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 [Public Library of Science]
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.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚好五个字完成签到,获得积分10
刚刚
1秒前
2秒前
传奇3应助123采纳,获得10
2秒前
2秒前
ZLY完成签到,获得积分10
3秒前
赘婿应助YPHCC采纳,获得10
3秒前
李健应助Curiosity采纳,获得10
3秒前
愉快盼柳应助chen采纳,获得10
4秒前
月沁蓝山完成签到,获得积分10
6秒前
船舵发布了新的文献求助10
6秒前
Lucas应助紫津采纳,获得10
6秒前
owo666ooo发布了新的文献求助10
8秒前
漫不经心完成签到,获得积分20
9秒前
123应助文件撤销了驳回
10秒前
10秒前
September完成签到,获得积分10
11秒前
dw完成签到,获得积分20
12秒前
LWERTH完成签到,获得积分10
13秒前
模拟哥完成签到,获得积分10
13秒前
13秒前
zzzzzzxz发布了新的文献求助20
14秒前
小可爱发布了新的文献求助10
16秒前
老实芹完成签到,获得积分10
17秒前
18秒前
oyc完成签到,获得积分10
18秒前
ttt发布了新的文献求助10
18秒前
清脆斌完成签到,获得积分10
20秒前
2025110031077完成签到 ,获得积分10
21秒前
22秒前
小白发布了新的文献求助30
23秒前
23秒前
Sarah完成签到 ,获得积分10
23秒前
生动的访琴完成签到,获得积分10
24秒前
Heimdall发布了新的文献求助50
25秒前
26秒前
天真土豆发布了新的文献求助10
27秒前
科研通AI6.4应助ttt采纳,获得10
27秒前
charles发布了新的文献求助10
28秒前
27完成签到 ,获得积分10
30秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Markov Chain Monte Carlo 5000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Evidence Summary. Injection (subcutaneous):op- timal administration 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7492723
求助须知:如何正确求助?哪些是违规求助? 9084354
关于积分的说明 19373770
捐赠科研通 7104968
什么是DOI,文献DOI怎么找? 3249442
关于科研通互助平台的介绍 2418909
邀请新用户注册赠送积分活动 2234974