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Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants

BACKGROUND: Genome-wide association studies (GWASs) have identified multiple risk loci for bipolar disorder (BD). However, pinpointing functional (or causal) variants in the reported risk loci and elucidating their regulatory mechanisms remain challenging. METHODS: We first integrated chromatin immu...

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Autores principales: Chen, Rui, Yang, Zhihui, Liu, Jiewei, Cai, Xin, Huo, Yongxia, Zhang, Zhijun, Li, Ming, Chang, Hong, Luo, Xiong-Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9121601/
https://www.ncbi.nlm.nih.gov/pubmed/35590387
http://dx.doi.org/10.1186/s13073-022-01057-3
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author Chen, Rui
Yang, Zhihui
Liu, Jiewei
Cai, Xin
Huo, Yongxia
Zhang, Zhijun
Li, Ming
Chang, Hong
Luo, Xiong-Jian
author_facet Chen, Rui
Yang, Zhihui
Liu, Jiewei
Cai, Xin
Huo, Yongxia
Zhang, Zhijun
Li, Ming
Chang, Hong
Luo, Xiong-Jian
author_sort Chen, Rui
collection PubMed
description BACKGROUND: Genome-wide association studies (GWASs) have identified multiple risk loci for bipolar disorder (BD). However, pinpointing functional (or causal) variants in the reported risk loci and elucidating their regulatory mechanisms remain challenging. METHODS: We first integrated chromatin immunoprecipitation sequencing (ChIP-Seq) data from human brain tissues (or neuronal cell lines) and position weight matrix (PWM) data to identify functional single-nucleotide polymorphisms (SNPs). Then, we verified the regulatory effects of these transcription factor (TF) binding–disrupting SNPs (hereafter referred to as “functional SNPs”) through a series of experiments, including reporter gene assays, allele-specific expression (ASE) analysis, TF knockdown, CRISPR/Cas9-mediated genome editing, and expression quantitative trait loci (eQTL) analysis. Finally, we overexpressed PACS1 (whose expression was most significantly associated with the identified functional SNPs rs10896081 and rs3862386) in mouse primary cortical neurons to investigate if PACS1 affects dendritic spine density. RESULTS: We identified 16 functional SNPs (in 9 risk loci); these functional SNPs disrupted the binding of 7 TFs, for example, CTCF and REST binding was frequently disrupted. We then identified the potential target genes whose expression in the human brain was regulated by these functional SNPs through eQTL analysis. Of note, we showed dysregulation of some target genes of the identified TF binding–disrupting SNPs in BD patients compared with controls, and overexpression of PACS1 reduced the density of dendritic spines, revealing the possible biological mechanisms of these functional SNPs in BD. CONCLUSIONS: Our study identifies functional SNPs in some reported risk loci and sheds light on the regulatory mechanisms of BD risk variants. Further functional characterization and mechanistic studies of these functional SNPs and candidate genes will help to elucidate BD pathogenesis and develop new therapeutic approaches and drugs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-022-01057-3.
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spelling pubmed-91216012022-05-21 Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants Chen, Rui Yang, Zhihui Liu, Jiewei Cai, Xin Huo, Yongxia Zhang, Zhijun Li, Ming Chang, Hong Luo, Xiong-Jian Genome Med Research BACKGROUND: Genome-wide association studies (GWASs) have identified multiple risk loci for bipolar disorder (BD). However, pinpointing functional (or causal) variants in the reported risk loci and elucidating their regulatory mechanisms remain challenging. METHODS: We first integrated chromatin immunoprecipitation sequencing (ChIP-Seq) data from human brain tissues (or neuronal cell lines) and position weight matrix (PWM) data to identify functional single-nucleotide polymorphisms (SNPs). Then, we verified the regulatory effects of these transcription factor (TF) binding–disrupting SNPs (hereafter referred to as “functional SNPs”) through a series of experiments, including reporter gene assays, allele-specific expression (ASE) analysis, TF knockdown, CRISPR/Cas9-mediated genome editing, and expression quantitative trait loci (eQTL) analysis. Finally, we overexpressed PACS1 (whose expression was most significantly associated with the identified functional SNPs rs10896081 and rs3862386) in mouse primary cortical neurons to investigate if PACS1 affects dendritic spine density. RESULTS: We identified 16 functional SNPs (in 9 risk loci); these functional SNPs disrupted the binding of 7 TFs, for example, CTCF and REST binding was frequently disrupted. We then identified the potential target genes whose expression in the human brain was regulated by these functional SNPs through eQTL analysis. Of note, we showed dysregulation of some target genes of the identified TF binding–disrupting SNPs in BD patients compared with controls, and overexpression of PACS1 reduced the density of dendritic spines, revealing the possible biological mechanisms of these functional SNPs in BD. CONCLUSIONS: Our study identifies functional SNPs in some reported risk loci and sheds light on the regulatory mechanisms of BD risk variants. Further functional characterization and mechanistic studies of these functional SNPs and candidate genes will help to elucidate BD pathogenesis and develop new therapeutic approaches and drugs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-022-01057-3. BioMed Central 2022-05-20 /pmc/articles/PMC9121601/ /pubmed/35590387 http://dx.doi.org/10.1186/s13073-022-01057-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Rui
Yang, Zhihui
Liu, Jiewei
Cai, Xin
Huo, Yongxia
Zhang, Zhijun
Li, Ming
Chang, Hong
Luo, Xiong-Jian
Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants
title Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants
title_full Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants
title_fullStr Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants
title_full_unstemmed Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants
title_short Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants
title_sort functional genomic analysis delineates regulatory mechanisms of gwas-identified bipolar disorder risk variants
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9121601/
https://www.ncbi.nlm.nih.gov/pubmed/35590387
http://dx.doi.org/10.1186/s13073-022-01057-3
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