research papers on the heart

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• Osteosarcopenia and Mortality in Older Adults Undergoing Transcatheter Aortic Valve Replacement Pablo Solla-Suarez, MD, MSc; et al. Original Investigation online first has multimedia Pablo Solla-Suarez, MD, MSc; et al. Editor's Note
• Physical Activity and Progression of Coronary Artery Calcification Kerem Shuval, PhD; et al. Original Investigation online first Kerem Shuval, PhD; et al.
• Complete vs Culprit-Only Revascularization in Older Patients With MI and High Bleeding Risk Andrea Erriquez, MD; et al. Original Investigation online first Andrea Erriquez, MD; et al.
• Osteosarcopenia and Mortality After Transcatheter Aortic Valve Replacement Patrick T. O’Gara, MD; et al. Editor's Note online first Patrick T. O’Gara, MD; et al.
• Underrepresentation of Women in Revascularization Trials Celina M. Yong, MD, MBA, MSc; et al. Viewpoint online first Celina M. Yong, MD, MBA, MSc; et al.
• Fontan Junctional Rhythm Seshadri Balaji, MBBS, MRCP, PhD; et al. Viewpoint online first Seshadri Balaji, MBBS, MRCP, PhD; et al.
• Wide Complex Tachycardia in a Middle-Aged Woman With Diarrhea Matthew G. Peters, MD; et al. JAMA Cardiology Clinical Challenge online first has active quiz Matthew G. Peters, MD; et al.
• Interventions for Optimization of Guideline-Directed Medical Therapy Amber B. Tang, MD; et al. Review has active quiz Amber B. Tang, MD; et al.
• Sexual Orientation and Gender Identity Data Capture in Cardiovascular Care Brototo Deb, MD; et al. Special Communication has active quiz Brototo Deb, MD; et al. Editorial
• 23,308 Views Sex Differences in Blood Pressure Trajectories Over the Life Course
• 7,550 Views Reversals in the Decline of Heart Failure Mortality in the US, 1999 to 2021
• 6,465 Views Atrial Fibrillation Ablation in Heart Failure With Reduced vs Preserved Ejection Fraction
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• 3,403 Views Clopidogrel vs DAPT in Acute Coronary Syndromes and High Ischemic/Bleeding Risk
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• 203 Citations Prevalence of Clinical and Subclinical Myocarditis in Competitive Athletes With Recent SARS-CoV-2 Infection
• 177 Citations Inflammatory Heart Disease in Professional Athletes With Prior COVID-19 and Return-to-Play Cardiac Screening
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• 126 Citations Clopidogrel Monotherapy After 1 to 2 Months of DAPT vs 12 Months of DAPT in Acute Coronary Syndrome
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The heart plays a hidden role in our mental health.

The organ sends messages to the brain. How those signals influence it is still unclear

Messages that the heart sends to the brain could hold clues to understanding mental health disorders and what drives consciousness.

Christian Gralingen

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By Laura Sanders

May 16, 2024 at 1:00 pm

Everyone knows that the brain influences the heart.

Stressful thoughts can set the heart pounding, sometimes with such deep force that we worry people can hear it. Anxiety can trigger the irregular skittering of atrial fibrillation. In more extreme and rarer cases, emotional turmoil from a shock — the death of a loved one, a cancer diagnosis, an intense argument — can trigger a syndrome that mimics a heart attack.

But not everyone knows that the heart talks back.

Powerful signals travel from the heart to the brain, affecting our perceptions, decisions and mental health. And the heart is not alone in talking back. Other organs also send mysterious signals to the brain in ways that scientists are just beginning to tease apart.

A bodywide perspective that seeks to understand our biology and behavior is relatively new, leaving lots of big, basic questions. The complexities of brain-body interactions are “only matched by our ignorance of their organization,” says Peter Strick, a neuroscientist at the University of Pittsburgh.

Exploring the relationships between the heart, other organs and the brain isn’t just fascinating anatomy. A deeper understanding of how we sense and use signals from inside our bodies — a growing field called interoception — may point to new treatments for disorders such as anxiety.

“We have forgotten that interactions with the internal world are probably as important as interactions with the external world,” says cognitive neuroscientist Catherine Tallon-Baudry of École Normale Supérieure in Paris.

These internal signals, most of which we are wholly unaware of, may even hold clues to one of the grandest scientific puzzles of all — what drives human consciousness.

The heart pulls the brain’s strings

Coalitions of cells in the brain exert exquisite control over the heart. In some parts of the brain, more than 1 in 3 nerve cells influence the heart’s rhythm, Tallon-Baudry and her colleagues reported in 2019 in the Journal of Neuroscience . One of these brain regions, the entorhinal cortex, is famous for its role in memory and navigation. It makes sense that these two jobs — physically moving through the world and influencing heart rate — would fall to the same neurons; the tasks of seeing a jogging path and priming the heart for running are linked.

The brain bosses the heart around. But that’s not the whole story — not even close. Scientists are finding that information from the heart can boss around our brains and our behavior, too.

Each heartbeat serves as a little signal to the brain. It’s an event, much like seeing an apple or hearing the first note of a song. But unlike those external events, the heartbeat signals come from inside the body. The brain senses these internal signals. Each heartbeat prompts a reliable and measurable neural reaction that scientists call a heartbeat-evoked response, or HER.

And though this heart-initiated, neural thrumming is only on the inside, it can influence what we see in the outside world, Tallon-Baudry and colleagues have found. In one study of 17 people, messages from the heart sharpened eyesight . When certain areas of the brain responded strongly to heartbeat, creating a large HER, people were more likely to see faint gray lines around a red dot. When the HER was weaker, people were less likely to see the lines, the researchers reported in 2014 in Nature Neuroscience .

Seeing with heartbeats

Study participants were asked to look out for a hard-to-see gray circle (stimulus), while scientists measured their heartbeats (left, bottom) and brain activity (right, bottom) in the same moment (gray arrows). When the brain responded strongly to the heart rhythm, people were more likely to report seeing the gray circle.

Signals from the heart also appear to play a role in memory. In lab experiments, people were shown brief blips of words on a screen. When a word showed up as the heart was contracting, a squeezing phase called systole, people were more likely to forget the word on later memory tests, neuroscientist Sarah Garfinkel and colleagues reported in 2013 in Psychophysiology .

There are hints that the heart can influence intuitions, decision making and emotions. People who were better able to feel their hearts’ rhythms reacted more intensely to emotional images than people who were worse at sensing their heartbeat, for instance.

These results and others suggest the tantalizing possibility that our brains are taking in and using information from the heart — and perhaps other interoceptive awareness — to help us make sense of the world. But findings from people are often correlational. It’s been hard to know whether beating hearts caused the effects or whether they just happened at the same time.

A recent study in mice got around this problem in an unexpected way ( SN: 3/14/23 ). The experiment relied on a powerful technique that can control neuron behavior with light, developed in part by neuroscientist Karl Deisseroth at Stanford University. Called optogenetics, the method uses specific wavelengths of light to force cells to fire an electrical impulse ( SN: 6/18/21 ). Along with Deisseroth, bioengineer Ritchie Chen used the technique to control mice’s heartbeats with exquisitely precise timing. “We can target a specific cell without ever touching it,” says Chen, of the University of California, San Francisco.

With each flash of a light, delivered through a fabric vest worn by the mice, muscles in the heart ventricles contracted, slamming blood out of the heart and into the body. “It was incredibly exciting to see these really precise heart contractions being evoked with light just delivered through the skin,” Chen says.

The researchers then studied the brains and behaviors of mice whose hearts were set racing. An artificially fast heartbeat didn’t always affect mouse behavior, the team was surprised to learn. In some situations, the mice didn’t seem to notice. But when they encountered danger — an exposed area, where in the wild the mice would be vulnerable to predators, or a sip of water that could come with a shock — the mice behaved more anxiously when their hearts were forced to race than when their hearts beat normally.

