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The TreadWheel: Interval Training Protocol for Gently Induced Exercise in Drosophila melanogaster
Published on: June 8, 2018
Genomic and transcriptomic predictors of triglyceride response to regular exercise
Mark A Sarzynski1, Peter K Davidsen2, Yun Ju Sung3
1Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA Department of Exercise Science, University of South Carolina, Columbia, SC, USA.
Aim:
We performed genome-wide and transcriptome-wide profiling to identify genes and single nucleotide polymorphisms (SNPs) associated with the response of triglycerides (TG) to exercise training.
Methods:
Plasma TG levels were measured before and after a 20-week endurance training programme in 478 white participants from the HERITAGE Family Study. Illumina HumanCNV370-Quad v3.0 BeadChips were genotyped using the Illumina BeadStation 500GX platform. Affymetrix HG-U133+2 arrays were used to quantitate gene expression levels from baseline muscle biopsies of a subset of participants (N=52). Genome-wide association study (GWAS) analysis was performed using MERLIN, while transcriptomic predictor models were developed using the R-package GALGO.
Results:
The GWAS results showed that eight SNPs were associated with TG training-response (ΔTG) at p<9.9×10(-6), while another 31 SNPs showed p values <1×10(-4). In multivariate regression models, the top 10 SNPs explained 32.0% of the variance in ΔTG, while conditional heritability analysis showed that four SNPs statistically accounted for all of the heritability of ΔTG. A molecular signature based on the baseline expression of 11 genes predicted 27% of ΔTG in HERITAGE, which was validated in an independent study. A composite SNP score based on the top four SNPs, each from the genomic and transcriptomic analyses, was the strongest predictor of ΔTG (R(2)=0.14, p=3.0×10(-68)).
Conclusions:
Our results indicate that skeletal muscle transcript abundance at 11 genes and SNPs at a number of loci contribute to TG response to exercise training. Combining data from genomics and transcriptomics analyses identified a SNP-based gene signature that should be further tested in independent samples.
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