Molecular Profiling of Diabetes and its Complications

在目前的项目中，正在使用经典流行病学和遗传流行病学技术来确定2型糖尿病的决定因素、其危险因素及其并发症。其他项目（DK069028-24，糖尿病和肥胖遗传流行病学和DK069094-06，糖尿病并发症遗传流行病学）评估遗传因素的影响；目前的研究主要集中在遗传因素下游的分子过程，如基因转录、蛋白质表达和细胞代谢。正在对凤凰城2型糖尿病高危人群进行纵向研究。收集样本用于基因组DNA的研究，这些样本也适用于DNA甲基化和组蛋白修饰等表观遗传因素的研究。收集的样品适合RNA提取和大规模蛋白质水平和代谢组学研究。收集有关家庭成员的资料，以便纳入以家庭为基础的分析。

In the current project, the techniques of classic epidemiology and of genetic epidemiology are being used to identify determinants of type 2 diabetes, its risk factors and its complications. The effects of genetic factors are assessed in other projects (DK069028-24, Genetic Epidemiology of Diabetes and Obesity and DK069094-06, Genetic Epidemiology of Diabetic Complications); the present study focuses on molecular processes that are downstream of genetic factors, such as gene transcription, protein expression and cellular metabolism. Longitudinal studies are being conducted in individuals at high risk for type 2 diabetes in urban Phoenix. Samples are collected for studies of genomic DNA, and these samples are also suitable for studies of epigenetic factors, such as DNA methylation and histone modification. Samples are collected that suitable for RNA extraction and for large scale studies of protein levels and metabolomics. Information on family membership is collected for inclusion in family-based analyses. Recent analyses of genome-wide transcription in skeletal muscle tissue have shown that a small number of transcripts have a clearly bimodal frequency distribution; the vast majority of these are accounted for by the effect of a genetic polymorphism in close proximity the region encoding for the transcript. Analyses using empirical identity by descent estimates from dense genotypic data suggest that a large amount of the heritability in gene expression is due to the action of variants within or near the region coding for the transcipt. Large scale genome-wide transcription profiles are also being measured in peripheral blood samples in collaboration with investigators from Texas Biomedical Research Institute. Initial analyses have shown a large number of transcripts associated with age, sex and markers of inflammation (C-reactive protein), and these data are being compared with those from other cohorts in a collaborative meta-analysis. Additional analyses of the relationship of genetic polymorphisms associated with platelet count with whole blood transcription have been performed. Studies of whole blood transcripts suggest that the effect of an established type 2 diabetes variant in SLC16A11 is mediated by expression of the nearby RNASEK. Analyses of the relationship of transcription in peripheral blood samples with diabetes, obesity and related factors are currently in process, as is the assessment of heritability and parent-of-origin effects. Recruitment of additional individuals and families and longitudinal follow-up are also ongoing.