ArticlePsychological medicine2024
Genetic architecture and socio-environmental risk factors for major depressive disorder in Nepal.
Article in Psychological medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Genetic Architecture of Alcohol Use Disorder in Nepal.medRxiv : the preprint server for health sciences · 2025Article
- Genetic analysis of psychosis Biotypes: shared Ancestry-adjusted polygenic risk and unique genomic associations.Molecular psychiatry · 2025Article
- Association between living arrangement and psychological well-being among patients with major depressive disorder: the moderating role of body mass index.BMC psychiatry · 2025Article
- Genetic Analysis of Psychosis Biotypes: Shared Ancestry-Adjusted Polygenic Risk and Unique Genomic Associations.medRxiv : the preprint server for health sciences · 2024Article
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14 authors.
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Abstract
backgroundMajor depressive disorder (MDD) is the leading cause of disability globally, with moderate heritability and well-established socio-environmental risk factors. Genetic studies have been mostly restricted to European settings, with polygenic scores (PGS) demonstrating low portability across diverse global populations.
methodsThis study examines genetic architecture, polygenic prediction, and socio-environmental correlates of MDD in a family-based sample of 10 032 individuals from Nepal with array genotyping data. We used genome-based restricted maximum likelihood to estimate heritability, applied S-LDXR to estimate the cross-ancestry genetic correlation between Nepalese and European samples, and modeled PGS trained on a GWAS meta-analysis of European and East Asian ancestry samples.
resultsWe estimated the narrow-sense heritability of lifetime MDD in Nepal to be 0.26 (95% CI 0.18-0.34,
conclusionsEstimates of lifetime MDD heritability in this Nepalese sample were similar to previous European ancestry samples, but PGS trained on European data did not predict MDD in this sample. This may be due to differences in ancestry-linked causal variants, differences in depression phenotyping between the training and target data, or setting-specific environmental factors that modulate genetic effects. Additional research among under-represented global populations will ensure equitable translation of genomic findings.
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