This application, """"""""Epigenetic Biomarkers of Common Chronic Diseases,"""""""" addresses broad Challenge Area (03) Biomarker Discovery and Validation and specific Challenge Topic, 03-OD-101: Use of Epigenetic Signatures in Blood Cells to Predict Disease. Diabetes, kidney disease, and the microvascular complications from hypertension (in the brain, peripheral arteries, and coronary arteries) are a major burden on the public's health(1, 2) and appear to aggregate in some population subgroups more frequently than expected by chance alone. For example, African-Americans experience these diseases in epidemic proportion and at earlier ages than non-Hispanic Whites(3, 4). While traditional diagnostic criteria for diabetes or kidney disease identify individuals with high risk of debilitating clinical outcomes, such as extremity amputation and dialysis, there is a pressing need to identify at-risk individuals well before the presentation of clinical diagnostic symptoms to avert these severe health outcomes. Heritable and non-heritable phenomena that affect gene expression, known as epigenetic mechanisms (DNA methylation, histone modification, and microRNA), play a key role in multiple cellular processes and have been hypothesized as a link between environmental factors, lifestyle, and alterations in chronic disease susceptibility(5, 6). Inter-individual differences in DNA methylation profiles has the potential to identify individuals at risk for the development of disease outcomes at a presymptomatic stage when preventive efforts will be most beneficial(7). DNA methylation profiles, also known as epigenetic profiles, are promising biomarkers to assess for predictive utility for these chronic disease phenotypes and are easily accessible through peripheral blood samples. For the past 14 years, the Genetic Epidemiology Network of Arteriopathy has been working to collect clinical and subclinical measures of micro and macro vascular disease and its impact on the kidney, heart, brain, and peripheral arteries in hypertensives - one of the most prevalent and high risk subgroups in the US. Diabetes is also highly prevalent in this high risk subgroup due in part to what has been called the metabolic syndrome. The GENOA study has created a rich resource of biological samples (DNA, serum, urine) as well as demographic, anthropometric, environmental, clinical, biochemical, physiological, and genomic data for understanding the epigenetic predictors of chronic diseases and its risk factors.

Public Health Relevance

(provided by applicant): This application addresses the specific Challenge Topic, 03-OD-101: Use of Epigenetic Signatures in Blood Cells to Predict Disease and a provides a unique opportunity to examine the utility of epigenetic profiles as biomarkers for predicting chronic disease phenotypes in African-Americans, a group with increased risk of diabetes, kidney disease, and the microvascular complications from hypertension. The goal of this proposed project is to identify new biomarkers of common diseases using epigenetic markers that are measured in the genome of easily accessible blood cells. Our project will investigate these potential epigenetic biomarkers in a high risk subgroup of the population that could benefit greatly from advanced knowledge and increased prevention.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
NIH Challenge Grants and Partnerships Program (RC1)
Project #
5RC1HL100185-02
Application #
7936366
Study Section
Special Emphasis Panel (ZRG1-PSE-C (58))
Program Officer
Stoney, Catherine
Project Start
2009-09-30
Project End
2012-12-31
Budget Start
2010-08-01
Budget End
2012-12-31
Support Year
2
Fiscal Year
2010
Total Cost
$499,957
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Taylor, Jacquelyn Y; Schwander, Karen; Kardia, Sharon L R et al. (2016) A Genome-wide study of blood pressure in African Americans accounting for gene-smoking interaction. Sci Rep 6:18812
Ligthart, Symen; Marzi, Carola; Aslibekyan, Stella et al. (2016) DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases. Genome Biol 17:255
Smith, Jennifer A; Zagel, Alicia L; Sun, Yan V et al. (2014) Epigenomic Indicators of Age in African Americans. Hereditary Genet 3:
Ng, Maggie C Y; Shriner, Daniel; Chen, Brian H et al. (2014) Meta-analysis of genome-wide association studies in African Americans provides insights into the genetic architecture of type 2 diabetes. PLoS Genet 10:e1004517
Sun, Yan V (2014) The Influences of Genetic and Environmental Factors on Methylome-wide Association Studies for Human Diseases. Curr Genet Med Rep 2:261-270
Fox, Ervin R; Musani, Solomon K; Barbalic, Maja et al. (2013) Genome-wide association study of cardiac structure and systolic function in African Americans: the Candidate Gene Association Resource (CARe) study. Circ Cardiovasc Genet 6:37-46
Sun, Yan V; Lazarus, Alicia; Smith, Jennifer A et al. (2013) Gene-specific DNA methylation association with serum levels of C-reactive protein in African Americans. PLoS One 8:e73480
Sun, Yan V; Smith, Alicia K; Conneely, Karen N et al. (2013) Epigenomic association analysis identifies smoking-related DNA methylation sites in African Americans. Hum Genet 132:1027-37
Sun, Yan V; Turner, Stephen T; Smith, Jennifer A et al. (2010) Comparison of the DNA methylation profiles of human peripheral blood cells and transformed B-lymphocytes. Hum Genet 127:651-8