Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs

Abstract

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17–29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn’s disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

Assessment of first and second degree relatives of individuals with bipolar disorder shows increased genetic risk scores in both affected relatives and young At‐Risk Individuals

“…Many genomic variants together contribute to overall risk (termed polygenic risk) for a number of complex traits [Peterson et al, 2011; Hamshere et al, 2013; Meyers et al, 2013], and this genetic architecture is evident in a number of psychiatric conditions—including BP [Purcell et al, 2009; Lee et al, 2012, 2013; Smoller et al, 2013; Bramon et al, 2014]. While the elucidation of the genetic causes for BP has been challenging, the field is progressing in understanding the genetic architecture of this complex disorder (reviewed in [Craddock and Sklar, 2013]) and in identifying specific genes which increase risk [Sklar et al, 2011].…”

“…We chose to focus our study on 32 SNPs that were the most significant independently associated variants in the PGC‐GWAS analysis [Sklar et al, 2011]. While we acknowledge that our limited SNP selection represents only a small fraction of the total variation that contributes to bipolar disorder risk [Lee et al, 2013, 2011], the selected SNPs arguably represent the largest effect sizes on a population level and are potentially least subject to statistical fluctuation and type I error.…”

“…Individually, each of those genes/loci contributes only a small fraction toward overall disease risk, typically <1% of the phenotypic variance [Ferreira et al, 2008]. It is now understood that multiple genes containing both common and rare variants contribute to the genetic architecture of BP [Sullivan et al, 2012], and there are significant overlaps in the single nucleotide polymorphism (SNP)‐based heritabilities of BP with both schizophrenia and major depression [Lee et al, 2013]. Indeed, variation across many thousands of common risk variants together (termed polygenic risk [Purcell et al, 2009]) contributes a substantial proportion (i.e., 25–40%) of the percentage of phenotypic variance at a population level [Lee et al, 2011; 2013]—although most of those loci do not individually reach genome‐wide significance thresholds for disease association with current sample sizes [Craddock and Sklar, 2013; Dudbridge, 2013].…”

Investigating shared aetiology between type 2 diabetes and major depressive disorder in a population based cohort

“…The Scottish Family Health Study (GS:SFHS) is a family and population‐based study that recruited from the lists of General Practitioners throughout Scotland; the protocol for recruitment is described in detail elsewhere [Smith et al, 2006; Lee et al, 2013]. All components of GS:SFHS have received ethical approval from the NHS Tayside Committee on Medical Research Ethics (REC Reference Number: 05/S1401/89).…”

“…The aim of this study was to investigate causal relationships and genetic overlap between T2D and MDD in the population based cohort, Generation Scotland: the Scottish Family Health Study (GS:SFHS) (N = 21,516) [Smith et al, 2006; Lee et al, 2013]. Using three techniques; MR, PRS, and LD score regression we aim to build evidence to explore the relationship between T2D and MDD with the hope of understanding more about the biological basis of these traits which will inform treatment of co‐morbid cases of T2D and MDD.…”