Literature DB >> 30635639

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

Liang Ma1, Stephen A Semick1, Qiang Chen1, Chao Li1, Ran Tao1, Amanda J Price1,2, Joo Heon Shin1, Yankai Jia1, Nicholas J Brandon3, Alan J Cross3, Thomas M Hyde1,4,5, Joel E Kleinman1,4, Andrew E Jaffe1,6,7, Daniel R Weinberger1,2,4,5,8, Richard E Straub9.   

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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Year:  2019        PMID: 30635639     DOI: 10.1038/s41380-018-0293-0

Source DB:  PubMed          Journal:  Mol Psychiatry        ISSN: 1359-4184            Impact factor:   15.992


  15 in total

1.  Deep learning predicts DNA methylation regulatory variants in the human brain and elucidates the genetics of psychiatric disorders.

Authors:  Jiyun Zhou; Qiang Chen; Patricia R Braun; Kira A Perzel Mandell; Andrew E Jaffe; Hao Yang Tan; Thomas M Hyde; Joel E Kleinman; James B Potash; Gen Shinozaki; Daniel R Weinberger; Shizhong Han
Journal:  Proc Natl Acad Sci U S A       Date:  2022-08-15       Impact factor: 12.779

2.  Integration of multidimensional splicing data and GWAS summary statistics for risk gene discovery.

Authors:  Ying Ji; Qiang Wei; Rui Chen; Quan Wang; Ran Tao; Bingshan Li
Journal:  PLoS Genet       Date:  2022-06-30       Impact factor: 6.020

3.  Joint-Tissue Integrative Analysis Identified Hundreds of Schizophrenia Risk Genes.

Authors:  Yong Wu; Xiao-Lin Yu; Xiao Xiao; Ming Li; Yi Li
Journal:  Mol Neurobiol       Date:  2021-10-09       Impact factor: 5.682

4.  Powerful and robust inference of complex phenotypes' causal genes with dependent expression quantitative loci by a median-based Mendelian randomization.

Authors:  Lin Jiang; Lin Miao; Guorong Yi; Xiangyi Li; Chao Xue; Mulin Jun Li; Hailiang Huang; Miaoxin Li
Journal:  Am J Hum Genet       Date:  2022-04-22       Impact factor: 11.043

5.  Transcriptomic analyses of humans and mice provide insights into depression.

Authors:  Hui-Juan Li; Xi Su; Lu-Wen Zhang; Chu-Yi Zhang; Lu Wang; Wen-Qiang Li; Yong-Feng Yang; Lu-Xian Lv; Ming Li; Xiao Xiao
Journal:  Zool Res       Date:  2020-11-18

Review 6.  Sorting Out Sorting Nexins Functions in the Nervous System in Health and Disease.

Authors:  Neide Vieira; Teresa Rito; Margarida Correia-Neves; Nuno Sousa
Journal:  Mol Neurobiol       Date:  2021-05-01       Impact factor: 5.590

7.  ExonSkipAD provides the functional genomic landscape of exon skipping events in Alzheimer's disease.

Authors:  Mengyuan Yang; Yiya Ke; Pora Kim; Xiaobo Zhou
Journal:  Brief Bioinform       Date:  2021-09-02       Impact factor: 11.622

8.  Trends in the incidence and DALYs of schizophrenia at the global, regional and national levels: results from the Global Burden of Disease Study 2017.

Authors:  Hairong He; Qingqing Liu; Ning Li; Liyang Guo; Fengjie Gao; Ling Bai; Fan Gao; Jun Lyu
Journal:  Epidemiol Psychiatr Sci       Date:  2020-01-13       Impact factor: 6.892

9.  dotdotdot: an automated approach to quantify multiplex single molecule fluorescent in situ hybridization (smFISH) images in complex tissues.

Authors:  Kristen R Maynard; Madhavi Tippani; Yoichiro Takahashi; BaDoi N Phan; Thomas M Hyde; Andrew E Jaffe; Keri Martinowich
Journal:  Nucleic Acids Res       Date:  2020-06-19       Impact factor: 16.971

Review 10.  An alternative splicing hypothesis for neuropathology of schizophrenia: evidence from studies on historical candidate genes and multi-omics data.

Authors:  Chu-Yi Zhang; Xiao Xiao; Zhuohua Zhang; Zhonghua Hu; Ming Li
Journal:  Mol Psychiatry       Date:  2021-03-08       Impact factor: 15.992

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