Linking Genome-Wide Association Studies to Pharmacological Treatments for Psychiatric Disorders

作者：Aurina Arnatkevičiūtė, Alex Fornito, Janette Tong, Ken C. Pang, Ben Fulcher, Mark A. Bellgrove · 发表于：JAMA Psychiatry · 年份：2024 · DOI：10.1001/jamapsychiatry.2024.3846 · 被引用次数：9 · 研究领域：Genetic Associations and Epidemiology、Bioinformatics and Genomic Networks、Genomics and Rare Diseases

Importance: Large-scale genome-wide association studies (GWAS) should ideally inform the development of pharmacological treatments, but whether GWAS-identified mechanisms of disease liability correspond to the pathophysiological processes targeted by current pharmacological treatments is unclear. Objective: To investigate whether functional information from a range of open bioinformatics datasets can elucidate the relationship between GWAS-identified genetic variation and the genes targeted by current treatments for psychiatric disorders. Design, Setting, and Participants: Associations between GWAS-identified genetic variation and pharmacological treatment targets were investigated across 4 psychiatric disorders-attention-deficit/hyperactivity disorder, bipolar disorder, schizophrenia, and major depressive disorder. Using a candidate set of 2232 genes listed as targets for all approved treatments in the DrugBank database, each gene was independently assigned 2 scores for each disorder-one based on its involvement as a treatment target and the other based on the mapping between GWAS-implicated single-nucleotide variants (SNVs) and genes according to 1 of 4 bioinformatic data modalities: SNV position, gene distance on the protein-protein interaction (PPI) network, brain expression quantitative trail locus (eQTL), and gene expression patterns across the brain. Study data were analyzed from November 2023 to September 2024. Main Outcomes and Measures: Gene scores for pharmacologic...