Genome-wide Mendelian randomization identifies actionable novel drug targets for psychiatric disorders

孟德尔随机化 精神分裂症(面向对象编程) 全基因组关联研究 药物重新定位 双相情感障碍 重性抑郁障碍 表达数量性状基因座 精神科 医学 转录组 药品 生物信息学 生物 单核苷酸多态性 遗传学 基因 遗传变异 认知 基因表达 基因型
作者
Jiewei Liu,Yuqi Cheng,Ming Li,Zhijun Zhang,Tao Li,Xiong‐Jian Luo
出处
期刊:Neuropsychopharmacology [Springer Nature]
卷期号:48 (2): 270-280 被引量:54
标识
DOI:10.1038/s41386-022-01456-5
摘要

Psychiatric disorders impose tremendous economic burden on society and are leading causes of disability worldwide. However, only limited drugs are available for psychiatric disorders and the efficacy of most currently used drugs is poor for many patients. To identify novel therapeutic targets for psychiatric disorders, we performed genome-wide Mendelian randomization analyses by integrating brain-derived molecular quantitative trait loci (mRNA expression and protein abundance quantitative trait loci) of 1263 actionable proteins (targeted by approved drugs or drugs in clinical phase of development) and genetic findings from large-scale genome-wide association studies (GWASs). Using transcriptome data, we identified 25 potential drug targets for psychiatric disorders, including 12 genes for schizophrenia, 7 for bipolar disorder, 7 for depression, and 1 (TIE1) for attention deficit and hyperactivity. We also identified 10 actionable drug targets by using brain proteome data, including 4 (HLA-DRB1, CAMKK2, P2RX7, and MAPK3) for schizophrenia, 1 (PRKCB) for bipolar disorder, 6 (PSMB4, IMPDH2, SERPINC1, GRIA1, P2RX7 and TAOK3) for depression. Of note, MAPK3 and HLA-DRB1 were supported by both transcriptome and proteome-wide MR analyses, suggesting that these two proteins are promising therapeutic targets for schizophrenia. Our study shows the power of integrating large-scale GWAS findings and transcriptomic and proteomic data in identifying actionable drug targets. Besides, our findings prioritize actionable novel drug targets for development of new therapeutics and provide critical drug-repurposing opportunities for psychiatric disorders.
最长约 10秒,即可获得该文献文件

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
asdfzxcv发布了新的文献求助10
刚刚
刚刚
刚刚
1秒前
1秒前
1秒前
hl发布了新的文献求助30
1秒前
张再禹发布了新的文献求助10
1秒前
科研通AI6应助细腻初雪采纳,获得10
1秒前
xuhang发布了新的文献求助10
2秒前
dudu发布了新的文献求助10
2秒前
2秒前
情怀应助xgg采纳,获得10
2秒前
科研民工发布了新的文献求助10
2秒前
3秒前
4秒前
QQ完成签到 ,获得积分10
5秒前
所所应助邱洪晓采纳,获得10
6秒前
英姑应助科研小白采纳,获得10
6秒前
潇洒紫真发布了新的文献求助10
6秒前
李健应助辛勤的发箍采纳,获得10
7秒前
闪闪的完成签到,获得积分10
7秒前
香吉士发布了新的文献求助30
7秒前
7秒前
8秒前
喵喵发布了新的文献求助10
8秒前
8秒前
宇宙拿铁完成签到,获得积分10
10秒前
斩荆披棘发布了新的文献求助10
11秒前
hyg发布了新的文献求助10
12秒前
12秒前
12秒前
付艳完成签到,获得积分10
12秒前
12秒前
12秒前
13秒前
郭丹丹完成签到 ,获得积分10
13秒前
13秒前
13秒前
胡图图发布了新的文献求助10
13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
Binary Alloy Phase Diagrams, 2nd Edition 8000
Encyclopedia of Reproduction Third Edition 3000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 2000
From Victimization to Aggression 1000
Exosomes Pipeline Insight, 2025 500
Red Book: 2024–2027 Report of the Committee on Infectious Diseases 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5648015
求助须知:如何正确求助?哪些是违规求助? 4774710
关于积分的说明 15042383
捐赠科研通 4807069
什么是DOI,文献DOI怎么找? 2570494
邀请新用户注册赠送积分活动 1527283
关于科研通互助平台的介绍 1486389