Using Pre-existing Microarray Datasets to Increase Experimental Power: Application to Insulin Resistance

Although they have become a widely used experimental technique for identifying differentially expressed (DE) genes, DNA microarrays are notorious for generating noisy data. A common strategy for mitigating the effects of noise is to perform many experimental replicates. This approach is often costly and sometimes impossible given limited resources; thus, analytical methods are needed which increase accuracy at no additional cost. One inexpensive source of microarray replicates comes from prior work: to date, data from hundreds of thousands of microarray experiments are in the public domain. Although these data assay a wide range of conditions, they cannot be used directly to inform any particular experiment and are thus ignored by most DE gene methods. We present the SVD Augmented Gene expression Analysis Tool (SAGAT), a mathematically principled, data-driven approach for identifying DE genes. SAGAT increases the power of a microarray experiment by using observed coexpression relationships from publicly available microarray datasets to reduce uncertainty in individual genes' expression measurements. We tested the method on three well-replicated human microarray datasets and demonstrate that use of SAGAT increased effective sample sizes by as many as 2.72 arrays. We applied SAGAT to unpublished data from a microarray study investigating transcriptional responses to insulin resistance, resulting in a 50% increase in the number of significant genes detected. We evaluated 11 (58%) of these genes experimentally using qPCR, confirming the directions of expression change for all 11 and statistical significance for three. Use of SAGAT revealed coherent biological changes in three pathways: inflammation, differentiation, and fatty acid synthesis, furthering our molecular understanding of a type 2 diabetes risk factor. We envision SAGAT as a means to maximize the potential for biological discovery from subtle transcriptional responses, and we provide it as a freely available software package that is immediately applicable to any human microarray study

Basal lipolysis, not the degree of insulin resistance, differentiates large from small isolated adipocytes in high-fat fed mice

AIMS/HYPOTHESIS: Adipocytes in obesity are characterised by increased cell size and insulin resistance compared with adipocytes isolated from lean patients. However, it is not clear at present whether hypertrophy actually does drive adipocyte insulin resistance. Thus, the aim of the present study was to metabolically characterise small and large adipocytes isolated from epididymal fat pads of mice fed a high-fat diet (HFD). METHODS: C57BL/6J mice were fed normal chow or HFD for 8 weeks. Adipocytes from epididymal fat pads were isolated by collagenase digestion and, in HFD-fed mice, separated into two fractions according to their size by filtration through a nylon mesh. Viability was assessed by lactate dehydrogenase and 3-(4,5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium assays. Basal and insulin-stimulated d-[U-(14)C]glucose incorporation and lipolysis were measured. Protein levels and mRNA expression were determined by western blot and real-time RT-PCR, respectively. RESULTS: Insulin-stimulated D: -[U-(14)C]glucose incorporation into adipocytes isolated from HFD-fed mice was reduced by 50% compared with adipocytes from chow-fed mice. However, it was similar between small (average diameter 60.9 +/- 3.1 mum) and large (average diameter 83.0 +/- 6.6 mum) adipocytes. Similarly, insulin-stimulated phosphorylation of protein kinase B and AS160 were reduced to the same extent in small and large adipocytes isolated from HFD-mice. In addition, insulin failed to inhibit lipolysis in both adipocyte fractions, whereas it decreased lipolysis by 30% in adipocytes of chow-fed mice. In contrast, large and small adipocytes differed in basal lipolysis rate, which was twofold higher in the larger cells. The latter finding was associated with higher mRNA expression levels of Atgl (also known as Pnpla2) and Hsl (also known as Lipe) in larger adipocytes. Viability was not different between small and large adipocytes. CONCLUSIONS/INTERPRETATION: Rate of basal lipolysis but not insulin responsiveness is different between small and large adipocytes isolated from epididymal fat pads of HFD-fed mice