美国斯坦福大学Stephen B. Montgomery、Nathan S. Abell研究组取得一项新突破。他们的最新研究发现多种因果变异是人类遗传关联的基础。2022年3月18日，国际学术期刊《科学》发表了这一成果。

研究人员应用大规模平行报告基因分析（MPRA）对独立顺式表达数量性状基因座（eQTL）的高、局部连锁不平衡（LD）中的遗传变异进行了功能评估。研究发现17.7%的eQTL在强LD中表现出不止一种主要等位基因效应。研究人员发现了调节变体频率且特异性富集用于激活染色质结构和等位基因的转录因子结合。将MPRA分析与114种人类性状和疾病相关eQTL/复杂性状共定位相结合，研究确定了因果变异集，展示了遗传关联信号如何通过多个紧密相关的因果变异表现出来。

研究人员表示，遗传变异和性状之间的关联通常位于具有强LD的非编码区域，单个因果变异是确定关联的基础。

附：英文原文

Title: Multiple causal variants underlie genetic associations in humans

Author: Nathan S. Abell, Marianne K. DeGorter, Michael J. Gloudemans, Emily Greenwald, Kevin S. Smith, Zihuai He, Stephen B. Montgomery

Issue&Volume: 2022-03-18

Abstract: Associations between genetic variation and traits are often in noncoding regions with strong linkage disequilibrium (LD), where a single causal variant is assumed to underlie the association. We applied a massively parallel reporter assay (MPRA) to functionally evaluate genetic variants in high, local LD for independent cis-expression quantitative trait loci (eQTL). We found that 17.7% of eQTLs exhibit more than one major allelic effect in tight LD. The detected regulatory variants were highly and specifically enriched for activating chromatin structures and allelic transcription factor binding. Integration of MPRA profiles with eQTL/complex trait colocalizations across 114 human traits and diseases identified causal variant sets demonstrating how genetic association signals can manifest through multiple, tightly linked causal variants.

DOI: abj5117

Source: https://www.science.org/doi/10.1126/science.abj5117