Year: 2024
Type: preprint
Abstract: Natural selection acts ubiquitously on complex human traits, predominantly constraining the occurrence of extreme phenotypes (stabilizing selection). These constraints propagate to DNA sequence variants associated with traits under selection. The genetic signatures of such evolutionary events can thus be detected via combining effect size estimates from genetic association studies and the corresponding allele frequencies. Although this approach has been successfully applied to high-level traits, the prevalence and mode of selection acting on molecular traits remain poorly understood. Here, we estimate the action of natural selection on genetic variants associated with metabolite levels, an important layer of molecular traits. By leveraging summary statistics of published genome-wide association studies with large sample sizes, we find strong evidence of stabilizing selection for 15 out of 97 plasma metabolites, with nonessential amino acids displaying especially strong selection signatures. Mendelian randomization analysis reveals that metabolites under stronger stabilizing selection display larger effects on a range of clinically relevant complex traits, suggesting that maintaining a disease-free profile may be an important source of selective constraints on the metabolome. Metabolites under strong stabilizing selection in humans are also more conserved in their concentrations among diverse mammalian species, suggesting shared selective forces across micro- and macroevolutionary timescales. Overall, this study demonstrates that variation in metabolite levels among humans is frequently shaped by natural selection and this may act through their causal impact on disease susceptibility.
Source: Genome Research
Institutions: Russian Academy of Sciences, Institute of Biochemistry and Genetics of Ufa Scientific Centre, Bashkir State Medical University, University of Lausanne, SIB Swiss Institute of Bioinformatics, University of Szeged, HUN-REN Szegedi Biológiai Kutatóközpont, Institute of Biochemistry, Hungarian Research Network
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Funders: National Science Foundation, Imperial College London, European Commission, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Ministry of Education and Science of the Russian Federation, Magyar Tudományos Akadémia, Nemzeti Kutatási Fejlesztési és Innovációs Hivatal, National Research, Development and Innovation Office
Awards: G2406933141, G2656064768, G284703623, G3028329622, G4063980791, G434337789, G526467454, G7151416908, Establishing the Hungarian Center of Excellence for Molecular Medicine in partnership with EMBL, G736167370, Simultaneous estimation of selection strength for multiple complex traits using genome-wide association summary statistics
OpenAlex ID: W4401629559