Background. Genetic correlation and pleiotropic effects among psychiatric disorders have been reported. This study aimed to identify specific common genetic variants shared between five adult psychiatric disorders: schizophrenia, bipolar, major depressive disorder, attention deficit-hyperactivity disorder, and autism spectrum disorder.
Methods. A combined p-value of about 8 million single nucleotide polymorphisms (SNPs) was calculated in an equivalent sample of 151,672 cases and 284,444 controls of European ancestry from published data based on the latest genome-wide association studies of five major psychiatric disorder. SNPs that achieved genome-wide significance (P<5x10-08) were mapped to loci and genomic regions for further investigation; gene annotation and clustering were performed to understand the biological process and molecular function of the loci identified. We also examined CNVs and performed expression quantitative trait loci analysis for SNPs by genomic region.
Results. We find that 6,293 SNPs mapped to 336 loci shared by the three adult psychiatric disorders, 1,108 variants at 73 loci shared by the childhood disorders, and 713 variants at 47 genes shared by all five disorders at genome-wide significance (P<5x10-08). Of the 2,583 SNPs at the extended major histocompatibility complex identified for three adult disorders, none of them were associated with childhood disorders; and SNPs shared by all five disorders were located in regions that have been identified as containing copy number variation associated with autism and had largely neurodevelopmental functions.
Conclusion. We show a number of specific SNPs associated with psychiatric disorders of childhood or adult-onset, illustrating not only genetic heterogeneity across these disorders but also developmental genes shared by them all. These results provide a manageable list of anchors from which to investigate epigenetic mechanism or gene-gene interaction on the development of neuropsychiatric disorders and for developing a measurement matrix for disease risk to potentially develop a novel taxonomy for precision medicine.
