Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights
Year: 2016
Type: preprint
Study design: Observational Study
Abstract: ABSTRACT Genome-wide association studies (GWAS) have identified over 100 risk loci for schizophrenia, but the causal mechanisms remain largely unknown. We performed a transcriptome-wide association study (TWAS) integrating expression data from brain, blood, and adipose tissues across 3,693 individuals with schizophrenia GWAS of 79,845 individuals from the Psychiatric Genomics Consortium. We identified 157 genes with a transcriptome-wide significant association, of which 35 did not overlap a known GWAS locus; the largest number involved alternative splicing in brain. 42/157 genes were also associated to specific chromatin phenotypes measured in 121 independent samples (a 4-fold enrichment over background genes). This high-throughput connection of GWAS findings to specific genes, tissues, and regulatory mechanisms is an essential step toward understanding the biology of schizophrenia and moving towards therapeutic interventions.
DOI: 10.1101/067355
Institutions: Broad Institute, Harvard University, University of California, Los Angeles, Massachusetts Institute of Technology, Duke University, Duke Medical Center, Stanley Center for Psychiatric Research, Massachusetts General Hospital, University Medical Center Utrecht, Cardiff University, University of North Carolina at Chapel Hill, Karolinska Institutet
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funders: Yale University, Hertz Foundation, University of Pennsylvania, F. Hoffmann-La Roche, University of Chicago, University of Pittsburgh, Lieber Institute for Brain Development, National Institutes of Health, University of California, San Francisco, National Institute of Mental Health, National Human Genome Research Institute, National Institute of General Medical Sciences
Awards: Improving Polygenic Prediction using Next-Generation Data Sets, Integrative approaches for mapping the genetic risk of complex traits, G1342218999, G1414860548, G148749253, Identifying therapeutic targets for autism using Shank3-deficient mice, Statistical methods to localize disease heritability and identify biological mechanisms, G2182537161, Transcriptional and Epigenetic Signatures of Human Brain Development and Autism, G2946751114, G3021430819, White Matter Abnormalities in Schizophrenia, Medical Scientist Training Program, G37153953, G3742826060, G4126499158, G4225100588, G4324736015, Src hypoactivity as a mediator of various molecular alterations leading to NMDAR, Network-based prediction and validation of causal schizophrenia genes and variants, International Cohort Collection for Bipolar Disorder, Genetics Association in Schizophrenia and Other Disorders, G4867329959, G5115457503, G5303643983, Genetic variants affect brain gene expression and risks of psychiatric disorders, 1/3-Networks from Multidimensional Data for Schizophrenia and Related Disorders, G6588570868, Cis-Regulatory Epigenome Mappings in Schizophrenia, RNA Sequencing of the Limbic System in Bipolar Disorder, G7095773877, GABA Epigenomes in Autism, G7172570721, G8413678899, G8695630221, G9000064556, G9000152567, G9000174724, G9000247718, G9000254743, G9000286330
OpenAlex ID: W2506960987