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 HembyPatrick Sullivan, Schahram Akbarian, Andrew Chess, Joseph D. Buxbaum, Greg E. Crawford, Enrico Domenici, Bernie Devlin, Solveig K. Sieberts, Mette A. Peters, Panos Roussos

Research output: Contribution to journalArticlepeer-review

95 Scopus citations

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.

Original languageEnglish
Article number180
JournalScientific data
Volume6
Issue number1
DOIs
StatePublished - 1 Dec 2019

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