a newborn infant would have a sky-high metabolic rate. After all, a general rule in biology is that smaller animals burn calories faster than larger ones.

Instead, Dr. Pontzer said, for the first month of life, babies have the same metabolic rate as their mothers. But shortly after a baby is born, he said, “something kicks in and the metabolic rate takes off.”

The group also expected the metabolism of adults to start slowing when they were in their 40s or, for women, with the onset of menopause.

But, Dr. Pontzer said, “we just didn’t see that.”

The metabolic slowing that starts around age 60 results in a 20 percent decline in the metabolic rate by age 95.

Dr. Klein said that although people gain on average more than a pound and a half a year during adulthood, they can no longer attribute it to slowing metabolisms.

Energy requirements of the heart, liver, kidney and brain account for 65 percent of the resting metabolic rate although they constitute only 5 percent of body weight, Dr. Klein said. A slower metabolism after age 60, he added, may mean that crucial organs are functioning less well as people age. It might be one reason that chronic diseases tend to occur most often in older people.

Even college students might see the effects of the metabolic shift around age 20, Dr. Klein said. “When they finish college they are burning fewer calories than when they started.”

And around age 60, no matter how young people look, they are changing in a fundamental way.

“There is a myth of retaining youth,” Dr. Anderson said. “That’s not what the biology says. In and around age 60, things start to change.”

“There is a time point when things are no longer as they used to be.”

Gina Kolata writes about science and medicine. She has twice been a Pulitzer Prize finalist and is the author of six books, including “Mercies in Disguise: A Story of Hope, a Family's Genetic Destiny, and The Science That Saved Them.” More about Gina Kolata

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Metabolism in adulthood does not slow as commonly believed, study finds

Blaming those extra pounds on a slowing metabolism as you age? Not so fast.

A new international study counters the common belief that our metabolism inevitably declines during our adult lives. Well, not until we’re in our 60s, anyway.

Researchers found that metabolism peaks around age 1, when babies burn calories 50 percent faster than adults, and then gradually declines roughly 3 percent a year until around age 20. From there, metabolism plateaus until about age 60, when it starts to slowly decline again, by less than 1 percent annually, according to findings published Thursday in the journal Science .

To tease out the specific impact of age on metabolism, the researchers adjusted for factors such as body size (bigger bodies burn more calories overall than smaller ones) and fat-free muscle mass (muscles burn more calories than fat).

“Metabolic rate is really stable all through adult life, 20 to 60 years old,” said study author Herman Pontzer, an associate professor of evolutionary anthropology at Duke University and author of “Burn,” a new book about metabolism. “There's no effect of menopause that we can see, for example. And you know, people will say, 'Well when I hit 30 years old, my metabolism fell apart.' We don't see any evidence for that, actually.”

Pontzer and colleagues studied a database of more than 6,400 people, ages 8 days to 95 years, from 29 countries worldwide who had participated in “doubly labeled water” tests. With this method, individuals drink water in which some of the hydrogen and oxygen have been replaced with isotopes of these elements that can be traced in urine samples.

“By calculating how much hydrogen you lose per day, and how much oxygen you lose per day, we can calculate how much carbon dioxide your body produces every day,” Pontzer explained. “And that's a very precise measurement of how many calories you burn every day, because you can't burn calories without making carbon dioxide.”

The researchers analyzed average total daily energy expenditures, which include the calories we burn doing everything from breathing and digesting food to thinking and moving our bodies.

“There's nothing sort of more fundamental and basic than how our bodies burn energy , because that represents how all our cells are busy all day doing their various tasks, and we didn't have a good sense of how that changes over the course of a lifespan,” Pontzer said. “You need really big data sets to be able to answer that question. And this was the first time that we had the ability to do this with a really big data set that would allow us to pull apart the effects of body size and age and gender and all these things on our energy expenditures over the day.”

Take, for instance, the finding that metabolic rate declines in seniors, which might have been expected.

"People thought, 'Well, maybe it's because you're less active, or maybe it's because people tend to lose muscle mass as they get into their 60s, 70s and older,'" he said. "But we can correct for all those things. We can say, 'No, no, no, it's more than that.' It's that our cells are actually changing."

Results did not show that metabolic rates spiked upward during the teen years or pregnancy, as commonly thought, or that there were specific differences between men and women after accounting for body size and composition.

What factors cause weight gain?

Registered dietitian Colleen Tewksbury, a senior research investigator at the University of Pennsylvania and a spokesperson for the Academy of Nutrition and Dietetics, said the new study is surprising.

“Historical convention was really that with different life cycle changes — of puberty, of pregnancy, of menopause — we thought that there was some shift in metabolism and it impacted nutrition status and how we approached things from a nutrition standpoint,” she said. “This high-level rigorous assessment does not show that.”

It's not as if the weight gain is occurring because you don't ‘burn the same calories’ anymore.

But if changing metabolism is not playing a role in weight gain at certain points in adult life, there could be other contributing factors, she said.

“There are lots of things that impact weight status and also someone's nutritional status,” Tewksbury said. “It's not as simple as just one food or one lifestyle change or one change from a biological standpoint. It's more likely a much more complex web of lots of different changes happening at once. So that could be changes to food intake. It could be changes in activity levels. It can be where they're living, what they have access to, what are their sleep changes.”

Steven Malin, an associate professor of kinesiology and health and director of the Rutgers Applied Metabolism and Physiology Laboratory, called the study results “illuminating on something that we thought we know a lot about and realize that there's more to be discovered.”

Malin said the findings, for instance, contradict the belief that adults experience a decline in metabolism as they move from their 20s into their 30s and that this may be contributing to the obesity epidemic.

“It's not as if the weight gain is occurring because you don't ‘burn the same calories’ anymore,” he said.

Pontzer said the findings in early life highlight the critical importance of infant nutrition meeting the increasing energy demands of growing babies.

In addition, he said, the study results could have implications for how much medicine people need at various ages, when they could be metabolizing drugs differently.

In a commentary published with the new study, Timothy Rhoads and Rozalyn Anderson, who work in geriatrics at the University of Wisconsin, said the findings also may have implications for the study of age-related diseases.

“The decline from age 60 is thought to reflect a change in tissue-specific metabolism, the energy expended on maintenance,” they wrote. “It cannot be a coincidence that the increase in incidence of noncommunicable diseases and disorders begins in this same time frame.”

NBC News contributor Jacqueline Stenson is a health and fitness journalist who has written for the Los Angeles Times, Reuters, Health, Self and Shape, among others. She also teaches at the UCLA Extension Writers' Program.

Metabolism Changes With Age, Just Not When You Might Think

Researchers have precisely measured life’s metabolic highs and lows, from birth to old age, and the findings might surprise you.

Science shows that, pound-for-pound, a one-year-old burns calories 50% faster than an adult. Canva.com

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DURHAM, N.C. -- Most of us remember a time when we could eat anything we wanted and not gain weight. But a new study suggests your metabolism -- the rate at which you burn calories -- actually peaks much earlier in life, and starts its inevitable decline later than you might guess.

The findings  were published Aug. 12 in the journal Science.

“There are lots of physiological changes that come with growing up and getting older,” said study co-author Herman Pontzer , associate professor of evolutionary anthropology at Duke University. “Think puberty, menopause, other phases of life. What's weird is that the timing of our ‘metabolic life stages’ doesn't seem to match those typical milestones.”

Pontzer and an international team of scientists analyzed the average calories burned by more than 6,600 people ranging from one week old to age 95 as they went about their daily lives in 29 countries worldwide.

Previously, most large-scale studies measured how much energy the body uses to perform basic vital functions such as breathing, digesting, pumping blood -- in other words, the calories you need just to stay alive. But that amounts to only 50% to 70% of the calories we burn each day. It doesn’t take into account the energy we spend doing everything else: washing the dishes, walking the dog, breaking a sweat at the gym, even just thinking or fidgeting.

To come up with a number for total daily energy expenditure, the researchers relied on the “doubly labeled water” method. It’s a urine test that involves having a person drink water in which the hydrogen and oxygen in the water molecules have been replaced with naturally occurring “heavy” forms, and then measuring how quickly they’re flushed out.

Scientists have used the technique -- considered the gold standard for measuring daily energy expenditure during normal daily life, outside of the lab -- to measure energy expenditure in humans since the 1980s, but studies have been limited in size and scope due to cost. So multiple labs decided to share their data and gather their measurements in a single database , to see if they could tease out truths that weren’t revealed or were only hinted at in previous work.

Pooling and analyzing energy expenditures across the entire lifespan revealed some surprises. Some people think of their teens and 20s as the age when their calorie-burning potential hits its peak. But the researchers found that, pound for pound, infants had the highest metabolic rates of all.

Energy needs shoot up during the first 12 months of life, such that by their first birthday, a one-year-old burns calories 50% faster for their body size than an adult.

And that’s not just because, in their first year, infants are busy tripling their birth weight. “Of course they're growing, but even once you control for that, their energy expenditures are rocketing up higher than you'd expect for their body size and composition,” said Pontzer, author of the book, “ Burn ,” on the science of metabolism.

An infant’s gas-guzzling metabolism may partly explain why children who don’t get enough to eat during this developmental window are less likely to survive and grow up to be healthy adults.

“Something is happening inside a baby’s cells to make them more active, and we don't know what those processes are yet,” Pontzer said.

After this initial surge in infancy, the data show that metabolism slows by about 3% each year until we reach our 20s, when it levels off into a new normal.

Despite the teen years being a time of growth spurts, the researchers didn’t see any uptick in daily calorie needs in adolescence after they took body size into account. “We really thought puberty would be different and it’s not,” Pontzer said.

Midlife was another surprise. Perhaps you’ve been told that it’s all downhill after 30 when it comes to your weight. But while several factors could explain the thickening waistlines that often emerge during our prime working years, the findings suggest that a changing metabolism isn’t one of them.

In fact, the researchers discovered that energy expenditures during these middle decades – our 20s, 30s, 40s and 50s -- were the most stable. Even during pregnancy, a woman’s calorie needs were no more or less than expected given her added bulk as the baby grows.

The data suggest that our metabolisms don’t really start to decline again until after age 60. The slowdown is gradual, only 0.7% a year. But a person in their 90s needs 26% fewer calories each day than someone in midlife.

Lost muscle mass as we get older may be partly to blame, the researchers say, since muscle burns more calories than fat. But it’s not the whole picture. “We controlled for muscle mass,” Pontzer said. “It’s because their cells are slowing down.”

The patterns held even when differing activity levels were taken into account.

For a long time, what drives shifts in energy expenditure has been difficult to parse because aging goes hand in hand with so many other changes, Pontzer said. But the research lends support to the idea that it’s more than age-related changes in lifestyle or body composition.

“All of this points to the conclusion that tissue metabolism, the work that the cells are doing, is changing over the course of the lifespan in ways we haven’t fully appreciated before,” Pontzer said. “You really need a big data set like this to get at those questions.”

This research was supported by the United States National Science Foundation (BCS-1824466), the International Atomic Energy Agency, Taiyo Nippon Sanso and SERCON.

CITATION: "Daily Energy Expenditure Through the Human Life Course," Herman Pontzer, Yosuke Yamada, Hiroyuki Sagayama, et al. Science, Aug. 12, 2021. DOI:  10.1126/science.abe5017

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Metabolism peaks at age one and tanks after 60, study finds

  • Published 13 August 2021

Family

Middle-aged spread cannot be blamed on a waning metabolism, according to an unprecedented analysis of the body's energy use.

The study, of 6,400 people, from eight days old up to age 95, in 29 countries, suggests the metabolism remains "rock solid" throughout mid-life.

It peaks at the age of one, is stable from 20 to 60 and then inexorably declines.

Researchers said the findings gave surprising new insights about the body.

Ripped muscles

The metabolism is every drop of chemistry needed to keep the body going.

And the bigger the body - whether that is ripped muscles or too much belly fat - the more energy it will take to run.

So the researchers tweaked their measurements, adjusting for body size, to compare people's metabolism "pound for pound".

The study, published in the journal Science, found four phases of metabolic life:

  • birth to age one, when the metabolism shifts from being the same as the mother's to a lifetime high 50% above that of adults
  • a gentle slowdown until the age of 20, with no spike during all the changes of puberty
  • no change at all between the ages of 20 and 60
  • a permanent decline, with yearly falls that, by 90, leave metabolism 26% lower than in mid-life

Graphic

"It is a picture we've never really seen before and there is a lot of surprises in it," one of the researchers, Prof John Speakman, from the University of Aberdeen, said.

"The most surprising thing for me is there is no change throughout adulthood - if you are experiencing mid-life spread you can no longer blame it on a declining metabolic rate."

Childhood malnutrition

Other surprises came from what the study did not find.

There was no metabolic surge during either puberty or pregnancy and no slowdown around the menopause.

The high metabolism in the first years of life also emphasise how important a moment it is in development and why childhood malnutrition can have lifelong consequences.

"When people talk about metabolism, they think diet and exercise - but it is deeper than that, we are actually watching your body, your cells, at work," Prof Herman Pontzer, from Duke University, told BBC News.

"They are incredibly busy at one year old and when we see declines with age, we are seeing your cells stopping working."

Family

People's metabolism was measured using doubly labelled water.

Made from heavier forms of the hydrogen and oxygen atoms that make up water, this can be tracked as it leaves the body.

But doubly labelled water is incredibly expensive, so it took researchers working together across 29 countries to gather data on 6,400 people.

The researchers said fully understanding the shifting metabolism could have implications in medicine.

Prof Pontzer said it could help reveal whether cancers spread differently as the metabolism changes and if drug doses could be adjusted during different phases.

And there is even discussion about whether drugs that modify the metabolism could slow diseases of old age.

Drs Rozalyn Anderson and Timothy Rhoads, from the University of Wisconsin, said the "unprecedented" study had already led to "important new insights into human metabolism".

And it "cannot be a coincidence" diseases of old age kicked in as the metabolism fell.

Obesity epidemic

Prof Tom Sanders, from King's College London, said: "Interestingly, they found very little differences in total energy expenditure between early adult life and middle age - a time when most adults in developed countries put on weight.

"These findings would support the view that the obesity epidemic is fuelled by excess food energy intake and not a decline in energy expenditure."

Dr Soren Brage, from the University of Cambridge, said the total amount of energy used had been "notoriously difficult to measure".

"We urgently need to turn our attention not only to the global energy crisis defined by the burning of fossil fuels but also the energy crisis that is caused by not burning enough calories in our own bodies."

Follow James on Twitter .

More on this story

Metabolism 'obesity excuse' true

  • Published 24 October 2013

Obese child

Articles on Metabolism

Displaying 1 - 20 of 53 articles.

new research on metabolism

Thanksgiving sides are delicious and can be nutritious − here’s the biochemistry of how to maximize the benefits

Julie Pollock , University of Richmond

new research on metabolism

Tracking daily step counts can be a useful tool for weight management – an exercise scientist parses the science

Bob Buresh , Kennesaw State University

new research on metabolism

Ever wonder how your body turns food into fuel? We tracked atoms to find out

James Carter , Griffith University ; Brian Fry , Griffith University , and Kaitlyn O'Mara , Griffith University

new research on metabolism

Why do I crave sugar and carbs when I’m sick?

Hayley O'Neill , Bond University

new research on metabolism

Does it matter what time of day I eat? And can intermittent fasting improve my health? Here’s what the science says

Frederic Gachon , The University of Queensland and Meltem Weger , The University of Queensland

new research on metabolism

Renaming obesity won’t fix weight stigma overnight. Here’s what we really need to do

Ravisha Jayawickrama , Curtin University ; Blake Lawrence , Curtin University , and Briony Hill , Monash University

new research on metabolism

Exercise may or may not help you lose weight and keep it off – here’s the evidence for both sides of the debate

Donald M. Lamkin , University of California, Los Angeles

new research on metabolism

Fiber is your body’s natural guide to weight management – rather than cutting carbs out of your diet, eat them in their original fiber packaging instead

Christopher Damman , University of Washington

new research on metabolism

It’s time to bust the ‘calories in, calories out’ weight-loss  myth

Nick Fuller , University of Sydney

new research on metabolism

Looming behind antibiotic resistance is another bacterial threat – antibiotic tolerance

Megan Keller , Cornell University

new research on metabolism

Brains also have supply chain issues – blood flows where it can, and neurons must make do with what they get

Suzana Herculano-Houzel , Vanderbilt University

new research on metabolism

Is my medicine making me feel hotter this summer? 5 reasons why

Nial Wheate , University of Sydney and Jessica Pace , University of Sydney

new research on metabolism

Bulking and cutting: is it safe for your metabolism?

Christopher Gaffney , Lancaster University

new research on metabolism

Why are some people mosquito magnets and others unbothered? A medical entomologist points to metabolism, body odor and mindset

Jonathan Day , University of Florida

new research on metabolism

Why are bigger animals more energy-efficient ? A new answer to a centuries-old biological puzzle

Craig White , Monash University and Dustin Marshall , Monash University

new research on metabolism

Your body has an internal clock that dictates when you eat, sleep and might have a heart attack – all based on time of day

Shogo Sato , Texas A&M University

new research on metabolism

Is intermittent fasting the diet for you? Here’s what the science says

McKale Montgomery , Oklahoma State University

new research on metabolism

New insights from biology can help overcome siloed thinking in cancer clinical trials and treatment

Gerald Denis , Boston University

new research on metabolism

Gut microbes help hibernating ground squirrels emerge strong and healthy in spring

Hannah V. Carey , University of Wisconsin-Madison and Matthew Regan , Université de Montréal

new research on metabolism

How does excess sugar affect the developing brain throughout childhood and adolescence? A neuroscientist who studies nutrition explains

Lina Begdache , Binghamton University, State University of New York

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New Research Shifts Thinking on Metabolism and Aging

Tim Rhoads

There are many common beliefs about metabolism. Perhaps you’ve heard that a person’s metabolism slows around middle age, or that a woman’s metabolism is slower than a man’s. However widespread these beliefs are, recent research from the journal Science has found that these conceptions of metabolism are wrong. In a groundbreaking study, researchers have found that metabolism goes through four key phases over our lives, only beginning to slow around age 60. This, among other findings, are now changing how we think about human physiology and how we think about aging. Breaking down this new research and his perspective article on the findings , Dr. Rhoads describes our shifting understandings of metabolism and how it impacts chronic diseases like Alzheimer’s disease as we age.

Guest: Tim Rhoads, PhD, assistant scientist, Rozalyn Anderson laboratory, University of Wisconsin School of Medicine and Public Health

Episode Topics

2:30 - How is metabolism related to diseases of aging?

4:42 - What are the four distinct phases of metabolism and why are they important?

7:44 - What are other findings that change our understanding of metabolism?

12:00 - How does the decline in metabolism later in life affect chronic diseases like Alzheimer’s disease? Are there things we could do to prolong a high metabolism?

15:22 - How does caloric restriction affect the body and metabolism?

Read the perspective piece written by Dr. Rhoads and Dr. Rozalyn Anderson on the journal Science’s website .

Read the original research report, “Daily energy expenditure through the human life course,” by Pontzer et al. on the journal Science’s website .

Learn more about recent metabolism research in the article, “ What We Think We Know About Metabolism May Be Wrong ,” written for the New York Times .

Learn more about the Rozalyn Anderson Lab and their research at their website .

Transcript:

Intro : I’m Dr. Nathaniel Chin, and you’re listening to Dementia Matters , a podcast about Alzheimer's disease. Dementia Matters is a production of the Wisconsin Alzheimer's Disease Research Center. Our goal is to educate listeners on the latest news in Alzheimer's disease research and caregiver strategies. Thanks for joining us.

Dr. Nathaniel Chin : Welcome back to Dementia Matters . I'm here with Dr. Tim Rhoads, an assistant scientist with the Rozalyn Anderson lab at the University of Wisconsin's School of Medicine and Public Health where he studies the effect of caloric restriction on metabolism and aging. Recently, Dr. Rhoads and Dr. Rozalyn Anderson wrote a commentary for the journal Science called “Taking the long view on metabolism”. In this article, they break down new research that shows what we thought we knew about metabolism might be wrong and explain what this means in the context of aging and diseases of aging such as dementia. Dr. Rhoads, welcome to Dementia Matters . 

