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Baylin Group - Nutritional Epidemiology and Cardiovascular Disease

Sharon Kardia, Ph.D.

Titles

Professor, Epidemiology
Director, Public Health Genetics Program
Director, Life Sciences and Society Program
Senior Associate Dean for Administration

Full CV

Curriculum Vitae (PDF, 329,952 KB)

Research Groups & Projects

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Contact

E-mail: skardia@umich.edu

Office: (734) 763-1871

4605 SPH I
1415 Washington Heights
Ann Arbor, Michigan 48109-2029

 

Associated URL

Summary

Dr. Kardia received her master's degree in statistics and her doctoral degree in human genetics from the University of Michigan. She was then a post-doctoral fellow studying systems biology in the Department of Microbiology and Immunology. She joined the faculty of the University of Michigan School of Public Health in 1998. Dr. Kardia's main research interests are in the genetic epidemiology of common chronic diseases and their risk factors. She is particularly interested in gene-environment and gene-gene interactions and in developing novel analytical strategies to understand the complex relationship between genetic variation, environmental variation, and risk of common chronic diseases. Her research utilizes genomic, epigenomic, transcriptomic, and proteomic measures on large epidemiological cohorts.

Additional Information

Over the past five years, Dr. Kardia has served on five National Academy of Science Committees: 1) Genomics and the Public's Health in the 21st Century (Institute of Medicine), 2) Applications of Toxicogenomics Technologies to Predictive Toxicology (National Research Council), 3) Committee to Review the National Childhood Study (Institute of Medicine, National Academy of Sciences), 4) Assessing Social, Behavioral, and Genetic Interactions (Institute of Medicine), and 5) The Roundtable on Translating Genomic-Based Research for Health (Institute of Medicine).

Teaching

EPID503: Strategies and Uses of Epidemiology
EPID513: Applications in Public Health Genetics
EPID817: Advanced Genomic Epidemiology
PUBHLTH510: Intergroup Dialogues on Race, Socio-Economic Status and Health Equity

Projects

>> Coronary Artery Calcification

Coronary Artery Calcification (CAC) is a subclinical measure of coronary artery atherosclerosis. Our studies of CAC in the Genetic Epidemiology Network of Arteriopathy (GENOA) indicate that it is heritable and associated with variation in multiple genes.... More >>

Image courtesy of Duncan Creamer. 

>> Heart Failure

Cardiac hypertrophy is heritable and a clearly recognized risk factor for heart failure. Our studies and others have identified potential hypertrophy-associated SNPs in various heterogeneous populations and we are also trying to identify SNPs associated with heart failure mortality.... More >>

 

>> Peripheral Vascular Disease

Peripheral arterial disease is a common condition in the elderly. It has two important clinical consequences. First, affected individuals generally have widespread atherosclerosis and consequently are at increased risk of stroke, myocardial infarction, and cardiovascular death. Second, PAD can markedly affect quality-of-life by causing exertional leg pain (i.e., intermittent claudication) and functional impairment of the lower extremities. In the GENOA cohort, the ankle-brachial index was measured to assess PAD.... More >>

 

>> Gene Trigger Interactions: Costa Rica & Colombia

It has been shown that heavy physical exertion and coffee intake are two triggers of acute myocardial infarction (MI). We will use the unique characteristics of the case-crossover study to assess potential effect modification by genetic variation on the triggering of MI by coffee intake and heavy physical exertion.... More >>

 

>> Scan Statistics

We have developed a scan statistic methodology that is suitably general to be used in a variety of genome-wide studies.... More >>

 

>> Rochester Family Heart Study

The overall objective of the Rochester Family Heart Study was to identify and characterize genetic variations that influence the risk of cardiovascular disease and hypertension in the general population of Rochester, MN.... More >>

 

>> Exomic Sequencing in Sibships to Identify Target Organ Damage Genes

As part of the GENOA study, quantitative measures of subclinical target organ disease have already been collected. Measurement of 900,000 single nucleotide polymorphisms distributed across the genome, enabled pursuit of candidate genes under significant linkage peaks and unbiased genome-wide association analyses to identify common variants predisposing to subclinical disease. Yet, most of the heritable variation in these measures of target organ damage still remains unexplained and unexplored. In this project, we are gearing up to identify low-frequency and ... More >>

 

>> Genetic Epidemiology of Arteriopathy (GENOA)

