Literature DB >> 23990238

Integrative pathway analysis of a genome-wide association study of (V)O(2max) response to exercise training.

Sujoy Ghosh1, Juan C Vivar, Mark A Sarzynski, Yun Ju Sung, James A Timmons, Claude Bouchard, Tuomo Rankinen.   

Abstract

We previously reported the findings from a genome-wide association study of the response of maximal oxygen uptake (Vo2max) to an exercise program. Here we follow up on these results to generate hypotheses on genes, pathways, and systems involved in the ability to respond to exercise training. A systems biology approach can help us better establish a comprehensive physiological description of what underlies Vo2maxtrainability. The primary material for this exploration was the individual single-nucleotide polymorphism (SNP), SNP-gene mapping, and statistical significance levels. We aimed to generate novel hypotheses through analyses that go beyond statistical association of single-locus markers. This was accomplished through three complementary approaches: 1) building de novo evidence of gene candidacy through informatics-driven literature mining; 2) aggregating evidence from statistical associations to link variant enrichment in biological pathways to Vo2max trainability; and 3) predicting possible consequences of variants residing in the pathways of interest. We started with candidate gene prioritization followed by pathway analysis focused on overrepresentation analysis and gene set enrichment analysis. Subsequently, leads were followed using in silico analysis of predicted SNP functions. Pathways related to cellular energetics (pantothenate and CoA biosynthesis; PPAR signaling) and immune functions (complement and coagulation cascades) had the highest levels of SNP burden. In particular, long-chain fatty acid transport and fatty acid oxidation genes and sequence variants were found to influence differences in Vo2max trainability. Together, these methods allow for the hypothesis-driven ranking and prioritization of genes and pathways for future experimental testing and validation.

Entities:  

Keywords:  bioinformatics; endurance training; genotypes; pathway analysis; single-nucleotide polymorphisms

Mesh:

Year:  2013        PMID: 23990238      PMCID: PMC3841836          DOI: 10.1152/japplphysiol.01487.2012

Source DB:  PubMed          Journal:  J Appl Physiol (1985)        ISSN: 0161-7567


  47 in total

Review 1.  Analysing biological pathways in genome-wide association studies.

Authors:  Kai Wang; Mingyao Li; Hakon Hakonarson
Journal:  Nat Rev Genet       Date:  2010-12       Impact factor: 53.242

2.  Gene ontology analysis of GWA study data sets provides insights into the biology of bipolar disorder.

Authors:  Peter Holmans; Elaine K Green; Jaspreet Singh Pahwa; Manuel A R Ferreira; Shaun M Purcell; Pamela Sklar; Michael J Owen; Michael C O'Donovan; Nick Craddock
Journal:  Am J Hum Genet       Date:  2009-06-18       Impact factor: 11.025

3.  Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans.

Authors:  James A Timmons; Steen Knudsen; Tuomo Rankinen; Lauren G Koch; Mark Sarzynski; Thomas Jensen; Pernille Keller; Camilla Scheele; Niels B J Vollaard; Søren Nielsen; Thorbjörn Akerström; Ormond A MacDougald; Eva Jansson; Paul L Greenhaff; Mark A Tarnopolsky; Luc J C van Loon; Bente K Pedersen; Carl Johan Sundberg; Claes Wahlestedt; Steven L Britton; Claude Bouchard
Journal:  J Appl Physiol (1985)       Date:  2010-02-04

4.  Adipose acyl-CoA synthetase-1 directs fatty acids toward beta-oxidation and is required for cold thermogenesis.

Authors:  Jessica M Ellis; Lei O Li; Pei-Chi Wu; Timothy R Koves; Olga Ilkayeva; Robert D Stevens; Steven M Watkins; Deborah M Muoio; Rosalind A Coleman
Journal:  Cell Metab       Date:  2010-07-07       Impact factor: 27.287

5.  Adaptation to a standardized training program and changes in fitness in a large, heterogeneous population: the HERITAGE Family Study.

Authors:  J S Skinner; K M Wilmore; J B Krasnoff; A Jaskólski; A Jaskólska; J Gagnon; M A Province; A S Leon; D C Rao; J H Wilmore; C Bouchard
Journal:  Med Sci Sports Exerc       Date:  2000-01       Impact factor: 5.411

6.  A transcriptional map of the impact of endurance exercise training on skeletal muscle phenotype.

Authors:  Pernille Keller; Niels B J Vollaard; Thomas Gustafsson; Iain J Gallagher; Carl Johan Sundberg; Tuomo Rankinen; Steven L Britton; Claude Bouchard; Lauren G Koch; James A Timmons
Journal:  J Appl Physiol (1985)       Date:  2010-10-07

7.  Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits.

