Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome

表达数量性状基因座 生物 孟德尔随机化 遗传学 疾病 基因 转录组 全基因组关联研究 重性抑郁障碍 双相情感障碍 生物信息学 医学 基因表达 单核苷酸多态性 神经科学 内科学 基因型 认知 遗传变异
作者
Denis Baird,Yushi Liu,Jie Zheng,Solveig K. Sieberts,Thanneer M. Perumal,Benjamin Elsworth,Tom G Richardson,Chia Yen Chen,Minerva M. Carrasquillo,Mariet Allen,Joseph S. Reddy,Philip L. De Jager,Nilüfer Ertekin-Taner,Lara M. Mangravite,Benjamin A. Logsdon,Karol Estrada,Philip Haycock,Gibran Hemani,Heiko Runz,George Davey Smith,Tom R. Gaunt
出处
期刊:PLOS Genetics 卷期号:17 (1): e1009224-e1009224 被引量:31
标识
DOI:10.1371/journal.pgen.1009224
摘要

Discovering drugs that efficiently treat brain diseases has been challenging. Genetic variants that modulate the expression of potential drug targets can be utilized to assess the efficacy of therapeutic interventions. We therefore employed Mendelian Randomization (MR) on gene expression measured in brain tissue to identify drug targets involved in neurological and psychiatric diseases. We conducted a two-sample MR using cis-acting brain-derived expression quantitative trait loci (eQTLs) from the Accelerating Medicines Partnership for Alzheimer's Disease consortium (AMP-AD) and the CommonMind Consortium (CMC) meta-analysis study (n = 1,286) as genetic instruments to predict the effects of 7,137 genes on 12 neurological and psychiatric disorders. We conducted Bayesian colocalization analysis on the top MR findings (using P<6x10-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer's disease, 6 genes with Parkinson's disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.
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