Genes associated with obesity shared across ancestries, researchers find

(Press-News.org) UNIVERSITY PARK, Pa. — Obesity is a global epidemic affecting millions of people every day and is associated with comorbidities ranging from heart disease and Type 2 diabetes to osteoarthritis and social stigma. While lifestyle factors, like diet and exercise, affect obesity, years of genetic research have identified about 20 genes that have a high effect on the likelihood of a person developing the condition. 

Now, a new study published today (Oct. 30) in Nature Communications, by researchers at Penn State, involving about 850,000 adults across six continental ancestries, has identified 13 genes associated with obesity across ancestries. While eight of these genes had been found in previous studies, five were identified for the first time, having no previous links to obesity. In addition, the team dissected how these genes influence obesity-related comorbidities such as Type 2 diabetes and heart-failure risk.

“Obesity touches millions, but most studies have focused on a few,” said Deepro Banerjee, a graduate student in the bioinformatics and genomics program at Penn State and first author of the study. “Previous studies have relied predominantly on European-ancestry populations, reflecting an ancestral bias and missing opportunities to discover additional genes whose mutations may be more prevalent in other ancestries yet still clinically relevant for Europeans.”

The findings provide insight into the genetic underpinnings of obesity around the globe, the researchers said, explaining that this insight could help guide precision medicine efforts by revealing key genes that might be missed in single-population studies.

“Obesity is a complex trait that is influenced by many genetic and lifestyle factors,” said Santhosh Girirajan, T. Ming Chu Professor of Genomics and head of the Department of Biochemistry and Molecular Biology in the Penn State Eberly College of Science and an author of the paper. “Studies in a single population can lead us to miss important genes that are shared across populations but may not rise to statistical significance in any one of them, even if they are clinically important in that population. New databases that include more representation of individuals with ancestries from around the world are helping to alleviate this bias, but we still need more data from non-European populations.”

For the study, the researchers used data from just over 450,000 adults in the UK Biobank — a biomedical database including genetic, physical and health data from mostly healthy people in the United Kingdom — and nearly 385,000 adults in the All of Us Research Program, a U.S. National Institutes of Health precision-medicine initiative with a more inclusive cohort that mirrors U.S. ancestral diversity. The six continental ancestries included were African, American, East Asian, European, Middle Eastern and South Asian. 

“Even with very large cohorts, rare, damaging variants can be hard to find unless we look across diverse populations,” Banerjee said. “The UK Biobank is made up largely of Europeans, with only about 20,000 non-Europeans in our study sample. By combining UK Biobank with All of Us — which contributed about 167,000 non-Europeans — we were able to measure the impact on body mass index (BMI), a measure of body fat percentage used as an indicator for obesity, of genes with rare, loss-of-function variants independently in each of the six ancestral populations.”

The researchers explained that they focused on rare, loss-of-function variants because they are the most likely to have large effects on a disease. These variants disrupt the function of a gene and are often found at sites in the genome that are highly conserved through evolution. Their rarity reflects the fact that such harmful changes do not usually rise to high frequency in the population. 

The team combined the non-European populations and performed an association study of all protein-coding regions of the genome with BMI. They found 13 genes with statistically significant association to BMI in the European group that replicated in the non-Europeans. Of these, eight had been previously associated with obesity, including well-known genes like MC4R and BSN. Five genes — YLPM1, RIF1, GIGYF1, SLC5A3 and GRM7 — had not been associated with obesity in prior rare-variant studies. The researchers found that these novel genes conferred about a three-fold increase in risk of severe obesity, a level of impact similar to MC4R and BSN. Like genes previously associated with obesity, the newly identified genes are expressed in the brain and adipose tissue — fat — and were linked to obesity traits such as increased body-fat percentage.

“The novel genes identified in our study highlight both established and emerging pathways in obesity biology,” Banerjee said. “YLPM1, for example, is an understudied transcription factor expressed in brain tissues, with links to mental disorders. It’s a clear example of a gene whose lower prevalence in one population may have obscured it historically. In our cross-ancestry analysis, YLPM1 shows a remarkably consistent effect across ancestries, similar to MC4R.”

The researchers also found that several of these genes contribute to other obesity-related conditions, including Type 2 diabetes, hypertension and heart disease. Using a statistical method called mediation analysis, they showed different mechanisms through which comorbidity risk increases, helping to explain why obesity often leads to other serious health problems.  Mediation analysis helped the team answer whether these genes directly increase the risk of comorbid diseases, or indirectly by first increasing BMI that in turn drives the comorbid risk.  For example, the team found that genes such as BSN, GIGYF1, and SLTM increased the risk of Type 2 Diabetes through both direct and indirect paths, a phenomenon known as partial mediation. While both effects were significant, the direct effect of these genes on disease risk was stronger than the indirect effect through BMI.

In a subset of individuals whose biobank entries included plasma proteomics data — a comprehensive list of proteins found in their blood plasma — the team also identified changes in circulating proteins linked to the obesity genes that they identified. These changes point to potential drug targets and biomarkers that could guide future treatments and help track response to therapy, the researchers said.

“Our findings emphasize the power and importance of cross-ancestry studies,” Girirajan said. “Some of the previously discovered obesity genes appear to only have significant association to obesity in Europeans, which could limit their potential as therapeutic targets for a global population. We did still find some of the most talked about obesity genes, like MC4R and BSN, but we also found several new genes with similar effect sizes, most with clear functional connections to obesity. Our cross-ancestry approach is helping us develop a more comprehensive view of the factors involved in obesity, which will hopefully help us develop effective therapies that can be applied through precision medicine.”

The U.S. National Institutes of Health funded the research, with additional resources from Penn State and the Penn State Huck Institutes of the Life Sciences.

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