Lu Zeyun, Wang Xinran, Carr Matthew, Kim Artem, Gazal Steven, Mohammadi Pejman, Wu Lang, Pirruccello James, Kachuri Linda, Gusev Alexander, Mancuso Nicholas
Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Nat Genet. 2025 Jul 21. doi: 10.1038/s41588-025-02262-7.
Multiancestry statistical fine-mapping of cis-molecular quantitative trait loci (cis-molQTL) aims to improve the precision of distinguishing causal cis-molQTLs from tagging variants. Here we present the sum of shared single effects (SuShiE) model, which leverages linkage disequilibrium heterogeneity to improve fine-mapping precision, infer cross-ancestry effect size correlations and estimate ancestry-specific expression prediction weights. Through extensive simulations, we find that SuShiE consistently outperforms existing methods. We apply SuShiE to 36,907 molecular phenotypes including mRNA expression and protein levels from individuals of diverse ancestries in the TOPMed-MESA and GENOA studies. SuShiE fine-maps cis-molQTLs for 18.2% more genes compared with existing methods while prioritizing fewer variants and exhibiting greater functional enrichment. While SuShiE infers highly consistent cis-molQTL architectures across ancestries, it finds evidence of heterogeneity at genes with predicted loss-of-function intolerance. Lastly, using SuShiE-derived cis-molQTL effect sizes, we perform transcriptome- and proteome-wide association studies on six white blood cell-related traits in the All of Us biobank and identify 25.4% more genes compared with existing methods. Overall, SuShiE provides new insights into the cis-genetic architecture of molecular traits.
顺式分子数量性状基因座（cis-molQTL）的多祖先统计精细定位旨在提高区分因果cis-molQTL与标签变体的精度。在此，我们提出了共享单效应总和（SuShiE）模型，该模型利用连锁不平衡异质性来提高精细定位精度、推断跨祖先效应大小相关性并估计特定祖先的表达预测权重。通过广泛的模拟，我们发现SuShiE始终优于现有方法。我们将SuShiE应用于36907种分子表型，包括来自TOPMed-MESA和GENOA研究中不同祖先个体的mRNA表达和蛋白质水平。与现有方法相比，SuShiE对多18.2%的基因进行了cis-molQTL精细定位，同时优先考虑更少的变体并表现出更大的功能富集。虽然SuShiE推断出跨祖先高度一致的cis-molQTL结构，但它在预测为功能丧失不耐受的基因中发现了异质性证据。最后，使用SuShiE衍生的cis-molQTL效应大小，我们在“我们所有人”生物样本库中对六种与白细胞相关的性状进行了全转录组和全蛋白质组关联研究，与现有方法相比，鉴定出的基因多了25.4%。总体而言，SuShiE为分子性状的顺式遗传结构提供了新的见解。
