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Schizophrenia risk variants influence multiple classes of transcripts of sorting nexin 19 (SNX19)

Molecular Psychiatry volume 25, pages 831–843 (2020)Cite this article

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Abstract

Genome-wide association studies (GWAS) have identified many genomic loci associated with risk for schizophrenia, but unambiguous identification of the relationship between disease-associated variants and specific genes, and in particular their effect on risk conferring transcripts, has proven difficult. To better understand the specific molecular mechanism(s) at the schizophrenia locus in 11q25, we undertook cis expression quantitative trait loci (cis-eQTL) mapping for this 2 megabase genomic region using postmortem human brain samples. To comprehensively assess the effects of genetic risk upon local expression, we evaluated multiple transcript features: genes, exons, and exon−exon junctions in multiple brain regions—dorsolateral prefrontal cortex (DLPFC), hippocampus, and caudate. Genetic risk variants strongly associated with expression of SNX19 transcript features that tag multiple rare classes of SNX19 transcripts, whereas they only weakly affected expression of an exon−exon junction that tags the majority of abundant transcripts. The most prominent class of SNX19 risk-associated transcripts is predicted to be overexpressed, defined by an exon-exon splice junction between exons 8 and 10 (junc8.10) and that is predicted to encode proteins that lack the characteristic nexin C terminal domain. Risk alleles were also associated with either increased or decreased expression of multiple additional classes of transcripts. With RACE, molecular cloning, and long read sequencing, we found a number of novel SNX19 transcripts that further define the set of potential etiological transcripts. We explored epigenetic regulation of SNX19 expression and found that DNA methylation at CpG sites near the primary transcription start site and within exon 2 partially mediate the effects of risk variants on risk-associated expression. ATAC sequencing revealed that some of the most strongly risk-associated SNPs are located within a region of open chromatin, suggesting a nearby regulatory element is involved. These findings indicate a potentially complex molecular etiology, in which risk alleles for schizophrenia generate epigenetic alterations and dysregulation of multiple classes of SNX19 transcripts.

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Acknowledgements

We thank Amy Deep-Soboslay (Lieber Institute for Brain Development) and Llewellyn B. Bigelow, M.D. for their tireless efforts in clinical diagnosis and demographic characterization; R. Zielke, R.D. Vigorito, and R.M. Johnson (National Institute of Child Health and Human Development Brain and Tissue Bank for Developmental Disorders at the University of Maryland) for their provision of fetal, pediatric, and adolescent brain tissue specimens.

This work was supported by funding from the Lieber Institute for Brain Development and the Maltz Research Laboratories, from AstraZeneca, and from a Distinguished Investigator Award (2014) to J.E.K. from the Brain Behavior Research Foundation (NARSAD).

