Identification of novel proteins associated with movement-related adverse antipsychotic effects by integrating GWAS data and human brain proteomes

全基因组关联研究 候选基因 生物 孟德尔随机化 遗传关联 计算生物学 神经科学 遗传学 基因 单核苷酸多态性 基因型 遗传变异
作者
Jiqing Li,Jicheng Pang,Shucheng Si,Kai Zhang,Fang Tang,Fuzhong Xue
出处
期刊:Psychiatry Research-neuroimaging [Elsevier BV]
卷期号:317: 114791-114791 被引量:3
标识
DOI:10.1016/j.psychres.2022.114791
摘要

Genome-wide association studies (GWAS) have identified some variants for movement-related adverse antipsychotic effects (MAAE), while how these variants confer MAAE remains unclear. We used the probabilistic Mendelian randomization (PMR) method to identify candidate proteins for MAAE by integrating MAAE GWASs and protein quantitative trait loci (pQTL) data. An independent pQTL data from the Banner project and brain-derived eQTL data were used to perform confirmatory PMR. A total of 56 proteins were identified as candidate targets for MAAE after false discovery rates (FDR) correction, such as GRIN2B, ADRA1A, and PED4B. 12 genes were replicated in the confirmatory PMR, and 18 genes had consistent evidence at the transcript level. Furthermore, we investigated the associations between candidate proteins and the motor symptoms of Parkinson's disease (PD). There were 24, 38, and 10 candidate proteins that were significantly associated with PD, PD motor subtypes, and PD motor progression, respectively. Enrichment analysis identified 34 GO terms and 17 pathways that may be involved in MAAE, such as glutamatergic synapse, glutamate receptor complex, and GABAergic synapse. Our study identified multiple candidate genes and pathways that were associated with MAAE, providing new insights into the biological mechanism of MAAE and targets for further mechanistic and therapeutic studies.
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
空域发布了新的文献求助10
1秒前
benyu完成签到,获得积分10
2秒前
2秒前
温柔的牛青应助代dai采纳,获得10
3秒前
sanxuan完成签到 ,获得积分10
3秒前
林JJ的小可爱完成签到,获得积分10
3秒前
科研通AI6.1应助聪慧寄文采纳,获得10
3秒前
乐兰正雪发布了新的文献求助10
4秒前
Leohp完成签到,获得积分10
4秒前
sy193625完成签到,获得积分10
4秒前
DZQ完成签到,获得积分10
4秒前
Melon完成签到 ,获得积分10
4秒前
清欢完成签到,获得积分10
5秒前
锂离子完成签到,获得积分10
5秒前
5秒前
小豆包完成签到 ,获得积分10
7秒前
谢明明发布了新的文献求助30
7秒前
喜东东完成签到,获得积分10
7秒前
小白t73完成签到 ,获得积分10
8秒前
9秒前
11111111完成签到,获得积分10
9秒前
PHW完成签到,获得积分10
9秒前
小白完成签到,获得积分10
11秒前
12秒前
努力搬砖的小胡完成签到,获得积分10
13秒前
英俊的铭应助Iris采纳,获得10
13秒前
14秒前
chengche发布了新的文献求助10
14秒前
灰太狼完成签到,获得积分10
14秒前
pepperlight完成签到 ,获得积分10
14秒前
MCS完成签到,获得积分10
15秒前
15秒前
咕咕完成签到 ,获得积分10
15秒前
刘总完成签到 ,获得积分10
15秒前
自费上学又一天完成签到,获得积分10
16秒前
17秒前
17秒前
鱼瓜强发布了新的文献求助10
17秒前
骑猪兜风完成签到 ,获得积分10
18秒前
臭皮完成签到,获得积分10
18秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 800
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Bounds for Statistical Estimation in Semiparametric Models 500
Climate change and sports: Statistics report on climate change and sports 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6474043
求助须知:如何正确求助?哪些是违规求助? 8276949
关于积分的说明 17647516
捐赠科研通 5554561
什么是DOI,文献DOI怎么找? 2909870
邀请新用户注册赠送积分活动 1886625
关于科研通互助平台的介绍 1739115