Rhoads : Thank you so much. I'm excited to be here.

Chin: Well, we’re excited to have you. I always like to hear from our scientists and researchers what got them into the field, so to start, how did you get involved in aging research and choose caloric restriction as your area of focus?

Rhoads: I didn’t choose it as much as it chose me. So it was actually originally via collaboration. I was a postdoc here in Joshua Coon’s lab working on proteomics and kind of systems biology type work. We had a collaborative project to look at liver samples from the non-human primates aging and caloric restriction study here at the University of Wisconsin. That eventually connected me with Roz Anderson. And my time in Josh's lab was ending and I wanted to go back to something that was a little bit more biologically focused in terms of research, and so her lab was a natural fit. As we worked on those samples, she and I were communicating frequently and so it just sort of made sense.

Chin: This is a very complicated topic so I'm going to ask that you do your best to translate it for the rest of us who are not in metabolism and and aging research but metabolism is so important, and I think all of our audience members recognize that, so could you share with us, at the most basic level right now, how is metabolism related to diseases of aging – things like Alzheimer's disease or dementia – and how might changes in metabolism actually impact our brain?

Rhoads: Sure. Most people think of metabolism as basically energy, how our body takes in energy, how it uses energy. Pretty much every activity that we do requires energy, and that includes the brain. But metabolism is actually more than just energy usage because it also encompasses things like synthesis and modification of the basic building blocks that we use in our cells. That means that metabolism is basically a regulator of fundamental cellular activity. Everything the cell has to be able to do is going to require metabolism at some level. So the example I would use for something like dementia – AD is characterized by these protein aggregates and there's a lot of debate about what exactly they're doing in the context of AD, but our cells have a system for dealing with protein homeostasis and maintaining proteins. So when you have something like aggregates, that indicates at some level there's a failure in that machinery. That machinery requires energy to function so you're getting to a failure of metabolism eventually. It's not always obvious and apparent but a lot of – almost all of this stuff traces back to metabolism eventually. 

Chin: That's kind of deep there, Tim. So metabolism is not only about energy, but it's also about the creation and then even the modification of the building blocks of our cells and how we use the proteins or the machinery of our cells. 

Rhoads: Yes, absolutely.

Chin: Then fundamentally most diseases eventually relate to metabolism one way or the other.

Rhoads: I would definitely agree with that, yeah.

Chin: (laughs) Okay. Well then with that in mind, now you co-wrote this perspective in a very important journal  Science and in that article you describe four distinct phases of metabolism in the lifespan of a human being. So if you could share with us, what are those phases and why does this matter?

Rhoads: Right so the original article that the perspective piece was based on, which is also in Science, was using a technique called doubly-labeled water to examine just overall energy expenditure in humans as they go about their lives. They found that energy expenditure basically had, as you said, these four distinct phases and they correspond roughly with infancy, so up until about two years of age, childhood and adolescence up until about 20 years of age, adulthood from 20 all the way up until 60-65, and then advanced age. These phases are important because energy expenditure was substantially different across these different phases. Infants had dramatically higher energy expenditures than full adults. During childhood and adolescence, it slowly comes down until it settles at about the level it is throughout adulthood. Then after age 60 or 65 it starts to decline a little bit. And so one of the examples of how important this might be is for things like drug dosing and pharmaceuticals. Most of our pharmaceuticals are tested in full adults, but with metabolism playing such a role in how drugs are trafficked in the body, what we learn from drugs in a full adult might not apply to children and adolescence. Especially now that we can kind of see that metabolism is starting to decline in advanced age and most of these drugs are going to be against chronic diseases of advanced age, that has some important ramifications for how we think about drugs and how they should be dosed and things like that That's really one of the important consequences of looking at metabolism in this way.

Chin: And you know, to me as a geriatrician, of course that makes a lot of sense because I view the body differently for my patients who are 65 and older. I will tell you, Tim, I don't know if I would use the word advanced age, maybe older adults. I'm not sure if that could be modified in these papers. I think it's a really key thing here. And an important finding – one of the things in the paper that I thought was really beautiful is that your baby or a baby's metabolism mirrors that of its mother initially, like for the first month or so of its life. 

Rhoads: I think that was one of the surprising findings. And actually that during pregnancy, the amount that a woman's metabolism changes during pregnancy can basically be accounted for by accounting for the additional mass that goes along with pregnancy. That there wasn't any sort of distinct difference in metabolism as a result of being pregnant was one of the surprising things that we learned from this.

Chin: This just seems like this is such a key study. Are there other important findings that have really shifted our view on metabolism or our understanding of the impact of metabolism on our bodies?

Rhoads: Well I certainly looked at this and thought, well I can no longer sort of excuse an expanding waistline on a declining metabolism. I think one of the general assumptions that people have held is that metabolism – like the paper showed – peaks around young adults but then that it immediately starts to decline and shows this gradual decline all the way until the end and what this paper shows is that's probably not a great assumption. Actually your metabolism throughout adulthood is fairly stable and it really doesn't start to noticeably decline until you're older – 60 to 65 years of age. That, again, goes very much against what, I think, was the expected result. That's one of the things that was so important about studies like this. This was a very, very large study – over 6,000 participants– and it involved an unprecedented level of sort of data-sharing across lots of different sites and researchers. So that's one of the reasons why I think this is such an important study

Chin: And you're right. We cannot use metabolism or slowed metabolism as a reason for weight gain. Certainly we have seen that in this country, in particular, but throughout the world – this increased obesity epidemic or pandemic. You know, your paper also comments on the heterogeneity or the variability of metabolism. For my audience this is really that there's no one set value of metabolism for everyone. These are general trends. So is metabolism different between men and women? Large individuals and small individuals? Active people versus couch potatoes?

Rhoads: Yes I think heterogeneity is a very underappreciated facet. You know, our genetic code is 99+% identical across all of the humans, but there's so much individual variability and it's something as researchers we have to grapple with quite a lot. Speaking of metabolic variability, the biggest thing that this paper revealed was that size is really one of the dominating factors. The difference between men and women, as far as overall energy expenditure, mostly disappeared once they controlled for differences in fat and lean mass. In other words, women on average tend to be a little bit smaller than men and when you account for that difference, the metabolic difference between men and women largely goes away. That's not to say that there wouldn't be some differences between men and women metabolically. It's just that in the case of sort of overall energy expenditure that doesn't appear to be the case. As far as activity levels, I think it's another one where the difference is probably difficult to see at this scale. There’s almost certainly differences between active and more sedentary individuals. Active people are going to be using more energy but one of the things that I think people forget is how much energy it takes just to do the basic functions every day. Activity level can add to your expenditure a little bit but in the context of the amount of energy it takes to get your body through a day of just basic function, it's relatively small. So at the scale of this study I think it's hard to see.

Chin: I appreciate that comment though because that is a good perspective. It is good to exercise and get that activity but from a caloric standpoint, it really isn't a huge number, unless of course you're an athlete or professional athlete. But for the rest of us, yeah. 

Rhoads: And I don't want to minimize the effects of exercise and how good it is for you because it definitely is extremely good for you, but in that context of the amount of energy it takes to keep our body going is you know, that’s a large amount of energy.

Chin: Well I do want to touch on this because that finding that at 60 to 65, metabolism starts to decline but it really isn't a dramatic decline. It's just a slow decline. How is that important when we think about chronic diseases in older people – and these are of course things like Alzheimer's disease? And then in that context, are the things that we could do that might prolong a higher metabolism?

Rhoads: Yeah, I think the interesting thing to both Roz and I was that age 60 or thereabouts is right when the risk for these chronic diseases starts to really increase. So the fact that that's also when metabolism starts to decline, we think that can't be a coincidence. We think there's almost certainly going to be links there. Like I said towards the beginning, everything kind of comes back to metabolism ultimately. And so there can't be a coincidence. So I think maintaining a higher metabolism – I don't know if higher is necessarily the word I would use. Maybe more resilient metabolism might be better. But I certainly think that a healthier lifestyle would have benefits for both metabolism and disease risk. One of the things that I think is difficult is knowing exactly what will work for each individual person – going back to that heterogeneity concept. There's just so much variability that it's hard to often pinpoint for one individual what the best lifestyle is for them. II don't think it's a coincidence. We call them healthy lifestyles for a reason.

Chin: And then – I'm going to pivot here because you also do work within Roz Anderson's lab on caloric restriction and understanding the early molecular responses of caloric restriction. Can you tell us a bit more about that work within the lab?

Rhoads: Yeah. What we're trying to do is really to understand aging at a molecular level so that we can start to identify these biological mechanisms that result in this increased disease risk. Caloric restriction is a really useful model for this. It's been known since about the 1930s that caloric restriction actually extends lifespan; those initial experiments were done in rats. What that tells us is that caloric restriction alters the aging process. At the time it was kind of uncertain how well it was going to translate into humans. Back in the late 1980s here at the University of Wisconsin, a study of caloric restriction in the non-human primate Rhesus monkey was started. They're genetically very similar to humans and they have a similar risk profile for chronic diseases. That study was ongoing for 40 years and involved collecting tissues and assessing the health of the monkeys throughout. So my work in Roz's lab uses molecular profiling tools where we're trying to assess all of the biological molecules in a bunch of these different tissues and we compare monkeys that were on control diets, where they could eat as much as they wanted, and monkeys that were calorically restricted to try and see if we can see molecular differences in proteins, metabolites, and mRNA – the real popular molecule lately – and to try and understand why they might be different.

Chin: That's quite a task, Tim. And so if you could summarize for us, what is the impact of caloric restriction on the body and how does caloric restriction actually impact metabolism?

Rhoads: So the way the term that we use is it reprograms metabolism. It shifts what our body uses for fuel, how it stores energy, and you end up with the metabolism that is, generally I would say, more efficient because it has to be. Your body is adapting to lower nutrient intake. Especially if it's sustained for a long period of time, your body has to be able to accommodate that and still be able to function. And so it reprograms the metabolic set points. Really the question that we're trying to figure out is how does that lead to extended longevity. 

Chin: In your work does caloric restriction impact people differently or Rhesus monkeys differently based on their age? For instance, if you were to caloric restrict in your twenties compared to doing it in your seventies?

Rhoads: Yeah I think there's definitely going to be differences there. It's not always exactly clear what aspects of CR (caloric restriction) are you going to get if you start in your twenties versus in your seventies and eighties. One of the things about this is that a lot of the work has been done in rodents, and in rodents you can start CR very early, basically as soon as they're weaned. They’re very young, you know, 21 days of age. The earlier you start them on CR, the longer lifespan extension you get. However that may not be the case in primates. So I mentioned the UW non-human primate study. Around the same time, a study was started at the National Institutes of Health also in Rhesus monkeys, but they had a slightly different implementation. They had some different age groups. They started it in younger monkeys, for example, that weren't fully developed. They weren't full adults yet and there actually was a slightly higher mortality level in those individuals. So once you get to primates – I suspect this probably has something to do with brain and brain size and development – there might be a developmental cost to the lowered caloric intake really early on.

Chin: That's a very interesting finding. I know that we can't speculate as to what that would mean for humans, but that is interesting to know. I do want to ask you a question about food and caloric restriction, and I know you will give a very politically correct and scientific answer but I'm still going to ask it. Is there a relationship among caloric restriction, what you are studying, and things like intermittent fasting or the ketogenic diet, two very popular things that are researched by the general public.

Rhoads: Yeah I certainly think there are similarities. The fasting response is undoubtedly an important part of how CR works. The general implementation of CR is roughly a 20-30% reduction, which means cutting out basically a meal per day. That’s tricky to do without some level of fasting involved. So there’s definitely going to be similarities with intermittent fasting in that regard. The ketogenic diets are basically designed to force that fuel switch where you’re using more lipids as fuel rather than carbohydrates, which is something that caloric restriction also does. There are definitely similarities. The jury, I think, is still out on what it means for longevity. The intermittent fasting and ketogenic diets, I just don’t think there’s quite enough study of what the impact will be for those on longevity. So that’s what I would say for that.

Chin: That's actually more than I was anticipating, so thank you, Tim. Are there things, though, that we could do now that could impact our metabolism, whether you're in your twenties, thirties, fifties, seventies. Just as we’re thinking about decreasing risk of diseases of aging like Alzheimer's disease, is caloric restriction or fasting – is this something that you think is appropriate or at least a plausible idea for people?

Rhoads: I would caution probably not, at least caloric restriction specifically. I think one of the things about CR is anyone that's ever tried it, it's really difficult to maintain. As I mentioned, you're talking about a meal or so per day and it's not like you get to replace it somewhere else. You have to just cut those calories out entirely, and so I think that's very challenging. There are people that do it and they stick to it. I admire them greatly for it, but I love food a lot. So I would have a hard time contemplating caloric restriction. So I think as far as what people can do to impact their risk of disease, it's going to be perhaps a very bland answer. You know, healthy diets, exercise, sleep, and water. We know those things are fairly important for our overall health and that they work fairly well. So with caloric restriction and other specific diets like that, those are really tools to look at how aging works but I don't know how appropriate they are for people to implement in their daily lives.

Chin: I think that's well said. It's a model. It's not necessarily a recommendation for a real life application. I'm going to ask you, now, my last question, one that I also enjoy asking our guests, is about your own brain health. And so specifically for you – I mean, you kind of answered part of this but – do you think about caloric caloric restriction or intermittent fasting or eating a certain type of food or a certain timing of food as you think of addressing brain health?

Rhoads: I think about calorie restriction and like the idea that I would have more energy and things like that, but it comes back again, it would be really really difficult to maintain. So I do not personally do calorie restriction or intermittent fasting. I think, especially for brain health, one of the things that I think is very interesting is how much impact there seems to be from just making sure your brain is active and actively engaged for a big part of the day. I guess I think that's where maybe scientists have some advantages because that is what I spend a lot of my day doing, kind of solving logic puzzles almost, looking at data trying to come up with explanations. That keeps my brain very very engaged all the time. I think that's a really important one. Like I said, I love food. So doing something like CR is just – especially living in Wisconsin where there’s so much good cheese and beer, I can’t restrict myself from that.

Chin: I appreciate your honesty but I also appreciate the fact that you're right – when we think of metabolism, we're thinking of energy use. Certainly when we keep our brain stimulated, we are keeping an active metabolism of our brain cells. That is a great way to end. Thank you, Dr. Tim Rhodes, for being on Dementia Matters and answering these questions and talking to us about metabolism and aging.

Rhoads: Thank you so much. I really enjoyed it.

Outro:  Thanks for listening to Dementia Matters. Be sure to follow us on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts to be notified about upcoming episodes. You can also listen to our show by asking your smart speaker to play the Dementia Matters podcast. And please rate us on your favorite podcast app -- it helps other people find our show and lets us know how we are doing.

Dementia Matters is brought to you by the Wisconsin Alzheimer's Disease Research Center. The Wisconsin Alzheimer's Disease Research Center combines academic, clinical, and research expertise from the University of Wisconsin School of Medicine and Public Health and the Geriatric Research Education and Clinical Center of the William S. Middleton Memorial Veterans Hospital in Madison, Wisconsin. It receives funding from private university, state, and national sources, including a grant from the National Institutes of Health for Alzheimer's Disease Centers.

This episode of Dementia Matters was produced by Rebecca Wasieleski and edited by Caoilfhinn Rauwerdink. Our musical jingle is "Cases to Rest" by Blue Dot Sessions.

To learn more about the Wisconsin Alzheimer's Disease Research Center and Dementia Matters, check out our website at adrc.wisc.edu. You can also follow our Facebook page at Wisconsin Alzheimer’s Disease Research Center and our Twitter @wisconsinadrc . If you have any questions or comments, email us at [email protected] . Thanks for listening.

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Metabolism articles within Nature Reviews Cardiology

Research Highlight | 13 October 2023

Metabolic reprogramming unlocks the regenerative potential of the heart

The metabolic maturation of mammalian cardiomyocytes that occurs during the early postnatal period shapes the epigenetic landscape of cardiomyocytes and creates a barrier for cell division, but reversing this remodelling process can restore the reparative capacity of the heart in mice, according to a study published in Nature .

  • Irene Fernández-Ruiz

Review Article | 26 May 2023

Metabolic mechanisms in physiological and pathological cardiac hypertrophy: new paradigms and challenges

In this Review, Ritterhoff and Tian describe the metabolic reprogramming that occurs in cardiac hypertrophy and heart failure; discuss the contribution of metabolism to energy-generating and non-energy-generating functions, including signalling, protein function and gene expression regulation; and highlight the role of metabolism in non-cardiomyocytes and the potential to develop metabolic therapies for heart failure.

  • Julia Ritterhoff
  •  &  Rong Tian

Review Article | 04 July 2022

The molecular and metabolic landscape of iron and ferroptosis in cardiovascular disease

Since the discovery of ferroptosis a decade ago, this iron-dependent form of regulated cell death has been implicated in the pathogenesis of cardiovascular disease. In this Review, Fudi Wang and colleagues discuss the link between the metabolic pathways of iron signalling and ferroptosis in the context of the cardiovascular system and describe the potential of ferroptosis inhibitors in the treatment of cardiovascular disease.

  • Xuexian Fang
  • , Hossein Ardehali
  •  &  Fudi Wang

Research Highlight | 21 December 2021

Metabolic dysregulation drives endoreplication in heart disease

Cardiometabolic endoreplication (duplication of the nuclear genome without cell division), resulting in polyploidy and multinucleation, precedes cardiomyocyte hypertrophy in heart disease.

  • Gregory B. Lim

Research Highlight | 17 February 2021

A novel cardioprotective function for DRP1 inhibition

A new study identifies a small-molecule inhibitor of a mitochondrial fission protein that reduces PCSK9 secretion and atherosclerotic plaque formation.

  • Andrew Robson

Research Highlight | 18 January 2021

Rebalancing the pyruvate–lactate axis to treat heart failure

New research shows that the pyruvate–lactate axis is an important regulatory node for cardiac homeostasis and function and that alteration of this axis is an early event in cardiomyocyte hypertrophy and heart failure.

Hydralazine reduces myocardial infarct size

A new study shows that hydralazine, a drug used for the treatment of resistant hypertension and heart failure, can inhibit mitochondrial fission, thereby reducing cardiomyocyte death and myocardial infarct size after ischaemia–reperfusion injury in mice.

In Brief | 21 December 2020

Lipid metabolism in peripartum cardiomyopathy

Research Highlight | 09 November 2020

Quantification of fuel use in the human heart

A metabolomics approach to assess heart energy metabolism in humans provides new insights into what fuels are used by both the failing and non-failing heart.

Research Highlight | 30 September 2020

Cardiac macrophages team up to maintain heart health

A network of macrophages in the heart supports cardiac health and function by removing dysfunctional mitochondria and waste material released from cardiomyocytes in subcellular particles called exophers.

Research Highlight | 21 July 2020

Targeting Lp(a) to reduce ASCVD risk

In a prespecified secondary analysis of the ACCELERATE trial, Puri and colleagues report a stepwise relationship between lipoprotein(a) levels and risk of major adverse cardiac events in patients with high-sensitivity C-reactive protein levels ≥2 mg/l.

  • Karina Huynh

Targeting the mitochondria to reverse ageing-induced cardiac dysfunction

SS-31, an inhibitor of mitochondrial reactive oxygen species production, can rescue age-related cardiac dysfunction and normalize mitochondrial proton leak in old mice.

Research Highlight | 16 July 2020

Exercise adaptations to milk confer benefits to offspring

Maternal exercise during pregnancy confers benefits to offspring, including improvements in glucose metabolism, adiposity and cardiac function, via an oligosaccharide present in breast milk.

  • Shimona Starling

Research Highlight | 09 March 2020

Inhibiting fatty acid oxidation promotes cardiomyocyte proliferation

Inhibition of fatty acid metabolism to promote oxidation of glycolysis-derived pyruvate promotes cardiomyocyte proliferation and improves left ventricular function after myocardial infarction.

