Abstract
Background
Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive
disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared
genetic risk and sex differences in brain abnormalities across disorders suggest possible
shared sex-dependent genetic risk.
Methods
We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of
risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD)
and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.
Results
Across disorders, genome-wide significant single nucleotide polymorphism–by-sex interaction
was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10−8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase)
enzymes, implicating neuronal excitability. Three additional loci showed evidence
(p < 1 × 10−6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10−7; rs73033497, p = 8.8 × 10−7; rs7914279, p = 6.4 × 10−7), implicating various functions. Gene-based analyses identified G×S interaction across
disorders (p = 8.97 × 10−7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10−7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset
detected an interaction (rs13265509, p = 1.1 × 10−7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP,
and MDD. Pathway enrichment analysis detected significant G×S interaction of genes
regulating vascular endothelial growth factor receptor signaling in MDD (false discovery
rate-corrected p < .05).
Conclusions
In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there
was substantial genetic overlap between the sexes. However, significant sex-dependent
effects were enriched for genes related to neuronal development and immune and vascular
functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
Keywords
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