Conducting the first genome-wide association study and analysis based on a new definition of clinical obesity, a research team has identified genetic signals that differed substantially from those associated with body mass index (BMI)—yet showed stronger connections to cardiovascular health.

The researchers—nine from Johns Hopkins University, one from The Ohio State University—analyzed 151,642 people with clinical obesity and 128,874 controls without obesity spanning five ancestry groups, using data from the UK Biobank and All of Us Research Program. The biobank says it possesses the world’s most comprehensive dataset of biological health and lifestyle data gathered from a half million participants, while All of Us is the NIH initiative designed to advance precision medicine by collecting and study data from 1 million or more people living in the United States.

Researchers identified 127 independent genetic loci associated with clinical obesity. Of these, 63 had no significant association with BMI. The most discordant variant, researchers reported, was rs15285, a single-nucleotide polymorphism (SNP) located within the 3′-untranslated region (3′UTR) of the LPL gene that encodes lipoprotein lipase. That variant was colocalized to expression quantitative trait loci (eQTLs) for lipoprotein lipase, and associated with elevated triglyceride levels.

The team also developed a clinical obesity polygenic score that combined information from numerous genetic variants, a score that was shown to be significantly associated with BMI, body fat percentage, and waist circumference. Compared to a BMI polygenic score, the clinical obesity polygenic score developed by the researchers showed improved association with cardiovascular risk factors and proteomic markers of inflammation—such as interleukin-6, fibroblast growth factor 21, and hepatic growth factor—as well as markers of insulin resistance, including adiponectin, resistin, leptin, and leptin receptor.

The clinical obesity polygenic score improved risk discrimination over a BMI polygenic score for myocardial infarction (heart attack), heart failure, and stroke, the research team added.

Researchers then validated the improvement across four additional long-running U.S. public health studies:

• Atherosclerosis Risk in Communities (ARIC), a study of the NIH’s National Heart, Lung, and Blood Institute whose focus has widened from identifying risk factors for subclinical atherosclerosis to risk factors for heart diseases including heart attack, coronary heart disease, stroke, and heart failure. About 16,000 U.S. adults have been enrolled.
• Multi-Ethnic Study of Atherosclerosis (MESA), an NHLBI-sponsored study of the characteristics of subclinical cardiovascular disease and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA enrolled 6,814 adults during its baseline period between 2000-2002.
• Framingham Heart Study, under NHLBI direction, was launched in 1948 to identify common factors or characteristics that contribute to cardiovascular disease. Since 1971, the Boston University School of Medicine has served as NHLBI’s contractor and academic partner for the study. More than 15,400 across multiple cohorts have been enrolled.
• Women’s Health Initiative, which first won funding in 1992 and is also NHLBI-sponsored, focuses on strategies for preventing heart disease, breast and colorectal cancer, and osteoporosis in postmenopausal women. 161,808 women have been enrolled.

‘Biologically and clinically relevant’

“These findings demonstrate that clinical obesity captures genetic loci distinct from BMI that are biologically and clinically relevant to cardiovascular health,” the researchers concluded.

Findings were reported in “Genome-wide analysis and polygenic prediction of clinical obesity,” a poster study presented during the American Society of Human Genetics (ASHG) 2026 Annual Meeting, held October 20-24 in Montreal. Co-corresponding authors were Sohail Zahid, MD, PhD, an investigator at the Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease; and Alexis Battle, PhD, director of the Malone Center for Engineering in Healthcare and director of the Research, Strategy, and Partnerships, Data Science and Artificial Intelligence Institute at Johns Hopkins.

The research team posted a preprint version of their study on medRxiv on May 22.

“Stratifying individuals into low, intermediate, and high inherited obesity risk groups, we found that clinical obesity polygenic risk reclassified 35% of individuals compared to BMI polygenic risk,” researchers reported in the preprint. “Unlike rare variant panel testing which already guides targeted therapy in monogenic obesity, further work is needed to determine the incremental benefit of clinical obesity polygenic scores for diagnosis, risk stratification, or management beyond BMI-based assessment.”

The new clinical obesity definition used by researchers was introduced last year by The Lancet Diabetes & Endocrinology Commission.  The 58-member Commission set out to establish objective criteria for disease diagnosis, aid clinical decision making, and prioritize therapeutic interventions and public health strategies, by characterizing excess body fat and dysfunctional adiposity beyond BMI.

“We recommend that BMI should be used only as a surrogate measure of health risk at a population level, for epidemiological studies, or for screening purposes, rather than as an individual measure of health,” the Commission stated last year. “Excess adiposity should be confirmed by either direct measurement of body fat, where available, or at least one anthropometric criterion (e.g., waist circumference, waist-to-hip ratio, or waist-to-height ratio) in addition to BMI, using validated methods and cutoff points appropriate to age, gender, and ethnicity.”

In people with very high BMI (i.e., >40 kg/m²), the Commission continued, excess adiposity can pragmatically be assumed without further confirmation: “We also recommend that people with confirmed obesity status (i.e., excess adiposity with or without abnormal organ or tissue function) should be assessed for clinical obesity.”