Research Highlight | 24 January 2020

Intracoronary mitochondrial transplantation

Autologous mitochondrial transplantation for myocardial protection is feasible, safe and beneficial; however, the mechanisms by which these effects are achieved are uncertain.

Review Article | 16 May 2019

Dietary fats and cardiometabolic disease: mechanisms and effects on risk factors and outcomes

Dietary fats comprise heterogeneous molecules with diverse structures and complex health effects. This Review discusses the effects of different dietary fats on cell processes and cardiometabolic disease risk factors and clinical events, highlighting areas of controversy and future research directions to improve the prevention and management of cardiometabolic diseases through optimization of dietary fat intake.

  • Jason H. Y. Wu
  • , Renata Micha
  •  &  Dariush Mozaffarian

Research Highlight | 19 February 2019

T cells in the gut promote CVD and slow metabolism

A subset of T cells present in the small intestine modulate systemic metabolism and contribute to cardiovascular disease by limiting the bioavailability of the incretin hormone GLP1.

Review Article | 03 September 2018

Targeting mitochondria for cardiovascular disorders: therapeutic potential and obstacles

Mitochondrial dysfunction has a major role in the pathogenesis of multiple cardiovascular disorders. In this Review, Galluzzi and colleagues discuss the therapeutic potential of mitochondria-targeting agents in the treatment of cardiovascular disease, examine the obstacles that have limited their development thus far, and identify strategies for the development of these promising therapeutic tools.

  • Massimo Bonora
  • , Mariusz R. Wieckowski
  •  &  Lorenzo Galluzzi

Comment | 31 July 2018

The reality of getting old

Life expectancy around the world has increased steadily for nearly 200 years. This Focus Issue of Nature Reviews Cardiology features five insightful Review articles that describe numerous facets of the latest research on cardiovascular ageing.

  • Edward G. Lakatta

Review Article | 24 July 2018

Mitochondrial quality control mechanisms as molecular targets in cardiac ageing

Alterations in mitochondrial function, which are amplified by defective mitochondrial quality control (MQC) mechanisms, are major contributing factors to cardiac senescence. In this Review, the authors discuss the mechanisms linking defective MQC to organelle dysfunction in the context of cardiac ageing and consider how these pathways might be targeted for the prevention and treatment of age-related heart dysfunction.

  • , Robert T. Mankowski
  •  &  Christiaan Leeuwenburgh

Review Article | 18 June 2018

Metabolic remodelling in heart failure

In patients with heart failure, derangements of substrate utilization and intermediate metabolism, an energetic deficit, and oxidative stress are thought to underlie contractile dysfunction and disease progression. In this Review, Bertero and Maack describe the physiological processes of cardiac energy metabolism and their pathological alterations in heart failure and diabetes mellitus, and discuss promising treatments targeting substrate utilization or oxidative stress in mitochondria.

  • Edoardo Bertero
  •  &  Christoph Maack

Research Highlight | 26 October 2017

Myocardial salvage with HDL infusion after infarction

News & Views | 15 June 2016

Beyond the power of mitochondria

Mitochondria provide energy for specialized functions at the cellular and organ level. The remarkable symbiotic relationship between mitochondria and the cell touches on every aspect of cell biology. Recent studies in mitochondrial biology have uncovered ways in which mitochondria affect human disease and have identified new targets for clinical intervention.

  • Brian O'Rourke

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new research on metabolism

ScienceDaily

Metabolism linked to brain health

Every three seconds, someone in the world is diagnosed with dementia. And while there is no known cure, changes in the brain can occur years before a dementia diagnosis.

Now, a world-first study from the University of South Australia's Australian Centre for Precision Health has found a link between metabolism and dementia-related brain measures, providing valuable insights about the disease.

Analysing data from 26,239 people in the UK Biobank, researchers found that those with obesity related to liver stress, or to inflammation and kidney stress, had the most adverse brain findings.

The study measured associations of six diverse metabolic profiles and 39 cardiometabolic markers with MRI brain scan measures of brain volume, brain lesions, and iron accumulation, to identify early risk factors for dementia.

People with metabolic profiles linked to obesity were more likely to have adverse MRI profiles showing lower hippocampal and grey matter volumes, greater burden of brain lesions, and higher accumulation of iron.

UniSA researcher, Dr Amanda Lumsden, says the research adds a new layer of understanding to brain health.

"Dementia is a debilitating disease that affects more than 55 million people worldwide," Dr Lumsden says.

"Understanding metabolic factors and profiles associated with dementia-related brain changes can help identify early risk factors for dementia.

"In this research, we found that adverse neuroimaging patterns were more prevalent among people who had metabolic types related to obesity.

"These people also had the highest Basal Metabolic Rate (BMR) -how much energy your body requires when resting in order to support its basic functions -- but curiously, BMR seemed to contribute to adverse brain markers over and above the effects of obesity."

Senior Investigator, UniSA's Professor Elina Hyppönen says the finding presents a new avenue for understanding brain health.

"This study indicates that metabolic profiles are associated with aspects of brain health. We also found associations with many individual biomarkers which may provide clues into the processes leading to dementia," Prof Hyppönen says.

"The human body is complex, and more work is now needed to find out exactly why and how these associations arise."

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Materials provided by University of South Australia . Note: Content may be edited for style and length.

Journal Reference :

  • Amanda L. Lumsden, Anwar Mulugeta, Ville‐Petteri Mäkinen, Elina Hyppönen. Metabolic profile‐based subgroups can identify differences in brain volumes and brain iron deposition . Diabetes, Obesity and Metabolism , 2022; DOI: 10.1111/dom.14853

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The anabolic response to protein ingestion during recovery from exercise has no upper limit in magnitude and duration in vivo in humans

Affiliations.

  • 1 Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, the Netherlands.
  • 2 Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, the Netherlands; FrieslandCampina, 3818 LE Amersfoort, the Netherlands.
  • 3 Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, the Netherlands. Electronic address: [email protected].
  • PMID: 38118410
  • DOI: 10.1016/j.xcrm.2023.101324

The belief that the anabolic response to feeding during postexercise recovery is transient and has an upper limit and that excess amino acids are being oxidized lacks scientific proof. Using a comprehensive quadruple isotope tracer feeding-infusion approach, we show that the ingestion of 100 g protein results in a greater and more prolonged (>12 h) anabolic response when compared to the ingestion of 25 g protein. We demonstrate a dose-response increase in dietary-protein-derived plasma amino acid availability and subsequent incorporation into muscle protein. Ingestion of a large bolus of protein further increases whole-body protein net balance, mixed-muscle, myofibrillar, muscle connective, and plasma protein synthesis rates. Protein ingestion has a negligible impact on whole-body protein breakdown rates or amino acid oxidation rates. These findings demonstrate that the magnitude and duration of the anabolic response to protein ingestion is not restricted and has previously been underestimated in vivo in humans.

Keywords: absorption; autophagy; bioavailability; de novo; digestion; intermittent fasting; mTOR; meal frequency; protein requirements; time-restricted feeding.

Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.

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Building Community to Advance Metabolic Science

Listen to "building community to advance metabolic science".

Mitochondria and intermediary metabolism are central to health and disease, yet many of us learn a simplified version of this complex science. To develop expertise in metabolism research at Yale School of Medicine (YSM), Richard Kibbey, MD, PhD , professor of medicine (endocrinology and metabolism), created the Program for Mitochondrial Biology and Intermediary Metabolism (MBIM).

Mitochondria are key to the regulation of tissue function, such as insulin secretion, glucose production, nerve transmission, muscular contraction, and inflammation as well as cancer cell growth, Kibbey explains. The term “intermediary” refers to the compounds—the chemical metabolites—that are going through and transformed by the metabolic pathways.

There are a lot of misconceptions about how to measure mitochondrial function and metabolism and the meaning of various observations, Kibbey notes. “The educational component of MBIM will promote a deeper understanding of the fundamental mechanisms of mitochondrial metabolism and chemical biology, and how to design, perform, and interpret studies,” he said.

The goal of the program, which Kibbey launched in early 2023, is to catalyze collaboration, provide education, promote publications, offer innovative technologies, and help investigators obtain funding.

new research on metabolism

“Many labs across YSM are interested in studying metabolism, but they’re somewhat disconnected from each other,” Kibbey said. “I want to bring that community together and develop stronger resources to further metabolism studies that will challenge many assumptions we’ve made over the past 30 to 40 years and expand our understanding of metabolism.”

Cutting-edge technologies currently offered through the Chemical Metabolism Core component of MBIM measure targeted and untargeted metabolomics, cellular respiration, and metabolic fluxes using stable isotope labeled samples. Due to demand among investigators, Kibbey is working to add a new lipidomics facility that will measure many lipid species and their side chains quantitatively. These core services are offered to researchers at cost.

MBIM is already supporting a multi-institution grant that supports a large study involving stable isotope labeling and metabolomics to explore the intersection between diet, sex, genetics, and metabolism across multiple tissues, according to Kibbey. “That is one example of the types of projects that we hope to continue to develop,” he said.

We’re very eager to help people design, carry out, and interpret their metabolism studies to advance outstanding interdisciplinary metabolic science at Yale. Richard Kibbey, MD, PhD

The need to understand mitochondrial biology is of critical importance to our understanding of metabolic homeostasis and disease, said Anton Bennett, PhD, Dorys McConnell Duberg Professor of Pharmacology and professor of comparative medicine.

“This new program will provide the platform from which investigators can tackle questions relating to how mitochondrial function and regulation impacts metabolism,” Bennett said. “The expertise and instrumentation that the program provides in the area of mitochondrial biology fulfils an unmet research need and is anticipated to be of high impact across the medical school.”

“This program will be very important to our growing portfolio of metabolism research,” said Nancy J. Brown, MD, Jean and David W. Wallace Dean of the Yale School of Medicine and C.N.H. Long Professor of Internal Medicine.

As MBIM continues to build the metabolism community and draw connections across disciplines, Kibbey envisions the program supporting opportunities for retreats, seminar series, instrument educational workshops, collaborative papers, and grants.

“We’re very eager to help people design, carry out, and interpret their metabolism studies to advance outstanding interdisciplinary metabolic science at Yale,” he said.

Y ale School of Medicine’s Section of Endocrinology and Metabolism works to improve the health of individuals with endocrine and metabolic diseases by advancing scientific knowledge; applying new information to patient care; and training the next generation of physicians and scientists to become leaders in the field. To learn more, visit Endocrinology and Metabolism .

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Featured in this article

  • Richard Kibbey, MD/PhD Ensign Professor of Medicine (Endocrinology and Metabolism), and Professor of Molecular and Cellular Physiology; Faculty Director, Core in Chemical Metabolism; Associate Director, Yale Program for Translational Biomedicine; Associate Chief of Research, Endocrinology
  • Anton Bennett, PhD Dorys McConnell Duberg Professor of Pharmacology and Professor of Comparative Medicine; Director, Yale Center for Molecular and Systems Metabolism (YMSM); Director, BBS Minority Affairs
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  • Acta Pharm Sin B
  • v.9(6); 2019 Nov

Current trends in drug metabolism and pharmacokinetics

a School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou 510275, China

b The First Affiliated Hospital of Nanchang University, Nanchang 330006, China

c College of Pharmacy, Dalian Medical University, Dalian 116044, China

Mengbi Yang

d School of Pharmacy, the Chinese University of Hong Kong, Hong Kong, China

Dongyang Liu

e Drug Clinical Trial Center, Peking University Third Hospital, Beijing 100191, China

Xiangyu Hou

f Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China

g School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China

h School of Life Sciences, East China Normal University, Shanghai 200241, China

Yuanfeng Lyu

Xiaoyan chen.

i UC Davis School of Medicine, Sacramento, CA 95817, USA

Huichang Bi

Associated data.

Pharmacokinetics (PK) is the study of the absorption, distribution, metabolism, and excretion (ADME) processes of a drug. Understanding PK properties is essential for drug development and precision medication. In this review we provided an overview of recent research on PK with focus on the following aspects: (1) an update on drug-metabolizing enzymes and transporters in the determination of PK, as well as advances in xenobiotic receptors and noncoding RNAs (ncRNAs) in the modulation of PK, providing new understanding of the transcriptional and posttranscriptional regulatory mechanisms that result in inter-individual variations in pharmacotherapy; (2) current status and trends in assessing drug–drug interactions, especially interactions between drugs and herbs, between drugs and therapeutic biologics, and microbiota-mediated interactions; (3) advances in understanding the effects of diseases on PK, particularly changes in metabolizing enzymes and transporters with disease progression; (4) trends in mathematical modeling including physiologically-based PK modeling and novel animal models such as CRISPR/Cas9-based animal models for DMPK studies; (5) emerging non-classical xenobiotic metabolic pathways and the involvement of novel metabolic enzymes, especially non-P450s. Existing challenges and perspectives on future directions are discussed, and may stimulate the development of new research models, technologies, and strategies towards the development of better drugs and improved clinical practice.

Graphical abstract

Understanding of DMPK properties is essential for drug development and precision medication. In this article, we provided an overview of recent research on DMPK with focuses on the regulatory mechanisms of pharmacokinetics, drug–drug interaction, mathematical modeling, non-classical metabolism and so on. Existing challenges and perspectives on future directions are also discussed.

Image 1

1. Introduction

Pharmacokinetics (PK) is defined as the quantitative study of drug absorption, distribution, metabolism, and excretion (ADME)— i . e ., the ways the body processes a drug 1 while the drug exerts its actions in the body. The scope of PK not only covers studies on healthy subjects but also includes broad research on variations under a variety of physiologic or pathologic conditions and the underlying mechanisms, potential drug–drug interactions (DDI), and possible strategies such as dose adjustment to achieve precision medication. Collectively, these aspects of PK allow customization of drug dosage regimens to enhance therapeutic outcomes 1 . Therefore, PK study is a prerequisite to establish the relations and the underlying mechanisms of a drug to its activities and clinical benefits. The information obtained is crucial for lead identification and optimization in drug discovery, as well as dosage regimen design and adjustment in clinical practice 2 . The complexity of PK has evolved, largely in relation to the rapid developments in analytical chemistry, computer science, molecular biology and biochemistry. Although much is known with regard to the PK of many drugs, and many technologies have been established for PK research, recent studies are revealing the existence of new mechanisms by which how drugs are metabolized and how PK is regulated. New experimental models and computational modeling algorithms are arising for an improved understanding of the significance of PK in a whole-body system; nonetheless, many challenges remain.

This review will provide a comprehensive overview of recent developments in the areas of PK research. First, we will provide an update of findings on drug-metabolizing enzymes and transporters in the control of PK, as well as advances in nuclear receptors and noncoding RNAs (ncRNAs) in the modulation of PK, which will provide new insights into understanding the transcriptional and posttranscriptional regulatory mechanisms behind inter-individual variations in pharmacotherapy. Second, we will review the current status and trends in assessing DDIs, especially the interactions between drugs and herbs, between drugs and therapeutic biologics, and microbiota-mediated DDIs and HDIs. Third, we will summarize recent advances in disease–drug interactions, in particular, regulation of metabolizing enzymes and transporters and alteration of PK by different diseases or physiological states. Fourth, we will summarize the trends in mathematical modeling including physiologically-based PK, which could be applied to support clinical investigations. In addition, we will discuss novel animal models such as CRISPR/Cas9-based animal models for DMPK research and overview some interesting non-classical biotransformation pathways including those utilizing novel drug-metabolizing enzymes. Existing challenges and future perspectives are also discussed. It is expected that this review will provide an update on recent advances in PK fields and may stimulate the establishment of new research models, technologies, and strategies towards the development of better drugs and improvements in clinical practice.

2. Determinants of PK

Drug-metabolizing enzymes and transporters play a very important role in the control of PK. Furthermore, transcriptional and posttranscriptional factors such as nuclear receptors and noncoding RNAs (ncRNAs) are critical in the modulation of PK and provide in-depth insight into understanding regulatory mechanisms to solve problems in PK. These mechanism-driven PK studies can improve the success of drug development related to its efficacy and safety and improve the rational use of medication in clinical practice.

2.1. Drug-metabolizing enzymes in the control of PK

Drug-metabolizing enzymes mediate the metabolism of exogenous and endogenous substances. Most drugs lose their pharmacological activities mainly through metabolic transformation, yielding metabolites with high water solubility that are readily excreted. Hence, metabolizing enzymes play an extremely important role in the control of drug PK. The biotransformation of xenobiotics by xenobiotic-metabolizing enzymes (XMEs) may be classified into Phase I and Phase II reactions. Advanced characterizations of enzymes involved in human drug metabolism are urgently needed, which help to avoid severe adverse drug reactions. Advances are being made in understanding the role of drug-metabolizing enzymes in the control of PK, including individual isoforms of many enzymes such as cytochrome P450s (CYPs) and UGTs, and their selective substrates, inducers and inhibitors. Other non-P450 oxidative enzymes and conjugative enzymes are also discussed in this section since an increasing number of drugs are metabolized via these enzymes 3 .

2.1.1. CYPs critical for PK

CYPs can oxidize foreign substances, enhance the water solubility and make drugs easier to be eliminated from the body. Most drugs are metabolized by CYPs, which mainly are located in the inner membrane of mitochondria or the endoplasmic reticulum of cells 4 . There are a total of 57 human CYP genes in 18 families. The members of CYP1 to CYP4 families oxidize thousands of exogenous and endogenous substrates ( Table 1 ); whereas all members of CYP5 family and higher principally metabolize endogenous substrates in a highly substrate-specific manner 5 .

Endogenous and exogenous substrates of CYPs and ligands of transcription factors.

Most known chemical carcinogens, including aromatic amines and polycyclic aromatic hydrocarbons (PAHs), are substrates of CYP1 family, and their metabolism often results in the formation of active carcinogenic metabolites. In 2018, CYP1B1 was found in the mitochondria of cancer cells, where it reportedly metabolizes melatonin to form the metabolite N -acetylserotonin (NAS), which has antitumor effects 6 . CYP2D6, another important metabolic enzyme, is involved in the metabolism of many anti-cancer drugs, such as cyclophosphamide, tamoxifen, and gefitinib 7 . Recent research has found that in brain, CYP2D6 can metabolize both m-tyramine and p-tyramine into dopamine 8 . The CYP4 family has gained increasing attention for its potential to generate interesting metabolites and dispose of endogenous substrates in recent years. CYP4F11, together with CYP4F2, plays an important role in the synthesis of 20-hydroxyeicosatetraenoic acid (20-HETE) from arachidonic acid, and participates in the metabolism of vitamin K 9 . Cyp2a5 , the mouse correlate of human CYP2A6 , encodes an enzyme that exhibited circadian regulation 10 . The other CYP1 to CYP4 subfamilies are involved in metabolism of different endogenous and exogenous substrates, as listed in Table 1 .

Understanding variation in mechanism-based enzyme activity is crucial for improving the clinical use of drugs. Highly selective inducers and inhibitors of CYPs have been cited in Guidance for Industry by FDA ( https://www.fda.gov/drugs/drug-interactions-labeling/drug-development-and-drug-interactions-table-substrates-inhibitors-and-inducers ). Recent studies have revealed new chemicals and herb products as inducers or inhibitors of CYPs. For example, CYP7A1 is upregulated by an intestinal HIF-2 α inhibitor called PT2385 17 . The ketene intermediate of erlotinib can inactivate CYP3A4 and CYP3A5, which can result in liver injury 18 . Due to the complexity of components in the extract of herbs it is common that herb products exhibit different effects on the regulation of multiple enzymes. Sophora flavescens can inhibit CYP2B6, CYP2C8, CYP2C9, and CYP3A activities, while catalpol can inhibit the activity of CYP3A4, CYP2E1 and CYP2C9 19 , 20 . Other regulatory factors can also alter the expression of CYPs. For example, tumor suppressor p53 can regulate Cyp2b10 directly and thereby attenuate APAP-induced hepatotoxicity 21 .

Herbs may be used singly or in combination in the treatment of diseases 22 . It is very important to understand how drug exposure alters molecular mechanisms underlying many complex drug interactions. For example, data show that ellagic acid from pomegranate peel guava leaf extract can significantly increase the AUC of warfarin with concomitant use. A significant reduction in CYP2C8, 2C9, and 3A4 activity was the main reason for this interaction 23 .