A pounding heart “wasn’t this primal circuit to induce panic,” Chen says. The mice were integrating signals from their heart and signals from their environment to arrive at a course of action. “And that was exciting to us because it meant that the brain was involved.”

Further experiments turned up a key player in the brain: the insula. The human insula, one on each side of the brain, has been shown to have a role in emotions, internal sensations and pain. Shutting down neuron activity in the mice’s insula silenced the racing heart’s influence on behavior, the team found.

“Being able to manipulate the heart in this way,” Tallon-Baudry says, “opens all sorts of ways to look at things that are much more subtle and might not be related to anxiety at all.” The precise control of optogenetics could help researchers investigate the heart’s influence on perceptions, decisions and memory — some of the key attributes that shape how a thinking, remembering, feeling person experiences the world.

Wiring diagrams are missing

In Chen’s study, how signals moved from the heart to the insula and beyond isn’t clear. “We are very much at the beginning of circuit dissection between the brain and the body,” he says.

Still, scientists know some of the routes signals can take as they move from the heart to the brain. The textbook version goes something like this: Muscles in the heart ventricles contract, squeezing blood out. Cells in nearby blood vessels, including the aorta and carotid artery, sense the change and relay it to nerves. One of those nerves is the vagus nerve, a rambling superhighway to the brain that sends missives about heart rates, digestion and breathing ( SN: 11/13/15 ). Once the information arrives at the brain, it bounces from spot to spot in unknown ways. Our knowledge of these biological daisy chains is woefully incomplete, Tallon-Baudry says. “The full story is not so easy to get.”

Strick, the neuroscientist at the University of Pittsburgh, shares the same lament: “There are nerves that speak to the organs, and the organs speak to the brain, but we don’t know anything about the wiring diagram,” how and where these bits of crucial information actually get exchanged. And that’s an important thing to be missing. “You can say, “Who is driving whom?’ But we’re even more primitive than that. We don’t have a wiring diagram,” he says.

One way of scoping out the wiring involves, of all things, rabies virus. Years ago, Strick realized that he could use the virus to trace cell connections in the brain and body thanks to the virus’ very unusual trick: Rabies virus can hop backward from neuron to neuron, from message receiver to message sender. When designed to carry a fluorescent molecule, the virus can illuminate entire neural circuits in an animal.

That’s what Strick and colleagues have done with various organs — stomach and kidney, for instance — and the brain. Some of the most tantalizing connections he has found are between the adrenal glands, which pump out fight-or-flight hormones in an emergency, and specific brain regions, especially neural locales that control muscles.

And that’s what Strick would like to do with the heart as well. So far, he has a single glimpse of that data from a monkey. “We have one successful heart injection, and the data’s amazing,” Strick says. “The regions of the cerebral cortex that control the heart are mind-blowing. But it’s an n of 1.” This preliminary result needs to be confirmed in more animals, Strick emphasizes.

Tracing these paths would illuminate anatomical connections that undoubtedly exist. Strick and his colleagues are keen to explore more of the body, including the immune system’s spleen and the pancreas.

But another project has raised the possibility of a shortcut that jumps from heart to brain, and it was discovered by accident. Neuroscientist Veronica Egger of the University of Regensburg in Germany and colleagues were curious about the connections between nerve cells that process odors. To get a good look at the behavior of these cells, the team co-opted an ultrasimple system: a rat’s olfactory bulb, which is a part of the brain that handles smells, and the single blood vessel that supplies it with nutrients. In the experiment, an artificial pump sent fluid through the vessel.

But the experiment yielded a worrisome signal: rhythmic, collective activity in the nerve cells that seemed to be created by the pump. “Every neuroscientist knows pump artifacts and hates them,” Egger says.

But this signal, it turned out, was no artifact. It was the real deal. On a hike, Egger had a flash of insight that led to the discovery. Perhaps, she thought, the neurons were sensing the pressure caused by the pump directly.

This direct sensing is a cellular possibility. In 2021, neuroscientist Ardem Patapoutian, a Howard Hughes Medical Institute Investigator at Scripps Research in La Jolla, Calif., had received a Nobel Prize for the discovery of mechanical sensors called PIEZO1 and PIEZO2, present in many animals including humans. These sensors, which sit in cell membranes and look like three-bladed propellers, can detect pressure changes, including the inflating of lungs that comes after a deep breath, the stretch of a full bladder and the pressure of blood moving through a vessel.

Poised on neurons in the olfactory bulb, these sensors might be detecting when the pump had pushed fluid. When Egger and her colleagues analyzed the system, they found that the neurons were in fact responding to the pressure changes from the pump. Blood pushing through vessels in mice’s brains also influenced the firing activity of nerve cells elsewhere, further experiments revealed. That included the hippocampus, which is involved in memory, and the prefrontal cortex.

These effects , described in the Feb. 2 Science , aren’t large; they’re quite subtle, Egger says. “We haven’t seen this before because it’s a very weak effect.” Still, the effect seems to indicate that neurons throughout these rodents’ brains have their fingers on the body’s literal pulse — an immediate signal that doesn’t need to travel through nerves from the heart.

“It is extremely likely that human brains do this,” Egger says, though that remains to be shown. Also unclear is what the brain might do with this pulse information or how it might be used to take measure of the body’s internal state. “What the brain needs this fast pathway for is completely unknown,” she says. “We just know that it happens.”

Message delivered

Brain cells can take the heart’s pulse directly. When heart muscles squeeze (left), blood is pumped out into vessels, including those in the brain (rat brain shown, middle). In the olfactory bulb, specialized nerve cells called mitral cells (right) sense and respond to the pressure change, connecting the three rhythms (bottom lines).

Why should we listen to the heart?

With all these lines of research, the field of interoception is energized in a way it hasn’t been before, says Garfinkel, of University College London. “It’s blown my mind how much the field has changed, and how much people are embracing the idea.”

One of the reasons for the momentum is that body-brain communications might point to ways to treat disorders such as anxiety. “I do think it opens a window in understanding more about the fundamental etiology of these conditions,” Garfinkel says. “Looking at the brain, you’re looking at part of the story.”

Though Garfinkel was focused on study participants’ brain activity initially, she saw that their bodies were also responding, with racing hearts and other signs of panic. “Interoceptive numbing,” in which a person is less able to accurately sense their bodily signals, has been linked to suicide attempts . And a lessened awareness of heart activity has been tied to a poorly understood kind of seizure.

These days, Garfinkel is listening in on people’s heart-brain conversations and testing whether training people to better detect their own heartbeat could alleviate anxiety. Anyone can experience anxiety, but autistic people have higher than average rates of anxiety. In 2021 in eClinical Medicine , Garfinkel and colleagues reported that after undergoing rounds of training to better sense the rhythm of their hearts, people with autism reported being less anxious .The training procedure asked people to say whether a steady beat they listened to was the same or different from their own internal heartbeat. Over six training sessions, each lasting about half an hour, people’s accuracy improved. And their anxiety scores went down.

Garfinkel and her colleagues have since found similar results in people without autism, though those results have not yet been published.

It’s not at all clear why this training procedure might alleviate anxiety, Garfinkel says. But still, the link may point to ways to treat anxiety. In many ways, the body is easier to change than the brain, Garfinkel says. “Rather than hit people with heavy medications that change their brain, it’s intriguing and exciting to think there’s an easier route — to change the body.”

Understanding interoception may yield insights that go beyond alleviating anxiety. Some scientists, including Tallon-Baudry, suspect that signals from inside our bodies collectively help give rise to consciousness. The concept that consciousness requires a body that can be sensed and an organism striving to stay alive isn’t new, but recent interoception results have added evidence to support the idea that the body’s drive to monitor itself may be more important than previously thought.

