Genomic and transcriptomic predictors of triglyceride response to regular exercise

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 (R2=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.

Omics and Exercise: Global Approaches for Mapping Exercise Biological Networks

“…The human muscle resistance exercise training -responsive transcriptional networks in the settings of aging (Raue et al 2012), aging-associated muscle frailty , stress-induced immune activation (Gordon et al 2012), and combined aerobic training modes (Lundberg et al 2016) are also continuing to be unraveled using transcriptomics. New studies assessing other tissues and biological fluids have uncovered adipose tissue networks (Ronn et al 2014) and transcriptional landscapes involving human plasma biomarkers of triglyceride responses (Sarzynski et al 2015) and peripheral blood cell biomarkers of oxygen uptake responsiveness to endurance training (Dias et al 2015). Although not discussed in detail, small noncoding RNA molecules such as microRNA are also important contributors to exercise-regulated posttranscriptional modulation and represent an exciting area for future investigation in epigenetic control of the exercise response (as systematically reviewed in Flowers et al 2015).…”

Metabolism and Exercise During Youth

“…Sarzynski et al (8) found that numerous genes and SNPs contributed to the genetic and transcriptomic variation in the chronic exercise training response of TAG (i.e., white participants' TAG response to exercise training in the HERITAGE Family Study. Using an independent study for validation, 27% of the TAG exercise response was predicted by a molecular signature based on the baseline expression levels of 11 genes; this procedure was accomplished using a multivariate variable selection based on a genetic algorithm method that seeks to identify the best subset of genes for maximising the fitness of the regression model.…”

“…Importantly, they concluded that the genes most important in modifying changes in fasting TAG in response to regular exercise are not the same as the loci controlling variation in population TAG concentrations. Sarzynski et al (8) explain that, regardless of the "biological plausibility of the identified variants, identifying predictors of favourable and unfavourable TAG response to regular exercise could help to optimise inclusion of postprandial measures to overcome the limitation of previous studies that have relied on the less dynamic fasting plasma concentrations of the traditional risk factors listed above. The study was designed so that it was possible to separate the acute response, from the last exercise session, and the chronic two week training adaptation by including pre-exercise, 1-day postexercise and 3-day post-exercise measurements; however, a non-exercise matched control group was not included, but the authors suggested this is consistent with the HIIT literature.…”

Metabolism and Exercise During Youth

“…Sarzynski et al (8) used a combination of genomic and transcriptomic profiling techniques to identify genes and single nucleotide polymorphisms (SNPs), also known as sequence variants or allelic variants, associated with exercise training-induced changes in fasting plasma TAG concentration in a sub-sample of 49 white adults from the HERITAGE Family Study. A primary driver behind this research was concern that exercise, normally considered to be "safe" for most healthy individuals, led to an adverse metabolic outcome; in this case, an increase in TAG of at least two technical errors greater than no change (≥0.42 mmol/L) in a mixed race/sex sample of 1,687 exercisers (2).…”

“…Nevertheless, the possibility that this research might transfer to acute exercise postprandial lipaemia measures in young people was an exciting prospect and the main reason why this publication is featured here. Sarzynski et al (8) found that numerous genes and SNPs contributed to the genetic and transcriptomic variation in the chronic exercise training response of TAG (i.e., white participants' TAG response to exercise training in the HERITAGE Family Study. Using an independent study for validation, 27% of the TAG exercise response was predicted by a molecular signature based on the baseline expression levels of 11 genes; this procedure was accomplished using a multivariate variable selection based on a genetic algorithm method that seeks to identify the best subset of genes for maximising the fitness of the regression model.…”