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Remodeling of the extracellular matrix is a key component of the metabolic adaptations of adipose tissue in response to dietary and physiological challenges. Disruption of its integrity is a well-known aspect of adipose tissue dysfunction, for instance, during aging and obesity. Adipocyte regeneration from a tissue-resident pool of mesenchymal stem cells is part of normal tissue homeostasis. Among the pathophysiological consequences of adipogenic stem cell aging, characteristic changes in the secretory phenotype, which includes matrix-modifying proteins, have been described. Here, we show that the expression of the matricellular protein periostin, a component of the extracellular matrix produced and secreted by adipose tissue-resident interstitial cells, is markedly decreased in aged brown and white adipose tissue depots. Using a mouse model, we demonstrate that the adaptation of adipose tissue to adrenergic stimulation and high-fat diet feeding is impaired in animals with systemic ablation of the gene encoding for periostin. Our data suggest that loss of periostin attenuates lipid metabolism in adipose tissue, thus recapitulating one aspect of age-related metabolic dysfunction. In human white adipose tissue, periostin expression showed an unexpected positive correlation with age of study participants. This correlation, however, was no longer evident after adjusting for BMI or plasma lipid and liver function biomarkers. These findings taken together suggest that age-related alterations of the adipose tissue extracellular matrix may contribute to the development of metabolic disease by negatively affecting nutrient homeostasis.
To explore the genetic determinants of obesity and Type 2 diabetes (T2D), the German Center for Diabetes Research (DZD) conducted crossbreedings of the obese and diabetes-prone New Zealand Obese mouse strain with four different lean strains (B6, DBA, C3H, 129P2) that vary in their susceptibility to develop T2D. Genome-wide linkage analyses localized more than 290 quantitative trait loci (QTL) for obesity, 190 QTL for diabetes-related traits and 100 QTL for plasma metabolites in the out-cross populations. A computational framework was developed that allowed to refine critical regions and to nominate a small number of candidate genes by integrating reciprocal haplotype mapping and transcriptome data. The efficiency of the complex procedure was demonstrated for one obesity QTL. The genomic interval of 35 Mb with 502 annotated candidate genes was narrowed down to six candidates. Accordingly, congenic mice retained the obesity phenotype owing to an interval that contains three of the six candidate genes. Among these the phospholipase PLA2G4A exhibited an elevated expression in adipose tissue of obese human subjects and is therefore a critical regulator of the obesity locus. Together, our broad and complex approach demonstrates that combined- and comparative-cross analysis exhibits improved mapping resolution and represents a valid tool for the identification of disease genes.