Obesity and its associated disorders - dyslipidemia, hypertension, and diabetes - are major public health problems; the """"""""obesity epidemic"""""""" has caused a """"""""diabetes epidemic"""""""", resulting in substantial morbidity and mortality. Obesity-related insulin resistance is a key pathophysiologic mediator that can be reduced by lifestyle change or use of medications, but we must first identify the problem. However, our ability to recognize insulin resistance is limited because current criteria such as the """"""""metabolic syndrome"""""""" lack specificity and multiethnic applicability. Moreover, although insulin resistance is independently associated with risk of cardiovascular disease (CVD), the """"""""metabolic syndrome"""""""" is not. Insulin resistance can be measured in metabolic ward settings, but the procedures involved are invasive, inconvenient, and expensive. Thus, to enable appropriate preventive care, it would be of enormous importance to develop a measure of insulin resistance which could be used in routine clinical settings. Recent developments in proteomics suggest that new technologies are sufficiently robust to identify circulating biomarkers of insulin resistance in an appropriate model. Accordingly, we propose a proteomics analysis of insulin resistance in patients whose insulin resistance is reduced by weight loss. In a robust design that uses patients as their own controls, we will examine pairs of plasma samples during weight loss under R03 DK-067167, """"""""Insulin Resistance in Severely Obese Patients"""""""".
Aims : 1) To use frequently-sampled intravenous glucose tolerance tests (FSIGT) and biomarkers of oxidative stress and inflammation to metabolically phenotype weight loss-induced reduction in insulin resistance over 6 months in patients who undergo Roux-en-Y gastric bypass and patients who undergo very low calorie liquid formula diets. 2) To use quantitative mass spectrometry based on LC-MS/MS [depletion - 1Dgel - RPLC - MS/MS] to identify signature proteins associated with differences in insulin resistance in plasma pairs from obese patients who lose weight, allowing recognition of indicators of insulin resistance per se that are independent of the mechanism of weight loss, and that may help point to particularly important sets of regulatory mediators from the expanded adipose organ. In combination, this strategy should permit us to identify new proteomic biomarkers of insulin resistance, and obtain critical preliminary data to buttress an expanded hypothesis-driven R01 proposal. Since insulin resistance confers substantial morbidity and mortality, it needs to be the focus of both patient care and research. However, not all obese individuals are insulin-resistant, and not all insulin-resistant individuals are obese. Accordingly, both clinicians and investigators need a convenient, effective way to assess insulin resistance. Our proposed proteomics analyses are aimed to fill this critical gap in knowledge. ? ? ? ?