Authors:  Ayellet V Segrè; Leif Groop; Vamsi K Mootha; Mark J Daly; David Altshuler
Journal:  PLoS Genet       Date:  2010-08-12       Impact factor: 5.917

8.  Gene expression profiling in whole blood identifies distinct biological pathways associated with obesity.

Authors:  Sujoy Ghosh; Robert Dent; Mary-Ellen Harper; Shelby A Gorman; Joan S Stuart; Ruth McPherson
Journal:  BMC Med Genomics       Date:  2010-12-01       Impact factor: 3.063

Review 9.  Variability in training-induced skeletal muscle adaptation.

Authors:  James A Timmons
Journal:  J Appl Physiol (1985)       Date:  2010-10-28

10.  From SNPs to genes: disease association at the gene level.

Authors:  Benjamin Lehne; Cathryn M Lewis; Thomas Schlitt
Journal:  PLoS One       Date:  2011-06-30       Impact factor: 3.240

View more
  25 in total

Review 1.  Variability in Individual Response to Aerobic Exercise Interventions Among Older Adults.

Authors:  Mary O Whipple; Erica N Schorr; Kristine M C Talley; Ruth Lindquist; Ulf G Bronas; Diane Treat-Jacobson
Journal:  J Aging Phys Act       Date:  2018-06-20       Impact factor: 1.961

2.  Quantitative genomics of voluntary exercise in mice: transcriptional analysis and mapping of expression QTL in muscle.

Authors:  Scott A Kelly; Derrick L Nehrenberg; Kunjie Hua; Theodore Garland; Daniel Pomp
Journal:  Physiol Genomics       Date:  2014-06-17       Impact factor: 3.107

3.  Genetic polymorphisms to predict gains in maximal O2 uptake and knee peak torque after a high intensity training program in humans.

Authors:  Jinho Yoo; Bo-Hyung Kim; Soo-Hwan Kim; Yangseok Kim; Sung-Vin Yim
Journal:  Eur J Appl Physiol       Date:  2016-03-21       Impact factor: 3.078

Review 4.  Genomic and transcriptomic predictors of response levels to endurance exercise training.

Authors:  Mark A Sarzynski; Sujoy Ghosh; Claude Bouchard
Journal:  J Physiol       Date:  2016-07-03       Impact factor: 5.182

5.  Heterogeneity of physical function responses to exercise training in older adults.

Authors:  Elizabeth A Chmelo; Charlotte I Crotts; Jill C Newman; Tina E Brinkley; Mary F Lyles; Xiaoyan Leng; Anthony P Marsh; Barbara J Nicklas
Journal:  J Am Geriatr Soc       Date:  2015-03-06       Impact factor: 5.562

Review 6.  Personalized preventive medicine: genetics and the response to regular exercise in preventive interventions.

Authors:  Claude Bouchard; Ligia M Antunes-Correa; Euan A Ashley; Nina Franklin; Paul M Hwang; C Mikael Mattsson; Carlos E Negrao; Shane A Phillips; Mark A Sarzynski; Ping-Yuan Wang; Matthew T Wheeler
Journal:  Prog Cardiovasc Dis       Date:  2014-08-13       Impact factor: 8.194

7.  Exploring the underlying biology of intrinsic cardiorespiratory fitness through integrative analysis of genomic variants and muscle gene expression profiling.

Authors:  Sujoy Ghosh; Monalisa Hota; Xiaoran Chai; Jencee Kiranya; Palash Ghosh; Zihong He; Jonathan J Ruiz-Ramie; Mark A Sarzynski; Claude Bouchard
Journal:  J Appl Physiol (1985)       Date:  2019-01-03

8.  Genomic and transcriptomic predictors of triglyceride response to regular exercise.

Authors:  Mark A Sarzynski; Peter K Davidsen; Yun Ju Sung; Matthijs K C Hesselink; Patrick Schrauwen; Treva K Rice; D C Rao; Francesco Falciani; Claude Bouchard
Journal:  Br J Sports Med       Date:  2015-10-21       Impact factor: 13.800

9.  An investigation into the relationship between age and physiological function in highly active older adults.

Authors:  Ross D Pollock; Scott Carter; Cristiana P Velloso; Niharika A Duggal; Janet M Lord; Norman R Lazarus; Stephen D R Harridge
Journal:  J Physiol       Date:  2015-01-06       Impact factor: 5.182

Review 10.  The genetics of human performance.

Authors:  Daniel Seung Kim; Matthew T Wheeler; Euan A Ashley
Journal:  Nat Rev Genet       Date:  2021-09-14       Impact factor: 53.242

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.