4.7 Article

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

Journal

GENOME MEDICINE
Volume 14, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s13073-022-01057-3

Keywords

Bipolar disorder; Genome-wide association study (GWAS); Functional genomics; Transcription factor-disrupting SNPs; Expression quantitative trait loci (eQTL); Regulatory mechanisms

Funding

  1. National Nature Science Foundation of China [U2102205, 31970561, 82071534, 81871067, 31900414, 81830040, 82130042]
  2. Distinguished Young Scientists grant of Yunnan Province [202001AV070006]
  3. Western Light Innovative Research Team of the Chinese Academy of Sciences
  4. Key Research Project of Yunnan Province [202101AS070055]
  5. Science and Technology Program of Guangdong [2018B030334001]

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The study identified 16 functional SNPs in 9 risk loci that disrupted the binding of 7 transcription factors, such as CTCF and REST. Potential target genes regulated by these functional SNPs in the human brain were identified through eQTL analysis. Dysregulation of target genes of the identified TF binding-disrupting SNPs was shown in BD patients compared with controls, and overexpression of PACS1 reduced dendritic spine density, revealing possible biological mechanisms of these functional SNPs in BD.
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.

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