Based on recently available data, new information on the relative content of individual isoforms of P450 has been generated. Total CYP concentrations are significantly different between Chinese and Caucasian populations and the metabolic capabilities of CYPs in Chinese liver microsomes was significantly lower (<50%) in the CL int for substrates of CYP1A2, CYP2C9, CYP2C19 and CYP2E1 than those of Caucasian populations 24 . Large variations in protein content, mRNA levels, and intrinsic activities of ten P450s (CYP3A4, 1A2, etc) have been revealed and some single nucleotide polymorphisms had significant impact on P450 expression; for example, CYP2C19 activity varied more than 600-fold 25 . A recent human PK study further evaluated CYP1A2 content in Chinese compared with Caucasian populations, enhancing the confidence in pharmacokinetic prediction of CYP1A2 content using two substrates (caffeine and theophylline) 26 .

Other organs like kidney and intestine also have significant metabolic capacity. There is definitive evidence for CYP2B6 and 3A5 expression in human kidney, while multiple CYPs are expressed in intestine 27 , 28 . The role of renal and intestinal enzymes in herbal product metabolism has been uncovered. Aminoglycoside antibiotics are leading causes for nephrotoxicity; combination with herbs or dietary supplements at reduced dosage is possible to reduce the risk of drug-mediated renal toxicity. A recent study revealed that moringa oleifera seed oil could limit gentamicin-induced oxidative nephrotoxicity 29 . Additional herbs have been identified as having effects on intestinal metabolism, such as the extracts of Yin-Chen-Hao Tang (YCHT), a very popular hepatoprotective three-herb formula in China and Japan 30 . These findings contribute to the understanding of the metabolic characteristics of renal and intestinal metabolism.

2.1.2. Non-P450 oxidative enzymes

The contribution of non-P450 enzymes to drug metabolism can be significant and affect the overall development of drugs. Non-CYP enzymes can be divided into four general categories: namely oxidative, reductive, conjugative, and hydrolytic. Non-CYP oxidative enzymes include flavin-containing monooxygenases (FMOs), monoamine oxidases (MAOs), peroxidases, xanthine oxidases (XO), aldehyde oxidase (AO), alcohol dehydrogenase (ADHs) and aldehyde dehydrogenase (ALDHs) 31 .

Very little is known about the regulation of content and activity of non-P450 oxidative enzymes. Recently, some selective substrates and inhibitors of non-P450 enzymes have been identified in natural products and other sources. FMOs are involved in the metabolism of a wide array of xenobiotics. Well-known inhibitors of FMOs include indole-3-carbinol and methimazole, and 2-mercaptobenzimidazole 32 . Classified into two different isoforms (MAO-A, MAO-B), MAOs are enzymes involved in the catabolism of monoamines. Benextramine and its derivatives were identified as novel human monoamine oxidases inhibitors, which could be considered as candidate drugs for the treatment of neurodegenerative diseases 33 . In addition, 3-(3-(dimethylamino)propanoyl)-7-hydroxy-5-methyl-2 H -chromen-2-one hydrochloride has been found to function as a novel selective hMAO-B inhibitor, which is expected to be a promising multifunctional Parkinson's disease treatment agent 34 . XO and AO are involved in the oxidation of aldehydes and heterocycles, and carbazeran was used as a selective probe substrate of AO in hepatocytes 35 . Allopurinol and S -allyl cysteine (SAC) are XO inhibitors used in the treatment of gout and hyperuricemia 36 . A single-nucleotide polymorphism of human cytochrome P450 oxidoreductase (POR) in the Chinese population can regulate the content of POR and P450 isoforms 37 . Identifying specific inhibitor compounds will greatly facilitate investigation of enzyme-mediated drug disposition and drug interactions.

2.1.3. Importance of UDP-glucuronyltransferases (UGTs) in PK

UDP-glucuronyltransferases (UGTs) are a family of endoplasmic reticulum-bound enzymes which are responsible for the process of glucuronidation, a major part of phase II metabolism 38 . Human UGTs include 22 different functional enzymes and are classified into four gene families, UGT1, UGT2, UGT3 and UGT8 39 . The UGT1 and UGT2 families are primarily enzymes involved in drug glucuronidation, while the contribution of the UGT3 and UGT8 families to drug metabolism is minimal 40 .

Recently, UGT1A3 was found to be involved in the glucuronidation of alpinetin 41 . UGT1A4 is involved in the glucuronidation of metizolam 42 . Other UGT isoforms involved endogenous and exogenous substrates are listed in Table 2 23 , 43 , 44 , 45 , 46 .

Endogenous and exogenous substrates of UGTs and ligands of transcription factors.

Highly selective substrates and selective inhibitors of UGTs have been found in natural products and from other sources. Resveratrol can activate UGT1A8 expression, and is used for breast cancer treatment 47 . Different doses of emodin can inhibit the activity of UGT2B7 48 .

In some cases, herbal products are metabolized by multiple UGTs. Linoleic acid and glutaric acid can inhibit the glucuronidation of berberrubine, a lipid-lowing metabolite of berberine, as well as the activities of UGT isoforms, such as UGT1A7, 1A8, 1A9 49 . Glucuronidation of catalposide, an active component of Veronica species, was catalyzed by gastro-intestine-specific UGTs 1A8 and 1A10 50 .

Gene polymorphisms are a key factor in the regulation of the content and activity of UGTs. UGT1A and UGT2B genetic variation can alter nicotine and nitrosamine glucuronidation in European and African American smokers 51 . In addition, the UGT1A4*3 genetic polymorphism is associated with low posaconazole plasma concentrations in patients with hematological malignancies 52 . UGT1A1*6 polymorphisms are correlated with irinotecan-induced neutropenia in cancer patients 53 .

2.1.4. Other conjugative enzymes important for PK studies

In addition to UGTs, sulfonyl transferases (SULTs) and glutathione S -transferases (GSTs) are also important conjugative enzymes mediating phase II reaction.

SULTs catalyze the transfer of the water-soluble sulfonate group from 3′-phosphoadenosine 5′-phosphosulfate to drugs or endogenous molecules that contain hydroxy or amine group(s) 54 . At present, four families of human SULTs have been discovered, namely SULT1, SULT2, SULT4 and SULT6. SULT1E1 plays an important role in the metabolism and detoxification of estrogens and flavonoids 55 . SULT2 enzymes, mainly SULT2A and SULT2B, are primarily responsible for catalyzing the sulfation of hydroxysteroids 56 . A recent study found that tumor suppressor p53 could regulate the expression of SULTs 57 .

GSTs are a group of phase II drug-metabolizing enzymes that catalyze the binding of glutathione to various electrophilic compounds. In humans, cytosolic GST isoenzymes of the alpha, zeta, theta, mu, pi, sigma and omega classes have been found. GSTA1 plays a significant role in the metabolism of acetaminophen 58 . GSTA4 metabolizes electrophilic and carcinogenic substances such as endogenous carcinogen 4-hydroxy-2-nonenal 59 . The detailed substrates of SULTs and GSTs are listed in Table 3 .

Endogenous and xenobiotic substrates for GSTs and SULTs that are also ligands of particular transcription factors.

2.1.5. Updates on the nuclear receptor-mediated regulation of xenobiotic-metabolizing enzymes

The human nuclear receptors comprise a family of 48 ligand-regulated transcription factors that in turn regulate target genes involved in metabolism and other physiological functions. Some of these receptors ( e . g ., peroxisome proliferators-activated receptor (PPAR), liver X receptor (LXR), hepatocyte nuclear factor (HNF)) are of particular interest in regard to drug metabolism and disposition as they have been found to regulate many XMEs in recent years.

PPAR α induces the expression of CYP4A in response to a heterogeneous group of peroxisome proliferators. PPAR γ also regulates the expression of CYP4V2, a fatty acid metabolizing enzyme, in human tetrahydropyranyl 1 (THP1) macrophages 60 . LXR controls the transcription of Cyp7a1 and Cyp27a1 , Cyp3a11 and Cyp2e1 61 , 62 , 63 .

Traditional transcriptional factors can bind directly to specific DNA sequences and thus control the gene expression. However, epigenetic regulation like histone modification and DNA methylation modulates transcription of UGTs or CYPs mainly by changing chromatin architecture. For example, the UGT1A gene can be repressed by the recruitment of histones in females 64 . Several studies determined that microRNAs (miRNAs), could down-regulate the expression of metabolizing enzymes, which will be further reviewed in Section 2.3 .

In summary, the expression and activity of metabolizing enzymes can be regulated by multiple factors, including drugs, nuclear receptors, gene polymorphisms, and even ethnic categories. Non-P450 enzymes and other conjugative metabolizing enzymes have gained attention in drug metabolism in recent years. It is desirable to illustrate the key factors responsible for variable expression and activity of drug metabolizing enzymes, as it may be beneficial in the prediction of potential therapeutics, drug–drug interactions, and in modifying the PK of drugs.

2.2. Transporters in the control of PK

2.2.1. introduction of transporters.

Transporters are membrane-bound proteins expressed on the cell membrane in most tissues with varying abundance. They can transport a variety of endogenous or exogenous substrates (such as drugs and their metabolites) in and out of cells. For drugs, transporters are the gatekeepers for cells and control the uptake and efflux of drugs. Transporters are involved in the ADME process of drugs. Therefore, transporters play critical roles in the pharmacokinetics, efficacy and toxicity of drugs. Alteration of transporter function or expression may significantly change the blood and/or tissue exposure of drugs, leading to significant changes in pharmacokinetics. Furthermore, the induction or inhibition of transporters by co-administered drugs can change PK and pharmacodynamics of therapeutic drugs and produce DDI.

There are more than 400 membrane transporters belonging to two major superfamilies: adenosine triphosphate (ATP)-binding cassette (ABC) and solute carrier (SLC) transporters. They utilize the energy that is released by ATP hydrolysis or an electrochemical ion gradient to translocate drugs across the membrane.

2.2.1.1. The ABC family of drug transporters

ABC transporters mainly act as exporters and pump drug molecules out of cells by utilizing the energy released by the hydrolysis of ATP. According to the organization and sequence of ATP-binding domains, 49 ABC transporters are classified into seven subfamilies: ABC1/ABCA, multidrug resistance (MDR)/TAP/ABCB, MRP/ABCC, ALD/ABCD, OABP/ABCE, GCN20/ABCF and White/ABCG 65 . Among them, P-glycoprotein (P-gp, MDR1, ABCB1), MRPs/ABCCs, breast cancer resistance protein (BCRP/ABCG2) and bile salt export pump (BSEP/ABCB11) are recognized for their importance in drug disposition 66 . P-gp, which is expressed at a high level in the intestine, liver, kidney, brain and placenta, is the most studied ABC transporter. Many substrates of P-gp including antibiotics, statins, immunosuppressants, anticancer drugs and a broad spectrum of drugs overlap with the substrates of CYPs. The expression of P-gp is regulated by several transcription factors including PXR, CAR, vitamin D receptor (VDR) and CCAAT/enhancer binding protein (C/EBP) and some microRNA such as miR-451, miR-27a and miR-145 67 , 68 . Furthermore, P-gp is usually overexpressed in cancer cells and plays a critical role in MDR. For example, during chemotherapy, P-gp may be an obstacle for drug exposure if the therapeutic drugs are P-gp substrates 69 . Besides its role in MDR induction, P-gp plays a critical role in pharmacokinetics, pharmacology and toxicology. Through pumping multiple drugs out of cells, P-gp decreases the bioavailability of oral drugs and increases drug efflux into urine or bile. Furthermore, P-gp also plays a vital role in the maintenance of the blood–brain barrier by pumping drugs or toxins out of the CNS 70 . Another important ABC transporter group is the MRP family that consists of 9 MRP proteins (MRP1–MRP9). Among them, MRP2 is important in drug pharmacokinetics. MRP2, once known as the canalicular multispecific organic anion transporter, is highly expressed in liver, intestine and kidney. Chemotherapeutics such as methotrexate, melphalan, and statins are the classical substrates of MRP2. Since co-expressed in the liver, many liver-enriched transcription factors such as LXR, farnesoid X receptor (FXR), HNF and C/EBP regulate the transcription of MRP2. Another efflux transporter BCRP is a half transporter and is expressed at a high level in a wide variety of tissues such as intestine, kidney, liver, testis and brain. BCRP is modulated by the progesterone receptor B (PRB) and estrogen receptor (ER). Another ABC family drug transporter, BSEP, is primarily expressed in the liver and pumps bile acids and non-bile acid drugs such as pravastatin into bile.

2.2.1.2. The SLC family of drug transporters

The SLC family consists of 55 gene subfamilies and more than 360 family members. SLC transporters mainly utilize the energy stored in the ion gradients across membranes, but do not depend directly on ATP hydrolysis 71 . Several SLC family transporters play important roles in drug disposition including organic anion-transporting proteins (OATPs/SLC21/SLCO), organic anion and cation transporters (OATs and OCTs/SLC22), peptide transporters (PEPTs/SLC15) and sodium-dependent bile acid transporters (NTCP/SLC10A1). The OATP family consists of 11 members. Among them, four transporters including OATP1A2 (SLCO1A2), OATP1B1 (SLCO1B1), OATP1B3 (SLCO1B3) and OATP2B1 (SLCO2B1) are involved in drug transport 72 . OATP1A2 is expressed in the intestinal epithelium, renal epithelium and brain capillary endothelial cells, while OATP1B1, OATP1B3 and OATP2B1 are expressed predominantly in hepatocytes. Statins and anti-cancer drugs like paclitaxel, sorafenib and methotrexate are known as the substrates of OATPs. The SLC22 family consists of 23 members, including OCTs, zwitterion/cation transporters (OCTNs) and OATs. Among OCTs, OCT1 (SLC22A1) is mainly expressed in the liver, OCT2 (SLC22A2) is located at a high level in proximal tubular cells, and OCT3 (SLC22A3) has a broader expression range. Several drugs have been identified as OCT substrates including anesthetic drugs, the anti-diabetic drug metformin, antidepressants, β -blockers and anti-cancer chemotherapeutics. Among OATs, OAT1 (SLC22A6) and OAT3 (SLC22A8) have a broader expression range with the highest expression in kidney, while OAT2 (SLC22A7) is primarily expressed in the liver. OAT1 substrates include antiviral drugs, antibiotics, diuretics and angiotensin-converting enzyme (ACE) inhibitors. For the SLC15 subfamily, PEPT1 and PEPT2 are the most studied transporters. Both mediate oligopeptide uptake. PEPT1 is highly expressed in the intestine and mediates drug absorption, while PEPT2 is mainly expressed in kidney and affects renal reabsorption.

2.2.2. Transporters are critical for PK

The ADME process determines the blood and tissue concentration of drugs, as well as subsequent pharmacological or toxicological effects. The intestine and liver, both of which tightly regulate the entry of drugs into the blood circulation, are important organs in determining the bioavailability of oral drugs. Elimination of drugs or their active metabolites occurs either by metabolism to inactive metabolites that are excreted, or by direct excretion of drugs or active metabolites in the kidney. The transporters expressed in intestine, liver and kidney are involved in the absorption, distribution and excretion processes of drugs, and are the major determinant in blood and tissue concentration of drugs.

2.2.2.1. Transporter-mediated oral drug absorption

Oral drug absorption primarily occurs in the intestine, which is the major determinant of drug bioavailability, together with the first-pass extraction in the liver. Drug molecules pass through the membranes in the intestine through two pathways: passive diffusion and transporter-mediated absorption.

The process of transporter-mediated oral drug absorption consists of two parallel transport processes including transporter-mediated uptake and transporter-mediated efflux 73 , 74 ( Fig. 1 A). In general, net drug absorption depends on multiple uptake and efflux transporters in the intestine. Uptake transporters such as OATP2B1, PEPT1 and sodium-dependent bile acid transporter (ASBT/SLC10A2) are involved in the intestinal uptake of drugs across the brush border membrane 75 . For example, PEPT1 transports di/tripeptides-like anticancer drugs such as bestatin and β -lactam antibiotics into enterocytes 76 , 77 , 78 . Efflux transporters expressed on the brush border membrane of the intestine, are considered as the barriers for intestinal drug absorption. P-gp, MRP2 and BCRP are three major efflux transporters in the intestine. P-gp, the most studied efflux transporter, has broad substrate specificity and significantly limits the bioavailability of many oral drugs 79 . For example, co-treatment with verapamil, a P-gp inhibitor, increases the intestinal absorption of afatinib or bestatin due to P-gp inhibition in the intestine 80 , 81 . On the contrary, rifampin, a P-gp inducer, decreases the oral absorption of cyclosporine and tacrolimus through the induction of P-gp in the intestine 82 . BCRP is another efflux transporter expressed in the intestine and suppresses the intestinal absorption of drugs 83 . Due to only one ATP binding site and six putative transmembrane helices, BCRP is considered a “half-transporter”. The substrates of BCRP include statins (pitavastatin, rosuvastatin), antiviral drugs (lamivudine, zidovudine, abacavir), anticancer drugs (methotrexate, SN-38, irinotecan, gefitinib, imatinib, erlotinib) and antibiotics (nitrofurantoin, ciprofloxacin) 84 . The efflux transporter MRP2 is also expressed on the brush border membrane of the intestine and transports a variety of substrates conjugated with sulfate, glutathione and glucuronide, as well as various unmodified drugs. Previous studies showed that resveratrol inhibited MRP2 and thereby increased the intestinal absorption of methotrexate 85 .

Figure 1

Drug transporter expression in tissues. Drug transporter expression in the intestine (A), liver (B) and kidney (C). The arrows indicate the general directions in which the substrates are transported.

2.2.2.2. Transporter-mediated drug distribution

Transporters also affect the tissue distribution and contribute to the selective distribution of drugs to specific tissues. For example, OATP1B1 and OATP1B3 are the major uptake transporters in the liver for cilostazol, and MRP2, BCRP, P-gp pump cilostazol out of the liver into bile 86 . These transporters assist the liver-specific distribution of cilostazol. Another example is pravastatin, which enters into the liver through OATP1B1 and OATP1B3. After being excreted into the bile, pravastatin is reabsorbed in the intestine to the portal vein and taken up by the liver, and effectively undergoes enterohepatic circulation 87 . Therefore, the liver concentration should be higher than that in the circulating blood, leading to a high pharmacological effect at a relatively low plasma concentration. Transporters are also expressed on the blood–brain barrier and play critical roles in restricting the distribution of drugs into the brain. Increasing evidence has demonstrated that P-gp on the blood–brain barrier can suppress the distribution of drugs into the CNS 88 , 89 . Also, BCRP is recognized as an efflux transporter on the blood–brain barrier suppressing drug entry into the brain. Except for efflux transporters, uptake transporters are also expressed on the blood–brain barrier and play key roles in the uptake of neuroactive drugs. OAT3 is highly expressed on the basolateral membrane of brain capillaries 90 , and OCT2 is expressed in neurons and the choroid plexus. OCT2 is involved in the reabsorption of many drugs such as serotonin, norepinephrine, dopamine, choline and histamine from the cerebrospinal fluid.