Tallon-Baudry and her colleagues studied 68 people who had been fully unconscious. Their goal was to split these people into two groups: Those who still have no signs of consciousness, and those who had signs of consciousness in their brains. The team used HER signals, when a heartbeat prompts a neural thrum, to predict which people may have fleeting moments of consciousness but are unable to show it. “This is the moment when we do find the brain is responding to the heartbeat,” she says. These results, published in 2021 in the Journal of Neuroscience , highlight just how rich and powerful signals from the heart to the brain can be , she says.

All together now

Pacemaker cells in the heart, stomach and brain stem (controlling the lungs) and cells that can sense mechanical changes (mechanoreceptors) generate signals that can be used by the brain. These various body rhythms may contribute to a range of tasks, from perceptions to consciousness itself.

And remember that study she did that linked the HER thrum to whether a person saw a faint grid? She says that the people’s perception of the grid had a lot to do with the eyes, the visual system, but it also depended on having a perspective — a point of view. But the perception also requires a person to experience the vision, interpret it and have that point of view — the “I” in the simple sentence, “I see it.”

Interoceptive signals, and not just those from the heart, but also from the lungs, stomach, muscles, skin and more, may help create a person’s sense of self — their “I,” their identity as a conscious, aware entity with a point of view. Tallon-Baudry and colleagues described last year in Nature Neuroscience how rhythmic signals from the heart, the lungs and the stomach all converge in the brain . That review also advanced the idea that a sense of self relies on internal body signals.

Without a body and a beating heart, a stomach that can rumble and lungs that fill, the brain would be adrift. We navigate the world by seeing, hearing and touching too. We make choices to stay alive. Perhaps the real magic of consciousness comes from the combinations — of heart and brain, of the outside world and inside world, as mysterious as it may yet be.

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May 14, 2024

Anger may harm heart and blood vessel health

At a glance.

• Researchers found that brief bouts of anger can impair the ability of blood vessels to expand and contract, which might have consequences for heart health.
• Future studies will be needed to better understand the long-term effects of anger and other negative emotions on the body.

Several studies have found links between negative emotions and cardiovascular problems. The underlying mechanisms have been unclear, but impaired blood vessel function may contribute. The inner lining of blood vessels, called the endothelium, is known to help control blood vessel dilation. Previous research suggests that faulty activity of endothelial cells may be an early step leading to atherosclerosis and other heart-related disorders.

A research team led by Dr. Daichi Shimbo of Columbia University set out to learn more about potential links between negative emotions and blood vessel function. They enrolled 280 adults, ages 18 and older, in the New York City area. The average age of participants was 26. About 40% were Caucasian, 29% Hispanic/Latino, 19% Asian, and 14% Black. All were considered healthy, with no reported history of heart disease, stroke, type 2 diabetes, high blood pressure, or other serious conditions. None reported taking medications or dietary supplements.

Participants were randomly assigned to one of four groups: anger, anxiety, sadness, or emotionally neutral. Those in the anger or anxiety groups were asked to recall and talk for eight minutes about a personal memory that evoked the assigned emotion. Those in the sadness group read aloud for eight minutes a series of sentences designed to elicit sadness. And those in the fourth group repeatedly counted to 100 for the same amount of time, which controlled for potential effects of speaking.

The researchers collected several measurements before and after the emotion-related task. These included blood pressure, heart rate, and blood tests. Specialized probes placed on participants’ index fingers were used to detect changes to blood vessel dilation. The team also tested for evidence of cell injury or reduced repair capacity in blood vessels. Measurements were taken at baseline and at 3, 40, 70, and 100 minutes after the task. Results were reported in the Journal of the American Heart Association on May 7, 2024.

Participants in the anger group had significant impairment to blood vessel dilation compared to the neutral group. This impairment continued for up to 40 minutes after the anger task had ended. Blood vessel function in the anxiety group may also have been impaired, but the effect wasn’t large enough to prove it wasn’t due to chance. Blood vessel function in the sadness group was not significantly affected. The team found no significant evidence of cell injury or repair problems in any group.

The researchers propose that repeated episodes of negative emotions like anger might have a cumulative effect on cardiovascular health. Over time, ongoing anger might lead to permanent damage and increased risk for cardiovascular disease.

“We’ve long suspected, based on observational studies, that anger can negatively affect the heart,” says Dr. Laurie Friedman Donze, an NIH psychologist and program officer. “This study in healthy adults helps fill a real knowledge gap and shows how this might occur.”

“We saw that evoking an angered state led to blood vessel dysfunction, though we don’t yet understand what may cause these changes,” Shimbo notes. “Investigation into the underlying links between anger and blood vessel dysfunction may help identify effective intervention targets for people at increased risk of cardiovascular events.”

Related Links

• How SARS-CoV-2 Contributes to Heart Attacks and Strokes
• Irregular Sleep Patterns May Raise Risk of Heart Disease
• Lingering Feelings Over Daily Stresses May Impact Long-term Health
• Atherosclerosis
• Coronary Heart Disease

References:  Translational Research of the Acute Effects of Negative Emotions on Vascular Endothelial Health: Findings From a Randomized Controlled Study. Shimbo D, Cohen MT, McGoldrick M, Ensari I, Diaz KM, Fu J, Duran AT, Zhao S, Suls JM, Burg MM, Chaplin WF. J Am Heart Assoc . 2024 May 7;13(9):e032698. doi: 10.1161/JAHA.123.032698. Epub 2024 May 1. PMID: 38690710. 

Funding:  NIH’s National Heart, Lung, and Blood Institute (NHLBI).

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What to know

Learn facts about how race, ethnicity, age, and other risk factors can contribute to heart disease risk. It’s important for everyone to know the facts about heart disease.

Heart disease in the United States

In the United States:

• Heart disease is the leading cause of death for men, women, and people of most racial and ethnic groups. 1
• One person dies every 33 seconds from cardiovascular disease. 1
• About 695,000 people died from heart disease in 2021—that's 1 in every 5 deaths . 1 2
• Heart disease costs about $239.9 billion each year from 2018 to 2019. 3 This includes the cost of health care services, medicines, and lost productivity due to death.

Coronary artery disease (CAD)

• Coronary heart disease is the most common type of heart disease, killing 375,476 people in 2021. 2
• About 1 in 20 adults age 20 and older have CAD (about 5%). 2
• In 2021, about 2 in 10 deaths from CAD happened in adults less than 65 years old. 1

Heart attack

• In the United States, someone has a heart attack every 40 seconds. 2
• 605,000 are a first heart attack. 2
• 200,000 happen to people who have already had a heart attack. 2
• About 1 in 5 heart attacks are silent—the damage is done, but the person is not aware of it. 2

Did you know?‎

Who is affected

Heart disease deaths vary by sex, race, and ethnicity.

Heart disease is the leading cause of death for people of most racial and ethnic groups in the United States. These include African American, American Indian, Alaska Native, Hispanic, and White men. For women from the Pacific Islands and Asian American, American Indian, Alaska Native, and Hispanic women, heart disease is second only to cancer. 1

Below are the percentages of all deaths caused by heart disease in 2021, listed by ethnicity, race, and sex.

Race or Ethnic Group

% of Deaths

American Indian or Alaska Native

Black (Non-Hispanic)

Native Hawaiin or Other Pacific Islander

White (Non-Hispanic)

Americans at risk for heart disease

High blood pressure , high blood cholesterol , and smoking are key risk factors for heart disease.

