Evidence map›Paper›PMID 35590387›Full record

ArticleGenome medicine2022

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

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

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. dbBIP: a comprehensive bipolar disorder database for genetic research.Database : the journal of biological databases and curation · 2022
    Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 1 country.

Rui Chen *Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China.
Zhihui Yang *Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China.
Jiewei Liu *Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China.
Xin Cai *Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China.
Yongxia HuoKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China.
Zhijun ZhangDepartment of Neurology, Affiliated Zhongda Hospital, Southeast University, Nanjing, Jiangsu, 210096, China.
Ming LiKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China. limingkiz@mail.kiz.ac.cn.
Hong ChangKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China. changhong@mail.kiz.ac.cn.
Xiong-Jian LuoKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China. luoxiongjian@mail.kiz.ac.cn.
Chinese Academy of Sciences · CNUniversity of Chinese Academy of Sciences · CNZhongda Hospital Southeast University · CNKunming Institute of Zoology · CN

Funding

VESICULAR LOCALIZATION AND FUNCTION OF PRESENILIN 1 FRAGMENTP50AG005138 · NIA · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI GROSSMAN, HILLEL · 1985 to 2019
$37.9M
QUANTITATIVE ANALYSIS OF MICROVASCULAR CHANGES IN THE AGING BRAINP01AG002219 · NIA · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI HAROUTUNIAN, VAHRAM · 1985 to 2009
$19.2M
White Matter Abnormalities in SchizophreniaP50MH066392 · NIMH · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI O'DONOVAN, MICHAEL J · 2002 to 2012
$18.6M
Project 5: In vivo measurement of GABA transmission in healthy controls & subjectP50MH084053 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEWIS, DAVID A · 2008 to 2012
$11.5M
International Cohort Collection for Bipolar DisorderR01MH085542 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI SMOLLER, JORDAN W · 2008 to 2012
$10.7M
Genetics Association in Schizophrenia and Other DisordersR37MH057881 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DEVLIN, BERNIE · 2013 to 2022
$5.4M
Src mediates molecular alterations leading to NMDAR hypofunction in schizophreniaR01MH075916 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI BORGMANN-WINTER, KARIN, HAHN, CHANG-GYU · 2006 to 2019
$3.3M
Identifying therapeutic targets for autism using Shank3-deficient miceR01MH093725 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BUXBAUM, JOSEPH D. · 2011 to 2015
$2.5M
1/3-Networks from Multidimensional Data for Schizophrenia and Related DisordersR01MH097276 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SCHADT, ERIC E, SKLAR, PAMELA · 2012 to 2014
$2.5M
Plasma and CSF Abeta peptides in late-onset major depressionR01MH080405 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI POMARA, NUNZIO · 2007 to 2011
$1.6M
NIA NIH HHS P01 AG002219NIA NIH HHS P50 AG005138NIDA NIH HHS HHSN271201300031CNIMH NIH HHS P50 MH066392NIMH NIH HHS P50 MH084053NIMH NIH HHS R01 MH075916NIMH NIH HHS R01 MH080405NIMH NIH HHS R01 MH085542NIMH NIH HHS R01 MH093725NIMH NIH HHS R01 MH097276NIMH NIH HHS R37 MH057881
6 · The paper itself

Abstract

backgroundGenome-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.

methodsWe 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.

resultsWe 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.

conclusionsOur 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.

Indexed as

Bipolar DisorderGenome-Wide Association StudyAnimalsGenetic Predisposition to DiseaseGenomicsHumansMicePolymorphism, Single NucleotideVesicular Transport ProteinsPACS1 protein, humanPacs1 protein, mouseVesicular Transport ProteinsBipolar disorderExpression quantitative trait loci (eQTL)Functional genomicsGenome-wide association study (GWAS)Regulatory mechanismsTranscription factor–disrupting SNPs

Identifiers

PMID35590387
PMCPMC9121601
OpenAlexW4280609858

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