2.2.2.3. Transporter-mediated drug excretion

Drug elimination primarily occurs in the liver and kidney. Hepatobiliary elimination processes can be summarized as follows: (1) the uptake of drugs into hepatocytes via uptake transporters or passive diffusion; (2) drug metabolism in hepatocytes including CYP metabolism (phase I metabolism) and conjugation (phase II metabolism); (3) excretion from hepatocytes into bile or portal blood via efflux transporters. Hepatobiliary transport of drugs is attributable to transporters located on the basolateral (sinusoidal) or canalicular (apical) membrane of hepatocytes ( Fig. 1 B). SLC superfamily transporters are responsible for drug uptake from the portal blood into hepatocytes. Among them, OAT2, OCT1, OATPs and NTCP are major uptake transporters. Efflux transporters such as P-gp, BCRP, MRP2 and BSEP are responsible for the hepatobiliary excretion of drugs and their metabolites. In addition, the efflux transporter MRP3, 4 and 6 expressed on the basolateral membrane are responsible for the basolateral efflux of drugs from the liver into the blood circulation. The hepatic transporters OAT2, OATP1B1/1B3 and OCT1 are highly expressed in the liver and are considered to be of particular importance for hepatic drug elimination, PK and efficacy. Much like the interplay of transport and metabolic enzymes at the intestinal barrier, these transporters also have a “gatekeeper” function in the drug movement from the blood into hepatocytes; they regulate both the number of drugs available for metabolism by liver enzymes and the subsequent biliary excretion. Efflux transporters including P-gp, BCRP, MRP2 and BSEP are responsible for the biliary excretion of endogenous and exogenous molecules. Many studies have shown that P-gp transports amphiphilic cationic drugs such as doxorubicin, digoxin and vinblastine into bile 91 . BCRP is involved in the biliary excretion of sulfated conjugates of steroids and drugs such as doxorubicin, mitoxantrone and daunorubicin, while BSEP transports drugs including vinblastine and taxol, et al. Due to their important roles in hepatobiliary efflux, the inhibition of BSEP, BCRP and MRP2 may lead to cholestasis. Therefore, the effects of chemicals on transporter-mediated hepatobiliary excretion must be determined in drug discovery 92 .

The kidney is the major organ of drug excretion. Renal clearance of drugs consists of glomerular filtration, tubular secretion and reabsorption. The proximal tubule region is responsible for the active secretion and reabsorption of drugs. Many transporters are located at the renal tubular epithelial cells and are involved in the proximal tubular secretion and reabsorption ( Fig. 1 C). These transporters include OCTs, OATs, multidrug and toxin extrusion proteins (MATE1 and MATE2-K), sodium-phosphate transporter (NPT/SLC17A1), OATPs and PEPTs, as well as equilibrium and concentration nucleoside transporters (ENTs and CNTs/SLC28A). Among them, OCTs, OATs and MATEs play critical roles in the active secretion of renal proximal tubule. These transporters work in concert with efflux transporters to transfer drugs into urine. OATs mainly transport anionic drugs such as beta-lactam antibiotics and anti-inflammatory drugs. The competitive inhibition of OATs may lead to a decrease in renal tubular secretion and an increase in the systemic concentration of drugs. For example, co-administration of probenecid, one OAT inhibitor, decreases renal secretion, leading to an increase in the plasma concentration of bestatin 93 . JBP485, a dipeptide with potential protective activity against kidney, liver and intestinal injury, has been demonstrated to be a substrate of OATs. Co-administration of JBP485 and cephalexin decreased the accumulative renal excretion and renal clearance of both compounds 77 . When JBP485 and lisinopril were co-administered, the competitive inhibition of OAT1 and OAT3 were also observed in OAT1/3-HEK293 cells 94 . In addition, acyclovir, an antiviral drug, was also a substrate of OAT1/3 and JBP485 can inhibit its renal excretion 95 . Furthermore, the DDIs between JBP485 and entecavir through the competitive inhibition of OAT1 and OAT3 significantly decreased the renal excretion of both compounds 96 . On the other hand, OATs are involved in drug-related nephrotoxicity. Probenecid, by inhibiting OAT1 and OAT3, reduced the accumulation of cephaloridine and subsequently nephrotoxicity 97 , 98 .

Three OCT isoforms including OCT1, OCT2 and OCT3 have been found in the kidney. Among the three OCTs, OCT2 is the major transporter for renal secretion of a variety of drugs such as memantine, metformin and amantadine. DDIs may also occur through the competitive inhibition of OCTs. For example, through inhibiting OCT2, cimetidine decreases the renal excretion of metformin and increases its plasma concentration 99 . On the other hand, OCT2, by modulating the exposure of drugs to renal proximal tubule cells regulates the nephrotoxicity of anticancer drug cisplatin and its analogs 100 . Substrates taken up from the systemic circulation may subsequently undergo efflux across the brush border membrane of proximal tubule cells by various ABC efflux transporters such as P-gp and BCRP. For example, a probe P-gp substrate, methotrexate, is actively secreted into urine. Co-treatment with bestatin, another P-gp substrate, increases plasma concentrations and decreases the renal clearance of methotrexate 101 . MATE1 and MATE2-K are expressed on the brush border membrane of proximal tubular cells. MATE1 mediated the renal secretion of fluoroquinolones including gatifloxacin, ciprofloxacin, levofloxacin, enoxacin, pazufloxacin, norfloxacin and tosufloxacin.

In summary, the expression and activity of transporters can be regulated by drugs and competitive inhibition may occur after co-administration of more than one drug. Furthermore, species differences in transporters complicate pharmacokinetic scaling from preclinical species to humans. Additionally, the expression of transporters may also be regulated by disease progression 102 . Modulation of transporter expression by disease states can potentially modify the PK of drugs.

2.3. ncRNAs in the regulation of drug metabolism and pharmacokinetics

ncRNAs are genome-derived RNA molecules that are not translated into proteins. Indeed, the human genome is comprised of over 95% of noncoding sequences 103 that are transcribed into various forms of functional ncRNAs including miRs, transfer RNAs (tRNAs), ribosomal RNAs (rRNAs), small nucleolar RNAs (snoRNAs), and long noncoding RNAs (lncRNAs). Among them, miRNAs usually lead to translation inhibition or enhance mRNA degradation in cells through complementary base pairing with target transcripts. Many miRNAs have been shown to modulate the expression of drug-metabolizing enzymes or transporters, and consequently alter cellular drug metabolism and transport capacity, as well as drug responses (see recent reviews 104 , 105 , 106 ). For instance, miR-27b reduces CYP1B1 protein expression in human carcinoma cells and thus suppresses CYP1B1 enzymatic activity, as indicated by a P450-Glo™ luminescent assay 107 . Meanwhile, miR-27b modulates CYP3A4 expression through direct targeting of CYP3A4 3ʹ-untranslated region (3ʹUTR) and “indirect” targeting of transcriptional factors such as NR1I1/VDR 108 , which may significantly alter CYP3A4-mediated drug metabolism 109 , 110 . Furthermore, miR-27a/b regulates the expression of a number of transporters such as ABCB1/P-gp 111 , 112 , 113 , and thus influences intracellular drug accumulation and chemosensitivity. In addition, a number of Phase 2 drug-metabolizing enzymes such as the UGTs are regulated by miRNAs at the posttranscriptional level 114 , 115 , 116 , 117 , 118 , 119 . Findings on miRNA-controlled regulation of DMPK provide new insights into mechanisms behind inter-individual variations in pharmacotherapy.

Recent studies on miRNA regulation in DMPK also led to the development of novel research approaches and technologies. For example, while the luciferase reporter assay, gene mutagenesis and correlation analysis are helpful methods for the assessment of the interactions between miRNAs and target transcripts, a more direct approach has been established which is based on the change of RNA mobility after binding to miRNA, namely RNA electrophoretic mobility shift assay (EMSA) 120 , 121 . Using this RNA EMSA and other methods, a number of CYP genes ( e . g ., CYP2C19 , CYP2E1 and CYP2D6 ) and regulators have been shown to be regulated post-transcriptionally by particular miRNAs 121 , 122 , 123 , 124 , 125 . It is also noteworthy that miRNA research is limited to the use of miRNA-expressing plasmids or viruses, or chemically-synthesized or chemo-engineered miRNA mimics 126 , 127 , 128 . To better capture the properties of biologic RNA molecules and cellular miRNA machinery, a novel RNA bioengineering technology has been established for the production of biologic miRNA agents in living cells 109 , 129 , 130 , 131 , 132 , 133 . With such novel bioengineered miRNA agents produced cost effectively and on a large scale, extensive functional studies have been conducted and the results showed rather a modest change in the PK of major CYP probe drugs in mouse models 134 . Further studies have demonstrated the utility of miRNAs as therapeutics or sensitizing agents for the treatment of human diseases in various animal models 133 , 135 , 136 , 137 , 138 , 139 .

There is also growing evidence that lncRNAs may regulate the expression of drug-metabolizing enzymes and transporters. For example, expression of HNF1 α antisense RNA 1 (HNF1 α -AS1) and HNF4 α antisense RNA 1 (HNF4 α -AS1) shows a significant influence on the basal and drug-induced expression of drug-metabolizing enzymes in human cells 140 . H19, an lncRNA highly expressed in liver tissues, induces the expression of efflux transporter P-gp/MDR1/ABCB1 in drug-resistant HepG2 cells 141 . The lncRNA MRUL confers the overexpression of ABCB1 in drug-resistant gastric cancer cells 142 . Furthermore, some studies have demonstrated that a lncRNA modulates drug sensitivity through its action on miRNA-transporter axis 143 , 144 . In addition, as RNA editing and posttranscriptional modifications are critical for RNA stability and biological function, very recent studies have also demonstrated the alteration of DMPK gene expression following RNA editing 145 , 146 , 147 . Future studies in these areas will undoubtedly advance our understanding of RNA-based regulation in DMPK.

In summary, research on miRNA-controlled regulation of DMPK provides new insights into understanding the posttranscriptional regulatory mechanisms behind inter-individual variations. Novel technologies and research approaches are also established during the investigation of ncRNA regulation of DMPK gene expression, which should have broad impact on biomedical research. Evidence is accumulating that some lncRNAs may be involved in the regulation of DMPK, which represents a new area of research.

3. Drug–drug interactions

3.1. current status of research on drug–drug interactions.

DDIs may result in favorable or toxic effects. Patients frequently use more than one medication at a time. Depending on the clinical settings and the number of drugs prescribed, the incidence of potential DDIs ranges between 15% and 80% 148 . DDIs can be classified mechanistically into 3 major types: physio-chemical incompatibility, PK interactions, and pharmacodynamic interactions 149 . Physio-chemical interactions usually occur when positively and negatively charged compounds are mixed before they are administrated or absorbed. Pharmacokinetics-based DDIs, characterized by altered concentration of unbound drugs that exert pharmacological effects, can be caused by several mechanisms, including: 1) alteration of drug metabolizing enzymes ( e . g ., CYPs) 150 , 2) alteration of transporters involved in the absorption, distribution and excretion of drugs ( e . g ., MDR1, OAT, OCT, etc) 150 , 3) influence on plasma protein binding affinity 149 , and 4) changes in the function of organs ( e . g ., gut motility or stomach content pH) 149 . Pharmacodynamics-based DDIs are characterized by a shift of the unbound drug concentration versus response curve 149 . New responses that are not present when either of the drugs is given alone may also be observed when drugs are used in combination.

In vitro , in vivo and clinical studies are usually conducted to identify any potential DDIs. The in vitro studies are usually simple systems that can be used for high throughput screening and provide mechanistic information for potential DDIs. In vivo animal studies are often conducted using clinically relevant dosages and pharmacodynamic endpoints to confirm the in vitro observations. If evidence obtained from in vitro and in vivo animal models suggests strong DDIs potential further clinical trials are recommended 150 , 151 . Recently, mathematical modeling, particularly physiologically-based pharmacokinetic (PBPK) modeling has also been applied to investigate potential pharmacokinetic-based DDIs. A recent review by Min et al. 152 depicted how pharmacokinetic modeling improves and simplifies the investigation on DDIs. In addition, systematic reviews and databases summarize all the experimental and predicted data on DDIs, which are useful for providing warning and proper advice to patients in clinical practice 153 .

Although DDIs between small molecule drugs have been well investigated and documented, knowledges on interactions between drugs and herbs, interactions between therapeutic biologics, and interactions mediated by the gut microbiome are currently not well understood. The cutting-edge investigations on these aspects are briefly introduced in the following sections.

3.2. Current status of research on herb–drug interactions

Herbal plants and herbal products are commonly used as remedies and dietary supplements. When herbs are concurrently administered with drugs unrecognized herb–drug interactions (HDIs) may lead to side effects and toxicity. HDIs basically share the same mechanisms as DDIs. To avoid physio-chemical interactions between herbal components and drugs, it is usually recommended that herbs should be taken at two hours before or after the drugs. Moreover, herbs may sometimes alter the PK and/or pharmacodynamics of the concurrently administered drugs. PK and pharmacodynamic interactions have been reported between herbs and drugs with narrow therapeutic indexes, especially drugs for CNS and cardiovascular diseases 154 . For example, St John's wort ( Hypericum perforatum ) was reported to decrease warfarin plasma concentrations via inducing the activity of CYPs, leading to the loss of anticoagulant activity 155 . A traditional Chinese herb Danshen ( Salvia miltiorrhiza ) was reported to interact with warfarin on both its PK profiles and pharmacodynamic effects, resulting in over-anticoagulation and increased risk of bleeding 155 .

Investigation of HDIs is often more complicated than those of DDIs, due to the complex herbal components and the batch-to-batch variation of herbal products. As demonstrated in Table 4 , compared with DDIs, research on HDIs is still insufficient. In vitro screening assays, which are efficient ways for detecting potential DDIs, may not be applicable for testing crude herbs or herb extracts, due to the fact that some of the herbal components may not be bioavailable, and adding such herbal components to the in vitro cell/microsome systems may alter results. By using LC–MS/MS, several multi-compound pharmacokinetic studies allowed the simultaneous detection of the plasma/tissue concentrations of multiple components after ingestion of the studied herb, facilitating the discovery of the bioavailable active components and subsequent in vitro and in vivo mechanistic studies on potential HDIs 156 , 157 . Most of the reported HDIs are based on in vitro and in vivo animal models, providing evidence with low clinical relevance. Moreover, many clinical studies were conducted among healthy populations, where the impact of the herbs on the pharmacodynamics effects of the concurrent drug may not be determined. On the other hand, the wide variation between different batches of herbal products also leads to poor reproducibility of the tests. Although not true in all countries, herbal products in China are generally regulated and used as medicine with standardization of the content of the major active components, and the herbal products are sometimes investigated not only as the effector but also as the affected agent of HDIs. In addition to experimental approaches based on the pre-clinical and clinical data, mathematical models have been established to predict HDIs, demonstrating the feasibility of using PBPK modeling for the prediction of HDIs 152 . For example, PBPK modeling of two major active components from Wuzhi capsule ( Schisandra sphenanthera extract) predicts its interaction with tacrolimus metabolism by CYP3A4 inhibition 158 . However, the application of modeling and simulation on the investigation of HDIs is still restricted by the limited human pharmacokinetic data of herbal components 152 . More sophisticated designs of clinical studies are warranted to evaluate the safety and efficacy of the concomitant use of herbs and drugs.

Comparison between investigations on DDIs and HDIs 151 , 153 .

3.3. Trends in drug–drug interactions of therapeutic biologics

Therapeutic biologics include therapeutic proteins, monoclonal antibodies (mAbs), vaccines, and peptide and nucleic acid derivatives that are manufactured for pharmaceutical uses 159 . Development of therapeutic biologics is growing fast, and in clinical practice the risk of DDIs with biologics is increasing.

3.3.1. PK of therapeutic biologics

The PK of biologics is different from those of small molecules. Since most therapeutic biologics undergo rapid degradation in the gastrointestinal tract after oral administration, alternative routes, such as intravenous, intramuscular, and subcutaneous injection are often used for drug delivery 159 , 160 , 161 . The distribution of therapeutic biologics is mainly mediated by interstitial penetration, lymphatic drainage, transcytosis, and receptor-mediated cell uptake 159 , 160 , 161 . Therapeutic proteins usually have a limited volume of distribution and do not bind to plasma proteins, and their biliary and renal excretion is generally negligible 162 . Catabolism via proteolytic degradation is the predominant clearance pathway for most therapeutic proteins 159 , 160 , 161 , while target antigen-mediated disposition also plays a role 161 . Moreover, fragment crystallizable receptor (FcR)-mediated antibody recycling by monocytes, macrophages, and dendritic cells is a salvage pathway that prolongs the half-lives of many mAbs 159 , 160 , 161 . Immune responses participate in both the catabolism and the antibody recycling process, and therefore immunogenicity can significantly influence the clearance of therapeutic proteins 159 . A recent review by Ferri et al. 162 has summarized the pharmacokinetic DDIs of therapeutic antibodies. Unlike therapeutic proteins, nucleic acid and peptide drugs 160 are rapidly eliminated by peptidases and nucleases 159 , 163 , and may also undergo slow renal excretion 161 . Plasma binding of these oligomers can sometimes be very high and has been reported to affect their distribution and clearance 160 .

3.3.2. Pharmacokinetics-based interactions of therapeutic biologics

Direct competition between therapeutic biologics and small molecules in PK is not common due to their distinct pharmacokinetic pathways 163 . However, certain indirect pharmacokinetic DDI may occur. Immunosuppressive agents may decrease the immunogenicity of the therapeutic protein so as to hinder its clearance 163 . For example, concomitant treatment with the immunosuppressant methotrexate can decrease the clearance of mAbs including golimumab 164 , adalimumab 162 , and infliximab 165 . Another indirect pharmacokinetic DDI mechanism is cytokine–CYP modulation. Several biologics with immunomodulatory effects may alter CYP activities via modulating the cytokine levels leading to the altered PK of co-administered small molecules that are substrates of the affected CYPs 159 , 163 , 166 . For instance, tocilizumab, which can induce CYP3A4 activity by decreasing interleukin 6 levels, was found to reduce simvastatin systemic exposure 167 . Similarly, by triggering inflammation, influenza vaccination has been reported to decrease CYP activity and thus influence the systemic exposure of CYP substrates such as clozapine 168 . PBPK modeling is a powerful tool for the investigation of pharmacokinetic-based interactions between therapeutic biologics and small molecules, and has been successfully applied to quantitatively predict DDIs of CYP-modulating protein drugs (such as blinatumomab and sirukumab) and small molecule CYP substrates in patients 169 , 170 . On the other hand, pharmacokinetic interaction between two therapeutic biologics has seldom been reported. However, such pharmacokinetic DDIs may occur due to specific binding between two biologics. For example, palifermin is a truncated form of the endogenous fibroblast growth factor which contains the heparin-binding domains. Co-administration of palifermin with heparin was found to increase the systemic exposure to palifermin up to 5-fold 171 .

3.3.3. Pharmacodynamics-based interactions of therapeutic biologics

Comparing to the pharmacokinetics-based DDIs of therapeutics biologics, their pharmacodynamics-based DDIs are more commonly reported. A large volume of cases has demonstrated pharmacodynamic interactions among various hormones owing to their complex signaling networks 159 . For instance, insulin can interact with numerous drugs including hormones, antidiabetics, antibiotics, antipsychotics, etc 172 . Recombinant growth hormones interact with small molecule hormones such as glucocorticoids, estrogens, thyroxin, etc. 159 . Although co-administration of biologics indicated for the same disease usually results in additive or synergistic efficacy, co-administration may also induce toxicity. Both anakinra and etanercept are approved for the treatment of rheumatoid arthritis. However, combined use of the two biologics led to severe adverse effects including increased risk of infection and increased neutropenia without significant improvement in therapeutic efficacy 173 .

3.3.4. Risk assessment for DDIs of therapeutic biologics

Due to the distinct pharmacokinetic and pharmacodynamic properties of therapeutic biologics, the classic approach for DDIs prediction for small molecules may not applicable for therapeutic biologics. With the increase in therapeutic biologics in the market, it is critical to call for building strategies and regulations on the potential DDIs involving biologics. Based on the current findings on the major mechanisms for the pharmacokinetic-based DDIs of therapeutic biologics, assessment of the modulation of CYP activities and immunogenicity are recommended. In terms of pharmacodynamics-based DDIs, identification and monitoring of clinical endpoints relevant to both the efficacy as well the adverse effects of therapeutic biologics is highly recommended.

