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. 2015 Dec;49(23):1524-31.
doi: 10.1136/bjsports-2015-095179. Epub 2015 Oct 21.

Genomic and transcriptomic predictors of triglyceride response to regular exercise

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Genomic and transcriptomic predictors of triglyceride response to regular exercise

Mark A Sarzynski et al. Br J Sports Med. 2015 Dec.

Abstract

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.

Keywords: Exercise; Intervention; Lipids.

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Figures

Figure 1
Figure 1
Performance of the RNA-based regression model derived from the training set (N=37, grey dots) in the test set (N=12, red dots) for the prediction of exercise training-induced changes in triglycerides in HERITAGE.
Figure 2
Figure 2
Adjusted mean response to exercise training triglycerides (ΔTG) across eight single nucleotide polymorphisms (SNP) summary score categories in HERITAGE white participants. Values were adjusted for age, sex, baseline body mass index and baseline triglyceride level. Number of participants within each SNP score category is indicated inside each histogram bar.

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