Evidence map›Paper›PMID 39161423›Full record

ArticleFrontiers in genetics2024

Mendelian randomization analysis identified potential genes pleiotropically associated with gout.

Yu Wang, Jiahao Chen, Hang Yao, Yuxin Li, Xiaogang Xu, Delin Zhang

Abstract read
In one paragraph

Article in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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

6 authors.

Yu Wang *Graduate School of Jiangxi University of Traditional Chinese Medicine, Nanchang, China.
Jiahao Chen *School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, China.
Hang Yao *School of Traditional Chinese Medicine, Binzhou Medical University, Yantai, China.
Yuxin LiGraduate School of Jiangxi University of Traditional Chinese Medicine, Nanchang, China.
Xiaogang XuGraduate School of Jiangxi University of Traditional Chinese Medicine, Nanchang, China.
Delin ZhangGraduate School of Jiangxi University of Traditional Chinese Medicine, Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aims to prioritize genes potentially involved in multifactorial or causal relationships with gout. Methods: Using the Summary Data-based Mendelian Randomization (SMR) approach, this research analyzed expression quantitative trait loci (eQTL) data from blood and renal tissues and genome-wide association study (GWAS) data related to gout. It sought to identify genetic loci potentially involved in gout. Heterogeneity testing was conducted with the HEIDI test, and results were adjusted for the False Discovery Rate (FDR). Blood cis-eQTL data were sourced from the eQTLGen Consortium's summary-level data, and renal tissue data came from the V8 release of the GTEx eQTL summary data. Gout GWAS data was sourced from the FinnGen Documentation of the R10 release. Result: SMR analysis identified 14 gene probes in the eQTLGen blood summary-level data significantly associated with gout. The top five ranked genes are: ENSG00000169231 (labeled THBS3, P Conclusion: Our findings have highlighted several genes potentially involved in the pathogenesis of gout. These results offer valuable insights into the mechanisms of gout and identify potential therapeutic targets for its treatment.

Indexed as

expression quantitative trait locigenome-wide association studygoutpleotropic associationsummary data-based mendelian randomization

Identifiers

PMID39161423
PMCPMC11330811

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.