Abstract
In a genome-wide association study (GWAS) meta-analysis of 688,808 individuals with major depression (MD) and 4,364,225 controls from 29 countries across diverse and admixed ancestries, we identify 697 associations at 635 loci, 293 of which are novel. Using fine-mapping and functional tools, we find 308 high-confidence gene associations and enrichment of postsynaptic density and receptor clustering. A neural cell-type enrichment analysis utilizing single-cell data implicates excitatory, inhibitory, and medium spiny neurons and the involvement of amygdala neurons in both mouse and human single-cell analyses. The associations are enriched for antidepressant targets and provide potential repurposing opportunities. Polygenic scores trained using European or multi-ancestry data predicted MD status across all ancestries, explaining up to 5.8% of MD liability variance in Europeans. These findings advance our global understanding of MD and reveal biological targets that may be used to target and develop pharmacotherapies addressing the unmet need for effective treatment.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Cell |
| Vol/bind | 188 |
| Udgave nummer | 3 |
| Sider (fra-til) | 640-652.e9 |
| ISSN | 0092-8674 |
| DOI | |
| Status | Udgivet - 2025 |
Bibliografisk note
Funding Information:We would like to thank the participants and investigators from all studies and the research participants and employees of 23andMe for making this meta-analysis possible. This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by award no. 1IK2BX005058 and I01CX001849. This publication does not represent the views of the Department of Veteran Affairs or the United States Government. Major funding for the PGC is from the US National Institutes of Health (MH124873 and MH124871). Statistical analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org/) hosted by SURFsara. The iPSYCH team acknowledges funding from the Lundbeck Foundation (grants R102-A9118 and R155-2014-1724), the Stanley Medical Research Institute, the Novo Nordisk Foundation for supporting the Danish National Biobank resource, and the GenomeDK HPC facility. This research has been conducted using the UK Biobank Resource (application 4844) and data from dbGaP (accession phs000021, phs000196, and phs000187) and including data from the Molecular Genetics of Schizophrenia Collaboration (Pablo Gejman, Northwestern University), the NINDS CIDR:NGRC Parkinson's Disease Study, and the SNP Association Analysis of Melanoma: Case-Control and Outcomes Investigation (supported by the FNIH GAIN study, CA093459, CA097007, ES011740, and CA133996). Individual study funding and other acknowledgments are provided in the supplementary study information (Methods S1). This paper represents independent research partly funded by the NIHR Maudsley Biomedical Research Centre and Maudsley NHS Foundation Trust and King's College London, and the views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The current work was also supported by the Wellcome Trust (220857/Z/20/Z) and the European Union under the Horizon 2020 research and innovation programme (no. 847776 and 948561).
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