At the Icahn School of Medicine at Mount Sinai, researchers have overturned a fundamental assumption about how genetic traits work: instead of thousands of tiny genetic shifts pushing people toward health extremes, a smaller number of rare genetic variants with outsized power may explain why some individuals have unusually high or low cholesterol, blood glucose, height, and age at menopause.
The discovery matters because it opens a new window into some of medicine's biggest challenges. Scientists have long known that traits linked to heart disease, diabetes, and stroke are "polygenic"—shaped by the combined whisper of many common genetic variants, each barely moving the needle. But Paul O'Reilly, a professor of statistical genetics at Mount Sinai, and his team wondered whether the people at the far ends of the trait spectrum might operate by different rules entirely. Their answer, published in Nature in a paper titled "Distinct genetic architecture in the tails of complex traits," could reshape how doctors identify and treat those at highest genetic risk.
The reasoning comes from evolutionary biology: if extremely high or low trait values are sometimes dangerous, natural selection would prune away the rare genetic variants that strongly drive them. That means such variants should be rare in the population—but their effects should be large. The team decided to test this hypothesis directly.
Working with data from the UK Biobank and the All of Us Research Program, researchers analyzed 74 quantitative traits across hundreds of thousands of participants with diverse geographic backgrounds and ancestries. They developed two complementary statistical approaches: one analyzing population-level genetic data, the other comparing trait levels among siblings. They examined everything from hemoglobin and heart rate to body weight, searching for evidence that people at trait extremes carry rare genetic variants with bigger biological punch than the common variants that shape the general population.
The results confirmed their hunch. People falling at the extreme high or low ends of measured traits are indeed more likely to have a simpler genetic explanation—a smaller number of rare variants doing the heavy lifting—than previously thought.
"We typically think of these traits as being shaped by thousands of genetic changes, each having a very small effect," O'Reilly explains. "But our findings suggest that some people are at the ends of the trait spectrum because of a much smaller number of rare genetic variants with far stronger effects."
The implications ripple outward. If researchers can identify who carries these rare, high-impact variants, clinicians could offer preventive care or treatments tailored to each person's genetic risk profile rather than one-size-fits-all approaches. By focusing on individuals at the extremes, the team found they could uncover clearer biological signals that blur into noise when examining the general population—potentially revealing disease pathways that matter most when traits swing toward dangerous extremes.
The team acknowledges that their analysis captured genetic causes but didn't fully account for environmental and lifestyle factors, which also drive extreme trait values. Future research will aim to characterize these rare variants more precisely and understand how they influence disease risk—work that could eventually reshape preventive medicine and personalized treatment.