Several other medical conditions and lifestyle choices can also put people at a higher risk for heart disease, including:

• Overweight and obesity
• Unhealthy diet
• Physical inactivity
• Excessive alcohol use

What CDC is doing

• Million Hearts ®
• CDC: Heart Disease Communications Kit
• National Heart, Lung, and Blood Institute
• National Center for Health Statistics. Multiple Cause of Death 2018–2021 on CDC WONDER Database. Accessed February 2, 2023. https://wonder.cdc.gov/mcd.html
• Tsao CW, Aday AW, Almarzooq ZI, et al. Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association. Circulation. 2023;147:e93–e621.
• National Center for Health Statistics. Percentage of coronary heart disease for adults aged 18 and over, United States, 2019—2021. National Health Interview Survey. Accessed February 17, 2023. https://wwwn.cdc.gov/NHISDataQueryTool/SHS_adult/index.html

Heart Disease

Heart disease is the leading cause of death in the United States.

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• Ole Kleist Jeppesen 5 ,
• Alexander Kokkinos 11 ,
• A. Michael Lincoff   ORCID: orcid.org/0000-0001-8175-2121 12 ,
• Sebastian M. Meyhöfer 13 ,
• Tugce Kalayci Oral 5 ,
• Jorge Plutzky   ORCID: orcid.org/0000-0002-7194-9876 14 ,
• André P. van Beek   ORCID: orcid.org/0000-0002-0335-8177 15 ,
• John P. H. Wilding   ORCID: orcid.org/0000-0003-2839-8404 16 &
• Robert F. Kushner 17  

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In the SELECT cardiovascular outcomes trial, semaglutide showed a 20% reduction in major adverse cardiovascular events in 17,604 adults with preexisting cardiovascular disease, overweight or obesity, without diabetes. Here in this prespecified analysis, we examined effects of semaglutide on weight and anthropometric outcomes, safety and tolerability by baseline body mass index (BMI). In patients treated with semaglutide, weight loss continued over 65 weeks and was sustained for up to 4 years. At 208 weeks, semaglutide was associated with mean reduction in weight (−10.2%), waist circumference (−7.7 cm) and waist-to-height ratio (−6.9%) versus placebo (−1.5%, −1.3 cm and −1.0%, respectively; P  < 0.0001 for all comparisons versus placebo). Clinically meaningful weight loss occurred in both sexes and all races, body sizes and regions. Semaglutide was associated with fewer serious adverse events. For each BMI category (<30, 30 to <35, 35 to <40 and ≥40 kg m − 2 ) there were lower rates (events per 100 years of observation) of serious adverse events with semaglutide (43.23, 43.54, 51.07 and 47.06 for semaglutide and 50.48, 49.66, 52.73 and 60.85 for placebo). Semaglutide was associated with increased rates of trial product discontinuation. Discontinuations increased as BMI class decreased. In SELECT, at 208 weeks, semaglutide produced clinically significant weight loss and improvements in anthropometric measurements versus placebo. Weight loss was sustained over 4 years. ClinicalTrials.gov identifier: NCT03574597 .

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What is the pipeline for future medications for obesity?

The worldwide obesity prevalence, defined by body mass index (BMI) ≥30 kg m − 2 , has nearly tripled since 1975 (ref. 1 ). BMI is a good surveillance measure for population changes over time, given its strong correlation with body fat amount on a population level, but it may not accurately indicate the amount or location of body fat at the individual level 2 . In fact, the World Health Organization defines clinical obesity as ‘abnormal or excessive fat accumulation that may impair health’ 1 . Excess abnormal body fat, especially visceral adiposity and ectopic fat, is a driver of cardiovascular (CV) disease (CVD) 3 , 4 , 5 , and contributes to the global chronic disease burden of diabetes, chronic kidney disease, cancer and other chronic conditions 6 , 7 .

Remediating the adverse health effects of excess abnormal body fat through weight loss is a priority in addressing the global chronic disease burden. Improvements in CV risk factors, glycemia and quality-of-life measures including personal well-being and physical functioning generally begin with modest weight loss of 5%, whereas greater weight loss is associated with more improvement in these measures 8 , 9 , 10 . Producing and sustaining durable and clinically significant weight loss with lifestyle intervention alone has been challenging 11 . However, weight-management medications that modify appetite can make attaining and sustaining clinically meaningful weight loss of ≥10% more likely 12 . Recently, weight-management medications, particularly those comprising glucagon-like peptide-1 receptor agonists, that help people achieve greater and more sustainable weight loss have been developed 13 . Once-weekly subcutaneous semaglutide 2.4 mg, a glucagon-like peptide-1 receptor agonist, is approved for chronic weight management 14 , 15 , 16 and at doses of up to 2.0 mg is approved for type 2 diabetes treatment 17 , 18 , 19 . In patients with type 2 diabetes and high CV risk, semaglutide at doses of 0.5 mg and 1.0 mg has been shown to significantly lower the risk of CV events 20 . The SELECT trial (Semaglutide Effects on Heart Disease and Stroke in Patients with Overweight or Obesity) studied patients with established CVD and overweight or obesity but without diabetes. In SELECT, semaglutide was associated with a 20% reduction in major adverse CV events (hazard ratio 0.80, 95% confidence interval (CI) 0.72 to 0.90; P  < 0.001) 21 . Data derived from the SELECT trial offer the opportunity to evaluate the weight loss efficacy, in a geographically and racially diverse population, of semaglutide compared with placebo over 208 weeks when both are given in addition to standard-of-care recommendations for secondary CVD prevention (but without a focus on targeting weight loss). Furthermore, the data allow examination of changes in anthropometric measures such as BMI, waist circumference (WC) and waist-to-height ratio (WHtR) as surrogates for body fat amount and location 22 , 23 . The diverse population can also be evaluated for changes in sex- and race-specific ‘cutoff points’ for BMI and WC, which have been identified as anthropometric measures that predict cardiometabolic risk 8 , 22 , 23 .

This prespecified analysis of the SELECT trial investigated weight loss and changes in anthropometric indices in patients with established CVD and overweight or obesity without diabetes, who met inclusion and exclusion criteria, within a range of baseline categories for glycemia, renal function and body anthropometric measures.

Study population

The SELECT study enrolled 17,604 patients (72.3% male) from 41 countries between October 2018 and March 2021, with a mean (s.d.) age of 61.6 (8.9) years and BMI of 33.3 (5.0) kg m − 2 (ref. 21 ). The baseline characteristics of the population have been reported 24 . Supplementary Table 1 outlines SELECT patients according to baseline BMI categories. Of note, in the lower BMI categories (<30 kg m − 2 (overweight) and 30 to <35 kg m − 2 (class I obesity)), the proportion of Asian individuals was higher (14.5% and 7.4%, respectively) compared with the proportion of Asian individuals in the higher BMI categories (BMI 35 to <40 kg m − 2 (class II obesity; 3.8%) and ≥40 kg m − 2 (class III obesity; 2.2%), respectively). As the BMI categories increased, the proportion of women was higher: in the class III BMI category, 45.5% were female, compared with 20.8%, 25.7% and 33.0% in the overweight, class I and class II categories, respectively. Lower BMI categories were associated with a higher proportion of patients with normoglycemia and glycated hemoglobin <5.7%. Although the proportions of patients with high cholesterol and history of smoking were similar across BMI categories, the proportion of patients with high-sensitivity C-reactive protein ≥2.0 mg dl −1 increased as the BMI category increased. A high-sensitivity C-reactive protein >2.0 mg dl −1 was present in 36.4% of patients in the overweight BMI category, with a progressive increase to 43.3%, 57.3% and 72.0% for patients in the class I, II and III obesity categories, respectively.

Weight and anthropometric outcomes

Percentage weight loss.

