Genetic architecture and socio-environmental risk factors for major depressive disorder in Nepal.

BACKGROUND

Major 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.

METHODS

This 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.

RESULTS

We estimated the narrow-sense heritability of lifetime MDD in Nepal to be 0.26 (95% CI 0.18-0.34, = 8.5 × 10). Our analysis was underpowered to estimate the cross-ancestry genetic correlation (rg = 0.26, 95% CI -0.29 to 0.81). MDD risk was associated with higher age (beta = 0.071, 95% CI 0.06-0.08), female sex (beta = 0.160, 95% CI 0.15-0.17), and childhood exposure to potentially traumatic events (beta = 0.050, 95% CI 0.03-0.07), while neither the depression PGS (beta = 0.004, 95% CI -0.004 to 0.01) or its interaction with childhood trauma (beta = 0.007, 95% CI -0.01 to 0.03) were strongly associated with MDD.

CONCLUSIONS

Estimates 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.