3.4. Trends in microbiota mediated drug–drug interactions

Recent studies have indicated that the microbiota is a vital drug target in many disease treatments. Many therapeutics have great effects on altering the composition of the microbiota. As indicated in Fig. 2 A, changes in microbiota in the gastrointestinal tract may influence the metabolism of co-administered drugs, leading to altered pharmacokinetics. Findings have shown that gut microbiota can mediate drug metabolism including reduction 174 , oxidation 175 , dehydroxylation, decarboxylation 176 , etc. DDIs between antibiotics and drugs that are metabolized by gut microbiota are commonly reported. Many antibiotics can disturb the PK of a co-administered drug by affecting the enzymatic activities and composition of gut microbiota 177 , leading to an altered therapeutic effect. For example, the coagulant drug sulfinpyrazone can be metabolized to sulfinpyrazone sulfide in the gut contents. It was found that the plasma pharmacokinetic profile of sulfinpyrazone and sulfinpyrazone sulfide was changed in patients treated with the antibiotic metronidazole 178 . After reduction via azoreductases in gut microbiota, prontosil was metabolized to sulfanilamide, which exhibits potent antibacterial activities. In addition, it was noted in rats that the conversion of prontosil to sulfanilamide can be suppressed by antibiotics, leading to the reduced antibacterial effects 174 , 179 . Most recently, gnotobiotic mouse models and PBPK models have been established to untangle host and microbial contributions to the pharmacokinetic profile 180 . These novel experimental and computational strategies can be incorporated in future investigations on microbiota-mediated DDIs.

Figure 2

Microbiota-mediated pharmacokinetic and pharmacodynamic interactions between different drugs. (The solid arrow indicates an effect supported by obtained evidence, and the dotted arrow indicates potential effects.)

In addition to effects on pharmacokinetics, altered microbiota composition may also lead to pharmacodynamics changes in the concomitant drugs ( Fig. 2 B). It was noted that the presence of a certain type of bacteria may have an impact on chemotherapy and immunotherapy 181 , 182 . Clinical trials are currently conducted on microbiota interventions, such as probiotics and fecal microbiota transplant (FMT), to explore their influence on the efficacy and toxicity of co-administrated chemotherapeutic agents, immunotherapeutic agents and anti-inflammatory drugs 183 . The potential benefits of probiotics and FMT to increase the efficacy of pembrolizumab in the treatment of PD-1 resistance patients 184 and to reduce the adverse effects of aspirin 185 and irinotecan 186 are currently under clinical investigation.

Besides well-known influences on the microbiota from antibiotics and probiotics, influences from other types of drugs or natural products are very limited. Although evidence of gut microbiota-mediated DDIs remain limited, the growing interest in microbiota will definitely provide a better understanding on their influence on the PK and pharmacodynamics of drugs. Nevertheless, the impact of herbal medicine on the gut microbiome is unavoidable, and such research is expected to provide more in-depth understanding on herb–drug interactions. In summary, in addition to consideration of classical PK and pharmacodynamic interactions, microbiota-mediated drug–drug/herb–drug interactions are expected to bring additional insight into their therapeutic effects.

3.5. Summary

Investigation of herb–drug interactions (HDIs) is often more complicated than that on DDIs, due to the complex herbal components and the batch-to-batch variation of herbal products. More pharmacokinetic and pharmacodynamic data on the bioavailable herbal components from clinical studies using standardized herbal products are warranted for better understanding of HDIs. With the increasing number of therapeutic biologics in the market, it is critical to build strategies and regulations on the potential DDIs involved biologics. Based on the current findings on pharmacokinetic- and pharmacodynamic-based DDIs of therapeutic biologics, assessments on the modulation of CYP activity and immunogenicity, and identification and monitoring of clinical endpoints of the therapeutic biologics is recommended. In addition to consideration of classical PK and pharmacodynamics interactions, microbiota-mediated HDIs/DDIs are expected to bring additional insight into their interactions. Novel experimental and computational strategies, such as gnotobiotic animal models and physiologically-based pharmacokinetic modeling can be incorporated in future investigations on microbiota-mediated HDIs/DDIs.

In summary, the incidence of interactions between various therapeutics is high in patients taking multiple drugs and dietary supplements. Although DDIs between small molecule drugs are relatively well-characterized, other potential interactions are not fully explored. It is essential to develop efficient strategies for the investigation of the interactions between drugs and herbs, and between therapeutic biologics. Furthermore, the growing knowledge on the microbiota as therapeutic targets and as a site of drug metabolism leads us to pay more attention to microbiota-mediated interactions when examining potential DDIs and HDIs.

4. Disease–drug interactions

Understanding disease–drug interactions is clinically important due to the risk of treatment failure and the incidence of adverse reactions. An accumulation of strong research evidence indicates that disease–drug and drug–disease interactions can have a profound effect on the response to a medication, yet most of the existing results are only from animal models. Moreover, there are differences between animal disease models and human diseases 187 . Differences between different species should be also taken into account. In recent years PBPK modeling has gradually been applied to the prediction of disease–drug interactions 188 , 57 . However, further clinical study or real-life experience is needed to justify results from PBPK modeling. Additionally, the potential mechanism of disease–drug interactions remains poorly characterized. Therefore, further studies are also needed to reveal the in-depth and comprehensive mechanism involved in disease–drug interactions.

In recent years, apart from the DDI, disease–drug interactions have attracted lots of attention due to their potential impact on efficacy and safety of clinical therapy. Disease–drug interactions mainly refer to the disease itself can lead to changes in PK and pharmacodynamics of drugs, and also include the influence of alteration of endogenous substrates related to metabolism on disease status. Both effects of disease on drug metabolism and effects of metabolism regulation on diseases have the potential to increase the risk of treatment failure and the incidence of adverse reactions 189 . Although there have been some reports published on disease–drug interactions, there are still many unknown issues to be characterized. This review provides an update on the research on disease–drug interactions and offers an in-depth perspective on new strategies for the elucidation of disease–drug interactions.

4.1. Effects of diseases on drug metabolism

Disease is a vital factor affecting clinical medication. Disease changes the PK of a drug by altering the ADME process; on the other hand, disease can also change the sensitivity of the body to drugs by altering the number of receptors and their function in organs. Clinical practice should take into account the effects of a disease on a drug for the best therapeutic outcome and to avoid serious adverse reactions by adjusting the dose, the interval of administration, and the route of administration, etc. Current progress on disease effects on drug metabolism are listed in Table 5 .

Summary of the effects of specific diseases on drug metabolism.

4.1.1. Effects of diabetes on drug metabolism

Diabetes mellitus, commonly referred to as diabetes, is a group of metabolic disorders in which there are high blood sugar levels over a prolonged period. Diabetes mellitus is also a well-known risk factor for cardiovascular disease and atherosclerotic complications, especially coronary heart disease 209 . In recent years there have been many reports of the effect of diabetes on drug metabolism. Alterations in function and expression of ABC transporters at the blood–brain barrier in diabetes have been observed 210 ; for instance, it was found that the uptake of vincristine by cultured rat brain microvessel endothelial cells incubated in diabetic rat serum were higher than uptake in nondiabetic rat serum, which was related to the impairment of P-gp function and expression at the blood–brain barrier of diabetic rats 190 . Moreover, in brain cortex, STZ-induced diabetes mellitus may induce an impairment of function and expression of BCRP. The uptake of prazosin and cimetidine, two typical substrates of BCRP, was significantly increased in diabetic rats compared to uptake in non-diabetic rats 191 . However, different from the impairment of function and expression of P-gp and BCRP, diabetes may enhance MRP2 function and expression in liver, kidney and intestine, which then leads to increased excretion of sulfobromophthalein (a substrate of MRP2) via the bile, urine and intestinal perfusate 192 . Atorvastatin is a substrate of OATP1B1, an influx transporter expressed on the sinusoidal membrane of hepatocytes. Recent studies found that diabetes mellitus could enhance the hepatotoxicity and decrease exposure to atorvastatin in rats partly through upregulating hepatic Oatp2 193 , 194 .

In addition to Oatp2 , upregulation of hepatic Cyp3a also contributes to the decreased exposure to atorvastatin, simvastatin and simvastatin acid in diabetic rats 195 , 194 , 193 . Accumulated evidence shows that diabetes mellitus apparently alters the expression and activity of cytochrome P450 (CYP450) enzymes 196 , 211 . In diabetic rats, the AUC of theophylline was significantly smaller than that of normal rats because of significantly faster time-averaged total body clearance in diabetic rats, which was attributed to upregulated hepatic CYP1A2 and CYP2E1. Furthermore, diabetes mellitus could significantly increase exposure (area under the curve and peak concentration) to glibenclamide after oral administration. Data with hepatic microsomes suggested the impairment of glibenclamide metabolism and efflux in diabetic rats 197 . Accumulating evidence also has shown that diabetes increased the metabolism of CYP3A4 substrates by upregulating the function and expression of CYP3A4 in hepatic cells 198 . Interestingly, diabetes mellitus showed a tissue-specific effect on CYP3A expression and activity (induced in liver and inhibited in intestine), resulting in opposite pharmacokinetic behavior for verapamil after oral and intravenous administration to diabetic rats 212 . UGTs, the major phase II conjugation enzymes, can also be affected by diabetes mellitus. It was reported that the UGT1 family is adaptively upregulated in the diabetic gastrointestinal tract 199 . Given the essential regulatory role of the gastrointestinal site in drug disposition, such changes in UGTs may have an impact on the metabolism of therapeutic drugs and endogenous substrates.

4.1.2. Effects of liver disease on drug metabolism

There is growing evidence to suggest that many hepatic diseases can affect drug metabolism. The effect of liver disease on drug metabolism is mainly due to the alteration of liver hemodynamics and activity of liver microsomal enzymes. Local and systemic liver injuries have a major effect on the expression and activity of DMEs in the liver 213 . For example, compared to control rats, there were significant changes in pharmacokinetic profiles after administrations of rhubarb anthraquinone-extracts in CCl 4 -induced liver-injury rats. The plasma concentrations of the four pharmacokinetic markers (Rhein, emodin, aloe-emodin, chrysophanol) of rhubarb anthraquinone extract increased, which indicated that their metabolism and excretion changed after liver injury 200 . Liver failure is often associated with hepatic encephalopathy, due to dyshomeostasis of the central nervous system (CNS). One study showed that the function and expression of P-gp and BCRP decreased, while the function and expression of MRP2 increased in the brain of acute liver failure (ALF) mice 214 . The attenuated function and expression of P-gp at the BBB might enhance phenobarbital distribution in the brain and increase phenobarbital efficacy on the CNS of ALF mice 201 . In addition, ALF could enhance oral plasma exposure of zidovudine in rats by downregulation of hepatic UGT2B7 and intestinal P-gp 202 .

Fatty liver disease, also known as hepatic steatosis, is a condition where excess fat builds up in the liver. Previous research showed that valproic acid with a high-fat diet-induced fatty liver could upregulate UGTs and was accompanied by the increased expression of CAR and PPAR α 215 . Further analysis revealed that liver disease in warfarin users was associated with a significant increase in the likelihood of hemorrhage 216 .

4.1.3. Effects of heart failure on drug metabolism

Heart failure (HF) is considered an epidemic disease in the modern world affecting approximately 1%–2% of the adult population. Many CYP enzymes have been identified in the heart and their levels have been reported to be altered during HF. There is a great deal of discrepancy between various reports on CYP alterations during HF, likely due to differences in disease severity, the species in question and other underlying conditions. A recent review by Aspromonte et al. 217 has summarized a comprehensive modulation of cardiac CYP in patients with HF. In general, cardiac CYP1B and CYP2A , CYP2B , C YP2J , CYP4A and CYP11 mRNA levels and related enzyme activities are usually increased in HF 217 , 218 . On the other hand, HF plays an important role in the down-regulation of hepatic CYP involved in drug metabolism through several mechanisms which include hepatocellular damage, hypoxia, elevated levels of pro-inflammatory cytokines, and increased production of heme oxygenase-1 219 . For example, the plasma concentrations of caffeine (CYP1A2 probe), mephenytoin (CYP2C19 probe), dextromethorphan (CYP2D6 probe) and chlorzoxazone (CYP2E1 probe) were significantly elevated in patients with congestive HF 203 . It was suggested that the doses of these CYP enzymes substrates should be decreased when used in patients with congestive HF.

4.1.4. Effects of renal disease on drug metabolism

Evaluation of drug metabolism in patients with end-stage renal disease is important because these patients use a large number of medications and are at risk of adverse reactions and DDI. Previous studies found that end-stage renal disease patients had a 50% increase in the plasma warfarin S/R ratio relative to control subjects. This may be reflective of a selective decrease in hepatic CYP3A and CYP2C9 activity in renal failure 204 , 205 . Furthermore, results from a “cocktail” approach showed that the enzyme activities of CYP3A4 and CYP2C9 of patients with renal failure were selectively inhibited 220 . Therefore, if CYP34A and CYP2C9 substrates are used in patients with renal failure, the dose needs to be lowered. Although chronic renal failure (CRF) has been found to be associated with a decrease in liver CYP, the mechanism remains poorly understood. The N -demethylation of erythromycin was decreased by more than 35% ( P  < 0.001) in hepatocytes incubated with serum from rats with CRF 221 . It is speculated that the mediator(s) of uremic serum may down-regulate the CYP of normal hepatocytes. In addition, a recent study investigated the effects of adenine-induced chronic kidney disease (CKD) in rats on the activities of some XMEs in liver and kidneys. It was found that the plasma theophylline concentration was significantly increased in rats with CKD 206 . Moreover, a reduced metabolism of midazolam could be observed in rats with acute kidney injury (AKI) 207 .

4.1.5. Effects of sepsis on drug metabolism

Sepsis is the systemic inflammatory response syndrome caused by infection, which is a common complication following surgery, especially abdominal surgery, with higher mortality. It has been well documented that hepatocellular dysfunction occurs early in sepsis and contributes to multiple organ failure and ultimately death 222 . Among them, the effects of polymicrobial sepsis on the activity and gene expression of hepatic microsomal CYP450 have attracted considerable attention due to their potential disease–drug interactions in clinical therapy. It has been reported that the major hepatic CYP isoforms CYP1A1, 1A2, 2B1, 2E1 were down-regulated during polymicrobial sepsis 208 , 203 , 204 , 205 , 206 , 207 , 208 , 209 , 210 , 211 , 212 , 213 , 214 , 215 , 216 , 217 , 218 , 219 , 220 , 221 , 222 , 223 , 224 . Moreover, results from mechanistic studies show that nitric oxide (NO) and the AhR play key potential roles in down-regulation of hepatic CYP during sepsis 225 , 226 . Therefore, treatment with pharmaceutical agents that regulate or are metabolized by CYP enzymes might be approached cautiously in the septic patient.

On the other hand, early and appropriate antimicrobial treatment is the predominant intervening measure to decrease patient mortality 227 . However, the pathophysiologic changes during sepsis such as systemic capillary leak syndrome, altered shift of body fluid and hypoalbuminemia can lead to changes in pharmacokinetics/pharmacodynamics (PK/PD) parameters such as apparent volume of distribution ( V d ) 228 and clearance (CL) 229 that affect the achievement of PK targets and increase the risk of treatment failure with routine dosing. In addition, it is likely to cause low blood protein symptoms in sepsis due to the increased capillary permeability, decreased hepatic albumin synthesis and a large number of infusions 230 . Therefore, the effect of hypoalbuminemia on antibiotic PK also cannot be ignored. It is crucial to reduce patient mortality by adjusting antimicrobial doses and improving drug infusion to optimize antimicrobial therapy according to the characteristics of PK/PD during sepsis.

4.2. Effects of endogenous metabolism mediated by nuclear receptors on diseases

In recent years the regulation of endogenous metabolism mediated by nuclear receptors on diseases has received increasing attention with improvements in bioanalytical technology, especially the intervention of the various “omics”. Among them, PXR and CAR are two closely related and liver-enriched nuclear hormone receptors originally defined as xenobiotic receptors. However, an increasing body of evidence suggests that PXR and CAR also have endobiotic functions that impact glucose and lipid metabolism, as well as the pathogenesis of metabolic diseases. PXR and CAR not only regulate the transcription of drug-metabolizing enzymes and transporters, but also orchestrate energy metabolism and immune responses 231 . The cutting-edge investigations on these aspects are briefly shown in Table 6 .

Summary of endogenous substances related to diseases and nuclear receptors.

A recent study revealed that PXR ablation inhibited high-fat diet-induced obesity, hepatic steatosis, and insulin resistance 232 . These results may help to establish PXR as a novel therapeutic target, and PXR antagonists may be used for the prevention and treatment of obesity and type 2 diabetes. PXR was also reported to play a vital role in maintaining biliary bile acid homeostasis by regulating the biosynthesis and transport of bile salts 233 . Activation of the PXR pathway was associated with decreased lithocholic acid-induced cholestasis in mice 241 . PXR may be developed as a therapeutic target for cholesterol gallstone disease. Interestingly, study has revealed a function of PXR in enlarging liver size and changing liver cell fate by activation of the yes-associated protein (YAP) signaling pathway. This has implications for understanding the physiological functions of PXR 242 . In addition, PXR plays an important endobiotic role in adrenal steroid homeostasis. Activation of PXR markedly increased plasma concentrations of corticosterone and aldosterone 234 . These results suggest that PXR is a potential endocrine disrupting factor that may have broad implications in steroid homeostasis and drug–hormone interactions.

CAR has also been increasingly appreciated for its endobiotic functions in influencing glucose and lipid metabolism, with dysregulation implicated in two of the most prevalent metabolic disorders, obesity and type 2 diabetes 243 . Further study found that CAR suppresses hepatic gluconeogenesis by facilitating the ubiquitination and degradation of PGC1 α 244 . Given the metabolic benefits of CAR activation, CAR may represent an attractive therapeutic target to manage obesity and type 2 diabetes.

Nonalcoholic steatohepatitis (NASH) is common and medically significant because it is closely related to metabolic syndrome and has the potential to progress into the more harmful cirrhosis. Emerging evidence points to an important function of AhR in the uptake of fatty acids in the liver and the pathogenesis of fatty liver disease 236 . Activation of the AhR sensitizes mice to NASH by deactivating mitochondrial sirtuin deacetylase Sirt3 245 . These results suggest that the use of AhR antagonists might be a viable approach to prevent and treat NASH.

LXRs are known as sterol sensors that impact cholesterol and lipid homeostasis, as well as inflammation. The hepatic functions of LXRs are well documented and the pathophysiological role of LXRs was uncovered progressively in recent years. Activation of LXR prevents lipopolysaccharide-induced lung injury by regulating antioxidant enzymes and the implication of this regulation is pulmonary tissue protection 237 . Moreover, a recent study demonstrated that activation of LXR attenuates OA-induced acute respiratory distress syndrome by attenuating the inflammatory response and enhancing antioxidant capacity 238 .

FXR, a nuclear receptor mainly expressed in enterohepatic tissues, is a master regulator for bile acid, lipid and glucose homeostasis 246 . Emerging evidence indicates that restoration of FXR protein levels may represent a new strategy for enterohepatic and metabolic diseases. Hepatitis B virus X protein (HBx) is a hepatitis B virus protein that has multiple cellular functions, but its role in the pathogenesis of hepatocellular carcinoma (HCC) has been controversial. It was reported that transactivation of FXR by full-length HBx may represent a protective mechanism to inhibit HCC 247 . Additionally, FXR antagonism was also reported to be pivotal in attenuating obstructive cholestasis in bile duct-ligated mice 235 . These results suggest that FXR may be developed as a therapeutic target for cholesterol gallstone disease.

The tumor suppressor p53 is traditionally recognized as a surveillance molecule to preserve genome integrity. Recent studies have demonstrated that it contributes to metabolic diseases. It was found that the activation of p53 participated in promoting bile acid disposition and alleviating cholestatic syndrome by up-regulating the expression of Cyp2b10 , Sult2a1 and Abcc2/3/4 , which provides a potential therapeutic target for cholestasis 235 . In addition, p53 could attenuate acetaminophen-induced hepatotoxicity by regulating the CYPs, SULTs and MRPs, which provides a potential new therapeutic target for APAP-induced liver injury 248 .

