Fuyi Xu1, Yuanjian Chen1, Kaitlin A Tillman1, Yan Cui1, Robert W Williams1, Syamal K Bhattacharya1, Lu Lu2, Yao Sun3. 1. 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. 2. 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. 3. 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.
Abstract
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.
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.
Authors: Diego Fraidenraich; Elizabeth Stillwell; Elizabeth Romero; David Wilkes; Katia Manova; Craig T Basson; Robert Benezra Journal: Science Date: 2004-10-08 Impact factor: 47.728
Authors: Franck Mauvais-Jarvis; Noel Bairey Merz; Peter J Barnes; Roberta D Brinton; Juan-Jesus Carrero; Dawn L DeMeo; Geert J De Vries; C Neill Epperson; Ramaswamy Govindan; Sabra L Klein; Amedeo Lonardo; Pauline M Maki; Louise D McCullough; Vera Regitz-Zagrosek; Judith G Regensteiner; Joshua B Rubin; Kathryn Sandberg; Ayako Suzuki Journal: Lancet Date: 2020-08-22 Impact factor: 79.321
Authors: Wenyuan Zhao; Tieqiang Zhao; Yuanjian Chen; Fengbo Zhao; Qingqing Gu; Robert W Williams; Syamal K Bhattacharya; Lu Lu; Yao Sun Journal: PLoS One Date: 2015-08-04 Impact factor: 3.240
Authors: Xusheng Wang; Ashutosh K Pandey; Megan K Mulligan; Evan G Williams; Khyobeni Mozhui; Zhengsheng Li; Virginija Jovaisaite; L Darryl Quarles; Zhousheng Xiao; Jinsong Huang; John A Capra; Zugen Chen; William L Taylor; Lisa Bastarache; Xinnan Niu; Katherine S Pollard; Daniel C Ciobanu; Alexander O Reznik; Artem V Tishkov; Igor B Zhulin; Junmin Peng; Stanley F Nelson; Joshua C Denny; Johan Auwerx; Lu Lu; Robert W Williams Journal: Nat Commun Date: 2016-02-02 Impact factor: 14.919