Type II diabetes mellitus (T2DM) is a serious chronic disease that greatly impacts quality-of-life, morbidity and mortality of affected individuals. Its prevalence continues to rise rapidly in the US and worldwide, and the costs to patients and society as a whole are astronomic. We propose to study the disorder via metabolomic profiling. Metabolites occur as part of the many metabolic processes in a living being. The existence and quantity of individual metabolites can be indicative of health and disease, and specific chemical compounds are used as biomarkers for a variety of human conditions. Modern techniques make it now possible to identify and quantify many chemical compounds simultaneous in a small sample volume. We propose here to use two-dimensional gas chromatography and time-of-flight mass spectrometry (GCxGC-TOFMS) to generate metabolomic profiles of blood plasma. This novel, state-of-the-art approach detects molecules in the size range of ~50-1000 u (from highly volatile small molecules to amino acids, small sugars, small lipids, and small peptides), with much increased sensitivity over traditional instrumentation, allowing metabolite detection in the mid to high part-per- trillion range. Specifically, metabolomic profiles will be generated on blood plasma samples (collected at 2 time points 15-20 years apart) from 1,500 participants in the San Antonio Family Study (SAFS), a long-running study investigating genetic risk for complex diseases and associated quantitative risk factors in Mexican Americans families. We will then identify genetic factors influencing the quantitative levels of individual metabolites, taking advantage of the existing SNP genotype data, whole-genome sequence (WGS) data, and lymphocyte gene expression profiles. Novel statistical approaches will be used to identify rare variants of strong effect. Retrospective and prospective analyses will be used to identify biomarkers for T2DM and related quantitative traits. The long follow-up period allows for detection of very early biomarkers, before any sign of disease (including by any existing diagnostic markers) and commencement of prevention strategies or treatment. Putative T2DM biomarkers will be replicated in 1,500 participants in the Strong Heart Family Study. Laboratory-based assays of functionality will be conducted on the most interesting candidate genetic variants found to influence metabolite levels. This is a highly innovative study to investigate th genetic regulation of metabolite levels, and to identify metabolomic signatures of diabetes. The study is feasible because it leverages the unique resources of the SAFS. The investigative team comprises experts in metabolomics, molecular biology, statistical genetics, and diabetes. The proposed study has the potential for novel discoveries related to T2DM risk in the fast growing Mexican American minority population.

Public Health Relevance

Type II diabetes mellitus (T2DM) is a serious chronic disease that greatly impacts quality-of-life, morbidity and mortality of affected individuals. The frequenc of the disease keeps increasing in the US and worldwide, and it affects individuals at an ever-younger age. The costs to patients and society as a whole are astronomic. This study proposes to conduct a metabolomic screen on blood plasma to identify metabolic biomarkers of the disease, and to identify genetic variants influencing the concentration of individual metabolites. Findings from the study have the potential to improve disease prognosis via identification of early-stage biomarkers, illuminate the etiological and pathological disease processes, and to identify genetic risk factors for diabetes, which could ultimately lead to the development of bette drugs and strategies for prevention or treatment.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Project (R01)
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Special Emphasis Panel (ZRG1)
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Castle, Arthur
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Texas Biomedical Research Institute
San Antonio
United States
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Blondell, Lucy; Blackburn, August; Kos, Mark Z et al. (2018) Contribution of Inbred Singletons to Variance Component Estimation of Heritability and Linkage. Hum Hered 83:92-99
Blackburn, August; Almeida, Marcio; Dean, Angela et al. (2015) Effects of copy number variable regions on local gene expression in white blood cells of Mexican Americans. Eur J Hum Genet 23:1229-35