A multi-ancestry genetic study of pain intensity in 598,339 veterans

强度(物理) 医学 遗传谱系 人口学 环境卫生 社会学 量子力学 物理 人口
作者
Sylvanus Toikumo,Rachel Vickers‐Smith,Zeal Jinwala,Heng Xu,Divya Saini,Emily E. Hartwell,Mirko Pavicic,Kyle A. Sullivan,Ke Xu,Daniel Jacobson,Joel Gelernter,Christopher T. Rentsch,Mirko Pavicic,Eli A. Stahl,Martin D. Cheatle,Hang Zhou,Stephen G. Waxman,Amy C. Justice,Rachel L. Kember,Henry R. Kranzler
出处
期刊:Nature Medicine [Springer Nature]
卷期号:30 (4): 1075-1084 被引量:12
标识
DOI:10.1038/s41591-024-02839-5
摘要

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects the quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids had a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well-characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 126 independent genetic loci, 69 of which are new. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level and cognitive traits. Integration of the genome-wide association studies findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, β-blockers and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.
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
李爱国应助风中的丝袜采纳,获得10
1秒前
1123应助甜画舫采纳,获得30
1秒前
2秒前
科研通AI2S应助clear2000采纳,获得10
3秒前
Hello应助玲玲采纳,获得10
3秒前
WMT发布了新的文献求助10
3秒前
4秒前
慕青应助木木夕采纳,获得30
4秒前
汉堡包应助jonathan采纳,获得10
4秒前
5秒前
6秒前
带馅儿的酥饼完成签到,获得积分10
7秒前
111关闭了111文献求助
7秒前
英俊的铭应助YXM采纳,获得30
7秒前
李健应助ash采纳,获得10
8秒前
田様应助考研小白采纳,获得10
8秒前
pluto应助自由莆采纳,获得30
9秒前
10秒前
10秒前
光亮秋白发布了新的文献求助10
10秒前
我的天啊发布了新的文献求助10
10秒前
刻苦羽毛完成签到,获得积分10
12秒前
13秒前
13秒前
勤奋应助勤奋的夜春采纳,获得10
14秒前
kylooe415应助fanfan采纳,获得10
14秒前
英姑应助村长采纳,获得10
14秒前
火星上的如松完成签到,获得积分10
15秒前
斯文涔雨发布了新的文献求助10
15秒前
15秒前
16秒前
17秒前
19秒前
彭于晏应助感动的雁易采纳,获得10
19秒前
Luke发布了新的文献求助10
19秒前
没有逗完成签到,获得积分10
20秒前
考研小白发布了新的文献求助10
20秒前
星星发布了新的文献求助10
20秒前
Owen应助alden采纳,获得10
21秒前
丘比特应助罗某人采纳,获得10
21秒前
高分求助中
Genetics: From Genes to Genomes 3000
Production Logging: Theoretical and Interpretive Elements 2500
Continuum thermodynamics and material modelling 2000
Healthcare Finance: Modern Financial Analysis for Accelerating Biomedical Innovation 2000
Applications of Emerging Nanomaterials and Nanotechnology 1111
Les Mantodea de Guyane Insecta, Polyneoptera 1000
Diabetes: miniguías Asklepios 800
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3471080
求助须知:如何正确求助?哪些是违规求助? 3063958
关于积分的说明 9086723
捐赠科研通 2754610
什么是DOI,文献DOI怎么找? 1511504
邀请新用户注册赠送积分活动 698446
科研通“疑难数据库(出版商)”最低求助积分说明 698351