Relating pathogenic loss-of function mutations in humans to their evolutionary fitness costs

  1. Ipsita Agarwal  Is a corresponding author
  2. Zachary L Fuller
  3. Simon R Myers
  4. Molly Przeworski
  1. Columbia University, United States
  2. University of Oxford, United Kingdom

Abstract

Causal loss-of-function (LOF) variants for Mendelian and severe complex diseases are enriched in 'mutation intolerant' genes. We show how such observations can be interpreted in light of a model of mutation-selection balance, and use the model to relate the pathogenic consequences of LOF mutations at present-day to their evolutionary fitness effects. To this end, we first infer posterior distributions for the fitness costs of LOF mutations in 17,318 autosomal and 679 X-linked genes from exome sequences in 56,855 individuals. Estimated fitness costs for the loss of a gene copy are typically above 1%; they tend to be largest for X-linked genes, whether or not they have a Y homolog, followed by autosomal genes and genes in the pseudoautosomal region. We then compare inferred fitness effects for all possible de novo LOF mutations to those of de novo mutations identified in individuals diagnosed with one of six severe, complex diseases or developmental disorders. Probands carry an excess of mutations with estimated fitness effects above 10%; as we show by simulation, when sampled in the population, such highly deleterious mutations are typically only a couple of generations old. Moreover, the proportion of highly deleterious mutations carried by probands reflects the typical age of onset of the disease. The study design also has a discernible influence: a greater proportion of highly deleterious mutations is detected in pedigree than case-control studies, and for autism, in simplex than multiplex families and in female versus male probands. Thus, anchoring observations in human genetics to a population genetic model allows us to learn about the fitness effects of mutations identified by different mapping strategies and for different traits.

Data availability

All source data are freely available to researchers, with sources listed in Table S4. Code for simulations, and output is available at https://github.com/zfuller5280/MutationSelection and https://github.com/agarwal-i/loss-of-function-fitness-effects. Estimates of fitness costs of LOF mutations are provided as Table S2.

Article and author information

Author details

  1. Ipsita Agarwal

    Department of Biological Sciences, Columbia University, New York, United States
    For correspondence
    ia2337@columbia.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8537-0008
  2. Zachary L Fuller

    Department of Biological Sciences, Columbia University, New York, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4765-9227
  3. Simon R Myers

    Department of Statistics, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  4. Molly Przeworski

    Department of Systems Biology, Columbia University, New York, United States
    Competing interests
    Molly Przeworski, Senior editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5369-9009

Funding

National Institutes of Health (GM121372)

  • Molly Przeworski

National Institutes of Health (HG011432)

  • Molly Przeworski

National Institutes of Health (GM128318)

  • Zachary L Fuller

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. George H Perry, Pennsylvania State University, United States

Publication history

  1. Received: September 1, 2022
  2. Accepted: January 16, 2023
  3. Accepted Manuscript published: January 17, 2023 (version 1)

Copyright

© 2023, Agarwal et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Ipsita Agarwal
  2. Zachary L Fuller
  3. Simon R Myers
  4. Molly Przeworski
(2023)
Relating pathogenic loss-of function mutations in humans to their evolutionary fitness costs
eLife 12:e83172.
https://doi.org/10.7554/eLife.83172
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