This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Objective: To generate early warning diagnostics for increased metabolic syndrome risk that will facilitate intervention andpreventative treatment, and provide insights into the mechanistic basis of the disease. Metabolic syndrome alters serum factors that influence metabolism and inflammation, including lipoproteins, fatty acids and adipokines. We will use the rhesus macaque model to determine whether levels of these factors in the pre-diseased state can be predictive of future disease development. This study will test the hypothesis that lipoprotein, fatty acid, and adipokine pro-inflammatory profiles, in combination, constitute an early predictor of metabolic syndrome development.
Specific Aim1 : To determine the lipoprotein particle size distribution profile in serum from healthy controls and impaired animals at the time of diagnosis and 2 years before disease onset.
Specific Aim 2 : To quantify fatty acid concentration and composition in serum from healthy and impaired animals before and after disease onset.
Specific Aim 3 : To determine levels of adipokines and pro-inflammatory factors in serum from healthy and impaired animals before and after disease onset. This study is novel in that it explores the use of serum adipokine and lipid profiles in combination as a predictive marker of increased risk for metabolic syndrome. The rationale behind this study is that metabolism and inflammation are linked through serum factors common to both processes. Because these elements are likely responsible for increased risk for metabolic syndrome, novel therapeutic strategies may be elucidated upon identification of the key factors. The project is significant in that it has the potential to provide a critical early diagnostic that would dramatically improve outcomes for obese pediatric patients that are at risk of metabolic syndrome development. The study has only begun and as such data have yet to be generated.
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