medRxivGenetic & Genomic MedicinePreprint
Genome-wide association study of adolescent-onset depression
Poppy Zenzi GrimesiD, Brittany L. MitchelliD, Katherine Nina ThompsoniD, Qingkun Deng, Xueyi SheniD, Jareth C. WolfeiD, Jodi T. ThomasiD, Robyn E. WoottoniD, Daniel E. AdkinsiD, Saranya Arirangan, Elham AssaryiD, Chris ChatzinakosiD, Charlotte A. DennisoniD, Swathi Hassan Gangaraju, Andreas JangmoiD, Yeongmi JeongiD, Siim KurvitsiD, Qingqin S. LiiD, Ehsan MotazediiD, Joonas NaamankaiD, Thuy-Dung Nguyen, Ilja Maria NolteiD, Vanessa OtaiD, Joëlle A. PasmaniD, Mina Shahisavandi, , Alex S. F. KwongiD
Abstract
Adolescent depression is a heritable psychiatric condition with rising global prevalence and severe long-term outcomes, yet its biological underpinnings remain poorly understood. We conducted the first genome-wide association study of adolescent-onset depression, comprising 102,428 cases (diagnosis or clinical symptom thresholds) and 286,911 controls, including diverse ancestries. Cross-ancestry meta-analysis identified 52 independent variants across 17 loci; European-only analysis found 61 variants at 29 loci, with a SNP-based heritability of 9.8%. Comparative analyses revealed two genes unique to adolescent-onset versus lifetime depression, enriched in neuronal subtypes, and two genes as potential drug repurposing targets. Polygenic scores were associated with adolescent-onset depression across ancestries, persistent depression trajectories, more severe outcomes, as well as reduced cortical volume, surface area and white matter integrity. Genetic correlation and Mendelian randomisation analyses support shared genetic liability and causal links with early puberty and modifiable health and behavioural risk factors. These findings uncover novel genetic loci and refine biological pathways underlying adolescent-onset depression, revealing age-specific mechanisms and early intervention opportunities.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 3
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