The average percentage weight-loss trajectories with semaglutide and placebo over 4 years of observation are shown in Fig. 1a (ref. 21 ). For those in the semaglutide group, the weight-loss trajectory continued to week 65 and then was sustained for the study period through week 208 (−10.2% for the semaglutide group, −1.5% for the placebo group; treatment difference −8.7%; 95% CI −9.42 to −7.88; P  < 0.0001). To estimate the treatment effect while on medication, we performed a first on-treatment analysis (observation period until the first time being off treatment for >35 days). At week 208, mean weight loss in the semaglutide group analyzed as first on-treatment was −11.7% compared with −1.5% for the placebo group (Fig. 1b ; treatment difference −10.2%; 95% CI −11.0 to −9.42; P  < 0.0001).

a , b , Observed data from the in-trial period ( a ) and first on-treatment ( b ). The symbols are the observed means, and error bars are ±s.e.m. Numbers shown below each panel represent the number of patients contributing to the means. Analysis of covariance with treatment and baseline values was used to estimate the treatment difference. Exact P values are 1.323762 × 10 −94 and 9.80035 × 10 −100 for a and b , respectively. P values are two-sided and are not adjusted for multiplicity. ETD, estimated treatment difference; sema, semaglutide.

Categorical weight loss and individual body weight change

Among in-trial (intention-to-treat principle) patients at week 104, weight loss of ≥5%, ≥10%, ≥15%, ≥20% and ≥25% was achieved by 67.8%, 44.2%, 22.9%, 11.0% and 4.9%, respectively, of those treated with semaglutide compared with 21.3%, 6.9%, 1.7%, 0.6% and 0.1% of those receiving placebo (Fig. 2a ). Individual weight changes at 104 weeks for the in-trial populations for semaglutide and placebo are depicted in Fig. 2b and Fig. 2c , respectively. These waterfall plots show the variation in weight-loss response that occurs with semaglutide and placebo and show that weight loss is more prominent with semaglutide than placebo.

a , Categorical weight loss from baseline at week 104 for semaglutide and placebo. Data from the in-trial period. Bars depict the proportion (%) of patients receiving semaglutide or placebo who achieved ≥5%, ≥10%, ≥15%, ≥20% and ≥25% weight loss. b , c , Percentage change in body weight for individual patients from baseline to week 104 for semaglutide ( b ) and placebo ( c ). Each patient’s percentage change in body weight is plotted as a single bar.

Change in WC

WC change from baseline to 104 weeks has been reported previously in the primary outcome paper 21 . The trajectory of WC change mirrored that of the change in body weight. At week 208, average reduction in WC was −7.7 cm with semaglutide versus −1.3 cm with placebo, with a treatment difference of −6.4 cm (95% CI −7.18 to −5.61; P  < 0.0001) 21 .

WC cutoff points

We analyzed achievement of sex- and race-specific cutoff points for WC by BMI <35 kg m − 2 or ≥35 kg m − 2 , because for BMI >35 kg m − 2 , WC is more difficult technically and, thus, less accurate as a risk predictor 4 , 25 , 26 . Within the SELECT population with BMI <35 kg m − 2 at baseline, 15.0% and 14.3% of the semaglutide and placebo groups, respectively, were below the sex- and race-specific WC cutoff points. At week 104, 41.2% fell below the sex- and race-specific cutoff points for the semaglutide group, compared with only 18.0% for the placebo group (Fig. 3 ).

WC cutoff points; Asian women <80 cm, non-Asian women <88 cm, Asian men <88 cm, non-Asian men <102 cm.

Waist-to-height ratio

At baseline, mean WHtR was 0.66 for the study population. The lowest tertile of the SELECT population at baseline had a mean WHtR <0.62, which is higher than the cutoff point of 0.5 used to indicate increased cardiometabolic risk 27 , suggesting that the trial population had high WCs. At week 208, in the group randomized to semaglutide, there was a relative reduction of 6.9% in WHtR compared with 1.0% in placebo (treatment difference −5.87% points; 95% CI −6.56 to −5.17; P  < 0.0001).

BMI category change

At week 104, 52.4% of patients treated with semaglutide achieved improvement in BMI category compared with 15.7% of those receiving placebo. Proportions of patients in the BMI categories at baseline and week 104 are shown in Fig. 4 , which depicts in-trial patients receiving semaglutide and placebo. The BMI category change reflects the superior weight loss with semaglutide, which resulted in fewer patients being in the higher BMI categories after 104 weeks. In the semaglutide group, 12.0% of patients achieved a BMI <25 kg m − 2 , which is considered the healthy BMI category, compared with 1.2% for placebo; per study inclusion criteria, no patients were in this category at baseline. The proportion of patients with obesity (BMI ≥30 kg m − 2 ) fell from 71.0% to 43.3% in the semaglutide group versus 71.9% to 67.9% in the placebo group.

In the semaglutide group, 12.0% of patients achieved normal weight status at week 104 (from 0% at baseline), compared with 1.2% (from 0% at baseline) for placebo. BMI classes: healthy (BMI <25 kg m − 2 ), overweight (25 to <30 kg m − 2 ), class I obesity (30 to <35 kg m − 2 ), class II obesity (35 to <40 kg m − 2 ) and class III obesity (BMI ≥40 kg m − 2 ).

Weight and anthropometric outcomes by subgroups

The forest plot illustrated in Fig. 5 displays mean body weight percentage change from baseline to week 104 for semaglutide relative to placebo in prespecified subgroups. Similar relationships are depicted for WC changes in prespecified subgroups shown in Extended Data Fig. 1 . The effect of semaglutide (versus placebo) on mean percentage body weight loss as well as reduction in WC was found to be heterogeneous across several population subgroups. Women had a greater difference in mean weight loss with semaglutide versus placebo (−11.1% (95% CI −11.56 to −10.66) versus −7.5% in men (95% CI −7.78 to −7.23); P  < 0.0001). There was a linear relationship between age category and degree of mean weight loss, with younger age being associated with progressively greater mean weight loss, but the actual mean difference by age group is small. Similarly, BMI category had small, although statistically significant, associations. Those with WHtR less than the median experienced slightly lower mean body weight change than those above the median, with estimated treatment differences −8.04% (95% CI −8.37 to −7.70) and −8.99% (95% CI −9.33 to −8.65), respectively ( P  < 0.0001). Patients from Asia and of Asian race experienced slightly lower mean weight loss (estimated treatment difference with semaglutide for Asian race −7.27% (95% CI −8.09 to −6.46; P  = 0.0147) and for Asia −7.30 (95% CI −7.97 to −6.62; P  = 0.0016)). There was no difference in weight loss with semaglutide associated with ethnicity (estimated treatment difference for Hispanic −8.53% (95% CI −9.28 to −7.76) or non-Hispanic −8.52% (95% CI −8.77 to 8.26); P  = 0.9769), glycemic status (estimated treatment difference for prediabetes −8.53% (95% CI −8.83 to −8.24) or normoglycemia −8.48% (95% CI −8.88 to −8.07; P  = 0.8188) or renal function (estimated treatment difference for estimated glomerular filtration rate (eGFR) <60 or ≥60 ml min −1  1.73 m − 2 being −8.50% (95% CI −9.23 to −7.76) and −8.52% (95% CI −8.77 to −8.26), respectively ( P  = 0.9519)).

Data from the in-trial period. N  = 17,604. P values represent test of no interaction effect. P values are two-sided and are not adjusted for multiplicity. The dots show estimated treatment differences, and the error bars show 95% CIs. Details of the statistical models are available in Methods . ETD, estimated treatment difference; HbA1c, glycated hemoglobin; MI, myocardial infarction; PAD, peripheral artery disease; sema, semaglutide.

