Characterizing modifier genes of cardiac fibrosis phenotype in hypertrophic cardiomyopathy.


Journal

International journal of cardiology
ISSN: 1874-1754
Titre abrégé: Int J Cardiol
Pays: Netherlands
ID NLM: 8200291

Informations de publication

Date de publication:
01 05 2021
Historique:
received: 13 10 2020
revised: 18 01 2021
accepted: 24 01 2021
pubmed: 3 2 2021
medline: 29 5 2021
entrez: 2 2 2021
Statut: ppublish

Résumé

Clinical phenotypes of hypertrophic cardiomyopathy (HCM) vary greatly even among patients with the same gene mutations. This variability is largely regulated by unidentified modifier loci. The purpose of the study is to identify modifier genes for cardiac fibrosis-a major phenotype of HCM-using the BXD family, a murine cohort. The relative severity of cardiac fibrosis was estimated by quantitation of cardiac collagen volume fraction (CCVF) across 66 members of the BXD family. Quantitative trait locus (QTL) mapping for cardiac fibrosis was done using GeneNetwork. Candidate modifier loci and genes associated with fibrosis were prioritized based on an explicit scoring system. Networks of correlation between fibrosis and cardiac transcriptomes were evaluated to generate causal models of disease susceptibility. CCVF levels varied greatly within this family. Interval mapping identified a significant CCVF-related QTL on chromosome (Chr) 2 in males, and a significant QTL on Chr 4 Mb in females. The scoring system highlighted two strong candidate genes in the Chr 2 locus-Nek6 and Nr6a1. Both genes are highly expressed in the heart. Cardiac Nek6 mRNA levels are significantly correlated with CCVF. Nipsnap3b and Fktn are lead candidate genes for the Chr 4 locus, and both are also highly expressed in heart. Cardiac Nipsnap3b gene expression correlates well with CCVF. Our study demonstrated that candidate modifier genes of cardiac fibrosis phenotype in HCM are different in males and females. Nek6 and Nr6a1 are strong candidates in males, while Nipsnap3b and Fktn are top candidates in females.

Sections du résumé

BACKGROUND
Clinical phenotypes of hypertrophic cardiomyopathy (HCM) vary greatly even among patients with the same gene mutations. This variability is largely regulated by unidentified modifier loci. The purpose of the study is to identify modifier genes for cardiac fibrosis-a major phenotype of HCM-using the BXD family, a murine cohort.
METHODS
The relative severity of cardiac fibrosis was estimated by quantitation of cardiac collagen volume fraction (CCVF) across 66 members of the BXD family. Quantitative trait locus (QTL) mapping for cardiac fibrosis was done using GeneNetwork. Candidate modifier loci and genes associated with fibrosis were prioritized based on an explicit scoring system. Networks of correlation between fibrosis and cardiac transcriptomes were evaluated to generate causal models of disease susceptibility.
RESULTS
CCVF levels varied greatly within this family. Interval mapping identified a significant CCVF-related QTL on chromosome (Chr) 2 in males, and a significant QTL on Chr 4 Mb in females. The scoring system highlighted two strong candidate genes in the Chr 2 locus-Nek6 and Nr6a1. Both genes are highly expressed in the heart. Cardiac Nek6 mRNA levels are significantly correlated with CCVF. Nipsnap3b and Fktn are lead candidate genes for the Chr 4 locus, and both are also highly expressed in heart. Cardiac Nipsnap3b gene expression correlates well with CCVF.
CONCLUSION
Our study demonstrated that candidate modifier genes of cardiac fibrosis phenotype in HCM are different in males and females. Nek6 and Nr6a1 are strong candidates in males, while Nipsnap3b and Fktn are top candidates in females.

Identifiants

pubmed: 33529666
pii: S0167-5273(21)00129-7
doi: 10.1016/j.ijcard.2021.01.047
pmc: PMC8105878
mid: NIHMS1668452
pii:
doi:

Substances chimiques

NEK6 protein, human EC 2.7.11.1
NIMA-Related Kinases EC 2.7.11.1

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

135-141

Subventions

Organisme : NHLBI NIH HHS
ID : R01 HL128350
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL151438
Pays : United States

Informations de copyright

Copyright © 2021 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest None.

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Auteurs

Fuyi Xu (F)

Division of Cardiovascular Diseases, Department of Medicine, Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States of America.

Yuanjian Chen (Y)

Division of Cardiovascular Diseases, Department of Medicine, Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States of America.

Kaitlin A Tillman (KA)

Division of Cardiovascular Diseases, Department of Medicine, Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States of America.

Yan Cui (Y)

Division of Cardiovascular Diseases, Department of Medicine, Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States of America.

Robert W Williams (RW)

Division of Cardiovascular Diseases, Department of Medicine, Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States of America.

Syamal K Bhattacharya (SK)

Division of Cardiovascular Diseases, Department of Medicine, Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States of America.

Lu Lu (L)

Division of Cardiovascular Diseases, Department of Medicine, Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States of America. Electronic address: llu@uthsc.edu.

Yao Sun (Y)

Division of Cardiovascular Diseases, Department of Medicine, Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States of America. Electronic address: yasun@uthsc.edu.

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Classifications MeSH