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- de Jong, Jasper M. A., et al.
(författare)
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Human brown adipose tissue is phenocopied by classical brown adipose tissue in physiologically humanized mice
- 2019
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Ingår i: Nature Metabolism. - : Springer Science and Business Media LLC. - 2522-5812. ; 1:8, s. 830-843
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Tidskriftsartikel (refereegranskat)abstract
- Human and rodent brown adipose tissues (BAT) appear morphologically and molecularly different. Here we compare human BAT with both classical brown and brite/beige adipose tissues of 'physiologically humanized' mice: middle-aged mice living under conditions approaching human thermal and nutritional conditions, that is, prolonged exposure to thermoneutral temperature (approximately 30 degrees C) and to an energy-rich (high-fat, high-sugar) diet. We find that the morphological, cellular and molecular characteristics (both marker and adipose-selective gene expression) of classical brown fat, but not of brite/beige fat, of these physiologically humanized mice are notably similar to human BAT. We also demonstrate, both in silico and experimentally, that in physiologically humanized mice only classical BAT possesses a high thermogenic potential. These observations suggest that classical rodent BAT is the tissue of choice for translational studies aimed at recruiting human BAT to counteract the development of obesity and its comorbidities.
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| 2. |
- Timmons, James A., et al.
(författare)
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Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans
- 2010
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Ingår i: Journal of applied physiology. - : American Physiological Society. - 8750-7587 .- 1522-1601. ; 108:6, s. 1487-1496
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Tidskriftsartikel (refereegranskat)abstract
- Timmons JA, Knudsen S, Rankinen T, Koch LG, Sarzynski M, Jensen T, Keller P, Scheele C, Vollaard NB, Nielsen S, Akerstrom T, MacDougald OA, Jansson E, Greenhaff PL, Tarnopolsky MA, van Loon LJ, Pedersen BK, Sundberg CJ, Wahlestedt C, Britton SL, Bouchard C. Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans. J Appl Physiol 108: 1487-1496, 2010. First published February 4, 2010; doi:10.1152/japplphysiol.01295.2009.-A low maximal oxygen consumption ((V) over dotO(2max)) is a strong risk factor for premature mortality. Supervised endurance exercise training increases (V) over dotO(2max) 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 (V) over dotO(2max) training response. We then hypothesized that the classifier genes would harbor DNA variants that contributed to the heterogeneous (V) over dotO(2max) 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 (V) over dotO(2max) (""predictor"" genes). The HERITAGE Family Study (n = 473) was used for genotyping. We discovered a 29-RNA signature that predicted (V) over dotO(2max) training response on a continuous scale; these genes contained similar to 6 new single-nucleotide polymorphisms associated with gains in (V) over dotO(2max) 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 (V) over dotO(2max), corresponding to similar to 50% of the estimated genetic variance for (V) over dotO(2max). In conclusion, combining RNA profiling with single-gene DNA marker association analysis yields a strongly validated molecular predictor with meaningful explanatory power. (V) over dotO(2max) responses to endurance training can be predicted by measuring a similar to 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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