Safety and tolerability according to baseline BMI category

We reported in the primary outcome of the SELECT trial that adverse events (AEs) leading to permanent discontinuation of the trial product occurred in 1,461 patients (16.6%) in the semaglutide group and 718 patients (8.2%) in the placebo group ( P  < 0.001) 21 . For this analysis, we evaluated the cumulative incidence of AEs leading to trial product discontinuation by treatment assignment and by BMI category (Fig. 6 ). For this analysis, with death modeled as a competing risk, we tracked the proportion of in-trial patients for whom drug was withdrawn or interrupted for the first time (Fig. 6 , left) or cumulative discontinuations (Fig. 6 , right). Both panels of Fig. 6 depict a graded increase in the proportion discontinuing semaglutide, but not placebo. For lower BMI classes, discontinuation rates are higher in the semaglutide group but not the placebo group.

Data are in-trial from the full analysis set. sema, semaglutide.

We reported in the primary SELECT analysis that serious adverse events (SAEs) were reported by 2,941 patients (33.4%) in the semaglutide arm and by 3,204 patients (36.4%) in the placebo arm ( P  < 0.001) 21 . For this study, we analyzed SAE rates by person-years of treatment exposure for BMI classes (<30 kg m − 2 , 30 to <35 kg m − 2 , 35 to <40 kg m − 2 , and ≥40 kg m − 2 ) and provide these data in Supplementary Table 2 . We also provide an analysis of the most common categories of SAEs. Semaglutide was associated with lower SAEs, primarily driven by CV event and infections. Within each obesity class (<30 kg m − 2 , 30 to <35 kg m − 2 , 35 to <40 kg m − 2 , and ≥40 kg m − 2 ), there were fewer SAEs in the group receiving semaglutide compared with placebo. Rates (events per 100 years of observation) of SAEs were 43.23, 43.54, 51.07 and 47.06 for semaglutide and 50.48, 49.66, 52.73 and 60.85 for placebo, with no evidence of heterogeneity. There was no detectable difference in hepatobiliary or gastrointestinal SAEs comparing semaglutide with placebo in any of the four BMI classes we evaluated.

The analyses of weight effects of the SELECT study presented here reveal that patients assigned to once-weekly subcutaneous semaglutide 2.4 mg lost significantly more weight than those receiving placebo. The weight-loss trajectory with semaglutide occurred over 65 weeks and was sustained up to 4 years. Likewise, there were similar improvements in the semaglutide group for anthropometrics (WC and WHtR). The weight loss was associated with a greater proportion of patients receiving semaglutide achieving improvement in BMI category, healthy BMI (<25 kg m − 2 ) and falling below the WC cutoff point above which increased cardiometabolic risk for the sex and race is greater 22 , 23 . Furthermore, both sexes, all races, all body sizes and those from all geographic regions were able to achieve clinically meaningful weight loss. There was no evidence of increased SAEs based on BMI categories, although lower BMI category was associated with increased rates of trial product discontinuation, probably reflecting exposure to a higher level of drug in lower BMI categories. These data, representing the longest clinical trial of the effects of semaglutide versus placebo on weight, establish the safety and durability of semaglutide effects on weight loss and maintenance in a geographically and racially diverse population of adult men and women with overweight and obesity but not diabetes. The implications of weight loss of this degree in such a diverse population suggests that it may be possible to impact the public health burden of the multiple morbidities associated with obesity. Although our trial focused on CV events, many chronic diseases would benefit from effective weight management 28 .

There were variations in the weight-loss response. Individual changes in body weight with semaglutide and placebo were striking; still, 67.8% achieved 5% or more weight loss and 44.2% achieved 10% weight loss with semaglutide at 2 years, compared with 21.3% and 6.9%, respectively, for those receiving placebo. Our first on-treatment analysis demonstrated that those on-drug lost more weight than those in-trial, confirming the effect of drug exposure. With semaglutide, lower BMI was associated with less percentage weight loss, and women lost more weight on average than men (−11.1% versus −7.5% treatment difference from placebo); however, in all cases, clinically meaningful mean weight loss was achieved. Although Asian patients lost less weight on average than patients of other races (−7.3% more than placebo), Asian patients were more likely to be in the lowest BMI category (<30 kg m − 2 ), which is known to be associated with less weight loss, as discussed below. Clinically meaningful weight loss was evident in the semaglutide group within a broad range of baseline categories for glycemia and body anthropometrics. Interestingly, at 2 years, a significant proportion of the semaglutide-treated group fell below the sex- and race-specific WC cutoff points, especially in those with BMI <35 kg m − 2 , and a notable proportion (12.0%) fell below the BMI cutoff point of 25 kg m − 2 , which is deemed a healthy BMI in those without unintentional weight loss. As more robust weight loss is possible with newer medications, achieving and maintaining these cutoff point targets may become important benchmarks for tracking responses.

The overall safety profile did not reveal any new signals from prior studies, and there were no BMI category-related associations with AE reporting. The analysis did reveal that tolerability may differ among specific BMI classes, since more discontinuations occurred with semaglutide among lower BMI classes. Potential contributors may include a possibility of higher drug exposure in lower BMI classes, although other explanations, including differences in motivation and cultural mores regarding body size, cannot be excluded.

Is the weight loss in SELECT less than expected based on prior studies with the drug? In STEP 1, a large phase 3 study of once-weekly subcutaneous semaglutide 2.4 mg in individuals without diabetes but with BMI >30 kg m − 2 or 27 kg m − 2 with at least one obesity-related comorbidity, the mean weight loss was −14.9% at week 68, compared with −2.4% with placebo 14 . Several reasons may explain the observation that the mean treatment difference was −12.5% in STEP 1 and −8.7% in SELECT. First, SELECT was designed as a CV outcomes trial and not a weight-loss trial, and weight loss was only a supportive secondary endpoint in the trial design. Patients in STEP 1 were desirous of weight loss as a reason for study participation and received structured lifestyle intervention (which included a −500 kcal per day diet with 150 min per week of physical activity). In the SELECT trial, patients did not enroll for the specific purpose of weight loss and received standard of care covering management of CV risk factors, including medical treatment and healthy lifestyle counseling, but without a specific focus on weight loss. Second, the respective study populations were quite different, with STEP 1 including a younger, healthier population with more women (73.1% of the semaglutide arm in STEP 1 versus 27.7% in SELECT) and higher mean BMI (37.8 kg m − 2 versus 33.3 kg m − 2 , respectively) 14 , 21 . Third, major differences existed between the respective trial protocols. Patients in the semaglutide treatment arm of STEP 1 were more likely to be exposed to the medication at the full dose of 2.4 mg than those in SELECT. In SELECT, investigators were allowed to slow, decrease or pause treatment. By 104 weeks, approximately 77% of SELECT patients on dose were receiving the target semaglutide 2.4 mg weekly dose, which is lower than the corresponding proportion of patients in STEP 1 (89.6% were receiving the target dose at week 68) 14 , 21 . Indeed, in our first on-treatment analysis at week 208, weight loss was greater (−11.7% for semaglutide) compared with the in-trial analysis (−10.2% for semaglutide). Taken together, all these issues make less weight loss an expected finding in SELECT, compared with STEP 1.

The SELECT study has some limitations. First, SELECT was not a primary prevention trial, and the data should not be extrapolated to all individuals with overweight and obesity to prevent major adverse CV events. Although the data set is rich in numbers and diversity, it does not have the numbers of individuals in racial subgroups that may have revealed potential differential effects. SELECT also did not include individuals who have excess abnormal body fat but a BMI <27 kg m − 2 . Not all individuals with increased CV risk have BMI ≥27 kg m − 2 . Thus, the study did not include Asian patients who qualify for treatment with obesity medications at lower BMI and WC cutoff points according to guidelines in their countries 29 . We observed that Asian patients were less likely to be in the higher BMI categories of SELECT and that the population of those with BMI <30 kg m − 2 had a higher percentage of Asian race. Asian individuals would probably benefit from weight loss and medication approaches undertaken at lower BMI levels in the secondary prevention of CVD. Future studies should evaluate CV risk reduction in Asian individuals with high CV risk and BMI <27 kg m − 2 . Another limitation is the lack of information on body composition, beyond the anthropometric measures we used. It would be meaningful to have quantitation of fat mass, lean mass and muscle mass, especially given the wide range of body size in the SELECT population.

