Department of Biomedical Engineering, Whiting School of Engineering and School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Am J Med Genet B Neuropsychiatr Genet. 2021 Jun;186(4):251-258. doi: 10.1002/ajmg.b.32841. Epub 2021 Mar 8.
Variants identified by genome-wide association studies (GWAS) are often expression quantitative trait loci (eQTLs), suggesting they are proxies or are themselves regulatory. Across many data sets, analyses show that variants often affect multiple genes. Lacking data on many tissue types, developmental time points, and homogeneous cell types, the extent of this one-to-many relationship is underestimated. This raises questions on whether a disease eQTL target gene explains the genetic association or is a bystander and puts into question the direction of expression effect of on the risk, since the many variants-regulated genes may have opposing effects, imperfectly balancing each other. We used two brain gene expression data sets (CommonMind and BrainSeq) for mediation analysis of schizophrenia-associated variants. We confirm that eQTL target genes often mediate risk but the direction in which expression affects risk is often different from that in which the risk allele changes expression. Of 38 mediator genes significant in both data sets 33 showed consistent mediation direction (Chi test p = 6 × 10 ). One might expect that the expression would correlate with the risk allele in the same direction it correlates with the disease. For 15 of these 33 (45%), however, the expression change associated with the risk allele was protective, suggesting the likely presence of other target genes with overriding effects. Our results identify specific risk mediating genes and suggest caution in interpreting the biological consequences of targeted modifications of gene expression, as not all eQTL targets may be relevant to disease while those that are, might have different from expected directions.
全基因组关联研究 (GWAS) 鉴定的变体通常是表达数量性状基因座 (eQTL),这表明它们是替代物或本身就是调节物。在许多数据集的分析中表明,变体通常会影响多个基因。由于缺乏许多组织类型、发育时间点和同质细胞类型的数据,这种一一对应的关系的程度被低估了。这就提出了一个问题,即疾病 eQTL 靶基因是否解释了遗传关联,或者它只是一个旁观者,并质疑风险的表达效应的方向,因为许多受变体调节的基因可能具有相反的效应,彼此之间的平衡并不完美。我们使用了两个大脑基因表达数据集 (CommonMind 和 BrainSeq) 进行与精神分裂症相关变体的中介分析。我们证实,eQTL 靶基因通常介导风险,但表达影响风险的方向通常与风险等位基因改变表达的方向不同。在两个数据集都显著的 38 个中介基因中,有 33 个显示出一致的中介方向 (Chi 检验 p=6×10 )。人们可能期望表达与风险等位基因的相关性与其与疾病的相关性方向相同。然而,对于这 33 个中的 15 个 (45%),与风险等位基因相关的表达变化是保护性的,这表明可能存在其他具有压倒性影响的靶基因。我们的研究结果确定了特定的风险介导基因,并建议在解释针对基因表达的靶向修饰的生物学后果时要谨慎,因为并非所有的 eQTL 靶基因都与疾病相关,而那些与疾病相关的靶基因,其方向可能与预期的不同。