From its inception in 1995, the Genetic Epidemiology Network of Arteriopathy's (GENOA) long-term objective was to elucidate the genetics of arteriosclerotic target organ complications of hypertension, including both atherosclerotic or "macrovascular" and arteriolosclerotic or "microvascular" complications involving the heart, brain, kidneys, and peripheral arteries.... More >>

 

>> Genetic Architecture of Leukoaraiosis

Ischemic damage to the subcortical white matter of the brain, referred to as leukoaraiosis, is a frequent complication of hypertension-related microvascular disease and contributes to the risk of stroke and vascular dementia. As part of a NINDS grant entitled Genetics of Microangiopathic Brain Injury (RO1 NS41558), GENOA participants have been assessed for leukoaraiosis as well as brain atrophy and ventricular volume using magnetic resonance imaging (MRI).... More >>

Image courtesy of BMJ, from Debette, S. and Markus, H. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 2010; 341:c3666. 

>> Genetics of Kidney Phenotypes

In 2002, the Kidney Disease Outcome Quality Initiative of the National Kidney Foundation defined chronic kidney disease (CKD) as the presence of a marker of kidney damage, such as proteinuria (e.g., albumin/creatinine ratio 30 mg×g-1 on spot urine testing), or a decreased glomerular filtration rate (GFR) for 3 months. In GENOA, serum creatinine and urinary albumin were measured during both Phase I and II providing the ability to estimate GFR and the urinary albumin-creatinine ratio.... More >>

 

>> Exomic Sequencing of Low-Renin Hypertensives

High blood pressure (BP), or hypertension, affects one billion people worldwide and is the most prevalent modifiable risk factor for vascular diseases of the brain, heart, and kidneys. The underlying causes remain enigmatic in most cases (90%), referred to as primary hypertension. Biometrical analyses have consistently demonstrated the heritability of BP levels and hypertension; however, most DNA sequence variants contributing to BP elevation have eluded discovery through candidate gene or whole-genome analyses. Consequently, the potential to improve ... More >>

 

>> Genetics of Kidney Stones

We are currently using genome-wide association data to identify key genes and gene-diet interactions in the development of kidney stones.... More >>

 

>> Predictors of Blood Pressure Control

 

>> Random Forests

As part of the GENOA study, a large amount of genetic and phenotypic data has been collected on individuals from multiple ethnic groups. As a first step toward understanding the capability of novel machine learning algorithms to capture high dimensional structure for prediction of who is at risk in the population we applied two machine learning algorithms, Random Forests and RuleFit, to identify the best predictors of having high coronary artery calcification burden (CAC) burden.... More >>

 

>> Risk Index Methods

Integrating clinical and genetic information to improve clinicians' ability to estimate an individual's disease risk is an important biomedical research challenge. Beginning from the concept of genetic risk scores, which estimate an individual's risk of developing a disease by summing risk information from single nucleotide polymorphisms (SNPs), we have developed a "risk index" procedure that combines clinical data and genome-wide genotypes to make a prediction about an individual's risk of disease.... More >>

 

>> Graphical Methods (Kgraph)

The KGraph is a data visualization system that we developed to display the complex relationships between the univariate and bivariate associations among an outcome of interest, a set of covariates, and a set of genetic variations such as single nucleotide polymorphisms (SNPs).... More >>

 

>> Toward a New Molecular Classification of Cancer

For most types of cancer, histopathology is insufficient to predict disease progression and clinical outcome. Working with researchers at the UM Cancer Center, we helped develop and apply methods for identifying genes expression profiles based on microarray analysis that could be used for identifying histological subtypes of cancers, distinguishing between cancer stages, and predicting patient survival.... More >>

Image from Beer, et al. Nature Medicine  8, 816 - 824 (2002)  

>> Gene Expression Predictors of Ischemic Brain Injury

In this project we are using a functional genomic strategy based on gene expression measurements to identify genetic variants influencing MRI measures of structural brain injury (leukoaraiosis, cerebral atrophy, and ventricular volume).... More >>

 

>> Epigenetic Predictors of Common Chronic Diseases

Epigenetic mechanisms 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. We are studying inter-individual differences in DNA methylation profiles to identify individuals at risk for the development of disease outcomes at a presymptomatic stage when preventive efforts will be most beneficial.... More >>

Image from Sun, et al. Hum Genet. 2010 Jun;127(6):651-8. 

>> Echocardiographic Traits

 

>> Anthropometric Traits

 

>> Blood Pressure

 

>> Kidney Phenotypes

 

>> Brain Ischemia

Image courtesy of BMJ, from Debette, S. and Markus, H. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 2010; 341:c3666. 

