Type 2 diabetes is a major public health concern. Diabetes currently affects 25.8 million people in the US alone, 90-95% of all cases are type 2 and it disproportionately affects ethnic minorities in the US, including Mexican Americans. There are many microvascular and macrovascular complications related to diabetes, including a significantly increased risk of heart disease and stroke, blindness, kidney failure and kidney disease, neuropathy, and retinopathy. Several risk factors predispose individuals to the development of this disease including demographic characteristics like sex, age and ethnicity; and behavioral and lifestyle-related modifications. In addition, metabolic determinants such as impaired glucose tolerance and insulin resistance increase the risk of an individual progressing to type 2 diabetes. There have been continued efforts to localize and characterize T2D susceptibility genes using genome-wide linkage and genome-wide association study approaches, aside from the traditional candidate gene approach. Although linkage studies have identified various T2D susceptibility loci, subsequent gene discovery successes from such efforts have been limited. In recent years, the GWAS method has become a popular design with unprecedented successes in localization of several novel T2D susceptibility loci, however, these common variants explain only about 10% of the total heritability indicating more loci remain to be identified. This has led to an increased interest in the potential role of rare variants in common complex diseases. As one of the five research groups involved in the T2D-GENES consortium, the data obtained from our San Antonio Mexican American Family Studies (SAMAFS) have contributed to the two major projects of T2D- GENES. This proposal, submitted in response to the RFA-DK-14-003 (AMP T2D-GENES consortium) aims to build on and expand the research activities of the T2D-GENES consortium. We will (i) expand the WGS data with an additional (already available) 1,000 whole genomes from SAMAFS to reaffirm the already found rare and private variant associations with T2D and glucose traits in Mexican Americans; and replicate selected rare association findings in other cohorts; (ii) recall approximately 300 (100 T2D and 200 non-T2D) SAMAFS participants from families carrying rare or private variants to perform deep phenotyping in which we will collect metabolic information, 3 tissues (muscle, fat, and PBMCs) for gene expression analysis and metabolomic profiling; and (iii) directly identify putative regulatory variants in gene regions of interest influencing T2D and perform preliminary functional assessment of associated variants, both rare and common. The estimated economic burden of diabetes in the United States alone is approximately $245 billion per year, making this disease of major public health importance. The ability to identify genes that are causally involved in disease risk provides an unparalleled opportunity to quickly determine biological pathways that are involved in disease pathology. A better understanding of the genetic contribution to diabetes development will provide novel approaches for the characterization, treatment and potential prevention of this costly disease.

Public Health Relevance

Type 2 diabetes (T2D) has become a major health issue globally including the US. T2D and its comorbid conditions such as obesity, cardiovascular disease, and metabolic syndrome disproportionately affect ethnic minorities in the United States including Mexican Americans. It is a complex disorder influenced by genetic and environmental factors and their interactive influences, but knowledge on specific genetic factors that underlie variation in T2D is still limited. Therefore, the major objective of this study is to identify potetial functional variants influencing T2D and its related traits. The ability to identify individuals wit elevated susceptibility to T2D would be critical to initiating effective early prevention strategie or to treat individuals in these at-risk groups. This study has great potential to generate excellet data for an overall understanding of the health disparities in the US populations.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project--Cooperative Agreements (U01)
Project #
6U01DK085524-07
Application #
9054831
Study Section
Special Emphasis Panel (ZDK1)
Program Officer
Pawlyk, Aaron C
Project Start
2009-09-20
Project End
2020-04-30
Budget Start
2016-05-01
Budget End
2017-04-30
Support Year
7
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of Texas Rio Grande Valley
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
069444511
City
Edinburg
State
TX
Country
United States
Zip Code
78539
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