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October 12, 2025Genetics4 citationsOpen Access

Mutation-selection-drift balance models of complex diseases

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JBJeremy J. BergXLXinyi LiKRKellen Riall

Key Points

  • The model shows that complex disease prevalence is shaped by mutation-selection-drift balance, and is influenced by genetic variation.
  • Findings indicate that common genetic variation for complex diseases is minimally affected by directional selection, as seen in genome-wide association studies.
  • The methodology used was a tailored mutation-selection-drift balance model focusing specifically on complex disease susceptibility.
  • Results imply that existing heritability estimates may be biased, highlighting the need for refined models in understanding complex diseases.

Abstract

Abstract Genetic variation that influences complex disease susceptibility is introduced into the population by mutation and removed by natural selection and genetic drift. This mutation-selection-drift-balance (MSDB) shapes the prevalence of a disease and its genetic architecture. To date, however, MSDB has only been modeled for monogenic (Mendelian) diseases. Here, we develop a MSDB model for complex disease susceptibility: we assume that genotype relates to disease risk according to the canonical liability threshold model and that the selection on variants affecting risk stems from the fitness cost of the disease. We focus on diseases that are highly polygenic, entail a substantial fitness cost, and are neither extremely common in the population nor exceedingly rare. The comparison of model predictions with genome-wide association studies and other observations in humans indicates that common genetic variation affecting complex disease susceptibility is little affected by directional selection, and instead shaped by pleiotropic stabilizing selection on other traits. In turn, directional selection may exert a more substantial effect on rare, large effect variants. Our results also suggest that current estimates of disease heritability are likely biased. The model thus provides a better understanding of the evolutionary processes that shape the architecture and prevalence of complex diseases.

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Cite This Study

Berg et al. (2025) studied this question.

synapsesocial.com/papers/68ec1be02b8fa9b2b78ad1aahttps://doi.org/10.1093/genetics/iyaf220
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