Dr. Elizabeth Hauser is a Statistical Geneticist and Genetic Epidemiologist who has worked in the area of human genetics for over 20 years. Her research interests range from statistical methods development and study design to applications of genetic analysis methods to a wide range of diseases and conditions. She collaborates with other investigators to include new methods of genomic analysis in applied gene identification studies.
Dr. Hauser’s first project at Duke University was a family study of early-onset cardiovascular disease, called GENECARD, in collaboration with Dr. William Kraus and a large international consortium of academic researchers and researchers from Glaxo-Smith-Kline. The GENECARD study collected over 1000 families (1) and performed genome-wide linkage studies(2), ultimately identifying and replicating several genes associated with coronary artery disease including the genes KALRN (3), GATA2 (4), LSAMP (5), FAM5C (6), NPY (7), ALOX5AP (8), TNC (9), and PLA2G7 (10). We are fortunate to have also been able to assemble a second dataset, CATHGEN, including nearly 10,000 samples from the Duke Cardiac Catheterization Lab that was successfully used to perform genetic association tests as replication of GENECARD findings. We are also examining the impact of risk factors for cardiovascular disease and gene-by-environment interactions on cardiovascular disease risk, including lipid levels (11,12) , smoking (13), air pollution, psychosocial stress (14,15) and age (7,16). The studies in gene-by-air pollution interactions have expanded our research networks to include researchers in the Duke Department of Statistical Science and the Environmental Protection Agency interested in the effects of air pollution on cardiovascular health. The studies in the gene-by-psychosocial stress interactions are in collaboration with Dr. Redford Williams and researchers at the Behavioral Medicine Research Institute. Our cardiovascular collaborative team includes multiple staff and faculty in the DMPI including Drs. Svati Shah and Simon Gregory who began as junior faculty but now run thriving programs in the genetics of cardiovascular disease that have augmented the available CATHGEN dataset with gene expression, metabolomics, epigenetic and sequence data.
A key focus of our cardiovascular genetics research has been in the relationship between age and cardiovascular disease. For Dr. Hauser this has grown into a more general focus on aging with her involvement in the Duke Older Americans Independence Center (OAIC) or Pepper Center. As part of the Pepper Center Dr. Hauser has participated in genetic studies of osteoarthritis (17), survivorship in cardiovascular disease (18) and an epigenetic study of smooth-muscle cell aging that identified the COL15A1 gene (19). Recently Dr. Hauser has collaborated with Dr. Zeng Yi and colleagues (20,21) on a recently-completed genome-wide association study of over 2300 centenarians from a population based survey of healthy aging in China.
Dr. Hauser is also participating in studies of kidney disease with Drs. Michelle Winn and Laura Svetkey through the Duke O’Brien Kidney Center, studies of progression to colon cancer and screening for colon cancer and other diseases impacting the health of US military veterans with Dr. Dawn Provenzale at the Durham VA Medical Center and studies of the use of a computerized family health history in primary care with Dr. Lori Orlando and colleagues through the Center for Personalized Medicine (22). These projects, and others like them, illustrate the wide range of ways in which human genetics and genetic analysis may be studied in the context of health and medical care.
Statistical Methods Development:
As a biostatistician and statistical geneticist, Dr. Hauser is interested in developing methods to improve assessment of genetic models for complex diseases. The software programs listed below are available on the Software Downloads page.These methodological studies often include extensive statistical simulation studies, for which Dr. Hauser and colleagues have created the SIMLA software package (23,24,25). Dr. Hauser and colleagues have developed the Ordered-Subset Analysis (OSA) programs for linkage analysis (26), family-based association analysis (27), case-control studies (28), and sequence analysis. The methods and related simulation studies address the pressing need for statistical methods that can be used for gene identification in genetic models of complex disease that include genetic heterogeneity and gene-by-environment interaction. Dr. Hauser is also interested in developing methods and software for integrated systems biology analysis by collaborating with bioinformaticians and computational biologists (29,30,31,32). Finally as the director of the Section of Computational Biology in the DMPI, Dr. Hauser is committed to methods development for reproducible research and excellence in research informatics.