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Variations and expression features of CYP2D6 contribute to schizophrenia risk

Genome-wide association studies (GWAS) have successfully identified 145 loci implicated in schizophrenia (SCZ). However, the underlying mechanisms remain largely unknown. Here, we analyze 1497 RNA-seq data in combination with their genotype data and identify SNPs that are associated with expression...

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Autores principales: Ma, Liang, Shcherbina, Anna, Chetty, Sundari
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440189/
https://www.ncbi.nlm.nih.gov/pubmed/32047265
http://dx.doi.org/10.1038/s41380-020-0675-y
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author Ma, Liang
Shcherbina, Anna
Chetty, Sundari
author_facet Ma, Liang
Shcherbina, Anna
Chetty, Sundari
author_sort Ma, Liang
collection PubMed
description Genome-wide association studies (GWAS) have successfully identified 145 loci implicated in schizophrenia (SCZ). However, the underlying mechanisms remain largely unknown. Here, we analyze 1497 RNA-seq data in combination with their genotype data and identify SNPs that are associated with expression throughout the genome by dissecting expression features to genes (eGene) and exon–exon junctions (eJunction). Then, we colocalize eGene and eJunction with SCZ GWAS using SMR and fine mapping. Multiple ChIP-seq data and DNA methylation data generated from brain were used for identifying the causal variants. Finally, we used a hypothesis-free (no SCZ risk loci considered) enrichment analysis to determine implicated pathways. We identified 171 genes and eight splicing junctions located within four genes (SNX19, ARL6IP4, APOPT1, and CYP2D6) that potentially contribute to SCZ susceptibility. Among the genes, CYP2D6 is significantly associated with SCZ SNPs in eGene and eJunction. In-depth examination of the CYP2D6 region revealed that a nonsynonymous single nucleotide variant rs16947 is strongly associated with a higher abundance of CYP2D6 exon 3 skipping junctions. While we found rs133377 and other functional SNPs in high linkage disequilibrium with rs16947 (r(2) = 0.9539), histone acetylation analysis showed they are located within active transcription start sites. Furthermore, our data-driven enrichment analysis showed that CYP2D6 is significantly involved in drug metabolism of codeine, tamoxifen, and citalopram. Our study facilitates an understanding of the genetic architecture of SCZ and provides new drug targets.
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spelling pubmed-84401892021-09-22 Variations and expression features of CYP2D6 contribute to schizophrenia risk Ma, Liang Shcherbina, Anna Chetty, Sundari Mol Psychiatry Article Genome-wide association studies (GWAS) have successfully identified 145 loci implicated in schizophrenia (SCZ). However, the underlying mechanisms remain largely unknown. Here, we analyze 1497 RNA-seq data in combination with their genotype data and identify SNPs that are associated with expression throughout the genome by dissecting expression features to genes (eGene) and exon–exon junctions (eJunction). Then, we colocalize eGene and eJunction with SCZ GWAS using SMR and fine mapping. Multiple ChIP-seq data and DNA methylation data generated from brain were used for identifying the causal variants. Finally, we used a hypothesis-free (no SCZ risk loci considered) enrichment analysis to determine implicated pathways. We identified 171 genes and eight splicing junctions located within four genes (SNX19, ARL6IP4, APOPT1, and CYP2D6) that potentially contribute to SCZ susceptibility. Among the genes, CYP2D6 is significantly associated with SCZ SNPs in eGene and eJunction. In-depth examination of the CYP2D6 region revealed that a nonsynonymous single nucleotide variant rs16947 is strongly associated with a higher abundance of CYP2D6 exon 3 skipping junctions. While we found rs133377 and other functional SNPs in high linkage disequilibrium with rs16947 (r(2) = 0.9539), histone acetylation analysis showed they are located within active transcription start sites. Furthermore, our data-driven enrichment analysis showed that CYP2D6 is significantly involved in drug metabolism of codeine, tamoxifen, and citalopram. Our study facilitates an understanding of the genetic architecture of SCZ and provides new drug targets. Nature Publishing Group UK 2020-02-11 2021 /pmc/articles/PMC8440189/ /pubmed/32047265 http://dx.doi.org/10.1038/s41380-020-0675-y Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ma, Liang
Shcherbina, Anna
Chetty, Sundari
Variations and expression features of CYP2D6 contribute to schizophrenia risk
title Variations and expression features of CYP2D6 contribute to schizophrenia risk
title_full Variations and expression features of CYP2D6 contribute to schizophrenia risk
title_fullStr Variations and expression features of CYP2D6 contribute to schizophrenia risk
title_full_unstemmed Variations and expression features of CYP2D6 contribute to schizophrenia risk
title_short Variations and expression features of CYP2D6 contribute to schizophrenia risk
title_sort variations and expression features of cyp2d6 contribute to schizophrenia risk
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440189/
https://www.ncbi.nlm.nih.gov/pubmed/32047265
http://dx.doi.org/10.1038/s41380-020-0675-y
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