Metabolism regulation mediated by downstream targets of the above transcriptional factors may also play an important role in diseases. For example, NAD(P)H: quinone oxidoreductase 1 (NQO1) has been reported to be a prognostic biomarker and a promising therapeutic target for patients with NSCLC due to its frequent overexpression and significantly increased activity in NSCLC. It was found that depleting tumor-NQO1 potentiates anoikis and inhibits the growth of NSCLC 239 . Furthermore, recent results from a metabolomics analysis have revealed that inhibition of cell proliferation upon NQO1 depletion was accompanied by suppressed glycometabolism in NQO1 high-expression human NSCLC A549 cells. Also, NQO1 depletion significantly decreased the gene expression of hexokinase II 240 .

4.3. Summary

Understanding disease–drug interactions is clinically important due to the risk of treatment failure and the incidence of adverse reactions. An accumulation of strong research evidence indicates that disease–drug and drug–disease interactions can have a profound effect on the response to a medication, but most of the existing results are only from animal models. In recent years, PBPK modeling has also gradually been applied to the prediction of disease–drug interactions 57 , 188 . However, further clinical study or real-life experience is certainly needed to justify the results from PBPK modeling. Additionally, the potential mechanisms of disease–drug interactions are not well-characterized. Therefore, further studies are needed to reveal the in-depth and comprehensive mechanism involved in disease–drug interactions.

5. Mathematical modeling

The application of mathematical modeling to problems in PK has a rich history in the form of pharmacokinetic modeling to explore how simulation can be used to improve our understanding of common issues not readily addressed in human pharmacology 249 . Animal models are mainly used in experimental physiology, experimental pathology and experimental therapeutics, especially in the study of new drugs. In the earliest stage of drug discovery/development, various cell-based models and animal models were used for the prediction of human PK and toxicokinetics 250 . In this section, the current status and future challenges on PBPK modeling and animal models are summarized.

5.1. The current status and challenges of PBPK modeling

As early as 1937 251 physiological parameters were introduced into pharmacokinetic parameter estimation. The term PBPK model appeared in 1977 252 . Although the PBPK method was proposed a long time ago, it was applied to support new drug development in the last decade since the mechanism of drug metabolism and transport gained clarity. Two known milestones of extensive application for industry are: 1) A PBPK review team was set up in the office of clinical pharmacology (CDER/FDA, US) because of increasing numbers of PBPK submissions in 2013 253 ; 2) PBPK guidance was released by FDA 254 and EMA 255 respectively during 2016–2018. A total of 217 PBPK submissions were reviewed by the FDA in 2016 256 . As one of the four major pharmacometric research methods 257 , the strategy of waiving clinical trials through PBPK study has been extensively accepted in western society and is gradually being accepted in China.

5.1.1. Basic concepts of PBPK

PBPK can be utilized to mechanistically understand and predict in vivo pharmacokinetic characteristics from a whole body perspective by integrating system-specific parameters (such as physiological parameters), drug-specific parameters (such as physical–chemical and mechanistic pharmacokinetic data), and specific PBPK model structure 258 . It can quantitatively describe drug concentration kinetics in the blood and each tissue through a series of mathematical differential equations, which allows it to accurately predict target tissue drug concentration as well as to understand drug absorption, distribution, metabolism, elimination, and transportation (ADMET) processes. Because it incorporates system-specific parameters into equations of each tissue, it can also be used to predict drug concentration in tissues under different scenarios, such as co-administration of enzyme inhibitor or in a specific population (hepatic- or renal-impaired patients, pediatrics, or elders), which could support new drug development strategy, clinical trial design, and improved clinical development efficiency.

5.1.2. PBPK in drug development

5.1.2.1. pk drug–drug interaction study.

As of August 2016, 60% of PBPK study cases submitted to FDA were related to drug–drug interactions (DDI) 256 . Among the three predominant DDI mechanisms, enzyme- 259 , transporter- 260 , and disease-mediated DDI 261 , 262 , enzyme-mediated DDI cases showed the best predictive performance in PBPK. Hsueh et al. 259 summarized 104 publications with DDI predictions, a total of 126 and 360 cases were reported for drug as metabolic “victim” and “perpetrator” respectively. The predictive performance of CYP3A- and CYP2D6-mediated DDI was found to be the best for new drugs as victim using the PBPK method. Two enzymes are involved in metabolism of large proportion of marketed drugs and well-established probe perpetrators are available 256 , 263 . The predictive performance was poorer for new drugs as perpetrator 259 . In order to accurately predict the quantitative effects of an enzyme inhibitor 264 or inducer 265 on a substrate, the FDA suggested the following study strategy 256 , 266 : a) Develop an initial PBPK model of enzyme–substrate based on in vitro data followed by verification using human single-dose PK data; b) develop a PBPK model of inducer or inhibitor and validate its enzyme modulation effect using in vivo (or literature data) data; c) predict the effect of inhibitor/inducer on substrate PK characteristics in humans using the PBPK model, which will support DDI study strategy or clinical trial design, especially for the dose selection; d) if a dedicated DDI was required and conducted, then the initial PBPK model will be verified and modified based on observed DDI data; e) predict other untested scenarios and validate dose selection. Following this strategy, predictive performance was summarized in report published by Hsueh et al. 259 . As stated in submitted cases to the FDA, AUCR or C max R (ratio of AUC or C max ) was estimated within the range of (0.80, 1.25) and (0.50, 2.00) for higher than 73% and 77% cases respectively. Although overall DDI of CYP-mediated interactions could be estimated well, prediction of time-dependent DDI and intestinal enzyme-mediated DDI was still challenging 256 .

Because tissue concentration can indicate efficacy or safety better than plasma concentration, it is more important to be predicted, especially for the drugs with a “disconnected” concentration in tissues compared to plasma concentration, which may be caused by significantly different distribution through transporters 267 . Unfortunately, the best prediction method theoretically, the PBPK method, showed worse predictive performance for transporter-mediated DDI compared to that of enzyme-mediated DDI, which was due to ubiquitous tissue distribution, unique cellular localization, and competing active and passive processes 268 . Furthermore, the lack of knowledge pertaining to disease- or population-specific factors makes PBPK more challenging for transporter-mediated DDI prediction. In order to accurately predict unbound and intra/subcellular drug concentrations while considering the role of a transporter, selecting appropriate in vitro (such as imaging) and in vivo experimental methods to determine tissue concentration followed by verification of PBPK model in animals may be helpful 267 . Recently, disease-mediated DDI received greater attention, especially for renal impairment affecting liver enzymes 262 . However, research on disease-mediated DDI are limited, and few PBPK cases to predict this kind of DDI have been reported 269 , 270 , and so further research to uncover the rationales behind of disease and physiological parameters is needed.

5.1.2.2. Specific population study

One of the most known characteristics of the PBPK model is that it can integrate drug-specific and system-specific parameters, which includes age, gender, disease status, and specific physiological status. This characteristic allows us to predict PK exposure changes by mechanistically changing specific parameters according to the different populations, such as pediatric, elderly, and in patients with hepatic or renal impairment. However, accurate prediction for these specific populations is still quite challenging because changes in system-specific parameters generally are not available or quantified accurately 271 . The FDA and other scientists summarized PBPK prediction strategy in patients with renal impairment 272 or hepatic impairment 273 , in the elderly 274 , pediatric 275 , fetal 276 , and pregnant patients 277 but, because of the above limits, these predictions could be utilized only to aid in clinical trial design in these specific populations rather than to waive these dedicated clinical trials without any verification in these specific populations.

5.1.2.3. Generic drug development

In comparison to the in vitro – in vivo correlation (IVIVC) method the PBPK method was advantageous because it could identify the contribution of penetration, intestinal metabolism and transport to the absorption–drug concentration–time curve. Therefore, PBPK analysis can estimate in vivo dissolution characteristics more accurately, which will be useful to guide drug development 278 , 279 . Therefore, the US FDA continuously held modeling and simulation workshops to make PBPK methods more useful in generic drug development 280 , 281 , 282 as well as suggested a research strategy for industry 283 , 284 . Additionally, physiologically-based oral absorption modeling can be utilized to guide Quality by Design (QbD) and predict food effects, effect of acid-reducing agents, SUPAC activities, and to influence label language. Although it was potentially powerful, its application is still limited because of physiological information missing in PBPK system models. The European OrBiTo (Oral Biopharmaceutical Tool) Project results showed that less than 50% of drugs could receive 2-fold error prediction performance using the PBPK modeling method 285 . Modified in vitro experiment data with more similarities to in vivo status and accurate physiological parameters affecting the rate-limiting absorption process may be able to improve its predictive performance.

5.1.2.4. Other applications and trends of PBPK modeling methods

In addition to the above applications, the PBPK modeling method also could be used to predict first-in-human PK profiles 286 . It may be helpful for those drugs with nonlinear metabolism characteristics. Recently, a semi-PBPK model (or minimal PBPK model) 287 , 288 was reported to extensively survey human biologics PK profiles to assess the predominant clearance site and dynamically describe system plasma concentrations and two other virtual compartments, lumped tissues with continuous and fenestrated vascular endothelium. This semi-PBPK model structure could allow investigators quickly estimate PBPK parameters using system drug concentrations considering drug-receptor binding in systems as well as in tissues, as described in two recent reviews 289 , 290 .

The PBPK modeling method is not an independent modeling method, and sometimes it is better to be integrated with other modeling methods for better results. In order to understand PK characteristics in mechanism, allometric scaling 291 and in vitro–in vivo extrapolation methods 292 can also be used to analyze preclinical data and compare the results with human data, which can provide more key information from different angles to develop a PBPK model more accurately indicating the real disposition process in humans 293 . Taking advantage of the PBPK ability to predict drug tissue concentration, a PBPK-PD model could be developed to capture pharmacodynamic characteristics in a more accurate way with more understanding of the mechanism 294 , 295 , which is helpful for those drugs with significantly inconsistent exposure between system and targeted tissues. For a new moiety entity clinical development, verification of an established PBPK model based on human data with the specific ADMET mechanism is required, which may need an additional clinical trial. Recently, global development is going to become routine strategy, and ethnic differences in PK characteristics will be important. Therefore, PBPK could support evaluation of ethnic differences by its unique contribution to the mechanistic understanding 296 . Because population PK (PopPK) is routinely used to identify the key factors affecting PK profiles followed by quantifying these key factors, a PopPK study could verify PBPK simulations under some extreme scenarios, which may allow sponsors to waive some dedicated clinical trials (PBPK-PopPK strategy) 297 . Under many scenarios, we only pay attention to drug concentration in tissues related to PK, PD, or safety characteristics, so we don't need to accurately capture drug kinetics in other tissues. Therefore, in order to increase parameter reliability without a decrease in PBPK power, we could shrink the typical PBPK model integrating each tissue in humans to a semi-PBPK model integrating necessary target tissues and replace other tissues with one or two compartments.

Along with the coadministration of herbal or natural products, the potential herb–drug interaction is gaining increasing attention, and can be predicted using a PBPK modeling method. But accurate prediction of herb–drug interactions is still a challenging mission because of the complex composition and relatively limited knowledge of individual constituents that produce the interactions. A feasible procedure is to firstly identify the major constituents followed by compound–compound interaction prediction as previous introduced 158 , 298 . The major concern with this procedure is to prove that the interaction of major constituents is similar to that of the whole herb.

5.2. Summary

In summary, PBPK can be utilized to mechanistically understand and predict a priori in vivo pharmacokinetic characteristics from a whole body perspective by integrating system-specific and drug-specific parameters. PBPK modeling has been routinely conducted for new entities to illustrate pharmacokinetic characteristics when drug–drug interactions happen or when dosing in specific populations needs optimization. The predictive performance of CYP3A- and CYP2D6-mediated DDI was found to be best for new drugs as victim using PBPK method, which could be applied to waive part of clinical trial. Due to unclear changes in transporter-mediated mechanism and system-specific parameters in specific populations, PBPK modeling power is limited to supporting clinical trial design.

6. Novel animal models for DMPK studies

Animal models are mainly used in experimental physiology, experimental pathology and experimental therapeutics, especially in the study of new drugs. In the earliest stage of drug discovery/development, various cell-based models and animal models were used for the prediction of human PK and toxicokinetics 250 . The common laboratory animals for DMPK include rats, rabbits, dogs, monkeys, etc. However, with the development of gene editing technology, animal models of special ADME genes are needed to better study the mechanisms of DMPK, including the metabolic pathway and its regulatory mechanism.

6.1. Conventional transgenic animal models for DMPK research

Traditional animal models are constructed by homologous recombination in embryonic stem cells. This method implements foreign gene knock-in, but the recombination efficiency is very low, and the recombinant site has certain randomness 299 . In 2009, the discovery and application of nucleic acid engineering enzymes greatly advanced gene knock-in technology 300 . Zinc-finger nucleases (ZFNs) are the first nucleic acid engineering enzymes to be discovered 300 . They cleave DNA at specific sites to form double-strand breaks (DSBs), which are then repaired by cell homology and used as templates by exogenous donor DNA. The repair of DSBs result in knocking out the foreign gene 300 . Another engineering nuclease that was subsequently discovered for gene editing is transcription activator-like effector nucleases (TALENs) 300 , 301 . Since the 1990s, Cyp knockout (KO) mice have been successfully constructed using gene KO techniques, such as Cyp1a2 , Cyp2e1 , Cyp2c9 , Cyp3a4 and Cyp2d6 302 , 303 , 304 , 305 . In recent years some of mouse models have been used to study the DMPK of drugs under specific Cyp knockout conditions. To overcome the differences in subtype composition, protein expression, catalytic activity and substrate specificity between mouse and human CYP enzymes, scientists have built humanized animal models to better evaluate drug metabolism characteristics of human CYPs. For example, in 2007 humanized Cyp1a1/2 mice were constructed for a toxicology study 306 . Humanized Cyp2c19 mice for drug metabolism 307 , humanized Cyp3a4 mice for drug interactions 308 , and humanized Cyp2d6 mice for drug interactions 309 were reported in 2008, 2011 and 2012, respectively. In 2012, Cyp2c knockout mice and Cyp2c9 humanized mice were generated for drug metabolism and drug interaction studies 304 . In 2015, humanized Cyp2b6 mice were also constructed for drug metabolism 310 .

Both Cyp gene KO and humanized mouse models have been constructed by traditional knockout techniques, i . e . homologous recombination of foreign DNA fragments with genes of the same or similar sequence in the host genome, thus replacing the corresponding gene sequences in the genome of the recipient cells and integrating them into the host. In the cell genome, the key technologies of this method include the acquisition of embryonic stem cells, the design of target, and the screening of embryonic stem cells. Homologous recombination is time-consuming, costly, as well as inefficient in gene editing, and may lead to adverse mutations. As it is difficult to obtain and culture embryonic stem cells in rats, the construction and application of knockout or knock-in rat models have lagged behind the mouse models. Rats are a rodent model animal widely used in DMPK and have many advantages over mice, such as larger size, easy manipulation, high tolerance to blood volume loss and large sample size. Moreover, rats in certain physiological and pathological states such as diabetes and breast cancer, are closer to humans than mice 311 , 312 . Therefore, it is particularly urgent to construct novel rat models of DMPK-related genes through KO and humanization.

6.2. Novel CRISPR/Cas9-based animal models for DMPK research

The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated 9 (Cas9) system, as the third generation of artificial nuclease technology, provides a promising tool for genetic engineering. It offers an efficient approach to develop genetically modified animal models and a potential strategy for targeted gene therapies. The CRISPR/Cas9 system allows simultaneous digestion of multiple targets at multiple sites in the same cell, making it possible to knock out or knock in multiple genes. CRISPR/Cas9 as a new gene editing technology has many characteristics and advantages, including high targeting accuracy, simultaneous knockout of multiple sites of target genes, simplicity of operation and no species restriction. In recent years, CRISPR/Cas9 has been applied to the study of drug absorption, disposition, metabolism and excretion, as well as the preparation of ADME animal models.

Today CRISPR/Cas9 technology enables DMPK scientists to develop better and more predictable ADME models in vitro and in vivo , especially to study ADME genes that have not been fully explored previously. Most published papers of CRISPR/Cas9-mediated ADME describe CYP drug metabolic enzymes and ABC drug transporters. For example, in 2016, the rat Cyp2d gene locus (containing Cyp2d1-5 ) was knocked out and replaced with human CYP2D6 in Wistar rats, but a functional characterization was not reported 313 . In the same year the rat Cyp2e1 gene was knocked out in Sprague Dawley rats, and the KO rats were physiological normal and lost the expression and function of the CYP2E1 enzyme 314 . In 2017, Cyp3a1 and Cyp3a2 double KO rats were generated by CRISPR/Cas9 technology 315 , and Cyp2c ( Cyp2c6 , Cyp2c11 and Cyp2c12 ) genes were also knocked out in rats 316 . Finally, Cyp2c11 gene was knocked out in Sprague Dawley rats 317 . In vitro and in vivo metabolic studies of the CYP substrates indicated that the target CYP isoform was functionally inactive in all KO rats 314 , 315 . It should be noted that KO models resulted in the compensatory regulation of other CYP isoforms involved in drug metabolism 314 , 315 . However, the potential mechanisms of these compensatory changes remain unclear. In addition, these KO models showed some differences, such as changes in serum testosterone concentrations 315 or alkaline phosphatase 314 . Some of these differences can be attributed to the deficiency of CYP functions, such as CYP3A-mediated testosterone metabolism. Therefore, these physiological changes in KO rats should be considered when comparing ADME data from KO models with data from wild-type rats. In addition to the rat KO models, a Cyp2b9/10/13 KO mouse model was also generated via CRISPR/Cas9 technology 318 . It is interesting that there were no significant compensatory changes in other CYP isoforms in Cyp2b KO mice, which may be due to low CYP2B hepatic expression, especially in male mice 318 . In 2019, a novel MDR1 ( Mdr1a/b ) double-knockout rat model was generated in Sprague Dawley rats by the CRISPR/Cas9 technology 319 . The loss of MDR1 function significantly increased digoxin uptake in Mdr1a/b − / − rats. The MDR1 KO rat model is of great significance to study the function of MDR1 in drug transport, toxicity and drug resistance.

6.3. Summary

In summary, genome editing based on CRISPR/Cas9 has been identified as a breakthrough technology in constructing animal models. Novel animal models are not only conducive to the basic research of human diseases, but also can be used to study the molecular mechanisms of drug pharmacodynamics, toxicity and clinical use. Furthermore, DMPK animal models will promote the study of DMPK mechanisms and strengthen the relationship between drug metabolism and pharmacology/toxicology. For example, the potentials and mechanisms of DDI between erlotinib and docetaxel was studies by using Cyp3a1/2 KO rats 320 . Docetaxel significantly increased the maximum concentration and systemic exposure of erlotinib in wild type (WT) rats, but the DDI was significantly attenuated in Cyp3a1/2 KO rats, suggesting that the CYP3A plays the perpetrating role of docetaxel on erlotinib.

7. Non-classical xenobiotic metabolic pathways

Drug metabolism or drug biotransformation is the process by which xenobiotics are enzymatically modified to make them more readily excretable and eliminate pharmacological activity. Drug metabolism is the prominent process in drug disposition. Understanding the metabolic fate and the corresponding enzymes are important with regard to metabolite toxicity and drug–drug interaction risks. Detailed data from drug metabolism studies aid in the drug clinical practice and drug design and modification. Over the past decades the basic mechanism and rules of drug metabolism, especially mediated by CYP, have been clarified. The strategies and approaches used for drug metabolism investigations have come to maturity and industrialization. Recently, with the rapid development of the separation technology and qualitative techniques, such as IMS-TOF/MS or novel 2D NMR technology, and the considerable amount of attention directed at non-CYP enzymes, several undesirable drug metabolites have been identified, and novel metabolic reactions were discovered. Some outwardly rational reactions are newly described based on the novel understandings of the mechanism underlying common biotransformations. This section briefly reviews a series of cases of novel metabolic reactions and pathways to provide readers new insights into investigations on drug metabolism.

7.1. Oxidative pathways

Oxidative pathways, including sp 3 -hybridized C -hydroxylation, unsaturated C -oxidation, N -dealkylation/deamination, O -dealkylation, S -dealkylation, N -oxidation, S -oxidation, and oxidative cleavage of esters and amides classified by functional groups are the most common biotransformations. In recent years some unexpected oxidative reactions or pathways have been reported.