An interesting observation from this SELECT weight loss data is that when BMI is ≤30 kg m − 2 , weight loss on a percentage basis is less than that observed across higher classes of BMI severity. Furthermore, as BMI exceeds 30 kg m − 2 , weight loss amounts are more similar for class I, II and III obesity. This was also observed in Look AHEAD, a lifestyle intervention study for weight loss 30 . The proportion (percentage) of weight loss seems to be less, on average, in the BMI <30 kg m − 2 category relative to higher BMI categories, despite their receiving of the same treatment and even potentially higher exposure to the drug for weight loss 30 . Weight loss cannot continue indefinitely. There is a plateau of weight that occurs after weight loss with all treatments for weight management. This plateau has been termed the ‘set point’ or ‘settling point’, a body weight that is in harmony with the genetic and environmental determinants of body weight and adiposity 31 . Perhaps persons with BMI <30 kg m − 2 are closer to their settling point and have less weight to lose to reach it. Furthermore, the cardiometabolic benefits of weight loss are driven by reduction in the abnormal ectopic and visceral depots of fat, not by reduction of subcutaneous fat stores in the hips and thighs. The phenotype of cardiometabolic disease but lower BMI (<30 kg m − 2 ) may be one where reduction of excess abnormal and dysfunctional body fat does not require as much body mass reduction to achieve health improvement. We suspect this may be the case and suggest further studies to explore this aspect of weight-loss physiology.

In conclusion, this analysis of the SELECT study supports the broad use of once-weekly subcutaneous semaglutide 2.4 mg as an aid to CV event reduction in individuals with overweight or obesity without diabetes but with preexisting CVD. Semaglutide 2.4 mg safely and effectively produced clinically significant weight loss in all subgroups based on age, sex, race, glycemia, renal function and anthropometric categories. Furthermore, the weight loss was sustained over 4 years during the trial.

Trial design and participants

The current work complies with all relevant ethical regulations and reports a prespecified analysis of the randomized, double-blind, placebo-controlled SELECT trial ( NCT03574597 ), details of which have been reported in papers describing study design and rationale 32 , baseline characteristics 24 and the primary outcome 21 . SELECT evaluated once-weekly subcutaneous semaglutide 2.4 mg versus placebo to reduce the risk of major adverse cardiac events (a composite endpoint comprising CV death, nonfatal myocardial infarction or nonfatal stroke) in individuals with established CVD and overweight or obesity, without diabetes. The protocol for SELECT was approved by national and institutional regulatory and ethical authorities in each participating country. All patients provided written informed consent before beginning any trial-specific activity. Eligible patients were aged ≥45 years, with a BMI of ≥27 kg m − 2 and established CVD defined as at least one of the following: prior myocardial infarction, prior ischemic or hemorrhagic stroke, or symptomatic peripheral artery disease. Additional inclusion and exclusion criteria can be found elsewhere 32 .

Human participants research

The trial protocol was designed by the trial sponsor, Novo Nordisk, and the academic Steering Committee. A global expert panel of physician leaders in participating countries advised on regional operational issues. National and institutional regulatory and ethical authorities approved the protocol, and all patients provided written informed consent.

Study intervention and patient management

Patients were randomly assigned in a double-blind manner and 1:1 ratio to receive once-weekly subcutaneous semaglutide 2.4 mg or placebo. The starting dose was 0.24 mg once weekly, with dose increases every 4 weeks (to doses of 0.5, 1.0, 1.7 and 2.4 mg per week) until the target dose of 2.4 mg was reached after 16 weeks. Patients who were unable to tolerate dose escalation due to AEs could be managed by extension of dose-escalation intervals, treatment pauses or maintenance at doses below the 2.4 mg per week target dose. Investigators were allowed to reduce the dose of study product if tolerability issues arose. Investigators were provided with guidelines for, and encouraged to follow, evidence-based recommendations for medical treatment and lifestyle counseling to optimize management of underlying CVD as part of the standard of care. The lifestyle counseling was not targeted at weight loss. Additional intervention descriptions are available 32 .

Sex, race, body weight, height and WC measurements

Sex and race were self-reported. Body weight was measured without shoes and only wearing light clothing; it was measured on a digital scale and recorded in kilograms or pounds (one decimal with a precision of 0.1 kg or lb), with preference for using the same scale throughout the trial. The scale was calibrated yearly as a minimum unless the manufacturer certified that calibration of the weight scales was valid for the lifetime of the scale. Height was measured without shoes in centimeters or inches (one decimal with a precision of 0.1 cm or inches). At screening, BMI was calculated by the electronic case report form. WC was defined as the abdominal circumference located midway between the lower rib margin and the iliac crest. Measures were obtained in a standing position with a nonstretchable measuring tape and to the nearest centimeter or inch. The patient was asked to breathe normally. The tape touched the skin but did not compress soft tissue, and twists in the tape were avoided.

The following endpoints relevant to this paper were assessed at randomization (week 0) to years 2, 3 and 4: change in body weight (%); proportion achieving weight loss ≥5%, ≥10%, ≥15% and ≥20%; change in WC (cm); and percentage change in WHtR (cm cm −1 ). Improvement in BMI category (defined as being in a lower BMI class) was assessed at week 104 compared with baseline according to BMI classes: healthy (BMI <25 kg m − 2 ), overweight (25 to <30 kg m − 2 ), class I obesity (30 to <35 kg m − 2 ), class II obesity (35 to <40 kg m − 2 ) and class III obesity (≥40 kg m − 2 ). The proportions of individuals with BMI <35 or ≥35 kg m − 2 who achieved sex- and race-specific cutoff points for WC (indicating increased metabolic risk) were evaluated at week 104. The WC cutoff points were as follows: Asian women <80 cm, non-Asian women <88 cm, Asian men <88 cm and non-Asian men <102 cm.

Overall, 97.1% of the semaglutide group and 96.8% of the placebo group completed the trial. During the study, 30.6% of those assigned to semaglutide did not complete drug treatment, compared with 27.0% for placebo.

Statistical analysis

The statistical analyses for the in-trial period were based on the intention-to-treat principle and included all randomized patients irrespective of adherence to semaglutide or placebo or changes to background medications. Continuous endpoints were analyzed using an analysis of covariance model with treatment as a fixed factor and baseline value of the endpoint as a covariate. Missing data at the landmark visit, for example, week 104, were imputed using a multiple imputation model and done separately for each treatment arm and included baseline value as a covariate and fit to patients having an observed data point (irrespective of adherence to randomized treatment) at week 104. The fit model is used to impute values for all patients with missing data at week 104 to create 500 complete data sets. Rubin’s rules were used to combine the results. Estimated means are provided with s.e.m., and estimated treatment differences are provided with 95% CI. Binary endpoints were analyzed using logistic regression with treatment and baseline value as a covariate, where missing data were imputed by first using multiple imputation as described above and then categorizing the imputed data according to the endpoint, for example, body weight percentage change at week 104 of <0%. Subgroup analyses for continuous and binary endpoints also included the subgroup and interaction between treatment and subgroup as fixed factors. Because some patients in both arms continued to be followed but were off treatment, we also analyzed weight loss by first on-treatment group (observation period until first time being off treatment for >35 days) to assess a more realistic picture of weight loss in those adhering to treatment. CIs were not adjusted for multiplicity and should therefore not be used to infer definitive treatment effects. All statistical analyses were performed with SAS software, version 9.4 TS1M5 (SAS Institute).

