Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants

Jessica C McAfee; Sool Lee; Jiseok Lee; Jessica L Bell; Oleh Krupa; Jessica Davis; Kimberly Insigne; Marielle L Bond; Nanxiang Zhao; Alan P Boyle; Douglas H Phanstiel; Michael I Love; Jason L Stein; W Brad Ruzicka; Jose Davila-Velderrain; Sriram Kosuri; Hyejung Won

doi:10.1016/j.xgen.2023.100404

Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants

Cell Genom. 2023 Sep 15;3(10):100404. doi: 10.1016/j.xgen.2023.100404. eCollection 2023 Oct 11.

Authors

Jessica C McAfee^{1

2

3}, Sool Lee^{1

2

4}, Jiseok Lee^{1

2}, Jessica L Bell^{1

2}, Oleh Krupa^{1

2}, Jessica Davis^{5

6

7

8

9}, Kimberly Insigne^{5

6

7

8

9}, Marielle L Bond^{1

3}, Nanxiang Zhao¹⁰, Alan P Boyle^{10

11}, Douglas H Phanstiel^{3

4

12

13}, Michael I Love^{1

14}, Jason L Stein^{1

2}, W Brad Ruzicka^{15

16

17}, Jose Davila-Velderrain¹⁸, Sriram Kosuri^{5

6

7

8

9}, Hyejung Won^{1

2}

Affiliations

¹ Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
² Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
³ Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
⁴ Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
⁵ Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA.
⁶ UCLA-DOE Institute for Genomics and Proteomics, University of California, Los Angeles, Los Angeles, CA 90095, USA.
⁷ Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA.
⁸ Quantitative and Computational Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA.
⁹ Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA.
¹⁰ Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
¹¹ Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
¹² Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
¹³ Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
¹⁴ Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
¹⁵ Laboratory for Epigenomics in Human Psychopathology, McLean Hospital, Belmont, MA 02141, USA.
¹⁶ Harvard Medical School, Boston, MA 02115, USA.
¹⁷ Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
¹⁸ Human Technopole, Viale Rita Levi-Montalcini 1, 20157 Milan, Italy.

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.

Keywords: GWAS; MPRA; accessibility-by-contact model; chromatin architecture; eQTL; gene regulation; high-throughput reporter assay; non-coding variants; schizophrenia; variant function.

Abstract

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