Aromatic ring-containing drugs are most common and generally metabolized by P450-mediated π -electron oxidations to form an arene-epoxidized intermediate. The latter undergoes a hydride shift spontaneously to produce stable phenol metabolite(s). However, for some specific structures, unstable epoxides are preferentially attacked by nucleophilic substances, thereby leading to reactive intermediate-related covalent attachments. For example, for cocaine, the covalent adducts of biological thiols are first characterized 321 . In vitro investigations revealed that CYP1A2, 2C9, and 2D6 catalyze the formation of a reactive epoxide intermediate from the oxidation of the cocaine phenyl moiety ( Fig. 3 A). Although an aryl moiety is generally considered a stable functional group, epoxide ring opening is attacked by nucleophilic thiolates, such as N -acetylcysteine or glutathione, for cocaine.

Figure 3

Cases of some unusual metabolic pathways of oxidation, including: (A) proposed mechanism for cocaine metabolism to thiol-related adduction, and (B) Baeyer–Villiger oxidation mediated by FMO5.

Carbon–carbon cleavage and formation reactions are rare in xenobiotic metabolism. Recent studies have focused on the roles of flavin-containing monooxygenases (FMOs) to catalyze unexpected Baeyer–Villiger oxidations, which is a kind of carbon–carbon bond cleavage reaction. E7016, a potential anticancer agent with a 4-hydroxypiperidine moiety was confirmed to be a substrate of FMO5 322 . The generation of the major ring-opened hydroxyl-carboxylate metabolite was proposed by a three-step reaction, as follows: dehydrogenation of the secondary alcohol on the parent drug to form piperidine-4-one, followed by insertion of an oxygen atom to form a lactone via the Baeyer–Villiger oxidation, and further CEs-mediated hydrolysis. Recently, the 2,3-dihydropyridin-4-one (DHPO) ring in MRX-I (an analog of the antibiotic linezolid) was also reported to undergo a similar carbon–carbon cleavage reaction in humans 323 . However, different from piperidine-4-one, Baeyer–Villiger oxidation of the DHPO ring forms an enol lactone and is further hydrolyzed to an enol, which can be transformed to an aldehyde intermediate by enol–aldehyde tautomerism. The aldehyde intermediate underwent either oxidation catalyzed by short-chain dehydrogenase, aldehyde ketone reductase, and aldehyde dehydrogenase (ALDH) or reduction mediated by ALDH to generate the observed directed DHPO ring-opening metabolites MRX459 or MRX455-1, respectively ( Fig. 3 B). H 2 18 O experiments were conducted to elucidate the mechanism underlying the formation of the two metabolites.

7.2. Reductive metabolic pathways

The majority of in vivo biotransformations are oxidation, while reductive reactions preferentially occur in anaerobic or low-O conditions. A considerable number of the same enzymes that catalyze oxidative metabolism, such as P450s, aldo-keto reductase, carbonyl reductase, xanthine oxidase, aldehyde oxidase, and quinone oxidoreductase, can also be involved in reductions. Under the catalysis of some specific enzymes or the involvement of reducing agents, some uncommon reductive metabolic pathways are observed.

NADPH-cytochrome P450 reductase (POR) and cytochrome-b5 is crucial for P450 electron transporter chain integrity because they donate electrons to P450s from NADPH. Thus, most marketed recombinant P450 enzymes generally contain cytochrome-b5 and POR to enhance their oxidative efficiencies. In some cases, POR alone can also catalyze one-electron reduction, such as with aristolochic acid 324 . Another reported substrate of POR is an aldehyde intermediate (M-CHO) that is formed during the metabolism of imrecoxib, which is a moderate COX-2 inhibitor 325 . POR expresses dual effects on further M-CHO metabolism, namely oxidation to form carboxylic acid metabolite (M2) and unexpected reduction to form a hydroxymethyl metabolite (M1), by donating electrons to P450s or competitively to the substrate, respectively ( Fig. 4 A). The two opposite metabolic pathways, especially M-CHO reduction, led to an underestimation of the amount of M2 in static in vitro incubations.

Figure 4

Instances of some unusual metabolic pathways for reduction, hydrolysis, and conjugation, including: (A) formation mechanism for M1 and M2, the major imrecoxib metabolites in humans, (B) hydrolysis pathways of vicagrel in humans, and (C) N + -glucuronidation of morinidazole.

7.3. Hydrolysis pathways

Many drugs with specific functional moieties, including esters, amides, thioesters, epoxides, sulfates, and glucuronides can be metabolized by adding water. Hydrolysis is generally carried out by the corresponding enzymes, such as esterase or amidases. Prodrug design has received increasing interest, thereby leading to considerable attention to the important roles of hydrolytic metabolism. Some novel hydrolytic enzymes also catalyze undesirable reactions.

For example, arylacetamide deacetylase (AADAC) is a serine hydrolase expressed in human liver and intestine that is rarely reported compared with other hydrolytic enzymes (CEs and paraxonase). Only one AADAC isoform is present in humans. AADAC is identified as a lipase that is capable of hydrolyzing endogenous cholesterol ester 326 ; however, it has been recently found to be responsible for some clinical drugs, such as prasugrel 327 and vicagrel 328 . Different from clopidogrel, the thiolactone metabolite of vicagrel is formed via a rapid hydrolysis before intestinal absorption 329 . The first activation step for vicagrel was initially believed to be mediated only by human intestine CES-2 (CES2) until a recent finding showed that AADAC also contributed to vicagrel hydrolysis ( Fig. 4 B). The activation of the parent drug before entering the systemic circulation guarantees short onset time and avoidance of “clopidogrel resistance” attributed to CYP2C9 gene polymorphisms.

Another case of hydrolytic enzymes newly identified is dipeptidyl peptidases (DPPs), which can catalyze the hydrolysis of cyanopyrrolidine DDP-4 inhibitors. Generally, a nitrile group in the drug structures prevents metabolism because of its well-known inertness, and as a result, a nitrile moiety is increasing introduced as a block on metabolically labile sites in drug design 330 . However, for vildagliptin, anagliptin, and besigliptin (not saxagliptin), the biotransformation of the nitrile group into carboxylic acid is the major metabolic pathway in vivo by the DPP family such as DPP-4, DPP-2, DPP-8, DPP-9, and fibroblast activation protein- α 331 . Among them, DPP-2 has the highest hydrolytic capacity after DPP-4. However, other substrates containing a nitrile group, such as lacosamide and flutamide, cannot be hydrolyzed by DPPs probably because the nitrile moiety in these structures cannot be positioned in the catalytic triad of Asp-His-Ser of DPPs.

7.4. Conjugation pathways

Generally, conjugation pathways involve the addition of an endogenous hydrophilic group to a drug or its metabolite(s), including glucuronidation, sulfation, glutathione conjugation, amino acid conjugation, acetylation, and methylation. Conjugation generally introduces polar groups to facilitate drug excretion, except for methylation and acetylation. Although this finding is true for many cases, several unusual conjugative reactions were reported in recent years.

The substrates for glucuronidation generally have an OH ( i . e ., alcohols, phenol, and carboxylic acids), amino ( i . e ., aliphatic tertiary amine, aromatic primary amine, and sulfonamide) or thiophenol group. In general, for drugs possessing both tertiary amine and hydroxyl groups, O -glucuronidation is always formed preferentially over N -glucuronidation. However, a reversible regioselectivity is observed in the conjugative metabolism of morinidazole in humans, where glucuronidation prefers the tertiary nitrogen of the morpholine ring to the aliphatic hydroxyl group at the side chain of morinidazole ( Fig. 4 C) 332 . Additionally, molecular modeling studies indicated that the regioselectivity for morinidazole glucuronidation is unrelated to steric hindrance. UGT1A4, as well as UGT1A3 and 2B10, are often considered enzymes that play important roles in N + -glucuronidation 333 , 334 , 335 . However, according to the morinidazole experience, UGT1A9 can be identified as a new UGT isoform specializing in tertiary aliphatic amine N -glucuronidation.

In addition, several novel conjugates, including carnitine conjugation to cyclopropanecarboxylic acid 336 creatinine conjugation to andrographolide 337 , and phosphoethanolamine conjugation to pimasertib 338 , recently have been discovered. The combination or further modification of the common conjugation process has been also reported 339 , 340 .

7.5. Summary

In recent years there has been an increased effort to better understand the role of enzymes beyond P450, UDP-glucuronosyltransferase, and aldehyde oxidase in drug metabolism. Recently, several biological enzymes responsible for endogenous substrate catalysis, such as dipeptidyl peptidases and arylacetamide deacetylase, are newly proven to have additional capabilities in drug transformation. Drugs that rely on these non-P450 enzymes for their in vivo clearance, however, usually undergo non-classical metabolic pathways. The basic mechanism and rules of drug metabolism cannot be characterized based on the structures of the drugs alone, because the presence of metabolic intermediates that would allow for the intra-molecular rearrangement are likely factors in unusual metabolite formation. This subtle but potentially significant hypothesis suggests that the electron or radical-mediated modulation of biotransformation characteristics may represent uncommon underlying mechanisms for undesirable metabolic pathways, with relevant toxicological consequences.

Several novel and unusual reactions and pathways have been reviewed. Most of these reactions are attributed to (I) metabolic intermediate formation and rearrangement and (II) the involvement of novel metabolic enzymes, especially non-P450s. Considering the availability of sophisticated and sensitive analytical instrumentation, as well as the introduction of modern approaches in drug metabolism investigation, new metabolic reactions continue to be discovered. Accurately predicting drug metabolism in an empirical manner and clarifying the metabolism mechanisms responsible for drug adverse reactions and drug–drug interactions will increase in the future. Additionally, valuable inspiration may be provided for rational drug design and modification with the expansion of metabolic enzymes, many of which are recognized as new therapeutic targets.

8. Conclusions and perspectives

DMPK research is essential for understanding the efficacy and safety of medications. Integrated studies on drug-metabolizing enzymes and transporters underlying the ADME processes as well as their transcriptional and posttranscriptional regulation mechanisms provide a comprehensive understanding of interindividual variations in pharmacotherapy. Future studies in these areas will undoubtedly advance our understanding to achieve better prediction of PK properties. Understanding the DDIs and disease–drug interactions is clinically important as such interactions may increase the risk of adverse reactions or lead to treatment failure. Although DDIs between small molecule drugs are relatively well-characterized, other potential interactions are not fully explored, including interactions with herbal biologics and other new forms of therapeutics. Furthermore, more attention should be paid to the microbiota-mediated drug interactions when examining potential DDIs and HDIs. There is emerging evidence indicating that disease–drug interactions can have a profound impact on the therapeutic outcomes. Further studies are needed to reveal the critical mechanisms by which disease–drug interactions are produced. While the benefits of PBPK are obvious for clinical trials, it is better to integrate PBPK with other modeling methods and consult experimental findings to design clinical trials in support of new drug development. Novel animal models such as those created through CRISPR-Cas9-based gene editing techniques should be an invaluable addition to current tools for PK studies. With the application of sensitive and accurate analytical instruments and technologies, many new metabolic reactions and biotransformation pathways have been and will be discovered. Predicting drug metabolism more accurately and clarifying the metabolic mechanisms responsible for adverse drug reactions and DDIs will become possible in the future. Collectively, DMPK research awaits further innovation and mechanistic studies while DMPK remains a critical component in drug development, and is essential for practicing precision medication.

Acknowledgments

This work was supported by National Natural Science Foundation of China (grants: 81573489, 81522047, 81730103, 81320108027, 81660618, and 81773808), the National Key Research and Development Program (grant: 2017YFE0109900 and 2017YFC0909303, China), the 111 project (grant: B16047, China), the Key Laboratory Foundation of Guangdong Province (grant: 2017B030314030, China), Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (2017BT01Y093, China), National Engineering and Technology Research Center for New drug Druggability Evaluation (Seed Program of Guangdong Province, 2017B090903004, China), Natural Science Foundation of Guangdong (grant: 2017A030311018 and 2015A030313124, China), and National Institutes of Health (grants No. R01CA225958 and R01GM113888 to Ai-Ming Yu, USA).

Peer review under responsibility of Institute of Materia Medica, Chinese Academy of Medical Sciences and Chinese Pharmaceutical Association.

Appendix A Supporting data to this article can be found online at https://doi.org/10.1016/j.apsb.2019.10.001 .

Appendix A. Supplementary data

The following is the supplementary data to this article:

Medical Xpress

Medical Xpress

Crash diets may work against you, and could have permanent consequences

Posted: January 3, 2024 | Last updated: January 3, 2024

Those trying to kick-start their weight loss or perhaps wanting to lose a few pounds before a big event or holiday may be tempted to try a crash diet. While it's true that in order to lose weight you need to eat fewer calories than your body uses each day, in reality crash diets may actually work against you—and may make weight loss more difficult.

Crash diets have been around for years, but have stayed popular more recently thanks to influencers and social media. Typically, these diets involve drastically reducing calorie intake to 800–1,200 calories a day for a few weeks at a time. Proponents of these diets claim it can lead to rapid weight loss , which may explain why they have such a significant appeal.

Indeed, research has shown these diets can actually be very effective for certain people.

In a study of 278 adults with obesity, a 12-week crash diet of 810 calories a day led to greater weight loss after 12 months than people who only reduced their calories by portion control. The crash diet group lost an average of nearly 11kg versus only 3kg in the moderate diet group.

Similarly, one study showed that very low-calorie diets may be beneficial for people with type 2 diabetes. The researchers found that 60% of participants who ate 600 calories a day for eight weeks were able to put their type 2 diabetes into remission. They also lost around 15kg on average.

A follow up at 12 weeks showed participants put around 3kg back on—but, importantly, their blood sugar levels remained similar.

But while these diets may lead to short-term weight loss success in some people, they can have the long-term consequence of damaging your metabolism. This may explain why around 80% of diets fail—with the person ultimately putting all the weight they lost back on , or even gaining more weight than they lost .

Crash diets and metabolism

Your metabolism is the sum of all chemical reactions in the body. It's responsible for converting the food we eat into energy, and storing any surplus energy as fat. Your metabolism is affected by many things—including diet, exercise and your hormones. Crash diets affect all these components.

With a crash diet, you consume far less food than normal. This means your body doesn't need to use as much energy (calories) to digest and absorb the foods you've eaten. You also lose muscle . All of these factors lower metabolic rate —meaning the body will burn fewer calories when not exercising.

In the short-term, crash diets can lead to feelings of tiredness , which makes doing any activity (let alone a workout) challenging. This is because less energy is available—and what is available is prioritized for life-sustaining reactions.

In the long term, crash diets can change the hormone makeup of our bodies. They increase our stress hormones, such as cortisol . And over an extended period of time, typically months, high cortisol levels can cause our body to store more fat .

Crash diets can also reduce levels of the hormone T3 , which is produced by the thyroid gland. It's critical in regulating our basal metabolic rate (the number of calories your body needs in order to sustain itself). Long-term changes in T3 levels can lead to hypothyroidism and weight gain .

Together, all these changes make the body more adept at putting on weight when you begin consuming more calories again. And these changes may exist for months, if not years .

Gradual dieting

If you're trying to lose weight, the best strategy to use is following a long-term, gradual weight loss diet.

Gradual diets have been shown to be more sustainable and have a less negative impact on your metabolic rate compared with crash diets. Gradual diets can also help maintain energy levels enough to exercise , which can help you lose weight.

These types of diet also preserve the function of our mitochondria —the calorie-burning powerhouses in our muscles. This creates a greater capacity for burning calories even after we finish dieting.

The ideal diet is one that reduces body weight by around 0.5 to 1kg a week . The number of calories you'll need to eat per day will depend on your starting weight and how physically active you are.

Eating certain foods can also help maintain your metabolism while dieting.

Fats and carbohydrates use fewer calories to power digestion, compared with protein. Indeed, high-protein diets increase your metabolic rate 11%–14% above normal levels , whereas diets high in carbohydrates or fats can only do this by 4%–8% . As such, try to ensure around 30% of your day's calories are made up of protein when trying to lose weight.

High-protein diets also help you feel fuller for longer. One study found that when a participant's diet consisted of 30% protein, they consumed 441 calories less over the 12-week study period compared with a 15% protein diet. This ultimately led to 5kg weight loss, of which 3.7kg was fat loss.

While it may be tempting to crash diet if you're trying to lose weight fast, it could have long-term consequences for your metabolism. The best way to lose weight is to slightly reduce the number of calories you need per day, exercise, and eat plenty of protein.

This article is republished from The Conversation under a Creative Commons license. Read the original article .

Provided by The Conversation

Credit: Pixabay/CC0 Public Domain

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  17. Research articles

    Janel Lape Carlos T. Moraes Article Open Access 30 Nov 2023 Efferocytosis-induced lactate enables the proliferation of pro-resolving macrophages to mediate tissue repair Efferocytosis-induced...

  18. Metabolism

    Article | 26 October 2023 Manganese regulation of COPII condensation controls circulating lipid homeostasis Wang et al. report that the secretory coat protein complex COPII undergoes liquid-liquid...

  19. The truth about metabolism

    A 2011 meta-analysis published in Obesity Reviews found that consuming about 250 milligrams of epigallocatechin gallate (the amount in about three cups of green tea) helped boost metabolism enough to burn an average of 100 extra calories a day. Disclaimer:

  20. New Research Shifts Thinking on Metabolism and Aging

    Breaking down this new research and his perspective article on the findings, Dr. Rhoads describes our shifting understandings of metabolism and how it impacts chronic diseases like Alzheimer's disease as we age. Guest: Tim Rhoads, PhD, assistant scientist, Rozalyn Anderson laboratory, University of Wisconsin School of Medicine and Public Health.

  21. Metabolism

    Julia Ritterhoff & Rong Tian Review Article | 04 July 2022 The molecular and metabolic landscape of iron and ferroptosis in cardiovascular disease Since the discovery of ferroptosis a decade ago,...

  22. Metabolism linked to brain health

    A new study has found a link between metabolism and dementia-related brain measures, providing valuable insights about the disease. FULL STORY Every three seconds, someone in the world is...

  23. Metabolic Health, Mitochondrial Fitness, Physical Activity, and Cancer

    The aim of this narrative review is to examine the correlation between metabolic health, mitochondrial fitness, physical activity, and cancer. The findings of this study can contribute to a better comprehension of this intricate illness and guide the development of new research methods and clinical interventions. 2.

  24. The anabolic response to protein ingestion during recovery from

    The belief that the anabolic response to feeding during postexercise recovery is transient and has an upper limit and that excess amino acids are being oxidized lacks scientific proof. Using a comprehensive quadruple isotope tracer feeding-infusion approach, we show that the ingestion of 100 g prote …

  25. Building Community to Advance Metabolic Science

    "This new program will provide the platform from which investigators can tackle questions relating to how mitochondrial function and regulation impacts metabolism," Bennett said. "The expertise and instrumentation that the program provides in the area of mitochondrial biology fulfils an unmet research need and is anticipated to be of high ...

  26. Current trends in drug metabolism and pharmacokinetics

    1. Introduction. Pharmacokinetics (PK) is defined as the quantitative study of drug absorption, distribution, metabolism, and excretion (ADME)—i.e., the ways the body processes a drug 1 while the drug exerts its actions in the body. The scope of PK not only covers studies on healthy subjects but also includes broad research on variations under a variety of physiologic or pathologic ...

  27. A Tutorial on Skeletal Muscle Metabolism and the Role of Blood Lactate

    Purpose: The purpose of this tutorial is threefold: (a) present relevant exercise science literature on skeletal muscle metabolism and synthesize the limited available research on metabolism of the adult human speech musculature in an effort to elucidate the role of metabolism in speech production; (b) introduce a well-studied metabolic serum biomarker in exercise science, lactate, and the ...

  28. Crash diets may work against you, and could have permanent ...

    Indeed, research has shown these diets can actually be very effective for certain people. In a study of 278 adults with obesity, a 12-week crash diet of 810 calories a day led to greater weight ...