Ghrelin, PAil and Their Associations with Adipokine

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This submission responds to the RFA for an Exploratory NCMHD Center for Excellence (RFA-MD-08- 0049). We propose to examine the distributions of two biomarkers in a large, ongoing, well-characterized longitudinal study of African Americans, the Jackson Heart Study, and to characterize their association with a number of known risk factors for metabolic syndrome (MetS), type 2 diabetes mellitus (T2D) and cardiovascular disease (CVD), with a long-term aim of identifying more precisely the plasma levels that would alert a primary care provider to those who are most likely to benefit from treatment. We will assess the relevance of family history by estimating familial correlations and the heritability. In addition to examining plasma levels of ghrelin and PAI-1, we wish to examine them in the context of other risk factors, including obesity and genetic risk factors in GWAS analyses. Specifically, this study aims to describe the distribution of plasma levels of ghrelin and PAI-1 and their heritability in the Jackson Heart Study (JHS) cohort, examine environmental and genetic correlations between plasma ghrelin and PAI-1 levels and factors predictive of heart disease in the JHS cohort, and find polymorphisms and haplotypes associated with plasma ghrelin and PAI-1 levels in the JHS. Because ghrelin plays a significant role in energy homeostasis via the hypothalamus by controlling food intake, and is a powerful orexigenic and adipogenic agent in human physiology, it is important to study this biomarker in a cohort at the epicenter of the obesity epidemic. Ghrelin's effect on metabolism is thought to be the opposite of leptin's, and these two peptide hormones may act synergistically to increase insulin resistance and metabolic abnormalities \ Leptin was assayed in the JHS exam 1. We propose to assay both ghrelin and leptin in exam 3, and to assay ghrelin in exam 1. Analysis of exam 1 biomarker data in conjunction with measures of obesity in exam 3, such as BMI, waist circumference, hip to waist ratio, as well as imaging data providing measures of visceral and subcutaneous adiposity and their ratio, will allow us to determine if the biomarkers play a predictive role in the development of obesity.