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• 研究报告 •    

自杀未遂的潜在风险蛋白:基于欧洲人群生物数据库多组学分析

彭美旗,向波   

  1. 西南医科大学附属医院精神科/睡眠医学中心,精神疾病基础与临床泸州市重点实验室,泸州 646000
  • 收稿日期:2025-11-22 修回日期:2026-01-23 发布日期:2026-02-14

Potential risk proteins for suicide attempts: multi-omics analysis based on European population biobanks

Meiqi Peng,Bo Xiang   

  1. Department of Psychiatry/Sleep Medical Center, Affiliated Hospital of Southwest Medical University, Fundamental and Clinical Research on Mental Disorders Key Laboratory of LuzhouLuzhou 646000, China  

  • Received:2025-11-22 Revised:2026-01-23 Online:2026-02-14

摘要:

自杀是个体蓄意或自愿采取各种手段结束自己生命的行为。自杀未遂(suicide-attemptsSA)是自杀死亡的一个重要的预测因子,自杀未遂的研究已经从社会心理学层面深入到分子生物学和遗传学层面。尽管全基因组关联研究(genome-wide association study, GWAS)已鉴定出多个与自杀未遂相关的风险位点,但这些风险位点的潜在机制仍不清楚。为了探寻该病的潜在风险机制,本研究通过蛋白质数量性状位点(protein quantitative trait Locus , pQTL)数据集(Banner数据集N = 152ROSMAP数据集N = 376)、表达数量性状位点(expression quantitative trait locus, eQTL)数据集(N = 452)以及自杀未遂GWAS数据(病例组N = 35786对照组N= 779392),构建了一个系统性分析流程。该流程包括蛋白质组全关联研究(proteome-wide association study, PWAS)、孟德尔随机化(Mendeian randomization, MR)、贝叶斯共定位分析(Bayesian colocalization)、转录组全关联研究transcriptome-wide association study, TWAS)和多基因关联分析(multi-marker analysis of genomic annotationMAGMA)系统性分析流程,识别并筛选出与大脑中自杀未遂机制相关的新型遗传学支持的候选蛋白质。在功能注释层面,通过GeneMANIA分析平台实现功能预测网络,整合共表达、物理互作及通路共定位以识别核心蛋白质。通过PWAS析,鉴定出3种大脑蛋白质的丰度变化与自杀未遂显著相关。其中,GMPPB被确立为自杀未遂的主要因果蛋白质,这一结论在孟德尔随机化分析(false discovery rateFDR<0.05,和贝叶斯共定位分析中(后验概率posterior probability , PPH4 ≥ 0.8)得到了强有力的验证。具体而言,遗传预测较高的GMPPB表达与较高的自杀未遂的风险有关。本研究主要聚焦于欧洲人群的数据,但鉴于遗传背景的共通性及全基因组数据分析方法的普适性,其对探索中国人群自杀未遂的生理机制、制定有效干预措施及遗传咨询等方面也具有一定的参考和借鉴意义

关键词:

自杀未遂, 全基因组关联分析, 蛋白质组全关联研究, 转录组全关联研究, 孟德尔随机化分析

Abstract:

Suicide is defined as an intentional act of ending one’s own life. Suicide attempt (SA) is a significant risk factor for suicide death. Research on SA has progressed from socio-psychological perspectives to the molecular and genetic levels. While the biological mechanisms underlying genome-wide association studies (GWAS) identified risk loci remain largely unclear. To investigate the potential risk mechanisms, we constructed a systematic analytic pipeline using brain protein quantitative trait locus (pQTL) datasets (Banner, N=152 ; ROSMAP, N=376),a brain expression quantitative trait locus (eQTL) datasets (N=452), and SA GWAS summary statistics (Ncase = 35,786, Ncontrol = 779,392).We performed proteome-wide association study (PWAS), Mendelian randomization (MR), Bayesian colocalization analysis, transcriptome-wide association study (TWAS), and multi-marker analysis of genomic annotation (MAGMA) to systematically identify and screen for novel genetically supported candidate proteins related to the biological mechanism of SA in the brain. For functional annotation, we used the GeneMANIA to bulid a functional prediction network integrating co-expression, physical interactions, and pathway colocalization to identify core proteins. PWAS identified three brain proteins whose genetically predicted abundance was significantly associated with SA. Among them, GMPPB was prioritized as putative causal protein, supported by MR analysis (false discovery rate, FDR<0.05) and Bayesian colocalization analysis (posterior probability PPH4≥0.8). Specifically, higher genetically predicted GMPPB protein levels were associated with increased risk of SA. Although our analyses primarily relied on datasets from European-ancestry populations, the shared genetic architecture across populations and the generalizability of genome-wide data analytical approaches suggest that our findings may still provide useful insights into the biological mechanisms underlying SA and help inforn the development of intervention strategies and genetic counseling in Chinese populations.

Key words:

suicide attempt, genome-wide association analysis, PWAS, TWAS, Mendelian randomization analysis