Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants
Jessica C. McAfee, Sool Lee, Jiseok Lee, Jessica Bell, Oleh Krupa, Jessica E. Davis, Kimberly D. Insigne, Marielle L. Bond, Nanxiang Zhao, Alan P. Boyle, Douglas H. Phanstiel, Michael I. Love, Jason L. Stein, W. Brad Ruzicka, José Dávila-Velderrain, Sriram Kosuri, Hyejung Won
Abstract
Genome-wide association studies (GWASs) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium makes it challenging to discern causal variants. We performed a massively parallel reporter assay (MPRA) on 5,173 fine-mapped schizophrenia GWAS variants in primary human neural progenitors and identified 439 variants with allelic regulatory effects (MPRA-positive variants). Transcription factor binding had modest predictive power, while fine-map posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit expressive quantitative trait loci signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. To predict the combinatorial effect of MPRA-positive variants on gene regulation, we propose an accessibility-by-contact model that combines MPRA-measured allelic activity with neuronal chromatin architecture.