학술논문
Exploring the underlying biology of intrinsic cardiorespiratory fitness through integrative analysis of genomic variants and muscle gene expression profiling.
Document Type
Academic Journal
Author
Ghosh S; Human Genomics Laboratory, Pennington Biomedical Research Center , Baton Rouge, Louisiana.; Cardiovascular and Metabolic Disorders Program and Centre for Computational Biology, Duke-National University of Singapore Medical School , Singapore.; Hota M; Cardiovascular and Metabolic Disorders Program and Centre for Computational Biology, Duke-National University of Singapore Medical School , Singapore.; Chai X; Cardiovascular and Metabolic Disorders Program and Centre for Computational Biology, Duke-National University of Singapore Medical School , Singapore.; Kiranya J; Cardiovascular and Metabolic Disorders Program and Centre for Computational Biology, Duke-National University of Singapore Medical School , Singapore.; Ghosh P; Center for Quantitative Medicine, Duke-National University of Singapore Medical School , Singapore.; He Z; Human Genomics Laboratory, Pennington Biomedical Research Center , Baton Rouge, Louisiana.; Department of Biology, China Institute of Sport Science , Beijing , China.; Ruiz-Ramie JJ; Department of Exercise Science, Arnold School of Public Health, University of South Carolina , Columbia, South Carolina.; Sarzynski MA; Department of Exercise Science, Arnold School of Public Health, University of South Carolina , Columbia, South Carolina.; Bouchard C; Human Genomics Laboratory, Pennington Biomedical Research Center , Baton Rouge, Louisiana.
Source
Publisher: American Physiological Society Country of Publication: United States NLM ID: 8502536 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1522-1601 (Electronic) Linking ISSN: 01617567 NLM ISO Abbreviation: J Appl Physiol (1985) Subsets: MEDLINE
Subject
Language
English
Abstract
Intrinsic cardiorespiratory fitness (CRF) is defined as the level of CRF in the sedentary state. There are large individual differences in intrinsic CRF among sedentary adults. The physiology of variability in CRF has received much attention, but little is known about the genetic and molecular mechanisms that impact intrinsic CRF. These issues were explored in the present study by interrogating intrinsic CRF-associated DNA sequence variation and skeletal muscle gene expression data from the HERITAGE Family Study through an integrative bioinformatics guided approach. A combined analytic strategy involving genetic association, pathway enrichment, tissue-specific network structure, cis-regulatory genome effects, and expression quantitative trait loci was used to select and rank genes through a variation-adjusted weighted ranking scheme. Prioritized genes were further interrogated for corroborative evidence from knockout mouse phenotypes and relevant physiological traits from the HERITAGE cohort. The mean intrinsic V̇o 2max was 33.1 ml O 2 ·kg -1 ·min -1 (SD = 8.8) for the sample of 493 sedentary adults. Suggestive evidence was found for gene loci related to cardiovascular physiology ( ATE1 , CASQ2 , NOTO , and SGCG ), hematopoiesis ( PICALM , SSB , CA9 , and CASQ2 ), skeletal muscle phenotypes ( SGCG , DMRT2 , ADARB1 , and CASQ2 ), and metabolism ( ATE1 , PICALM , RAB11FIP5 , GBA2 , SGCG , PRADC1 , ARL6IP5 , and CASQ2 ). Supportive evidence for a role of several of these loci was uncovered via association between DNA variants and muscle gene expression levels with exercise cardiovascular and muscle physiological traits. This initial effort to define the underlying molecular substrates of intrinsic CRF warrants further studies based on appropriate cohorts and study designs, complemented by functional investigations. NEW & NOTEWORTHY Intrinsic cardiorespiratory fitness (CRF) is measured in the sedentary state and is highly variable among sedentary adults. The physiology of variability in intrinsic cardiorespiratory fitness has received much attention, but little is known about the genetic and molecular mechanisms that impact intrinsic CRF. These issues were explored computationally in the present study, with further corroborative evidence obtained from analysis of phenotype data from knockout mouse models and human cardiovascular and skeletal muscle measurements.