Diabetes mellitus (DM) is an increasing threat to human health. Long-term exposure to DM can lead to devastating macro- and microvascular complications, including cardiovascular disease, blindness, amputation, and kidney failure via diabetic nephropathy (DN). However, not all diabetics develop complications at the same rate, and the causes of this variation in risk are largely unknown. Using a rich set of genome-wide gene expression profiles of 1,240 Mexican Americans from more than 40 extended families, we have identified 22 genes that exhibit highly significant genotype x duration of DM interaction effects. While many genes are differentially expressed in DM, this subset represents those genes with the greatest genetic variability in the response to disease exposure. The subset is enriched for genes related to oxidative stress and inflammation, including SMAD1, a putative early biomarker of DN. The subset is connected to thousands of other genes through both known pathways and via genetic correlation in the sample. In this study, we will combine genetic, transcriptomic, and bioinformatic data to identify gene networks with variable response to DM exposure, to develop hypotheses of causation and to search for new gene variants that may underlie individual variation in risk for complications. We will then test these hypotheses in the context of DN, using kidney function phenotypes measured in 858 of these same individuals ~10 years after acquisition of the expression phenotypes, as well as in 2,282 Mexican Americans from replicate samples recruited on probands with established DM and/or DN.

Public Health Relevance

As the prevalence of diabetes melitus increases and medical interventions permit longer survival of patients with DM, the economic, clinical, and social burdens of DM complications are likely to increase. The knowledge acquired in this study will help identify genetic factors leading to differential risk for development of complications under long-term diabetes. In particular, diabetic nephropathy (DN) is a devastating outcome for as many as 40% of patients with long-term DM and the primary cause of kidney failure and end-stage kidney disease in the US;treatment of kidney failure by dialysis or transplantation costs as much as $32 billion per year. By relating our discoveries to kidney-related outcomes, the study will seek to identify biological pathways that could be targeted for personalized risk assessment and/or preventative therapies.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK084289-02
Application #
8335461
Study Section
Kidney, Nutrition, Obesity and Diabetes (KNOD)
Program Officer
Rasooly, Rebekah S
Project Start
2011-09-20
Project End
2015-06-30
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
2
Fiscal Year
2012
Total Cost
$378,437
Indirect Cost
$143,339
Name
Texas Biomedical Research Institute
Department
Type
DUNS #
007936834
City
San Antonio
State
TX
Country
United States
Zip Code
78245
Kent Jr, Jack W (2016) Pathway-based analyses. BMC Genet 17 Suppl 2:5