CommonMind Consortium provides transcriptomic and epigenomic data for Schizophrenia and Bipolar Disorder

Schizophrenia and bipolar disorder are serious mental illnesses that affect more than 2% of adults. While large-scale genetics studies have identified genomic regions associated with disease risk, less is known about the molecular mechanisms by which risk alleles with small effects lead to schizophrenia and bipolar disorder. In order to fill this gap between genetics and disease phenotype, we have undertaken a multi-cohort genomics study of postmortem brains from controls, individuals with schizophrenia and bipolar disorder. Here we present a public resource of functional genomic data from the dorsolateral prefrontal cortex (DLPFC; Brodmann areas 9 and 46) of 986 individuals from 4 separate brain banks, including 353 diagnosed with schizophrenia and 120 with bipolar disorder. The genomic data include RNA-seq and SNP genotypes on 980 individuals, and ATAC-seq on 269 individuals, of which 264 are a subset of individuals with RNA-seq. We have performed extensive preprocessing and quality control on these data so that the research community can take advantage of this public resource available on the Synapse platform at http://CommonMind.org

Joint Analysis Of Psychiatric Disorders Increases Accuracy Of Risk Prediction For Schizophrenia, Bipolar Disorder, And Major Depressive Disorder

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk

Genetic Differences in the Immediate Transcriptome Response to Stress Predict Risk-Related Brain Function and Psychiatric Disorders

Depression risk is exacerbated by genetic factors and stress exposure; however, the biological mechanisms through which these factors interact to confer depression risk are poorly understood. One putative biological mechanism implicates variability in the ability of cortisol, released in response to stress, to trigger a cascade of adaptive genomic and non-genomic processes through glucocorticoid receptor (GR) activation. Here, we demonstrate that common genetic variants in long-range enhancer elements modulate the immediate transcriptional response to GR activation in human blood cells. These functional genetic variants increase risk for depression and co-heritable psychiatric disorders. Moreover, these risk variants are associated with inappropriate amygdala reactivity, a transdiagnostic psychiatric endophenotype and an important stress hormone response trigger. Network modeling and animal experiments suggest that these genetic differences in GR-induced transcriptional activation may mediate the risk for depression and other psychiatric disorders by altering a network of functionally related stress-sensitive genes in blood and brain

Randomized controlled trial of chlorhexidine gluconate for washing, intranasal mupirocin, and rifampin and doxycycline versus no treatment for the eradication of methicillin-resistant staphylococcus aureus colonization

Background. Eradication of methicillin-resistant Staphylococcus aureus (MRSA) carriage may reduce the risk of MRSA infection and prevent transmission of the organism to other patients. Methods. To determine the efficacy of decolonization therapy, patients colonized with MRSA were randomized (3 : 1 allocation) to receive treatment (2% chlorhexidine gluconate washes and 2% mupirocin ointment intranasally, with oral rifampin and doxycycline for 7 days), or no treatment. Follow-up samples for MRSA culture were obtained from the nares, perineum, skin lesions, and catheter exit sites monthly for up to 8 months. The primary outcome measure was detection of MRSA at 3 months of follow-up. Univariate and multivariable analyses were performed to identify variables associated with treatment failure. Results. Of 146 patients enrolled in the study, 112 patients (87 treated; 25 not treated) were followed up for at least 3 months. At 3 months of follow-up, 64 (74%) of those treated had culture results negative for MRSA, compared with 8 (32%) of those not treated (P = .0001). This difference remained significant at 8 months of follow-up, at which time, 54% of those treated had culture results negative for MRSA (χ2 = 64.4; P < .0001, by log-rank test). The results of the multivariable analysis indicated that having a mupirocin-resistant isolate at baseline was associated with treatment failure (relative risk, 9.4; 95% confidence interval, 2.8–31.9; P = .0003), whereas decolonization therapy was protective (relative risk, 0.1; 95% confidence interval, 0.04–0.4; P = .0002). Mupirocin resistance emerged in only 5% of follow-up isolates. Conclusions. Treatment with topical mupirocin, chlorhexidine gluconate washes, oral rifampin, and doxycycline for 7 days was safe and effective in eradicating MRSA colonization in hospitalized patients for at least 3 months