Obesity, a growing epidemic in the US and a health care priority in Healthy People 2010, is a risk factor for type 2 diabetes mellitus, cardiovascular disease and other chronic diseases in renal transplant recipients. Renal transplant recipients gain an average of 22 Ibs during the first year following transplant, which is significantly more than the 2 Ibs average weight gain in US adults. In addition, African American (AA) females are most at risk for weight gain and morbidity. This predictable and significant weight gain within a short amount of time, particularly in AAs, and its association with morbidity and mortality makes this a high priority concern. The purpose of this application is to prospectively examine genetic (gene expression) and environmental factors (food intake, physical activity, demographic, health status, psychosocial) contributing to obesity at one year following renal transplantation in recipients who are non-obese at time of transplant. Long-term goals include prevention and treatment of obesity in recipients. Our hypothesis is that gene- environmental interactions can predict whether individuals will become obese at one year post transplant. Specifically we will (1) identify up to 10 environmental factors associated with post transplant obesity, (2) identify up to 10 gene expressions associated with obesity, (3) use Bayesian analysis to determine combinations of gene- environment interactions that predict obesity. A prospective design will be used to compare genetic and environmental factors and clinical outcomes at baseline, 3, 6, 12 and 24 months post transplant. Gene expression profiling using microarray analysis and real-time polymerase chain reaction on adipose tissue will be used to identify key regulatory elements that play a major role in obesity. Bayesian Network modeling will be used to investigate causal relationships. This significant and innovative study incorporates an interdisciplinary approach to combine emerging genomic and bioinformatic technologies with traditional methodologies to explicate key gene-environment interactions responsible for post transplant obesity. The relevance of this study is that findings will assist health care practitioners in caring for renal transplant recipients so that they do not gain weight and become obese following renal transplantation. This will result in fewer health care problems following transplantation.

Agency
National Institute of Health (NIH)
Institute
National Institute of Nursing Research (NINR)
Type
Research Project (R01)
Project #
5R01NR009270-04
Application #
7775084
Study Section
Nursing Science: Adults and Older Adults Study Section (NSAA)
Program Officer
Huss, Karen
Project Start
2007-05-15
Project End
2012-02-29
Budget Start
2010-03-01
Budget End
2011-02-28
Support Year
4
Fiscal Year
2010
Total Cost
$335,694
Indirect Cost
Name
University of Tennessee Health Science Center
Department
Other Health Professions
Type
Schools of Nursing
DUNS #
941884009
City
Memphis
State
TN
Country
United States
Zip Code
38163
Cho, Young-Eun; Kim, Hyung-Suk; Lai, Chen et al. (2016) Oxidative stress is associated with weight gain in recipients at 12-months following kidney transplantation. Clin Biochem 49:237-42
Stanfill, Ansley; Hathaway, Donna; Bloodworth, Robin et al. (2016) A Prospective Study of Depression and Weight Change After Kidney Transplant. Prog Transplant 26:70-4
Cashion, A K; Hathaway, D K; Stanfill, A et al. (2014) Pre-transplant predictors of one yr weight gain after kidney transplantation. Clin Transplant 28:1271-8
Taylor, Jacquelyn Y; Kraja, Aldi T; de Las Fuentes, Lisa et al. (2013) An overview of the genomics of metabolic syndrome. J Nurs Scholarsh 45:52-9
Cupples, Connie K; Cashion, Ann K; Cowan, Patricia A et al. (2012) Characterizing dietary intake and physical activity affecting weight gain in kidney transplant recipients. Prog Transplant 22:62-70
Ziebarth, Jesse D; Bhattacharya, Anindya; Chen, Anlong et al. (2012) PolymiRTS Database 2.0: linking polymorphisms in microRNA target sites with human diseases and complex traits. Nucleic Acids Res 40:D216-21
Cashion, Ann K; Umberger, Reba A; Goodwin, Shirlean B et al. (2011) Collection and storage of human blood and adipose for genomic analysis of clinical samples. Res Nurs Health 34:408-18
Cashion, A K; Sabek, O; Driscoll, C et al. (2010) Serial analysis of biomarkers of acute pancreas allograft rejection. Clin Transplant 24:E214-22
Bao, Lei; Xia, Xuefeng; Cui, Yan (2010) Expression QTL modules as functional components underlying higher-order phenotypes. PLoS One 5:e14313