TY - JOUR T1 - Natural selection influenced the genetic architecture of brain structure, behavioral and neuropsychiatric traits JF - bioRxiv DO - 10.1101/2020.02.26.966531 SP - 2020.02.26.966531 AU - Frank R Wendt AU - Gita A Pathak AU - Cassie Overstreet AU - Daniel S Tylee AU - Joel Gelernter AU - Elizabeth G Atkinson AU - Renato Polimanti Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/02/27/2020.02.26.966531.abstract N2 - Natural selection has shaped the phenotypic characteristics of human populations. Genome-wide association studies (GWAS) have elucidated contributions of thousands of common variants with small effects on an individual’s predisposition to complex traits (polygenicity), as well as wide-spread sharing of risk alleles across traits in the human phenome (pleiotropy). It remains unclear how the pervasive effects of natural selection influence polygenicity in brain-related traits. We investigate these effects by annotating the genome with measures of background (BGS) and positive selection, indications of Neanderthal introgression, measures of functional significance including loss-of-function (LoF) intolerant and genic regions, and genotype networks in 75 brain-related traits. Evidence of natural selection was determined using binary annotations of top 2%, 1%, and 0.5% of selection scores genome-wide. We detected enrichment (q<0.05) of SNP-heritability at loci with elevated BGS (7 phenotypes) and in genic (34 phenotypes) and LoF-intolerant regions (67 phenotypes). BGS (top 2%) significantly predicted effect size variance for trait-associated loci (σ2 parameter) in 75 brain-related traits (β=4.39×10−5, p=1.43×10−5, model r2=0.548). By including the number of DSM-5 diagnostic combinations per psychiatric disorder, we substantially improved model fit (σ2 ~ BTop2% × Genic × diagnostic combinations; model r2=0.661). We show that GWAS with larger variance in risk locus effect sizes are collectively predicted by the effects of loci under strong BGS and in regulatory regions of the genome. We further show that diagnostic complexity exacerbates this relationship and perhaps dampens the ability to detect psychiatric risk loci. ER -