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

AM Vicente - Cross-Disorder Group of the Psychiatric Genomics ConsortiumMost 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

An Excess of Risk-Increasing Low-Frequency Variants Can Be a Signal of Polygenic Inheritance in Complex Diseases

Peer reviewe

Detecting patient subgroups using reduced set of disease-related markers with iterative pruning Principal Component Analysis (ipPCA)

Genetic markers such as Single Nucleotide Polymorphisms (SNPs) can be used to find subgroups of populations or patients with carefully selected clustering algorithms. The iterative pruning principal component analysis (ipPCA) has been shown to be a powerful tool to identify fine substructures within general populations based on SNP profiles. Usually, SNPs contributing to such profiles have passed rigorous quality control procedures, similar to the ones used for GWAs. Alternatively, attention is restricted to a smaller subset such as PCA-correlated SNPs. Here, we applied ipPCA on real-life data consisting of the 163 known inflammatory-bowel disease (IBD) associated loci in 13,400 healthy individuals and 29,500 IBD (16,902 Crohn’s disease (CD), and 12,598 ulcerative colitis (UC)) patients from the IIBDGC. Prior to clustering by ipPCA, in each group separately, we regressed out the first five Principal Components (PCs) that were computed from a filtered panel of genome-wide SNPs, to account for general population strata. Next, we applied ipPCA on the healthy group, to learn about the presence of a population-specific partitioning in controls. Then we performed three subphenotype analyses: CD only, UC only and the combined group of CD and UC patients (IBD). For each patient subgroup analysis and for the ipPCA analysis on controls, we highlighted and compared the key SNP drivers. CD patients could be molecularly reclassified in two groups, and similar for UC patients. The combined patient group could be subdivided in four groups. Finally, we compared demographic and clinical features among the different groups and looked for meaningful characterizations of adjusted patient clusters by performing pathway analysis on driver genes.Foresting in Integromics Inferenc

Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis

Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10−4). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10−8), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals

Greater extracellular free-water in first-episode psychosis predicts better neurocognitive functioning

Free Water Imaging is a novel diffusion magnetic resonance (MR) imaging method that is able to separate changes affecting the extracellular space from those that reflect changes in neuronal cells and processes. A previous Free Water Imaging study in schizophrenia identified significantly greater extracellular water volume in the early stages of the disorder; however, its clinical and functional sequelae have not yet been investigated. Here, we applied Free Water Imaging to a larger cohort of 63 first-episode patients with psychosis and 70 healthy matched controls to better understand the functional significance of greater extracellular water. We used diffusion MR imaging data and the Tract-Based Spatial Statistics analytic pipeline to first analyze fractional anisotropy (FA), the most commonly employed metric for assessing white matter. This comparison was then followed by Free Water Imaging analysis, where two parameters, the fractional volume of extracellular free-water (FW) and cellular tissue FA (FA-t), were estimated and compared across the entire white matter skeleton between groups, and correlated with cognitive measures at baseline and following 12 weeks of antipsychotic treatment. Our results indicated lower FA across the whole brain in patients compared with healthy controls that overlap with significant increases in FW, with only limited decreases in FA-t. In addition, higher FW correlated with better neurocognitive functioning following 12 weeks of antipsychotic treatment. We believe this is the first study to suggest that an extracellular water increase during the first-episode of psychosis, which may be indicative of an acute neuroinflammatory process, and/or cerebral edema may predict better functional outcome