Leger Brittany S, Meredith John J, Ideker Trey, Sanchez-Roige Sandra, Palmer Abraham A
Program in Biomedical Sciences, University of California San Diego, La Jolla, California, USA.
Department of Psychiatry, University of California San Diego, La Jolla, California, USA.
Alcohol Clin Exp Res (Hoboken). 2024 Sep;48(9):1704-1715. doi: 10.1111/acer.15399. Epub 2024 Jun 21.
Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, genetic studies of alcohol consumption that use rare variants are still in their early stages. No prior studies of alcohol consumption have examined whether common and rare variants implicate the same genes and molecular networks, leaving open the possibility that the two approaches might identify distinct biology.
To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N = 666,978) and whole exome sequencing data (Genebass, N = 393,099) to identify a set of common and rare variants for alcohol consumption. We used gene-based analysis to implicate genes from common and rare variant analyses, which we then propagated onto a shared molecular network using a network colocalization procedure.
Gene-based analysis of each dataset implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified in only the rare variant analysis, but have been associated with other neuropsychiatric traits. Network colocalization revealed significant network overlap between the genes identified via common and rare variants. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. Seventy-one of the genes in the shared network were previously implicated in neuropsychiatric or substance use disorders but not alcohol-related behaviors (e.g. EXOC2, EPM2A, and CACNG4). Differential gene expression analysis showed enrichment in the liver and several brain regions.
Genes implicated by network colocalization identify shared biology relevant to alcohol consumption, which also underlie neuropsychiatric traits and substance use disorders that are comorbid with alcohol use, providing a more holistic understanding of two disparate sources of genetic information.
全基因组关联研究（GWAS）已鉴定出数百种与饮酒相关的常见变异。相比之下，利用罕见变异进行的饮酒遗传研究仍处于早期阶段。此前尚无饮酒研究考察常见变异和罕见变异是否涉及相同的基因和分子网络，这使得两种方法可能识别出不同生物学机制的可能性依然存在。
为填补这一知识空白，我们使用公开可用的饮酒GWAS汇总统计数据（GSCAN，N = 666,978）和全外显子测序数据（Genebass，N = 393,099）来鉴定一组饮酒相关的常见和罕见变异。我们采用基于基因的分析来确定常见和罕见变异分析所涉及的基因，然后使用网络共定位程序将这些基因映射到一个共享的分子网络上。
对每个数据集进行基于基因的分析分别鉴定出294个（常见变异）和35个（罕见变异）基因，包括乙醇代谢基因ADH1B和ADH1C，这两个基因在两种分析中均被鉴定出来，还有ANKRD12、GIGYF1、KIF21B和STK31，这些基因仅在罕见变异分析中被鉴定出来，但已与其他神经精神性状相关联。网络共定位揭示了通过常见变异和罕见变异鉴定出的基因之间存在显著的网络重叠。共享网络鉴定出了在酒精代谢中起作用的基因家族，包括ADH、ALDH、CYP和UGT。共享网络中的71个基因先前与神经精神或物质使用障碍有关，但与饮酒相关行为无关（例如EXOC2、EPM2A和CACNG4）。差异基因表达分析显示在肝脏和几个脑区存在富集。
通过网络共定位鉴定出的基因识别出了与饮酒相关的共享生物学机制，这些机制也是与饮酒共病的神经精神性状和物质使用障碍的基础，从而对两种不同的遗传信息来源有了更全面的理解。
