Study Links Extreme Health Trait Values to Rare but Potent Genetic Variants

For traits like cholesterol, blood glucose, height, and age at menopause, most people fall somewhere in the middle of the distribution. But for those at the far ends of the spectrum, a new study suggests the genetic explanation may be simpler—and more powerful—than the field has assumed.

Scientists at the Icahn School of Medicine at Mount Sinai report in Nature that individuals with extreme high or low values for certain traits are more likely to carry rare genetic variants with large biological effects, rather than the many small-effect common variants that typically shape these traits across the broader population.

Most health-related traits are considered polygenic—meaning they reflect the combined influence of thousands of common genetic variants, each contributing only a modest effect. The new work asks whether that model fully accounts for people at the extremes, and finds evidence that it may not.

"We typically think of these traits as being shaped by thousands of genetic changes, each having a very small effect," said senior corresponding author Paul O'Reilly. "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. If we can identify who these people are, clinicians may be able to offer them preventive care or treatments better suited to their genetic risk profile."

The team's hypothesis drew in part on evolutionary biology. Extremely high or low trait values can sometimes be disadvantageous, which means natural selection may reduce the frequency of genetic variants that strongly push traits to those extremes—making such variants rare in the population.

To test the idea, the researchers developed two complementary statistical approaches and applied them to 74 quantitative traits drawn from large-scale datasets including the UK Biobank and the All of Us Research Program. Together, those databases include health and genetic information from hundreds of thousands of participants representing a wide range of ancestries.

"By focusing on individuals at the extremes, we may be able to uncover clearer biological signals that are harder to detect in the general population," said Dr. O'Reilly.

The authors note that the analysis focused on genetic causes and did not fully account for environmental and lifestyle factors, which also contribute to extreme trait values. Future work will aim to further characterize the rare variants involved and clarify how they influence disease risk.