The recent insight that brown adipocytes and muscle cells share a common origin and in this respect are distinct from white adipocytes has spurred questions concerning the origin and molecular characteristics of the UCP1-expressing cells observed in classic white adipose tissue depots under certain physiological or pharmacological conditions. Examining precursors from the purest white adipose tissue depot (epididymal), we report here that chronic treatment with the peroxisome proliferator-activated receptor ␥ agonist rosiglitazone promotes not only the expression of PGC-1␣ and mitochondriogenesis in these cells but also a norepinephrine-augmentable UCP1 gene expression in a significant subset of the cells, providing these cells with a genuine thermogenic capacity. However, although functional thermogenic genes are expressed, the cells are devoid of transcripts for the novel transcription factors now associated with classic brown adipocytes (Zic1, Lhx8, Meox2, and characteristically PRDM16) or for myocyte-associated genes (myogenin and myomirs (muscle-specific microRNAs)) and retain white fat characteristics such as Hoxc9 expression. Co-culture experiments verify that the UCP1-expressing cells are not proliferating classic brown adipocytes (adipomyocytes), and these cells therefore constitute a subset of adipocytes ("brite" adipocytes) with a developmental origin and molecular characteristics distinguishing them as a separate class of cells.

Attainment of a brown adipocyte cell phenotype in white adipocytes, with their abundant mitochondria and increased energy expenditure potential, is a legitimate strategy for combating obesity. The unique transcriptional regulators of the primary brown adipocyte phenotype are unknown, limiting our ability to promote brown adipogenesis over white. In the present work, we used microarray analysis strategies to study primary preadipocytes, and we made the striking discovery that brown preadipocytes demonstrate a myogenic transcriptional signature, whereas both brown and white primary preadipocytes demonstrate signatures distinct from those found in immortalized adipogenic models. We found a plausible SIRT1-related transcriptional signature during brown adipocyte differentiation that may contribute to silencing the myogenic signature. In contrast to brown preadipocytes or skeletal muscle cells, white preadipocytes express Tcf21, a transcription factor that has been shown to suppress myogenesis and nuclear receptor activity. In addition, we identified a number of developmental genes that are differentially expressed between brown and white preadipocytes and that have recently been implicated in human obesity. The interlinkage between the myocyte and the brown preadipocyte confirms the distinct origin for brown versus white adipose tissue and also represents a plausible explanation as to why brown adipocytes ultimately specialize in lipid catabolism rather than storage, much like oxidative skeletal muscle tissue. microarray ͉ myocyte ͉ principal component analysis ͉ differentiation ͉ transcriptome

Mainly from cell culture studies, a series of genes that have been suggested to be characteristic of different types of adipocytes have been identified. Here we have examined gene expression patterns in nine defined adipose depots: interscapular BAT, cervical BAT, axillary BAT, mediastinic BAT, cardiac WAT, inguinal WAT, retroperitoneal WAT, mesenteric WAT, and epididymal WAT. We found that each depot displayed a distinct gene expression fingerprint but that three major types of depots were identifiable: the brown, the brite, and the white. Although differences in gene expression pattern were generally quantitative, some gene markers showed, even in vivo, remarkable depot specificities: Zic1 for the classical BAT depots, Hoxc9 for the brite depots, Hoxc8 for the brite and white in contrast to the brown, and Tcf21 for the white depots. The effect of physiologically induced recruitment of thermogenic function (cold acclimation) on the expression pattern of the genes was quantified; in general, the depot pattern dominated over the recruitment effects. The significance of the gene expression patterns for classifying the depots and for understanding the developmental background of the depots is discussed, as are the possible regulatory functions of the genes.

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 hypothesized that the classifier genes would harbor DNA variants that contributed to the heterogeneous VO2max response. Two independent preintervention RNA expression data sets were generated (n=41 gene chips) from subjects that underwent supervised endurance training: one identified and 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; these genes contained approximately 6 new single-nucleotide polymorphisms associated with gains in VO2max in the HERITAGE Family Study. Three of four novel candidate genes from the HERITAGE Family Study were confirmed as RNA predictor genes (i.e., "reciprocal" RNA validation of a quantitative trait locus 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 preset by genetic variation. Regression analysis yielded a model where 11 single-nucleotide polymorphisms explained 23% of the variance in gains in VO2max, corresponding to approximately 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 approximately 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.

