In a genome-wide association study (GWAS) meta-analysis of 685,808 individuals with major depression (MD) and 4,364,225 controls from 29 countries and across diverse and admixed ancestries, we identify 697 independent associations at 636 loci, 293 of which are novel. Using fine-mapping and functional genomic tools, we find 308 high-confidence gene associations and enrichment of postsynaptic density and receptor clustering. Leveraging new single-cell gene expression data, we conducted a causal neural cell type enrichment analysis that implicates dysregulation of excitatory and inhibitory midbrain and forebrain neurons, peptidergic neurons, and medium spiny neurons in MD. Our findings are enriched for the targets of antidepressants and provide potential antidepressant repurposing opportunities (e.g., pregabalin and modafinil). Polygenic scores (PGS) trained using either European or multi-ancestry data significantly predicted MD status across all five diverse ancestries and explained a maximum of 5.8% of the variance in liability to MD in Europeans. These findings represent a major advance in our understanding of MD across global populations. MD GWAS reveals known and novel biological targets that may be used to target and develop pharmacotherapies addressing the considerable unmet need for effective treatment.

Cathryn Lewis is a member of the SAB for Myriad Neuroscience and has received consultancy fees from UCB.

We would like to thank the participants and investigators from all studies and the research participants and employees of 23andMe for making this metaanalysis 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 #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, 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, phs000187) and including data from: the Molecular Genetics of Schizophrenia Collaboration (Pablo Gejman, Northwestern University), the NINDS CIDR:NGRC Parkinsons Disease Study, and the SNP Association Analysis of Melanoma: Case Control and Outcomes Investigation (supported by FNIH GAIN study, CA093459, CA097007, ES011740, and CA133996). Individual study funding and other acknowledgements are provided in the supplementary study information. This paper represents independent research partly funded by the NIHR Maudsley Biomedical Research Centre and Maudsley NHS Foundation Trust and Kings College London; 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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Ethical permission was given for all of the contributing datasets in this genome-wide association study meta-analysis.

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