The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the US National Institutes of Health. Additional funds were provided by the NCI, NHGRI, NHLBI, NIDA, NIMH, and the NINDS. Donors were enrolled at Biospecimen Source Sites funded by NCI/SAIC-Frederick, Inc. (SAIC-F) subcontracts to the National Disease Research Interchange (10XS170), Roswell Park Cancer Institute (10XS171) and Science Care, Inc. (X10S172). The Laboratory, Data Analysis and Coordinating Center (LDACC) were funded through a contract (HHSN268201000029C) to the Broad Institute, Inc. Biorepository operations were funded through an SAIC-F subcontract to Van Andel Institute (10ST1035). Additional data repository and project management were provided by SAIC-F (HHSN261200800001E). The Brain Bank was supported by supplements to University of Miami grants DA006227 and DA033684, and to contract N01MH000028. Statistical Methods development grants were made to the University of Geneva (MH090941 and MH101814), the University of Chicago (MH090951, MH090937, MH101820, MH101825), the University of North Carolina at Chapel Hill (MH090936 and MH101819), Harvard University (MH090948), Stanford University (MH101782), Washington University St. Louis (MH101810) and the University of Pennsylvania (MH101822). The data used for the analyses described in this manuscript were obtained from dbGaP accession number phs000424.v6.p1 on October 6, 2015. Data were generated as part of the CommonMind Consortium supported by funding from Takeda Pharmaceuticals Company Limited, F. Hoffman-La Roche, Ltd. and NIH grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881 and R37MH057881S1, HHSN271201300031C, AG02219, AG05138 and MH06692. Brain tissue for the study was obtained from the following brain-bank collections: the Mount Sinai NIH Brain and Tissue Repository, the University of Pennsylvania Alzheimer’s Disease Core Center, the University of Pittsburgh NeuroBioBank and Brain and Tissue Repositories and the NIMH Human Brain Collection Core. CMC Leadership: P. Sklar, J. Buxbaum (Icahn School of Medicine at Mount Sinai), B. Devlin, D. Lewis (University of Pittsburgh), R. Gur, C.-G. Hahn (University of Pennsylvania), K. Hirai, H. Toyoshiba (Takeda Pharmaceuticals Company, Ltd.), E. Domenici, L. Essioux (F. Hoffman-La Roche, Ltd.), L. Mangravite, M. Peters (Sage Bionetworks), T. Lehner, B. Lipska (NIMH Laboratories).

BrainSeq: A Human Brain Genomics Consortium

Daniel Hoeppner9, Mitsuyuki Matsumoto9, Takeshi Saito9, Katsunori Tajinda9, Nicholas J. Brandon10, Alan10, David Charles Airey11, John N. Calley11, David Andrew Collier11, Brain J. Eastwood11, Philip J. Ebert11, Yupeng Li11, Yushi Liu11, Karim Malki11, Bradley Bryan Miller11, Cara Lee Ann Ruble11, James E. Scherschel11, Hong Wang11, Maura Furey12,13, Derrek Hibar12,13, Hartmuth Kolb12,13, Andrew E. Jaffe1, Joo Heon Shin1, Richard E. Straub1, Daniel R. Weinberger1, Michael Didriksen14, Lasse Folkersen14, Jie Quan15, Simon Xi15, Tony Kam-Thong16, Dheeraj Malhotra16

9Astellas Pharma, Inc.

10AstraZeneca LP

11Eli Lilly and Company

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13Johnson and Johnson, Inc.

14H. Lundbeck A/S

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  1. These authors contributed equally: Liang Ma, Stephen A. Semick

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  1. Lieber Institute for Brain Development, Baltimore, MD, 21205, USA

    Liang Ma, Stephen A. Semick, Qiang Chen, Chao Li, Ran Tao, Amanda J. Price, Joo Heon Shin, Yankai Jia, Thomas M. Hyde, Joel E. Kleinman, Andrew E. Jaffe, Daniel R. Weinberger & Richard E. Straub

  2. McKusick-Nathans Institute of Genetic Medicine, Baltimore, MD, 21205, USA

    Amanda J. Price & Daniel R. Weinberger

  3. AstraZeneca Neuroscience, IMED Biotech Unit, AstraZeneca R&D, Boston, MA, 02451, USA

    Nicholas J. Brandon & Alan J. Cross

  4. Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA

    Thomas M. Hyde, Joel E. Kleinman & Daniel R. Weinberger

  5. Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA

    Thomas M. Hyde & Daniel R. Weinberger

  6. Department of Mental Health, Johns Hopkins School of Public Health, Baltimore, MD, 21205, USA

    Andrew E. Jaffe

  7. Department of Biostatistics, Johns Hopkins School of Public Health, Baltimore, MD, 21205, USA

    Andrew E. Jaffe

  8. Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA

    Daniel R. Weinberger

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Ma, L., Semick, S.A., Chen, Q. et al. Schizophrenia risk variants influence multiple classes of transcripts of sorting nexin 19 (SNX19). Mol Psychiatry 25, 831–843 (2020). https://doi.org/10.1038/s41380-018-0293-0

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