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

Data will be shared with bona fide researchers who submit a research proposal approved by the independent review board. Individual patient data will be shared in data sets in a deidentified and anonymized format. Information about data access request proposals can be found at https://www.novonordisk-trials.com/ .

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Acknowledgements

Editorial support was provided by Richard Ogilvy-Stewart of Apollo, OPEN Health Communications, and funded by Novo Nordisk A/S, in accordance with Good Publication Practice guidelines ( www.ismpp.org/gpp-2022 ).

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Donna H. Ryan

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Contributions

D.H.R., I.L. and S.E.K. contributed to the study design. D.B.H., I.L., D.D., A.K., S.M.M., A.P.v.B., C.C. and J.P.H.W. were study investigators. D.B.H., I.L., D.D., A.K., S.M.M., A.P.v.B., C.C. and J.P.H.W. enrolled patients. D.H.R. was responsible for data analysis and manuscript preparation. All authors contributed to data interpretation, review, revisions and final approval of the manuscript.

Corresponding author

Correspondence to Donna H. Ryan .

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Competing interests.

D.H.R. declares having received consulting honoraria from Altimmune, Amgen, Biohaven, Boehringer Ingelheim, Calibrate, Carmot Therapeutics, CinRx, Eli Lilly, Epitomee, Gila Therapeutics, IFA Celtics, Novo Nordisk, Pfizer, Rhythm, Scientific Intake, Wondr Health and Zealand Pharma; she declares she received stock options from Calibrate, Epitomee, Scientific Intake and Xeno Bioscience. I.L. declares having received research funding (paid to institution) from Novo Nordisk, Sanofi, Mylan and Boehringer Ingelheim. I.L. received advisory/consulting fees and/or other support from Altimmune, AstraZeneca, Bayer, Biomea, Boehringer Ingelheim, Carmot Therapeutics, Cytoki Pharma, Eli Lilly, Intercept, Janssen/Johnson & Johnson, Mannkind, Mediflix, Merck, Metsera, Novo Nordisk, Pharmaventures, Pfizer, Regeneron, Sanofi, Shionogi, Structure Therapeutics, Target RWE, Terns Pharmaceuticals, The Comm Group, Valeritas, WebMD and Zealand Pharma. J.D. declares having received consulting honoraria from Amgen, Boehringer Ingelheim, Merck, Pfizer, Aegerion, Novartis, Sanofi, Takeda, Novo Nordisk and Bayer, and research grants from British Heart Foundation, MRC (UK), NIHR, PHE, MSD, Pfizer, Aegerion, Colgate and Roche. S.E.K. declares having received consulting honoraria from ANI Pharmaceuticals, Boehringer Ingelheim, Eli Lilly, Merck, Novo Nordisk and Oramed, and stock options from AltPep. B.B. declares having received honoraria related to participation on this trial and has no financial conflicts related to this publication. H.M.C. declares being a stockholder and serving on an advisory panel for Bayer; receiving research grants from Chief Scientist Office, Diabetes UK, European Commission, IQVIA, Juvenile Diabetes Research Foundation and Medical Research Council; serving on an advisory board and speaker’s bureau for Novo Nordisk; and holding stock in Roche Pharmaceuticals. C.C. declares having received consulting honoraria from Novo Nordisk, Eli Lilly, Merck, Brace Pharma and Eurofarma. D.D. declares having received consulting honoraria from Novo Nordisk, Eli Lilly, Boehringer Ingelheim and AstraZeneca, and received research grants through his affiliation from Novo Nordisk, Eli Lilly, Boehringer Ingelheim and Rhythm. D.B.H. declares having received research grants through her academic affiliation from Novo Nordisk and Eli Lilly, and advisory/consulting honoraria from Novo Nordisk, Eli Lilly and Gelesis. A.K. declares having received research grants through his affiliation from Novo Nordisk and Pharmaserve Lilly, and consulting honoraria from Pharmaserve Lilly, Sanofi-Aventis, Novo Nordisk, MSD, AstraZeneca, ELPEN Pharma, Boehringer Ingelheim, Galenica Pharma, Epsilon Health and WinMedica. A.M.L. declares having received honoraria from Novo Nordisk, Eli Lilly, Akebia Therapeutics, Ardelyx, Becton Dickinson, Endologix, FibroGen, GSK, Medtronic, Neovasc, Provention Bio, ReCor, BrainStorm Cell Therapeutics, Alnylam and Intarcia for consulting activities, and research funding to his institution from AbbVie, Esperion, AstraZeneca, CSL Behring, Novartis and Eli Lilly. S.M.M. declares having received consulting honoraria from Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Daichii-Sankyo, esanum, Gilead, Ipsen, Eli Lilly, Novartis, Novo Nordisk, Sandoz and Sanofi; he declares he received research grants from AstraZeneca, Eli Lilly and Novo Nordisk. J.P. declares having received consulting honoraria from Altimmune, Amgen, Esperion, Merck, MJH Life Sciences, Novartis and Novo Nordisk; he has received a grant, paid to his institution, from Boehringer Ingelheim and holds the position of Director, Preventive Cardiology, at Brigham and Women’s Hospital. A.P.v.B. is contracted via the University of Groningen (no personal payment) to undertake consultancy for Novo Nordisk, Eli Lilly and Boehringer Ingelheim. J.P.H.W. is contracted via the University of Liverpool (no personal payment) to undertake consultancy for Altimmune, AstraZeneca, Boehringer Ingelheim, Cytoki, Eli Lilly, Napp, Novo Nordisk, Menarini, Pfizer, Rhythm Pharmaceuticals, Sanofi, Saniona, Tern Pharmaceuticals, Shionogi and Ysopia. J.P.H.W. also declares personal honoraria/lecture fees from AstraZeneca, Boehringer Ingelheim, Medscape, Napp, Menarini, Novo Nordisk and Rhythm. R.F.K. declares having received consulting honoraria from Novo Nordisk, Weight Watchers, Eli Lilly, Boehringer Ingelheim, Pfizer, Structure and Altimmune. E.B., G.K.H., O.K.J. and T.K.O. are employees of Novo Nordisk A/S.

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Extended data

Extended data fig. 1 effect of semaglutide treatment or placebo on waist circumference from baseline to week 104 by subgroups..

Data from the in-trial period. N  = 17,604. P values represent test of no interaction effect. P values are two-sided and not adjusted for multiplicity. The dots show estimated treatment differences and the error bars show 95% confidence intervals. Details of the statistical models are available in Methods . BMI, body mass index; CI, confidence interval; CV, cardiovascular; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; ETD, estimated treatment difference; HbA1c, glycated hemoglobin; MI, myocardial infarction; PAD, peripheral artery disease; sema, semaglutide.

Supplementary information

Reporting summary, supplementary tables 1 and 2.

Supplementary Table 1. Baseline characteristics by BMI class. Data are represented as number and percentage of patients. Renal function categories were based on the eGFR as per Chronic Kidney Disease Epidemiology Collaboration. Albuminuria categories were based on UACR. Smoking was defined as smoking at least one cigarette or equivalent daily. The category ‘Other’ for CV inclusion criteria includes patients where it is unknown if the patient fulfilled only one or several criteria and patients who were randomized in error and did not fulfill any criteria. Supplementary Table 2. SAEs according to baseline BMI category. P value: two-sided P value from Fisher’s exact test for test of no difference.

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Ryan, D.H., Lingvay, I., Deanfield, J. et al. Long-term weight loss effects of semaglutide in obesity without diabetes in the SELECT trial. Nat Med (2024). https://doi.org/10.1038/s41591-024-02996-7

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Accepted : 12 April 2024

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DOI : https://doi.org/10.1038/s41591-024-02996-7

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