1. Publications

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

Gabriel E. Hoffman, Jaroslav Bendl, Georgios Voloudakis, Kelsey S. Montgomery, Laura Sloofman, Ying-Chih Wang, Hardik R. Shah, Mads E. Hauberg, Jessica S. Johnson, Kiran Girdhar, Lingyun Song, John F. Fullard, Robin Kramer, Chang-Gyu Hahn, Raquel Gur, Stefano Marenco, Barbara K. Lipska, David A. Lewis, Vahram Haroutunian, Scott Hemby, Patrick Sullivan, Schahram Akbarian, Andrew Chess, Joseph D. Buxbaum, Greg E. Crawford, Enrico Domenici, Bernie Devlin, Solveig K. Sieberts, Mette A. Peters & Panos Roussos.
Sci Data. 2019-09-24;6(1):180.
Abstract
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 .
Datasets
DSR129VOZ