Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Mental Illness Research, Education and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA.
Addiction. 2023 Oct;118(10):1942-1952. doi: 10.1111/add.16229. Epub 2023 May 22.
BACKGROUND AND AIMS: Genome-wide association studies (GWAS) of opioid use disorder (OUD) and cannabis use disorder (CUD) have lagged behind those of alcohol use disorder (AUD) and smoking, where many more loci have been identified. We sought to identify novel loci for substance use traits (SUTs) in both African- (AFR) and European- (EUR) ancestry individuals to enhance our understanding of the traits' genetic architecture. DESIGN: We used multi-trait analysis of GWAS (MTAG) to analyze four SUTs in EUR subjects (OUD, CUD, AUD and smoking initiation [SMKinitiation]), and three SUTs in AFR subjects (OUD, AUD and smoking trajectory [SMKtrajectory]). We conducted gene-set and protein-protein interaction analyses and calculated polygenic risk scores (PRS) in two independent samples. SETTING: This study was conducted in the United States. PARTICIPANTS: A total of 5692 EUR and 4918 AFR individuals in the Yale-Penn sample and 29 054 EUR and 10 265 AFR individuals in the Penn Medicine BioBank sample. FINDINGS: MTAG identified genome-wide significant (GWS) single nucleotide polymorphisms (SNPs) for all four traits in EUR: 41 SNPs in 36 loci for OUD; 74 SNPs in 60 loci for CUD; 63 SNPs in 52 loci for AUD; and 183 SNPs in 144 loci for SMKinitiation. MTAG also identified GWS SNPs in AFR: 2 SNPs in 2 loci for OUD; 3 SNPs in 3 loci for AUD; and 1 SNP in 1 locus for SMKtrajectory. In the Yale-Penn sample, the MTAG-derived PRS consistently yielded more significant associations with both the corresponding substance use disorder diagnosis and multiple related phenotypes than the GWAS-derived PRS. CONCLUSIONS: Multi-trait analysis of genome-wide association studies boosted the number of loci found for substance use traits, identifying genes not previously linked to any substance, and increased the power of polygenic risk scores. Multi-trait analysis of genome-wide association studies can be used to identify novel associations for substance use, especially those for which the samples are smaller than those for historically legal substances.
背景和目的：与酒精使用障碍 (AUD) 和吸烟相比，阿片类药物使用障碍 (OUD) 和大麻使用障碍 (CUD) 的全基因组关联研究 (GWAS) 滞后，其中已经确定了更多的基因座。我们试图在非洲裔 (AFR) 和欧洲裔 (EUR) 个体中识别物质使用特征 (SUT) 的新基因座，以增强我们对这些特征遗传结构的理解。 设计：我们使用多特质 GWAS 分析 (MTAG) 分析了 EUR 受试者的四个 SUT（OUD、CUD、AUD 和吸烟起始 [SMKinitiation]），以及 AFR 受试者的三个 SUT（OUD、AUD 和吸烟轨迹 [SMKtrajectory]）。我们进行了基因集和蛋白质-蛋白质相互作用分析，并在两个独立样本中计算了多基因风险评分 (PRS)。 地点：本研究在美国进行。 参与者：耶鲁-宾厄姆样本中的 5692 名 EUR 和 4918 名 AFR 个体，以及宾夕法尼亚大学医学生物银行样本中的 29054 名 EUR 和 10265 名 AFR 个体。 结果：MTAG 确定了 EUR 中所有四个特征的全基因组显著 (GWS) 单核苷酸多态性 (SNP)：OUD 有 36 个基因座的 41 个 SNP；CUD 有 60 个基因座的 74 个 SNP；AUD 有 52 个基因座的 63 个 SNP；SMKinitiation 有 144 个基因座的 183 个 SNP。MTAG 还确定了 AFR 的 GWS SNP：OUD 有 2 个基因座的 2 个 SNP；AUD 有 3 个基因座的 3 个 SNP；SMKtrajectory 有 1 个基因座的 1 个 SNP。在耶鲁-宾厄姆样本中，与相应的物质使用障碍诊断和多个相关表型相比，MTAG 衍生的 PRS 产生了更显著的关联。 结论：全基因组关联研究的多特质分析增加了物质使用特征的基因座数量，确定了以前与任何物质都没有关联的基因，并提高了多基因风险评分的效能。全基因组关联研究的多特质分析可用于识别物质使用的新关联，特别是对于那些样本小于历史上合法物质的关联。
Neuropsychopharmacology. 2024-10
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