Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits,American Journal of Human Genetics

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Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits
American Journal of Human Genetics ( IF 9.8 ) Pub Date : 2022-06-17 , DOI: 10.1016/j.ajhg.2022.05.014
Roshni A Patel ₁ , Shaila A Musharoff ₂ , Jeffrey P Spence ₁ , Harold Pimentel ₃ , Catherine Tcheandjieu ₄ , Hakhamanesh Mostafavi ₁ , Nasa Sinnott-Armstrong ₂ , Shoa L Clarke ₄ , Courtney J Smith ₁ , , Peter P Durda ₅ , Kent D Taylor ₆ , Russell Tracy ₅ , Yongmei Liu ₇ , W Craig Johnson ₈ , Francois Aguet ₉ , Kristin G Ardlie ₉ , Stacey Gabriel ₉ , Josh Smith ₁₀ , Deborah A Nickerson ₁₀ , Stephen S Rich ₁₁ , Jerome I Rotter ₆ , Philip S Tsao ₄ , Themistocles L Assimes ₄ , Jonathan K Pritchard ₁₂

Affiliation

Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Genetics, Stanford University School of Medicine, Stanford, CA, USA; VA Palo Alto Health Care System, Palo Alto, CA, USA.
Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA.
VA Palo Alto Health Care System, Palo Alto, CA, USA; Stanford University School of Medicine, Stanford, CA, USA.
The Robert Larner, M.D. College of Medicine at The University of Vermont, Burlington, VT, USA.
Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
Duke University School of Medicine, Durham, NC, USA.
Biostatistics, University of Washington, Seattle, WA, USA.
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Genome Sciences, University of Washington, Seattle, WA, USA.
Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
Genetics, Stanford University School of Medicine, Stanford, CA, USA; Biology, Stanford University, Stanford, CA, USA.

Despite the growing number of genome-wide association studies (GWASs), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWASs are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate, although this is not significant, most likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits.

中文翻译：

遗传相互作用驱动基因表达和复杂性状的因果变异效应大小的异质性

尽管全基因组关联研究 (GWAS) 的数量不断增加，但基因与基因和基因与环境的相互作用在多大程度上影响人类的复杂性状仍不清楚。复杂性状中遗传相互作用的程度一直难以量化，因为 GWAS 通常不足以检测具有小效应的个体相互作用。在这里，我们开发了一种方法来测试遗传相互作用，该方法汇总了所有与性状相关的基因座的信息。具体来说，我们测试了欧裔美国人和混血的非裔美国人共享的欧洲血统区域中的 SNP 是否具有相同的因果效应大小。我们假设在非裔美国人中，遗传相互作用的存在将推动欧洲血统地区 SNP 的因果效应大小与非洲血统地区 SNP 的因果效应大小更相似。我们将我们的方法应用于两个特征：动脉粥样硬化多种族研究 (MESA) 中 296 名非裔美国人和 482 名欧洲美国人的基因表达，以及 74,000 名非洲裔美国人和 296,000 名欧洲美国人的低密度脂蛋白胆固醇 (LDL-C)百万退伍军人计划 (MVP)。我们在基因表达分析中发现了遗传相互作用的重要证据；对于 LDL-C，我们观察到类似的点估计，尽管这并不显着，很可能是由于较低的统计功效。这些结果表明，基因与基因或基因与环境的相互作用改变了人类复杂特征中因果变异的影响大小。

更新日期：2022-06-17

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