bioRxivBioinformaticsPreprint
Genetic correlations among psychiatric and immune-related phenotypes based on genome-wide association data.
Daniel S. TyleeiD, Jiayin Sun, Jonathan L. Hess, Muhammad A. Tahir, Esha Sharma, Rainer MalikiD, Bradford B. WorralliD, Andrew J. LevineiD, Jeremy J. Martinson, Sergey NejentseviD, Doug SpeediD, Annegret Fischer, Eric O. MickiD, Brian Robert WalkeriD, Andrew Crawford, Struan F.A. GrantiD, Constantin Polychronakos, Jonathan P. Bradfield, Patrick M. Abou‐SleimaniD, Hakon H. HakonarsoniD, Eva EllinghausiD, James T. ElderiD, Lam C. TsoiiD, Richard C. TrembathiD, Jonathan N. Barker, , Stephen J. GlattiD
Abstract
Individuals with psychiatric disorders have elevated rates of autoimmune comorbidity and altered immune signaling. It is unclear whether these altered immunological states have a shared genetic basis with those psychiatric disorders. The present study sought to use existing summary-level data from previous genome-wide association studies (GWASs) to determine if commonly varying single nucleotide polymorphisms (SNPs) are shared between psychiatric and immune-related phenotypes. We estimated heritability and examined pair-wise genetic correlations using the linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (HESS) methods. Using LDSC, we observed significant genetic correlations between immune-related disorders and several psychiatric disorders, including anorexia nervosa, attention deficit-hyperactivity disorder, bipolar disorder, major depression, obsessive compulsive disorder, schizophrenia, smoking behavior, and Tourette syndrome. Loci significantly mediating genetic correlations were identified for schizophrenia when analytically paired with Crohns disease, primary biliary cirrhosis, systemic lupus erythematosus, and ulcerative colitis. We report significantly correlated loci and highlight those containing genome-wide associations and candidate genes for respective disorders. We also used the LDSC method to characterize genetic correlations amongst the immune-related phenotypes. We discuss our findings in the context of relevant genetic and epidemiological literature, as well as the limitations and caveats of the study.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- research focus: fine-mapping
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 4
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