Pub Date : 2025-12-23DOI: 10.1016/j.biopsych.2025.11.002
Sameer A. Sheth, Timon Merk, Nicole R. Provenza
{"title":"Predictors of Response to Deep Brain Stimulation for Depression","authors":"Sameer A. Sheth, Timon Merk, Nicole R. Provenza","doi":"10.1016/j.biopsych.2025.11.002","DOIUrl":"10.1016/j.biopsych.2025.11.002","url":null,"abstract":"","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":"99 3","pages":"Pages 180-181"},"PeriodicalIF":9.0,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145801873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-23DOI: 10.1016/j.biopsych.2025.11.003
Jennifer W. Evans, Carlos A. Zarate Jr.
{"title":"Network Localization of Functional Brain Changes Associated With Ketamine's Therapeutic Effects in Depression","authors":"Jennifer W. Evans, Carlos A. Zarate Jr.","doi":"10.1016/j.biopsych.2025.11.003","DOIUrl":"10.1016/j.biopsych.2025.11.003","url":null,"abstract":"","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":"99 3","pages":"Pages 184-185"},"PeriodicalIF":9.0,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145801875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-23DOI: 10.1016/j.biopsych.2025.10.026
Maria Teresa Gallo
{"title":"Two Windows, Two Outcomes: Developmental Timing and Sex-Specific Consequences of Early Fluoxetine Exposure","authors":"Maria Teresa Gallo","doi":"10.1016/j.biopsych.2025.10.026","DOIUrl":"10.1016/j.biopsych.2025.10.026","url":null,"abstract":"","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":"99 3","pages":"Pages 186-188"},"PeriodicalIF":9.0,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-18DOI: 10.1016/j.biopsych.2025.11.025
Alex S. Cohen, Brian Kirkpatrick, Mark Opler, Kazunori Tatsumi, Seema Bhat, Laxminarayan Bhat
{"title":"A single, interpretable vocal biomarker for enriching antipsychotic clinical trials","authors":"Alex S. Cohen, Brian Kirkpatrick, Mark Opler, Kazunori Tatsumi, Seema Bhat, Laxminarayan Bhat","doi":"10.1016/j.biopsych.2025.11.025","DOIUrl":"https://doi.org/10.1016/j.biopsych.2025.11.025","url":null,"abstract":"","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":"23 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1016/j.biopsych.2025.11.024
Laurence Nisbet, Yang Wu, Mark Adams, Mary-Ellen Lynall, Jens Hjerling-Leffler, Naomi R Wray, Andrew M McIntosh, Xueyi Shen
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 the OPERA software to identify molecular phenotypes associated with MD through shared causal variants, using genome-wide association study (GWAS) summary statistics and xQTL data for five phenotypes in the blood and brain. The xQTL phenotypes were gene expression, DNA methylation, splicing variation, chromatin accessibility and protein abundance.
Results: We identified 939 genes in blood and 607 genes in brain associated with MD via at least one molecular phenotype. Drug targets were enriched in our significant genes in both tissues. Twenty-three genes showed associations via three 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 GWAS studies 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 upon GWAS findings to identify novel associations with MD. However, our study took a broad approach using bulk brain and blood. Future research should expand these analyses into cell and region-specific contexts.
{"title":"Integrating multi-omic summary data identifies candidate molecular mechanisms for Major Depression.","authors":"Laurence Nisbet, Yang Wu, Mark Adams, Mary-Ellen Lynall, Jens Hjerling-Leffler, Naomi R Wray, Andrew M McIntosh, Xueyi Shen","doi":"10.1016/j.biopsych.2025.11.024","DOIUrl":"https://doi.org/10.1016/j.biopsych.2025.11.024","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>We used the OPERA software to identify molecular phenotypes associated with MD through shared causal variants, using genome-wide association study (GWAS) summary statistics and xQTL data for five phenotypes in the blood and brain. The xQTL phenotypes were gene expression, DNA methylation, splicing variation, chromatin accessibility and protein abundance.</p><p><strong>Results: </strong>We identified 939 genes in blood and 607 genes in brain associated with MD via at least one molecular phenotype. Drug targets were enriched in our significant genes in both tissues. Twenty-three genes showed associations via three 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 GWAS studies of MD such as CDH13 and RAB27B, as well as novel associations such as H6PD.</p><p><strong>Conclusions: </strong>Our results highlight promising new targets for biomarker and drug target identification, and successfully expand upon GWAS findings to identify novel associations with MD. However, our study took a broad approach using bulk brain and blood. Future research should expand these analyses into cell and region-specific contexts.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145773399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-11DOI: 10.1016/j.biopsych.2025.12.005
Ashley Ross, Anna M. Patterson, Tory A. Eisenlohr-Moul
{"title":"Molecular Mechanisms of Menstrual Cycle-Related Suicide Risk: A Selective Review of Promising Candidate Systems","authors":"Ashley Ross, Anna M. Patterson, Tory A. Eisenlohr-Moul","doi":"10.1016/j.biopsych.2025.12.005","DOIUrl":"https://doi.org/10.1016/j.biopsych.2025.12.005","url":null,"abstract":"","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":"19 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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