Evidence map›Paper›PMID 42920133›Full record

ArticleBMC medicine2026

Genetic prioritization of HSDL2 in suicide and intentional self-harm: multi-omics evidence linking lipid metabolism and neuronal vulnerability.

Ziyan Zhang, Yutong Wu, Fanxu Meng, Hanbing Ji, Hai Zhong, Shucheng Si, Yun Wei, Yilei Ge, Sijia Wu, Qingxin Luo and 13 more

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Article in BMC medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

23 authors.

Ziyan Zhang *Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Yutong Wu *National Institute of Health and Medical Big Data, Jinan, 250003, China.
Fanxu MengNational Institute of Health and Medical Big Data, Jinan, 250003, China.
Hanbing JiDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Hai ZhongDepartment of Radiology, the Second Qilu Hospital of Shandong University, Shandong University, Jinan, 250063, China.
Shucheng SiResearch Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, 100191, China.
Yun WeiNational Institute of Health and Medical Big Data, Jinan, 250003, China.
Yilei GeNational Institute of Health and Medical Big Data, Jinan, 250003, China.
Sijia WuNational Institute of Health and Medical Big Data, Jinan, 250003, China.
Qingxin LuoNational Institute of Health and Medical Big Data, Jinan, 250003, China.
Le WangDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Tiemei LiuDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Jiawei XiuDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Yiman GuoDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Yue LiDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Lei HouNational Institute of Health and Medical Big Data, Jinan, 250003, China.
Hao ChenDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Xiaoru SunNational Institute of Health and Medical Big Data, Jinan, 250003, China.
Yuanyuan YuNational Institute of Health and Medical Big Data, Jinan, 250003, China.
Qingzhen HouDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Shanshan GaoCenter for Reproductive Medicine, the Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China. 202162019102@email.sdu.edu.cn.ORCID http://orcid.org/0000-0003-4355-8365
Fuzhong XueNational Institute of Health and Medical Big Data, Jinan, 250003, China. xuefzh@sdu.edu.cn.ORCID http://orcid.org/0000-0003-0378-7956
Hongkai LiDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China. lihongkaiyouxiang@163.com.ORCID http://orcid.org/0000-0003-1848-937X

Funding

Key Technology Research and Development Program of Shandong Province 2024CXPT085National Key Research and Development Program of China 2020YFC2003500National Natural Science Foundation of China 82330108National Natural Science Foundation of China 82404368National Natural Science Foundation of China 82404370National Natural Science Foundation of China 82404377National Natural Science Foundation of China 82404378Natural Science Foundation of Shandong Province ZR2023QH236Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China SDAST2024QTB020Shandong Medical Association Clinical Research Fund - Qilu Special Project of China YXH2022DZX02008the Jinan Municipal "20 Measures for Universities, 2025 Edition" Competitive Science and Technology Innovation Platform Program 202534084the Major Science and Technology Special Project of the Ministry of Science and Technology of China 2026ZD0557904
6 · The paper itself

Abstract

backgroundSuicide or other intentional self-harm (SSH) represents a critical global public health burden, yet biologically informed targets remain poorly defined due to its complex and incompletely understood etiology. This study aimed to prioritize genetically supported candidate targets for SSH and characterize their biological and translational relevance.

methodsWe developed a multi-omics evidence framework integrating transcriptomic and proteomic Mendelian randomization, colocalization, and sensitivity diagnostics. The primary SSH outcome was from FinnGen R12 (11,538 cases; 488,810 controls). eQTLGen and GTEx were used for transcriptomic analyses, and UKB-PPP and ARIC for proteomic validation. Downstream analyses included functional enrichment, tissue expression profiling, exploratory metabolomic pathway analysis, brain cell-type-specific eQTL analyses, phenome-wide liability scanning, structural modeling with docking, virtual screening and molecular dynamics simulations, and baseline SSH classification in UKB-PPP individual-level proteomic data.

resultsTranscriptome-wide MR identified 1,164 FDR-significant genes, of which 55 were retained as Tier 1-4 prioritized candidates after proteomic validation, colocalization, and sensitivity assessment. HSDL2 was the sole Tier 1 candidate, supported by consistent eQTL and pQTL evidence, adequate instrument strength, and colocalization at the HSDL2 locus (PP.H4 = 0.797). Genetically predicted HSDL2 expression was associated with higher SSH risk in eQTLGen (OR = 1.133, 95% CI: 1.076-1.192) and showed directionally consistent protein-level evidence in UKB-PPP (OR = 1.050, 95% CI: 1.005-1.098). Enrichment and metabolomic analyses implicated lipid-, bile acid-, and organelle-related pathways. Brain cell-type-specific analyses suggested neuronal involvement, with consistent excitatory-neuron associations across discovery and validation datasets and additional support for inhibitory neurons in SingleBrain, while oligodendrocyte signals required cautious interpretation. Structural analyses supported a putative HSDL2 ligand-binding pocket, providing hypothesis-generating structural context for the metabolic findings. Phenome-wide MR analyses identified additional disease associations, providing phenotypic context for future target evaluation. UKB-PPP baseline classification analyses provided complementary individual-level support for the prioritized protein signal.

conclusionsHSDL2 was prioritized as a genetically supported and biologically plausible candidate target for SSH, implicating a potential lipid-metabolic and neuronal vulnerability axis. These findings provide a foundation for future mechanistic validation and translational investigation.

Indexed as

Lipid MetabolismNeuronsSelf-Injurious BehaviorSuicideGene Expression ProfilingHumansMultiomicsProteomicsQuantitative Trait LociAlphaFold 3Brain cell-type specificityHSDL2Lipid metabolismMendelian randomizationMulti-omicsSuicide or other intentional self-harm

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.