IntroductionRegular physical activity (PA) can reduce the risk of developing type 2 diabetes, but adherence to time-orientated (150 min week−1 or more) PA guidelines is very poor. A practical and time-efficient PA regime that was equally efficacious at controlling risk factors for cardio-metabolic disease is one solution to this problem. Herein, we evaluate a new time-efficient and genuinely practical high-intensity interval training (HIT) protocol in men and women with pre-existing risk factors for type 2 diabetes.Materials and methodsOne hundred eighty-nine sedentary women (n = 101) and men (n = 88) with impaired glucose tolerance and/or a body mass index >27 kg m−2 [mean (range) age: 36 (18–53) years] participated in this multi-center study. Each completed a fully supervised 6-week HIT protocol at work-loads equivalent to ~100 or ~125% V˙O2 max. Change in V˙O2 max was used to monitor protocol efficacy, while Actiheart™ monitors were used to determine PA during four, weeklong, periods. Mean arterial (blood) pressure (MAP) and fasting insulin resistance [homeostatic model assessment (HOMA)-IR] represent key health biomarker outcomes.ResultsThe higher intensity bouts (~125% V˙O2 max) used during a 5-by-1 min HIT protocol resulted in a robust increase in V˙O2 max (136 participants, +10.0%, p < 0.001; large size effect). 5-by-1 HIT reduced MAP (~3%; p < 0.001) and HOMA-IR (~16%; p < 0.01). Physiological responses were similar in men and women while a sizeable proportion of the training-induced changes in V˙O2 max, MAP, and HOMA-IR was retained 3 weeks after cessation of training. The supervised HIT sessions accounted for the entire quantifiable increase in PA, and this equated to 400 metabolic equivalent (MET) min week−1. Meta-analysis indicated that 5-by-1 HIT matched the efficacy and variability of a time-consuming 30-week PA program on V˙O2 max, MAP, and HOMA-IR.ConclusionWith a total time-commitment of <15 min per session and reliance on a practical ergometer protocol, 5-by-1 HIT offers a new solution to modulate cardio-metabolic risk factors in adults with pre-existing risk factors for type 2 diabetes while approximately meeting the MET min week−1 PA guidelines. Long-term randomized controlled studies will be required to quantify the ability for 5-by-1 HIT to reduce the incidence of type 2 diabetes, while strategies are required to harmonize the adaptations to exercise across individuals.

Genome-wide association studies (GWAS), relying on hundreds of thousands of individuals, have revealed >200 genomic loci linked to metabolic disease (MD). Loss of insulin sensitivity (IS) is a key component of MD and we hypothesized that discovery of a robust IS transcriptome would help reveal the underlying genomic structure of MD. Using 1,012 human skeletal muscle samples, detailed physiology and a tissue-optimized approach for the quantification of coding (>18,000) and non-coding (>15,000) RNA (ncRNA), we identified 332 fasting IS-related genes (CORE-IS). Over 200 had a proven role in the biochemistry of insulin and/or metabolism or were located at GWAS MD loci. Over 50% of the CORE-IS genes responded to clinical treatment; 16 quantitatively tracking changes in IS across four independent studies (P = 0.0000053: negatively: AGL, G0S2, KPNA2, PGM2, RND3 and TSPAN9 and positively: ALDH6A1, DHTKD1, ECHDC3, MCCC1, OARD1, PCYT2, PRRX1, SGCG, SLC43A1 and SMIM8). A network of ncRNA positively related to IS and interacted with RNA coding for viral response proteins (P < 1 × 10−48), while reduced amino acid catabolic gene expression occurred without a change in expression of oxidative-phosphorylation genes. We illustrate that combining in-depth physiological phenotyping with robust RNA profiling methods, identifies molecular networks which are highly consistent with the genetics and biochemistry of human metabolic disease.

Mutations in PINK1 cause the mitochondrial-related neurodegenerative disease Parkinson's. Here we investigate whether obesity, type 2 diabetes, or inactivity alters transcription from the PINK1 locus. We utilized a cDNA-array and quantitative real-time PCR for gene expression analysis of muscle from healthy volunteers following physical inactivity, and muscle and adipose tissue from nonobese or obese subjects with normal glucose tolerance or type 2 diabetes. Functional studies of PINK1 were performed utilizing RNA interference in cell culture models. Following inactivity, the PINK1 locus had an opposing regulation pattern (PINK1 was down-regulated while natural antisense PINK1 was up-regulated). In type 2 diabetes skeletal muscle, all transcripts from the PINK1 locus were suppressed and gene expression correlated with diabetes status. RNA interference of PINK1 in human neuronal cell lines impaired basal glucose uptake. In adipose tissue, mitochondrial gene expression correlated with PINK1 expression although remained unaltered following siRNA knockdown of Pink1 in primary cultures of brown preadipocytes. In conclusion, regulation of the PINK1 locus, previously linked to neurodegenerative disease, is altered in obesity, type 2 diabetes and inactivity, while the combination of RNAi experiments and clinical data suggests a role for PINK1 in cell energetics rather than in mitochondrial biogenesis.

DNA microarrays and RNAseq are complementary methods for studying RNA molecules. Current computational methods to determine alternative exon usage (AEU) using such data require impractical visual inspection and still yield high false-positive rates. Integrated Gene and Exon Model of Splicing (iGEMS) adapts a gene-level residuals model with a gene size adjusted false discovery rate and exon-level analysis to circumvent these limitations. iGEMS was applied to two new DNA microarray datasets, including the high coverage Human Transcriptome Arrays 2.0 and performance was validated using RT-qPCR. First, AEU was studied in adipocytes treated with (n = 9) or without (n = 8) the anti-diabetes drug, rosiglitazone. iGEMS identified 555 genes with AEU, and robust verification by RT-qPCR (∼90%). Second, in a three-way human tissue comparison (muscle, adipose and blood, n = 41) iGEMS identified 4421 genes with at least one AEU event, with excellent RT-qPCR verification (95%, n = 22). Importantly, iGEMS identified a variety of AEU events, including 3′UTR extension, as well as exon inclusion/exclusion impacting on protein kinase and extracellular matrix domains. In conclusion, iGEMS is a robust method for identification of AEU while the variety of exon usage between human tissues is 5–10 times more prevalent than reported by the Genotype-Tissue Expression consortium using RNA sequencing.

Larger and more heterogeneous studies are required for specifically evaluating NIRS performance in detecting intracranial lesions requiring emergency evacuation.