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

Overview of attention for article published in Genome Medicine, May 2022
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 news outlet
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6 Dimensions

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Title
Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants
Published in
Genome Medicine, May 2022
DOI 10.1186/s13073-022-01057-3
Pubmed ID
Authors

Rui Chen, Zhihui Yang, Jiewei Liu, Xin Cai, Yongxia Huo, Zhijun Zhang, Ming Li, Hong Chang, Xiong-Jian Luo

Abstract

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. 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. 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. 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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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 15%
Unspecified 1 5%
Student > Doctoral Student 1 5%
Librarian 1 5%
Professor 1 5%
Other 1 5%
Unknown 12 60%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 15%
Unspecified 1 5%
Psychology 1 5%
Neuroscience 1 5%
Medicine and Dentistry 1 5%
Other 0 0%
Unknown 13 65%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 June 2022.
All research outputs
#2,552,747
of 22,714,025 outputs
Outputs from Genome Medicine
#586
of 1,435 outputs
Outputs of similar age
#56,005
of 436,262 outputs
Outputs of similar age from Genome Medicine
#17
of 33 outputs
Altmetric has tracked 22,714,025 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,435 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.6. This one has gotten more attention than average, scoring higher than 58% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 436,262 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.