Fine mapping of Alcohol Use Disorder
Alcohol Use Disorders (AUD) are important and costly public health concerns. AUD have strong evidence of aggregate genetic risk factors and show genetic correlation (rG) with many psychiatric disorders including bipolar disorder (BIP), major depressive disorder (MDD), schizophrenia (SCZ) and externalizing liability (EXT). AUD gene discovery lags behind these other disorders, and we propose to leverage rG to increase AUD gene discovery power through joint analysis with correlated disorders to improve disease understanding. The results of large sample genomewide association studies (GWAS) of AUD and correlated traits are publicly available for all traits proposed for study, and exome sequence data is available for most traits or for a proxy measure. We propose here to integrate three complementary approaches to fine-mapping within an overall Bayesian concordance framework for joint analysis of common variant signals and rare variant data to identify putative causal genes within GWAS loci, one of the most critical and challenging goals in psychiatric genetics. Our overarching hypothesis, supported by our and others’ prior work, is that joint analysis of correlated traits using all available genomic and functional data will increase detection of common variant effects on gene expression and identify risk genes, which in turn will identify molecular pathways, cell types and developmental windows to elucidate disease etiology. Here, we seek 1) to assemble and harmonize large-scale GWAS, exome and gene expression datasets from our own work and other consortia, 2) to undertake state-of-the-art fine mapping of GWAS loci from AUD and correlated traits, 3) to apply our Bayesian integrative analysis framework within and between correlated traits, and 4) to characterize the functional and spatio-temporal relationships of identified genes and genesets to reveal disease mechanisms. We anticipate that multiple risk genes for AUD and correlated disorders will be identified, along with the pathways, cell types and developmental windows important in disease.