Clinical Obesity Genetics Show Stronger Cardiovascular Links Than BMI Signals

A genetic score built around clinical obesity may provide a clearer view of cardiovascular risk than one based on BMI alone. In a study spanning five ancestry groups, researchers identified obesity-linked genetic signals that BMI did not capture and found that a clinical obesity score better distinguished risk for heart attack, heart failure and stroke. That’s a meaningful distinction: BMI is widely used because it’s simple to calculate, but simplicity can conceal differences in body fat and its effects on health.

Signals beyond BMI

The team analyzed 151,642 people with clinical obesity and 128,874 controls without obesity, drawing on the UK Biobank and the All of Us Research Program. The dataset covered five ancestry groups, allowing the researchers to look for genetic associations across more than one population background. They identified 127 independent genetic loci associated with clinical obesity; 63 showed no significant association with BMI. That gap suggests the two measures don’t capture precisely the same inherited patterns.

The clearest mismatch involved rs15285, a variant in the 3′-untranslated region of LPL, the gene that encodes lipoprotein lipase. The variant colocalized with expression quantitative trait loci for the gene and was associated with higher triglyceride levels. Those results connect a clinical obesity signal with both gene expression and a cardiovascular risk factor, although an association alone doesn’t establish that the variant causes either outcome.

That distinction matters because BMI is a proxy for body size, while the clinical obesity definition used in the study also considers excess body fat and impaired organ or tissue function. BMI can be useful for screening populations, but it doesn’t directly measure fat or show how excess adiposity affects a person’s body. The genetic findings suggest that adding those clinical features can point to biology BMI-based analyses miss. This is more significant than it looks: a score built around a broader definition may identify patterns that a familiar screening measure leaves out.

A score with stronger cardiovascular associations

Researchers combined multiple variants into a clinical obesity polygenic score. It was associated with BMI, body fat percentage and waist circumference, which ties the score to several measures of body size and adiposity. It also showed stronger associations than a BMI-based polygenic score with cardiovascular risk factors and markers of inflammation and insulin resistance. The comparison is the study’s central claim: the clinical score appears to carry information relevant to health beyond its relationship with body size.

The inflammatory markers included interleukin-6, fibroblast growth factor 21 and hepatic growth factor. Markers linked to insulin resistance included adiponectin, resistin, leptin and the leptin receptor. These measures offer researchers ways to examine biological processes that may accompany obesity, but they don’t by themselves show how a score would guide care for an individual. The clinical obesity score also improved risk discrimination for myocardial infarction, heart failure and stroke. Better discrimination can help separate groups with different levels of inherited risk; whether that separation changes decisions is a separate question.

The team tested the findings in four additional U.S. studies: the Atherosclerosis Risk in Communities study, the Multi-Ethnic Study of Atherosclerosis, the Framingham Heart Study and the Women’s Health Initiative. Together, these cohorts extend the analysis across different populations and long-running research programs focused on cardiovascular health. Testing a result in additional cohorts can show whether an association holds beyond the dataset used to develop it. Still, validation of a statistical pattern isn’t the same as demonstrating practical benefit in routine care.

Reclassification and clinical questions

In a preprint posted May 22, the researchers reported that the clinical obesity score reclassified 35% of individuals into different low, intermediate or high inherited-risk groups compared with the BMI score. Reclassification means the two scores placed a substantial share of people into different categories; it doesn’t say, on its own, whether those moves were accurate enough to improve outcomes. The result points to a potential role in refining risk assessment, though the study doesn’t establish how much the score would change clinical decisions. The numbers here are underwhelming as a measure of clinical impact: a changed category matters only if it leads to a better assessment or action.

“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 researchers wrote.

The findings were presented in the poster study “Genome-wide analysis and polygenic prediction of clinical obesity” at the American Society of Human Genetics 2026 Annual Meeting, held October 20–24 in Montreal. Co-corresponding authors were Sohail Zahid, MD, PhD, of the Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, and Alexis Battle, PhD, of Johns Hopkins. The poster presentation provides the setting for the findings, while the researchers’ own caution about further work keeps the clinical implications in perspective.

The study’s definition of clinical obesity follows criteria introduced by The Lancet Diabetes & Endocrinology Commission. The Commission recommended using BMI as a population-level proxy or screening measure, while confirming excess adiposity through direct body-fat measurement or an additional anthropometric measure such as waist circumference. For people with a BMI above 40 kg/m², it said excess adiposity could be assumed without further confirmation. That framework helps explain why the study’s score may identify signals BMI-based approaches miss: the underlying definition includes evidence about adiposity and its effects, rather than relying on body size alone.

What the findings could mean

The researchers’ conclusion is that clinical obesity captures genetic signals with closer ties to cardiovascular health than BMI-associated signals. The next question is whether that added information improves diagnosis or care beyond existing BMI-based assessment. If you’re working in this space, the distinction to watch is between a score that sorts people into different risk groups and one that changes what clinicians can confidently do with that information. That’s the part most people overlook (and this is the part most people overlook).

For now, the study offers evidence that definitions shape what genetic analyses can detect. A measure designed to include excess adiposity and impaired function may reveal associations hidden by a measure focused on body size. But there’s still a gap between finding those associations and showing that a polygenic score adds useful information in practice. More work is needed to establish the incremental benefit the authors describe. Potential, but not proof.

The team’s preprint is available on medRxiv.