Exome sequencing identifies novel genetic variants associated with varicose veins.


Journal

PLoS genetics
ISSN: 1553-7404
Titre abrégé: PLoS Genet
Pays: United States
ID NLM: 101239074

Informations de publication

Date de publication:
Jul 2024
Historique:
received: 30 09 2023
accepted: 13 06 2024
medline: 9 7 2024
pubmed: 9 7 2024
entrez: 9 7 2024
Statut: epublish

Résumé

Varicose veins (VV) are one of the common human diseases, but the role of genetics in its development is not fully understood. We conducted an exome-wide association study of VV using whole-exome sequencing data from the UK Biobank, and focused on common and rare variants using single-variant association analysis and gene-level collapsing analysis. A total of 13,823,269 autosomal genetic variants were obtained after quality control. We identified 36 VV-related independent common variants mapping to 34 genes by single-variant analysis and three rare variant genes (PIEZO1, ECE1, FBLN7) by collapsing analysis, and most associations between genes and VV were replicated in FinnGen. PIEZO1 was the closest gene associated with VV (P = 5.05 × 10-31), and it was found to reach exome-wide significance in both single-variant and collapsing analyses. Two novel rare variant genes (ECE1 and METTL21A) associated with VV were identified, of which METTL21A was associated only with females. The pleiotropic effects of VV-related genes suggested that body size, inflammation, and pulmonary function are strongly associated with the development of VV. Our findings highlight the importance of causal genes for VV and provide new directions for treatment.

Sections du résumé

BACKGROUND BACKGROUND
Varicose veins (VV) are one of the common human diseases, but the role of genetics in its development is not fully understood.
METHODS METHODS
We conducted an exome-wide association study of VV using whole-exome sequencing data from the UK Biobank, and focused on common and rare variants using single-variant association analysis and gene-level collapsing analysis.
FINDINGS RESULTS
A total of 13,823,269 autosomal genetic variants were obtained after quality control. We identified 36 VV-related independent common variants mapping to 34 genes by single-variant analysis and three rare variant genes (PIEZO1, ECE1, FBLN7) by collapsing analysis, and most associations between genes and VV were replicated in FinnGen. PIEZO1 was the closest gene associated with VV (P = 5.05 × 10-31), and it was found to reach exome-wide significance in both single-variant and collapsing analyses. Two novel rare variant genes (ECE1 and METTL21A) associated with VV were identified, of which METTL21A was associated only with females. The pleiotropic effects of VV-related genes suggested that body size, inflammation, and pulmonary function are strongly associated with the development of VV.
CONCLUSIONS CONCLUSIONS
Our findings highlight the importance of causal genes for VV and provide new directions for treatment.

Identifiants

pubmed: 38980841
doi: 10.1371/journal.pgen.1011339
pii: PGENETICS-D-23-01104
doi:

Substances chimiques

PIEZO1 protein, human 0
ECE1 protein, human EC 3.4.24.71
Endothelin-Converting Enzymes EC 3.4.24.71
Ion Channels 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1011339

Informations de copyright

Copyright: © 2024 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Dan-Dan Zhang (DD)

Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.

Xiao-Yu He (XY)

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.

Liu Yang (L)

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.

Bang-Sheng Wu (BS)

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.

Yan Fu (Y)

Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.

Wei-Shi Liu (WS)

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.

Yu Guo (Y)

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.

Chen-Jie Fei (CJ)

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.

Ju-Jiao Kang (JJ)

Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China.
Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.

Jian-Feng Feng (JF)

Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China.
Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
Department of Computer Science, University of Warwick, Coventry, United Kingdom.

Wei Cheng (W)

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China.
Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
Department of Computer Science, University of Warwick, Coventry, United Kingdom.

Lan Tan (L)

Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.

Jin-Tai Yu (JT)

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.

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Classifications MeSH