>> Gene-by-Drug Interactions

Image courtesy of OpenCage.info 

>> Gene-by-Social Factor Interactions

Image courtesy of Naaman Saar Stavy. 

>> Gene-by-Risk Factor Interactions

Image courtesy of Ray Ordinario. 

>> Cognitive Function

 

>> Stress, Gene-Environment Interaction and Cardiovascular Disease

This NIH-funded project examines the interrelations between the social environments, stress processes, and cardiovascular risk. The project collects data on multiple biomarkers of stress in a large population based multiethnic sample in order to examine upstream social predictors of the stress response as well as the downstream consequences of stress for proximal biological pathways such as hemostasis, inflammation, and metabolic changes that may lead to cardiovascular disease. The project also collects data on stress responsivity using a standardized stress challenge. ... More >>

 

>> MESA SHARE Working Group on Psychosocial Factors and Gene-Environment Interactions Involving Social and Physical Environments

This working group collaborates with the MESA SHARE project to conduct research on genetic predictors of psychosocial factors and to investigate the presence of gene-by environment interactions involving social and psychosocial factors as well as various features of physical and social environments. Current projects include genetic predictors of psychsocial factors as well as investigations of interactions between neighborhood factors, socioeconomic position, and genes for cardiovascular risk factors.... More >>

 

>> Center for Integrative Approaches to Health Disparities (P60 MD002249)

The goal of the Michigan Center for Integrative Approaches to Health Disparities (CIAHD) is to promote and support research that comprehensively integrates social and biological factors within a multilevel framework in understanding the determinants of minority health and health disparities with a special focus on cardiovascular disease disparities. CIAHD is a collaboration between the University of Michigan and the Jackson Heart Study through its partners the University of Mississippi Medical Center and Jackson State University. CIAHD is funded through a ... More >>

 

Selected Publications

Search PubMed for publications by Sharon Kardia >>

  • Turner, S.T., Kardia, S.L.R., Boerwinkle, E., deAndrade, M. Multivariate linkage analysis of blood pressure and body mass index General Epidemiology, 27, 64-73.
  • O'Meara, J., Kardia, S.L.R., Armon, J.J., Turner, S.T. Prevalence, treatment, and control of dyslipidemia in a hypertensive population Archives of Internal Medicine, 164, 1313-1318.
  • Daniels, P.R., Kardia, S.L.R., Hanis, C.L., Brown, C.A., Hutchinson, R., Boerwinkle, E., Sing, C.F., Turner, S.T. (2004). Familial aggregation of hypertension treatment and control American Journal of Medicine, 116, 676-681.
  • Sing, C.F., Stengard, J.H., Kardia, S.L.R. (2003). Genes, environment, and cardiovascular disease ATVB, 23, 1190-1196.
  • Kardia, S.L.R., Modell, S., Peyser, P.A. (2003). Family-centered approaches to understanding and preventing coronary heart disease American Journal of Preventive Medicine, 24, 143-151.
  • Kardia, S.L.R., Rozek, L.S., Krushkal, J., Ferrell, R.E., Turner, S.T., Hutchinson, R., Brown, A., Sing, C.F., Boerwinkle, E.B. (2003). Genome-wide linkage analyses for hypertension genes in two ethnically and geographically diverse populations American Journal Hyt, 16, 154-157.
  • Small, K.M., Wagoner, L.E., Levin, A.M., Kardia, S.L.R., Liggett, S.B. (2002). Synergistic polymorphisms of ²1- and ±2C-adrenergic receptors and the risk of congestive heart failure New England Journal Medicine, 347, 1135-1142.
  • Beer, D.G., Kardia, S.L.R., Huang, C.C., Misek, D.E., Lin, L., Chen, G., Gharib, T.G., Giordano, T.J., Thomas, D.G., Lizyness, M.L., Kuick, R, Taylor, J., Iannettoni, M.D., Orringer, M.B., Hanash, S. (2002). Gene-expression profiles predict survival of patients with lung adenocarcinomas Nature Medicine, 8, 816-824.
  • Schwartz, D.R., Kardia, S.L.R., Shedden, K.A., Kuick, R., Michailidis, G., Taylor, J.M.G., Misek, D.E., Wu, R., Zhai, Y., Darrah, D.M., Reed, H., Ellensen, L.H., Giordano, T.J., Hanash, S.M., Cho, R. (2002). Gene expression in ovarian cancer reflects both morphology and biological behavior, distinguishing clear cell from other poor-prognosis ovarian carcinomas Cancer Research, 62, 4722-4729.