Wednesday, October 17, 2018 Print page
Centre of Inflammation and Metabolism (CIM)


To read the abstract, please click on the title of the publication of interest. If you want to access the publication on PubMed, please click on the PubMed ID.
To find specific publications, please use the sort and search functions. Please enter one word only as search term.

Click here to see all publications

142Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans.
Timmons JA; Knudsen S; Rankinen T; Koch LG; Sarzynski MA; Jensen T; Keller P; Scheele C; Vollaard NB; Nielsen S; Akerstrom T; Macdougald OA; Jansson E; Greenhaff PL; Tarnopolsky MA; van Loon LJ; Pedersen BK; Sundberg CJ; Wahlestedt C; Britton SL; Bouchard C
J Appl Physiol 2010; 108(6): 1487-96
PubMed ID: 20133430

A low maximal oxygen consumption (VO2max) is a strong risk factor for premature mortality. Supervised endurance exercise training increases VO2max with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial sample-sizes. In the present study we first use RNA expression profiling to produce a molecular classifier that predicts VO2max training response. We then hypothesised that the classifier genes would harbour DNA variants that contributed to the heterogeneous VO2max response. Two independent pre-intervention RNA expression data sets were generated (n=41 gene-chips) from subjects that underwent supervised endurance training. One identified, the second blindly validated an RNA expression signature that predicted change in VO2max ('predictor genes'). The HERITAGE Family Study (n=473) was used for genotyping. We discovered a 29 RNA signature that predicted VO2max training response on a continuous scale, and these genes contained ~6 new SNPs associated with gains in VO2max in HERITAGE. Three from 4 novel HERITAGE candidate genes were confirmed as RNA predictor genes (i.e. 'reciprocal' RNA validation of a QTL genotype), enhancing the performance of the 29 RNA based predictor. Notably, RNA abundance for the predictor genes was unchanged by exercise training, supporting the idea that expression was pre-set by genetic variation. Regression analysis yielded a model where 11 SNPs explained 23% of the variance in gains in VO2max, corresponding to ~50% of the estimated genetic variance for VO2max. In conclusion, combining RNA profiling with single-gene DNA marker association analysis yields a strongly validated molecular predictor with meaningful explanatory power. VO2max responses to endurance training can be predicted by measuring a ~30 gene RNA expression signature in muscle prior to training. The general approach taken could accelerate the discovery of genetic biomarkers, sufficiently discrete for diagnostic purposes, for a range of physiological and pharmacological phenotypes in humans. Key words: aerobic capacity, personalised medicine, genotype, endurance training.

© 2018 Centre of Inflammation and Metabolism