Extreme trait values often have simpler genetic explanations than thought

Researchers at the Icahn School of Medicine at Mount Sinai have found evidence that people who fall at the extreme high or low ends of certain traits, such as cholesterol, blood glucose, height, and age at menopause, are more likely to have a simple genetic explanation than previously thought.

Their findings, reported in the May 27 issue of Nature [https://doi.org/10.1038/s41586-026-10516-5], may lead to new insights into the causes of common diseases.

Many traits linked to human health are considered "polygenic," meaning they are shaped by the combined influence of many common genetic variants, each contributing only a small effect. But the new study explored whether individuals with extreme trait values may instead be influenced by rarer genetic variants that have a much larger impact.

The researchers say this possibility could help explain why some individuals develop unusually high or low levels of traits associated with conditions such as diabetes, heart disease, and stroke.

We typically think of these traits as being shaped by thousands of genetic changes, each having a very small effect. 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."

Paul O'Reilly, PhD, senior corresponding author, Professor of Statistical Genetics in the Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York

The team's hypothesis was based in part on evolutionary biology. Because extremely high or low trait values can sometimes be disadvantageous, natural selection may reduce the frequency of genetic variants that strongly drive those extremes. As a result, such variants are expected to be relatively rare in the population.

"Our goal was to better understand whether extreme trait values might sometimes arise from a different kind of genetic architecture," says Dr. O'Reilly. "If so, that could eventually help researchers pinpoint biological pathways that are especially important in disease."

To conduct the study, the researchers analyzed genetic patterns linked to a range of biomarkers and physical measurements, including hemoglobin, heart rate, and body weight. The team first developed two complementary statistical approaches to test whether people with extremely high or low trait values have a different genetic architecture from the broader population. One method relied on population-level genetic data, while the other compared trait levels among siblings.

Using these approaches, the team analyzed 74 quantitative traits from large-scale health and genetic datasets, including the UK Biobank and the All of Us Research Program in the United States. Together, these databases include health and genetic information from hundreds of thousands of volunteer participants representing a wide range of geographic backgrounds and ancestries.

The researchers then looked for evidence that people at the extreme ends of the traits were more likely to carry rare genetic variants with larger biological effects.

"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," says Dr. O'Reilly.

The authors note that additional studies will be needed to determine how broadly these findings apply across populations and traits. They also acknowledged that their analysis focused on the genetic causes of these traits and did not fully capture the potential influence of environmental and lifestyle factors, which are also major causes of extreme trait values.

Future research will aim to further characterize the rare variants involved and better understand how they influence disease risk.