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Genes to predict VO2max trainability: a systematic review

Overview of attention for article published in BMC Genomics, November 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

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1 news outlet
blogs
1 blog
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36 X users
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2 Facebook pages
wikipedia
3 Wikipedia pages
video
1 YouTube creator

Citations

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102 Dimensions

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319 Mendeley
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Title
Genes to predict VO2max trainability: a systematic review
Published in
BMC Genomics, November 2017
DOI 10.1186/s12864-017-4192-6
Pubmed ID
Authors

Camilla J. Williams, Mark G. Williams, Nir Eynon, Kevin J. Ashton, Jonathan P. Little, Ulrik Wisloff, Jeff S. Coombes

Abstract

Cardiorespiratory fitness (VO2max) is an excellent predictor of chronic disease morbidity and mortality risk. Guidelines recommend individuals undertake exercise training to improve VO2max for chronic disease reduction. However, there are large inter-individual differences between exercise training responses. This systematic review is aimed at identifying genetic variants that are associated with VO2max trainability. Peer-reviewed research papers published up until October 2016 from four databases were examined. Articles were included if they examined genetic variants, incorporated a supervised aerobic exercise intervention; and measured VO2max/VO2peak pre and post-intervention. Thirty-five articles describing 15 cohorts met the criteria for inclusion. The majority of studies used a cross-sectional retrospective design. Thirty-two studies researched candidate genes, two used Genome-Wide Association Studies (GWAS), and one examined mRNA gene expression data, in addition to a GWAS. Across these studies, 97 genes to predict VO2max trainability were identified. Studies found phenotype to be dependent on several of these genotypes/variants, with higher responders to exercise training having more positive response alleles than lower responders (greater gene predictor score). Only 13 genetic variants were reproduced by more than two authors. Several other limitations were noted throughout these studies, including the robustness of significance for identified variants, small sample sizes, limited cohorts focused primarily on Caucasian populations, and minimal baseline data. These factors, along with differences in exercise training programs, diet and other environmental gene expression mediators, likely influence the ideal traits for VO2max trainability. Ninety-seven genes have been identified as possible predictors of VO2max trainability. To verify the strength of these findings and to identify if there are more genetic variants and/or mediators, further tightly-controlled studies that measure a range of biomarkers across ethnicities are required.

X Demographics

X Demographics

The data shown below were collected from the profiles of 36 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 319 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 319 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 46 14%
Student > Bachelor 34 11%
Student > Ph. D. Student 31 10%
Researcher 22 7%
Student > Doctoral Student 18 6%
Other 43 13%
Unknown 125 39%
Readers by discipline Count As %
Sports and Recreations 80 25%
Medicine and Dentistry 29 9%
Agricultural and Biological Sciences 19 6%
Biochemistry, Genetics and Molecular Biology 17 5%
Nursing and Health Professions 15 5%
Other 22 7%
Unknown 137 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 40. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 April 2024.
All research outputs
#996,161
of 25,064,526 outputs
Outputs from BMC Genomics
#131
of 11,153 outputs
Outputs of similar age
#20,166
of 331,887 outputs
Outputs of similar age from BMC Genomics
#2
of 209 outputs
Altmetric has tracked 25,064,526 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,153 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,887 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 209 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.