Massimo Mezzavilla1, Annamaria Iorio2, Marco Bobbo2, Angela D'Eustacchio3, Marco Merlo2, Paolo Gasparini1, Sheila Ulivi4, Gianfranco Sinagra2. 1. Institute for Maternal and Child Health - IRCCS "Burlo Garofolo" - Trieste, University of Trieste, Italy. 2. Cardiovascular Department, Ospedali Riuniti and University of Trieste, Trieste, Italy. 3. Institute for Maternal and Child Health - IRCCS "Burlo Garofolo" - Trieste, Italy. 4. Institute for Maternal and Child Health - IRCCS "Burlo Garofolo" - Trieste, Italy. Electronic address: sheila.ulivi@burlo.trieste.it.
Abstract
BACKGROUND: Recent studies suggested that resting heart rate (RHR) might be an independent predictor of cardiovascular mortality and morbidity. Nonetheless, the interrelation between RHR and cardiovascular diseases is not clear. In order to resolve this puzzle, the importance of genetic determinants of RHR has been recently suggested, but it needs to be further investigated. OBJECTIVE: The aim of this study was to estimate the contribution of common genetic variations on RHR using Genome Wide Association Study. METHODS: We performed a Genome Wide Association Study in an isolated population cohort of 1737 individuals, the Italian Network on Genetic Isolates - Friuli Venezia Giulia (INGI-FVG). Moreover, a haplotype analysis was performed. A regression tree analysis was run to highlight the effect of each haplotype combination on the phenotype. RESULTS: A significant level of association (p<5 × 10(-8)) was detected for Single Nucleotide Polymorphisms (SNPs) in two genes expressed in the heart: MAML1 and CANX. Founding that the three different variants of the haplotype, which encompass both genes, yielded a phenotypic correlation. Indeed, a haplotype in homozygosity is significantly associated with the lower quartile of RHR (RHR ≤ 58 bpm). Moreover no significant association was found between cardiovascular risk factors and the different haplotype combinations. CONCLUSION: Mastermind-like 1 and Calnexin were found to be associated with RHR. We demonstrated a relation between a haplotype and the lower quartile of RHR in our populations. Our findings highlight that genetic determinants of RHR may be implicated in determining cardiovascular diseases and could allow a better risk stratification.
BACKGROUND: Recent studies suggested that resting heart rate (RHR) might be an independent predictor of cardiovascular mortality and morbidity. Nonetheless, the interrelation between RHR and cardiovascular diseases is not clear. In order to resolve this puzzle, the importance of genetic determinants of RHR has been recently suggested, but it needs to be further investigated. OBJECTIVE: The aim of this study was to estimate the contribution of common genetic variations on RHR using Genome Wide Association Study. METHODS: We performed a Genome Wide Association Study in an isolated population cohort of 1737 individuals, the Italian Network on Genetic Isolates - Friuli Venezia Giulia (INGI-FVG). Moreover, a haplotype analysis was performed. A regression tree analysis was run to highlight the effect of each haplotype combination on the phenotype. RESULTS: A significant level of association (p<5 × 10(-8)) was detected for Single Nucleotide Polymorphisms (SNPs) in two genes expressed in the heart: MAML1 and CANX. Founding that the three different variants of the haplotype, which encompass both genes, yielded a phenotypic correlation. Indeed, a haplotype in homozygosity is significantly associated with the lower quartile of RHR (RHR ≤ 58 bpm). Moreover no significant association was found between cardiovascular risk factors and the different haplotype combinations. CONCLUSION:Mastermind-like 1 and Calnexin were found to be associated with RHR. We demonstrated a relation between a haplotype and the lower quartile of RHR in our populations. Our findings highlight that genetic determinants of RHR may be implicated in determining cardiovascular diseases and could allow a better risk stratification.
Authors: Raymond Noordam; Colleen M Sitlani; Christy L Avery; James D Stewart; Stephanie M Gogarten; Kerri L Wiggins; Stella Trompet; Helen R Warren; Fangui Sun; Daniel S Evans; Xiaohui Li; Jin Li; Albert V Smith; Joshua C Bis; Jennifer A Brody; Evan L Busch; Mark J Caulfield; Yii-Der I Chen; Steven R Cummings; L Adrienne Cupples; Qing Duan; Oscar H Franco; Rául Méndez-Giráldez; Tamara B Harris; Susan R Heckbert; Diana van Heemst; Albert Hofman; James S Floyd; Jan A Kors; Lenore J Launer; Yun Li; Ruifang Li-Gao; Leslie A Lange; Henry J Lin; Renée de Mutsert; Melanie D Napier; Christopher Newton-Cheh; Neil Poulter; Alexander P Reiner; Kenneth M Rice; Jeffrey Roach; Carlos J Rodriguez; Frits R Rosendaal; Naveed Sattar; Peter Sever; Amanda A Seyerle; P Eline Slagboom; Elsayed Z Soliman; Nona Sotoodehnia; David J Stott; Til Stürmer; Kent D Taylor; Timothy A Thornton; André G Uitterlinden; Kirk C Wilhelmsen; James G Wilson; Vilmundur Gudnason; J Wouter Jukema; Cathy C Laurie; Yongmei Liu; Dennis O Mook-Kanamori; Patricia B Munroe; Jerome I Rotter; Ramachandran S Vasan; Bruce M Psaty; Bruno H Stricker; Eric A Whitsel Journal: J Med Genet Date: 2016-12-30 Impact factor: 6.318
Authors: Kaleigh L Evans; Heidi S Wirtz; Jia Li; Ruicong She; Juan Maya; Hongsheng Gui; Andrew Hamer; Christophe Depre; David E Lanfear Journal: Hum Genomics Date: 2019-05-21 Impact factor: 4.639