Characterizing the effect of background selection on the polygenicity of brain-related traits.
Characterizing the effect of background selection on the polygenicity of brain-related traits.
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描述背景选择对大脑相关性状多基因性的影响。
DOI：
10.1016/j.ygeno.2020.11.032
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发表时间：
2021-01
期刊：
影响因子：
4.4
通讯作者：
Polimanti R
中科院分区：
文献类型：
--
作者：
Wendt FR;Pathak GA;Overstreet C;Tylee DS;Gelernter J;Atkinson EG;Polimanti R
全基因组关联研究表明，精神病理表型受许多影响较小(多基因)的危险等位基因的影响。目前尚不清楚无处不在的进化压力如何影响这些特征的遗传结构。我们划分了单核苷酸多态的遗传力，以评估背景和正选择、尼安德特人的地方血统、功能意义和基因网络在75个脑相关性状(8,411个≤N≤1,131,181，平均N=205,289)中的贡献。我们根据全基因组范围内前2%、1%和0.5%的所有分数对每个测量结果进行二分处理，从而应用了二进制注释。用Genesis软件计算效应大小分布特征。我们检验了效应大小分布、描述性统计和自然选择之间的关系。在特征的子集中，我们探索在测试关系中包含诊断异质性(例如，诊断组合的数量和总症状)。对于BGS升高的基因座(7个表型)以及基因(34个表型)和功能丧失(LoF)不耐受区域(67个表型)，SNP遗传率被丰富(假发现率Q<；0.05)。这些影响在精神分裂症(1.90倍BGS，1.16倍基因和1.92倍LOF)、教育程度(1.86倍BGS，1.12倍基因和1.79倍LOF)和认知能力(2.29倍BGS，1.12倍基因和1.79倍LOF)中最强。BGS(前2%)显著预测了75个脑相关性状(σ2参数)的效应大小变异(β=4.39×10−5，p=1.43×10−5，模型R2=0.548)。考虑到每个精神障碍的诊断组合数，改进的模型拟合(σ2~BTop2%×GENIC×诊断组合；模型R2=0.661)。脑部相关表型的风险位点效应大小与BGS下的基因座相关。我们的探索性结果表明，诊断的复杂性也可能有助于增加精神疾病的多源性。
Genome-wide association studies (GWAS) have demonstrated that psychopathology phenotypes are affected by many risk alleles with small effect (polygenicity). It is unclear how ubiquitously evolutionary pressures influence the genetic architecture of these traits. We partitioned SNP heritability to assess the contribution of background (BGS) and positive selection, Neanderthal local ancestry, functional significance, and genotype networks in 75 brain-related traits (8,411≤N≤1,131,181, mean N=205,289). We applied binary annotations by dichotomizing each measure based on top 2%, 1%, and 0.5% of all scores genome-wide. Effect size distribution features were calculated using GENESIS. We tested the relationship between effect size distribution descriptive statistics and natural selection. In a subset of traits, we explore the inclusion of diagnostic heterogeneity (e.g., number of diagnostic combinations and total symptoms) in the tested relationship. SNP-heritability was enriched (false discovery rate q<0.05) for loci with elevated BGS (7 phenotypes) and in genic (34 phenotypes) and loss-of-function (LoF)-intolerant regions (67 phenotypes). These effects were strongest in GWAS of schizophrenia (1.90-fold BGS, 1.16-fold genic, and 1.92-fold LoF), educational attainment (1.86-fold BGS, 1.12-fold genic, and 1.79-fold LoF), and cognitive performance (2.29-fold BGS, 1.12-fold genic, and 1.79-fold LoF). 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). Considering the number of DSM-5 diagnostic combinations per psychiatric disorder improved model fit (σ2 ~ BTop2% × Genic × diagnostic combinations; model r2=0.661). Brain-related phenotypes with larger variance in risk locus effect sizes are associated with loci under BGS. We show exploratory results suggesting that diagnostic complexity may also contribute to increase the polygenicity of psychiatric disorders.
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影响因子：
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作者：
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通讯作者：
Kelso J
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作者：
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Bulik-Sullivan, Brendan K.;Loh, Po-Ru;Finucane, Hilary K.;Ripke, Stephan;Yang, Jian;Patterson, Nick;Daly, Mark J.;Price, Alkes L.;Neale, Benjamin M.
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Neale, Benjamin M.
影响因子：
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作者：
Finucane HK;Bulik-Sullivan B;Gusev A;Trynka G;Reshef Y;Loh PR;Anttila V;Xu H;Zang C;Farh K;Ripke S;Day FR;ReproGen Consortium;Schizophrenia Working Group of the Psychiatric Genomics Consortium;RACI Consortium;Purcell S;Stahl E;Lindstrom S;Perry JR;Okada Y;Raychaudhuri S;Daly MJ;Patterson N;Neale BM;Price AL
通讯作者：
Price AL
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作者：
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