Summary: A major study in statistical genetics overturns a long-held assumption about complex human traits. It shows that people at the extreme high or low ends of common health measurements are frequently influenced by a few rare, high-impact genetic variants rather than by thousands of small-effect common variants. This discovery clarifies the genetic architecture of trait extremes and points toward more precise identification of individuals at high risk for conditions such as diabetes, heart disease, and stroke.
Researchers analyzed 74 quantitative traits—ranging from cholesterol and blood glucose to body weight and age at menopause—using genetic and health data from hundreds of thousands of participants. By demonstrating that the genetic drivers in the trait “tails” differ fundamentally from those in the broader population, the study provides a clearer path for detecting people whose extreme measurements reflect strong, rare genetic causes rather than cumulative minor effects.
Key Facts
- Reexamining the polygenic model: Many human traits are considered polygenic—shaped by many common variants with small effects. This study shows that this model does not fully describe individuals at trait extremes.
- Rare-variant dominance in the tails: Instead of thousands of tiny contributing variants, extreme trait values are often driven by a smaller number of rare alleles with disproportionately large biological effects.
- Evolutionary explanation: The authors link these findings to natural selection. Because extreme trait values can be detrimental to survival or reproduction, selection suppresses high-impact variants, keeping them rare in the general population.
- Two independent statistical strategies: To avoid bias, the team used complementary approaches—one based on population-level polygenic scores and another using family-based comparisons among siblings—to test whether tails have a distinct genetic architecture.
- Large, diverse datasets: The analyses used extensive resources such as the UK Biobank and the All of Us Research Program, covering a wide range of ancestries and geographic backgrounds to validate the patterns across populations.
- Clinical implications: Recognizing when extreme traits arise from rare strong variants creates the opportunity for targeted prevention and more personalized intervention strategies tailored to an individual’s genetic risk.
Source: Mount Sinai Hospital
Overview of findings
Researchers at the Icahn School of Medicine at Mount Sinai report evidence that some individuals who present extremely high or low values for traits like cholesterol, blood glucose, height, hemoglobin, heart rate and age at menopause are more likely to have a relatively simple genetic explanation: a few rare variants with large effects. Published in the May 27 issue of Nature, the study explores how genetic architecture can vary along the continuum of a trait and how selection shapes that variation.
Senior corresponding author Paul O’Reilly, PhD, Professor of Statistical Genetics, explains that while the conventional view treats many complex traits as shaped by thousands of small-effect changes, the new results indicate that the extreme ends of the distribution can be driven by rare, high-impact variants. Identifying these individuals could allow clinicians to provide more precise preventive care and therapeutic options based on specific genetic risk profiles.
The team developed two complementary methods. One method evaluates deviations from common-variant architecture using polygenic risk scores across the population; the other is family-based and compares trait levels directly between siblings to control for shared environment and background genetics. Both methods consistently indicated that the tails of many traits deviate from the broadly polygenic pattern and that incorporating rare variants from sequence data reduces these deviations, implicating rare large-effect alleles as key contributors.
The paper emphasizes that stabilizing selection can produce the observed patterns: selection acts against variants that push traits to harmful extremes, keeping those alleles rare. The authors also used models of reproductive success to provide empirical support for selection’s role.
The researchers caution that environmental and lifestyle factors remain important contributors to extreme trait values, and additional studies are needed to define how generalizable these findings are across different populations and traits. Future work will focus on characterizing the rare variants involved and determining how they alter disease risk and biological pathways.
Paper title: “Distinct genetic architecture in the tails of complex traits.” Authors: T. Souaiaia, H. M. Wu, A. P. S. Ori, S. W. Choi, C. J. Hoggart & P. F. O’Reilly.
Key Questions Answered:
A: The genetic architecture in the extremes differs from the general population. While average trait variation often reflects many common variants with small effects, those at the far ends are frequently driven by a few rare variants with much larger effects. These strong variants can push a trait sharply up or down, producing clear biological signals.
A: Stabilizing selection acts as a filter. If extreme trait values reduce survival or reproductive success, natural selection reduces the frequency of alleles that create those extremes. Over generations, powerful trait-shifting variants remain rare in the overall population.
A: By pinpointing individuals whose extreme biomarkers are driven by rare, high-impact variants, clinicians can move from one-size-fits-all recommendations to precision prevention and treatment plans tailored to the underlying genetic cause. This targeted approach could improve outcomes for those at highest genetic risk.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- The journal paper was reviewed in full.
- Additional context was added by editorial staff.
About this genetics research news
Author: Karin Eskenazi
Source: Mount Sinai Hospital
Contact: Karin Eskenazi – Mount Sinai Hospital
Image: The image is credited to Neuroscience News
Original Research: Open access. “Distinct genetic architecture in the tails of complex traits” by T. Souaiaia, H. M. Wu, A. P. S. Ori, S. W. Choi, C. J. Hoggart & P. F. O’Reilly. Nature. DOI: 10.1038/s41586-026-10516-5
Abstract
Distinct genetic architecture in the tails of complex traits
Complex traits are generally highly polygenic, with heritability arising from many common variants of small effect together with some rare variants of large effect. How this architecture varies along the trait distribution and how natural selection shapes that variation has been underexplored.
The authors developed a polygenic risk score–based approach that reveals widespread departures from common-variant architecture in one or both tails of 74 quantitative traits. These observations were replicated across ancestries, cohorts and repeated measures, and using an independent family-based method. Including rare variants identified from sequence data substantially reduced the observed deviations, indicating that rare alleles of large effect are major drivers of trait-tail architecture.
Forward simulations show that stabilizing selection can produce the patterns seen, and analyses of reproductive success provide empirical support for selection’s influence. The results indicate that while complex traits are polygenic at the population level, their tails often have a distinct, less polygenic architecture due to selection—findings with implications for rare-variant discovery and for prediction of complex traits and disease risk.