{"doi":"10.1016/j.biopsych.2025.11.024","title":"Integrating Multi-Omics Summary Data Identifies Candidate Molecular Mechanisms for Major Depression","abstract":"BACKGROUND: Major depression (MD) is the most common psychiatric disorder. However, despite having a significant genetic component, the underlying biological mechanisms remain poorly understood. Our analyses leveraged molecular quantitative trait loci (xQTL) data to identify molecular biomarkers for MD. METHODS: We used OPERA (Omics Pleiotropic Association) software to identify molecular phenotypes associated with MD through shared causal variants, using genome-wide association study (GWAS) summary statistics and xQTL data for 5 phenotypes in blood and brain tissues. The xQTL phenotypes were gene expression, DNA methylation, splicing variation, chromatin accessibility, and protein abundance. RESULTS: We identified 939 genes in blood tissues and 607 genes in brain tissues associated with MD via at least 1 molecular phenotype. Drug targets were enriched in our significant genes in both tissues. A total of 23 genes showed associations via 3 or more molecular phenotypes, providing robust evidence for their causal role in MD and offering insights into their biomolecular mechanisms. These high-priority associations included genes that have been previously identified by GWASs of MD such as CDH13 and RAB27B as well as novel associations such as H6PD. CONCLUSIONS: Our results highlight promising new targets for biomarker and drug target identification and successfully expand on GWAS findings to identify novel associations with MD. However, our study took a broad approach using bulk brain and blood tissues. Future research should expand these analyses into cell- and region-specific contexts.","journal":"Biological Psychiatry","year":2025,"id":549462,"datarank":0.1791619677752397,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.014370124475023255,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.014370124475023255,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":2,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9342,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":5315,"name":"Yang Wu","orcid":"0000-0002-0128-7280","position":1,"is_corresponding":false},{"id":230720,"name":"Mark J. Adams","orcid":"0000-0002-3599-6018","position":2,"is_corresponding":false},{"id":669669,"name":"Mary-Ellen Lynall","orcid":"0000-0002-1939-7525","position":3,"is_corresponding":false},{"id":373790,"name":"Jens Hjerling‐Leffler","orcid":"0000-0002-4539-1776","position":4,"is_corresponding":false},{"id":5188,"name":"Naomi R. Wray","orcid":"0000-0001-7421-3357","position":5,"is_corresponding":false},{"id":217,"name":"Andrew M. McIntosh","orcid":"0000-0002-0198-4588","position":6,"is_corresponding":false},{"id":178,"name":"Xueyi Shen","orcid":"0000-0002-0538-4774","position":7,"is_corresponding":false},{"id":1443681,"name":"Laurence Nisbet","orcid":"0009-0009-0579-9513","position":0,"is_corresponding":true}],"reference_count":53,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:54:07.823422Z","pmid":"41407005","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}