& Patterson 2009; Felger & Lotrich 2013; Meyer 2014; Miller et al. 2013; Oskvig et al. 2012; Sekar et al. 2016; Shatz 2009; Smith et al. 2007). While some studies have already suggested potential genetic bases for the immune dysregulation observed in a subset of psychiatric patients (Jung et al. 2011; Stringer et al. 2014; The Network and Pathway Analysis Subgroup of the Psychiatric Genomics Consortium 2015; Wang et al. 2015), the extent to which co-occurrence or segregation of clinical phenotypes may be influenced by similarities in genome-wide genetic risk signals warrants further examination. Genome-wide association studies (GWASs) and meta-analyses can shed light on the regions of the genome that tend to associate with a clinical phenotype, quantitative trait, or biomarker; this is accomplished through tagging and association-testing of single nucleotide polymorphisms (SNPs) that vary within the population. Recently developed methods like linkage disequilibrium (LD) score regression (LDSC; B. Bulik-Sullivan et al. 2015) and Heritability Estimation from Summary Statistics (HESS; Shi et al. 2017) allow for direct comparison of GWAS summary statistics for two different phenotypes for quantitative assessment of genetic correlation.
