Summary: A large genome-wide association study identifies 178 genetic loci associated with major depressive disorder, offering new biological insights and potential therapeutic directions.
Source: Yale
A large-scale genome-wide association study (GWAS) analyzing genetic and health records from more than 1.2 million people has identified 178 genetic variants linked to major depressive disorder (MDD), a condition that affects a substantial portion of the global population.
Led by researchers from the U.S. Department of Veterans Affairs (V.A.), Yale University School of Medicine and the University of California San Diego (UCSD), the study pooled genomic and clinical data from multiple major biobanks to map genetic risk factors for depression. The full study was published in Nature Neuroscience on May 27.
The core dataset included genomes and medical records from over 300,000 participants in the V.A.’s Million Veteran Program (MVP), one of the world’s largest and most diverse repositories of genetic and health information. Researchers combined the MVP results with data from the UK Biobank, the Finland-based FinnGen cohort, and consumer-genetics results from 23andMe to create a meta-analysis of more than 1.2 million individuals. Findings were further validated against a separate 23andMe cohort of about 1.3 million volunteers.
When comparing results across these independent sources, most of the identified genetic markers associated with depression replicated with statistical significance, strengthening confidence in the findings. Replication across diverse cohorts is a critical benchmark for robust GWAS discoveries.
“Replication is a hallmark of good science, and this paper highlights how reliable and stable GWAS results are becoming,” said Daniel Levey, associate research scientist in the Yale Department of Psychiatry and a co-lead author. The study underscores that depression is genetically complex: risk emerges from combinations of many variants rather than any single causal mutation.
Joel Gelernter, Foundations Fund Professor of Psychiatry at Yale and co-senior author, noted the scale of discovery was expected but still striking. “We aren’t surprised by how many variants we found,” he said. “There may be hundreds—or possibly thousands—more to discover.”
Beyond cataloguing risk loci, the study provides biological context for several implicated genes. For example, NEGR1—identified among the significant loci—is a regulator of neural growth that is active in the hypothalamus, a brain region previously connected to depression. This finding aligns with earlier work highlighting neurotrophic mechanisms in mood disorders.
Transcriptome-wide association analyses also pointed to other brain-relevant genes, such as DRD2 in the nucleus accumbens, and identified overlapping gene expression patterns that help clarify how genetic variation might influence neural circuits linked to mood regulation.
The researchers fine-mapped 178 genomic risk loci and reported likely pathogenicity and overlapping expression for 17 genes from their transcriptome analyses, including TRAF3. Such functional insights can guide therapeutic discovery by highlighting molecular systems and druggable targets involved in depression.
For instance, multiple variants identified in the study affect the glutamate system, a neurotransmitter pathway that has received growing attention for depression treatment. Riluzole, an existing drug approved for amyotrophic lateral sclerosis (ALS) that modulates glutamate transmission, is among the compounds of interest based on these genetic signals. The authors emphasize that genetic evidence of pathway involvement can prioritize drugs for repurposing or new therapeutic development.
The large sample size and ancestry diversity in this GWAS enable improved development of polygenic risk scores that may eventually help clinicians identify individuals at elevated risk for major depressive disorder and related psychiatric conditions such as anxiety and post-traumatic stress disorder. Such risk stratification could inform prevention strategies and personalized treatment approaches.
“One of our goals is to bring forward new ways to treat people suffering from depression,” said co-senior author Murray Stein, staff psychiatrist at the V.A. San Diego Healthcare System and Distinguished Professor of Psychiatry and Public Health at UCSD.
Funding: The research was primarily funded by the U.S. Department of Veterans Affairs, including support for the Million Veteran Program and the Cooperative Studies Program. Daniel Levey also received a NARSAD Young Investigator Award from the Brain & Behavior Research Foundation.
About this genetics and depression research news
Source: Yale
Contact: Bess Connolly – Yale
Image: The image is in the public domain
Original Research: Closed access. “Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions” by Daniel F. Levey, Murray B. Stein, Frank R. Wendt, Gita A. Pathak, Hang Zhou, Mihaela Aslan, Rachel Quaden, Kelly M. Harrington, Yaira Z. Nuñez, Cassie Overstreet, Krishnan Radhakrishnan, Gerard Sanacora, Andrew M. McIntosh, Jingchunzi Shi, Suyash S. Shringarpure, John Concato, Renato Polimanti & Joel Gelernte. Nature Neuroscience
Abstract
Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions
Major depressive disorder is a common neuropsychiatric condition. This study reports a large meta-analysis combining data from the Million Veteran Program, 23andMe, UK Biobank and FinnGen, including individuals of European ancestry (n = 1,154,267; 340,591 cases) and African ancestry (n = 59,600; 25,843 cases). Transcriptome-wide association analyses revealed significant associations with expression of NEGR1 in the hypothalamus and DRD2 in the nucleus accumbens, among others.
The authors fine-mapped 178 genomic risk loci, identified likely pathogenic variants and overlapping gene expression for 17 genes from transcriptome-wide analyses, and demonstrated substantial replication in an independent cohort (n = 1,342,778) provided by 23andMe. The results expand understanding of the genetic architecture of depression and highlight biological pathways and potential therapeutic directions.