Research Projects

In addition to learning data collection and analysis methods, participants learn research collaboration efforts by engaging in group projects with other participants and graduate students. Group projects are designed and mentored by a faculty member in the Departments of Biostatistics or Epidemiology and by a graduate student or post-doctoral research fellow. This research is a good introduction to research methods, analysis, and organization and presentation of results.

Evaluating gene-environment interaction between oral contraceptive use and BRCA1/BRCA2 mutation on the risk of ovarian cancer

Faculty Mentor:
 Dr.Eric Tchetgen 
Graduate Student Mentor: Miguel Marino
Program Participants: Dana Bryant Rebbecca Wilson, and Willythssa Pierre-Louis

Use of oral contraceptives is known to reduce the risk of ovarian cancer. However, there is a need to further understand its effect on this risk in women with or without a BRCA1 or BRCA2 genetic mutation, an important genetic determinant of ovarian cancer. Students conducted an analysis to study the interaction between BRCA1/2 mutations and use of oral contraceptive on the risk of ovarian cancer. Students also used multivariate logistic regression methods for case-control data to evaluate the interaction between us of oral contraceptive and genetic mutations BRCA1/2 among approx. 1600 women in a case-control study conducted in Israel. The goal is to demonstrate that oral contraceptive use is less protective against ovarian cancer in women who carry the BRCA1/2 genetic mutation, when compared to non-carriers.


Evaluating the Prevalence of Psychiatric Disorders Across Races in HIV-positive and HIV-negative Associated Children

Faculty Mentor:
 Dr. Paige Williams
Graduate Student Mentor: Miguel Marino
Program Participants: Sophia Salazar, Irene Headen, and Marcia McNutt

The students examined whether there is a racial difference in the prevalence and severity of psychiatric disorders in both children who have HIV and children who live with someone who has HIV. Using linear and logistic regression, students found that no significant differences in prevalence nor severity among races were found. The secondary objective was to examine the percent agreement of children and their caregivers when reporting on the child’s psychiatric symptoms. Preliminary findings showed a disagreement between the child and caregiver when reporting for each disorder.


Genetic Determinants of Alcoholism

Faculty Mentor:
 Dr. Christoph Lange
Graduate Student Mentor: Peter Lipman
Program Participants: Gerald Morgan and Brittney Stewart

This project used regression models to investigate genetic determinants of alcoholism. They applied multivariate regression models to the Collaborative Study on the Genetics of Alcoholism (COGA), which contains genetic and phenotype information on approximately 1600 subjects from 143 families. The goal of the project was to identify any significant genetic markers of alcoholism (or surrogate phenotypic traits).


Examination of Arsenic Exposure Effects on Proteomic Profiles

Faculty Mentor:
 Dr. Xihong Lin
Post Doctoral Mentor: Dr. Caterina Stamoulis
Program Participants: Nian VerzosaSando Baysah, and Uche Amazigo

Arsenic, a human carcinogen, is one of the most serious environmental health hazards. In Bangladesh, 55-77 million people are at risk of drinking arsenic contaminated water—the largest mass poisoning of a population in history. Developing appropriate therapeutic interventions for treating arsenic exposed individuals rely on a detailed understanding of the biological mechanisms of response to heavy metal exposure. However, research on the effects of chronic arsenic is very limited.

Advanced proteomic technologies are useful tool for studying the abundances of many proteins simultaneously. We will use linear regression analysis to study the effect of chronic arsenic exposure on protein profiles of subjects from a large arsenic case-control study of skin disease in Bangladesh. The data contains phenotypic and proteomic information on 214 subjects. The goal is to determine which proteins have abundances associated with chronic exposure to arsenic.