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MicroRNAs (miRNA), small noncoding RNA molecules, may regulate protein synthesis, while resistance exercise training (RT) is an efficient strategy for stimulating muscle protein synthesis in vivo. However, RT increases muscle mass, with a very wide range of effectiveness in humans. We therefore determined the expression level of 21 abundant miRNAs to determine whether variation in these miRNAs was able to explain the variation in RT-induced gains in muscle mass. Vastus lateralis biopsies were obtained from the top and bottom ∼20% of responders from 56 young men who undertook a 5 day/wk RT program for 12 wk. Training-induced muscle mass gain was determined by dual-energy X-ray absorptiometry, and fiber size was evaluated by histochemistry. The expression level of each miRNA was quantified using TaqMan-based quantitative PCR, with the analysis carried out in a blinded manner. Gene ontology and target gene profiling were used to predict the potential biological implications. Of the 21 mature miRNAs examined, 17 were stable during RT in both groups. However, miR-378, miR-29a, miR-26a, and miR-451 were differentially expressed between low and high responders. miR-378, miR-29a, and miR-26a were downregulated in low responders and unchanged in high responders, while miR-451 was upregulated only in low responders. Interestingly, the training-induced change in miR-378 abundance was positively correlated with muscle mass gains in vivo. Gene ontology analysis of the target gene list of miR-378, miR-29a, miR-26a, and miR-451, from the weighted cumulative context ranking methodology, indicated that miRNA changes in the low responders may be compensatory, reflecting a failure to "activate" growth and remodeling genes. We report, for the first time, that RT-induced hypertrophy in human skeletal muscle is associated with selected changes in miRNA abundance. Our analysis indicates that miRNAs may play a role in the phenotypic change and pronounced intergroup variation in the RT response.

BackgroundTraditional high volume aerobic exercise training reduces cardiovascular and metabolic disease risk but involves a substantial time commitment. Extremely low volume high-intensity interval training (HIT) has recently been demonstrated to produce improvements to aerobic function, but it is unknown whether HIT has the capacity to improve insulin action and hence glycemic control.MethodsSixteen young men (age: 21 ± 2 y; BMI: 23.7 ± 3.1 kg·m-2; VO2peak: 48 ± 9 ml·kg-1·min-1) performed 2 weeks of supervised HIT comprising of a total of 15 min of exercise (6 sessions; 4–6 × 30-s cycle sprints per session). Aerobic performance (250-kJ self-paced cycling time trial), and glucose, insulin and NEFA responses to a 75-g oral glucose load (oral glucose tolerance test; OGTT) were determined before and after training.ResultsFollowing 2 weeks of HIT, the area under the plasma glucose, insulin and NEFA concentration-time curves were all reduced (12%, 37%, 26% respectively, all P < 0.001). Fasting plasma insulin and glucose concentrations remained unchanged, but there was a tendency for reduced fasting plasma NEFA concentrations post-training (pre: 350 ± 36 v post: 290 ± 39 μmol·l-1, P = 0.058). Insulin sensitivity, as measured by the Cederholm index, was improved by 23% (P < 0.01), while aerobic cycling performance improved by ~6% (P < 0.01).ConclusionThe efficacy of a high intensity exercise protocol, involving only ~250 kcal of work each week, to substantially improve insulin action in young sedentary subjects is remarkable. This novel time-efficient training paradigm can be used as a strategy to reduce metabolic risk factors in young and middle aged sedentary populations who otherwise would not adhere to time consuming traditional aerobic exercise regimes.

BackgroundSkeletal muscle insulin resistance (IR) is considered a critical component of type II diabetes, yet to date IR has evaded characterization at the global gene expression level in humans. MicroRNAs (miRNAs) are considered fine-scale rheostats of protein-coding gene product abundance. The relative importance and mode of action of miRNAs in human complex diseases remains to be fully elucidated. We produce a global map of coding and non-coding RNAs in human muscle IR with the aim of identifying novel disease biomarkers.MethodsWe profiled >47,000 mRNA sequences and >500 human miRNAs using gene-chips and 118 subjects (n = 71 patients versus n = 47 controls). A tissue-specific gene-ranking system was developed to stratify thousands of miRNA target-genes, removing false positives, yielding a weighted inhibitor score, which integrated the net impact of both up- and down-regulated miRNAs. Both informatic and protein detection validation was used to verify the predictions of in vivo changes.ResultsThe muscle mRNA transcriptome is invariant with respect to insulin or glucose homeostasis. In contrast, a third of miRNAs detected in muscle were altered in disease (n = 62), many changing prior to the onset of clinical diabetes. The novel ranking metric identified six canonical pathways with proven links to metabolic disease while the control data demonstrated no enrichment. The Benjamini-Hochberg adjusted Gene Ontology profile of the highest ranked targets was metabolic (P < 7.4 × 10-8), post-translational modification (P < 9.7 × 10-5) and developmental (P < 1.3 × 10-6) processes. Protein profiling of six development-related genes validated the predictions. Brain-derived neurotrophic factor protein was detectable only in muscle satellite cells and was increased in diabetes patients compared with controls, consistent with the observation that global miRNA changes were opposite from those found during myogenic differentiation.ConclusionsWe provide evidence that IR in humans may be related to coordinated changes in multiple microRNAs, which act to target relevant signaling pathways. It would appear that miRNAs can produce marked changes in target protein abundance in vivo by working in a combinatorial manner. Thus, miRNA detection represents a new molecular biomarker strategy for insulin resistance, where micrograms of patient material is needed to monitor efficacy during drug or life-style interventions.