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The Forced Swim Test as a Model of Depressive-like Behavior
Published on: March 2, 2015
Genetics of major depressive disorder in a homogeneous population with uniform phenotyping
Floris Huider1,2,3, Yuri Milaneschi4,5,6, René Pool4,7
1Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, 1081, Amsterdam, The Netherlands. f.huider@vu.nl.
Abstract:
Harmonized phenotyping and diverse population-specific studies are crucial for advancing gene discovery in psychiatric genetics. We conducted a genome-wide association (GWAS) mega-analysis of DSM-defined lifetime major depressive disorder (MDD) in 64 941 participants (25.7% cases) from the Dutch BIObanks Netherlands Internet Collaboration (BIONIC) consortium. Liability-scale SNP-based heritability was 12.0% (SE = 1.4%) as estimated by LDSC (assuming a lifetime prevalence of 15%) and 26.6% (SE = 1.1%) when estimated by LDAK-REML on individual-level genotype data, indicating substantial common-variant signal in this clinically harmonized sample. The genetic correlation with the latest major depression GWAS from the Psychiatric Genomics Consortium (PGC-MD) was high (rG = 0.89, SE = 0.048). Polygenic scores (PGSs) based on BIONIC predicted depression in UK Biobank, and PGSs derived from PGC-MD predicted MDD in BIONIC, supporting transferability of depression polygenic signal across cohorts and phenotype definitions. Within-family PGS analyses in twins suggested that the observed prediction was not primarily driven by detectable family-level confounding, and twin concordance for MDD increased with polygenic burden. We identified one genome-wide significant locus, indexed by rs3818852 in PALMD, but this finding currently lacks independent replication and should be interpreted cautiously. Finally, genetic correlation and latent causal variable analyses identified multiple traits showing shared or directionally consistent genetic associations with MDD. Together, these findings underscore the value of clinically harmonized phenotyping in regional biobank collaborations for studying the genetic architecture of MDD.
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