Sponsored Program Research

• Longitudinal Study of Older Adults in Mexico (PI: R. Wong)

  The MHAS (Mexican Health and Aging Study) is a study of the health of older adults in Mexico using a wide socioeconomic perspective. It includes a longitudinal survey of a national sample of individuals born in 1951 or earlier in Mexico (n=15,000), to study a large number of aspects of older adults’ well being such as physical and mental health, disability, cognition, health behaviors, health expenditures, job history, U.S. migration history, income, insurance, pensions, assets, the built environment, intergenerational transfers, and family and social networks. The study is funded by the National Institute on Aging of the National Institutes of Health. The baseline survey was conducted in 2001 with re-interviews to the same persons in 2003, and the study has recently received funding to re-interview persons in 2012 and 2014. The study includes an important component of dissemination and data sharing, to foster research on the health of older adults in Mexico with socio-economic and cross-national approaches. The principal investigator is Dr. Rebeca Wong, Professor of Preventive Medicine and Community Health and Senior Fellow of the Sealy Center on Aging. Collaborators include researchers from UTMB, the University of Wisconsin and University of Pennsylvania; and from Mexico, the INEGI (Statistical Bureau of Mexico), the InGER (National Institute of Geriatrics), and the INSP (National Institute of Public Health).

• Gulf Coast Health Alliance: health Risks related to the Macondo Spill (GC-HARMS) (PI: S. Petronella Croisant)

  The “Gulf Coast Health Alliance: health Risks related to the Macondo Spill (GC-HARMS)” consortium involves the University of Texas Medical Branch, the University of Pennsylvania, Texas A&M University at Galveston, Louisiana State University, and Gulf Coast communities impacted by the Deepwater Horizon (DWH) disaster. The coalition of community partners are represented by the Louisiana Environmental Action Network (Baton Rouge, LA), the Center for Environmental and Economic Justice (Biloxi, MS), the Mississippi Coalition for Vietnamese-American Fisherfolk and Families (Gulfport, MS), the United Houma Nation (Houma, LA), Bayou Interfaith Shared Community Organizing (Thibodeaux, LA), and the Alabama Fisheries Cooperative (Coden, AL). The mission of the GC-HARMS consortium is to explore the health impacts and community resiliency related to the DWH disaster by fostering collaborative interactions amongst multi-disciplinary, multi-institutional basic and clinical investigators—buttressed by active participation of various community partners—to pursue both fundamental and translational research pertinent to the effects of the oil spill on human health. The overall theme of the GC-HARMS consortium is to understand and communicate the human health risks of exposure to potentially hazardous food-borne petrogenic Polycyclic Aromatic Hydrocarbons (PAH). Our goals developed in collaboration with our community partners are to, 1) assess PAH contamination of Gulf seafood consumed by and sold by the subsistence fishing communities, 2) determine the toxicity of petrogenic PAH, 3) evaluate exposure and health outcomes in the human population, and 4) translate and disseminate findings to our community stakeholders for development of appropriate outreach and education activities.
  
  

• Soy and Breast Cancer Prevention (PI: L. Lu)

  Populations consuming high levels of soy, as in many Asian countries, have lower levels of ovarian hormones, lower rates of breast cancer, and reduced mammographic density than populations consuming typical Western diets. These observations may in part be explained by our clinical studies that found ovarian hormone levels of premenopausal women to be lowest while they were consuming a diet that provided 15% energy from soymilk containing weakly estrogenic isoflavones. Further questions are whether isoflavones and/or soy proteins are the critical components influencing breast cancer risk, which are being tested by two randomized, double-blind, placebo controlled clinical trials (www.clinicaltrials.gov and the identifiers are NCT00204477 and NCT00204490).

  Women with dense breasts have a 4-6 fold excess risk of developing breast cancer. Moreover, greater breast density makes it more difficult to detect early breast cancer by mammography. In one trial (funded by NIH), the effect on breast density of 2-year supplementation with pills of soy isoflavones (treatment) is being compared with pills without isoflavones (placebo). In the second trial (funded by Army’s Breast Cancer Research Program), the effect on breast density of 2-year supplementation with soy protein without isoflavones (treatment) is being compared with cow’s milk proteins without other female hormones (placebo). Reducing breast density by soy isoflavones and/or soy proteins can be expected to reduce the volume of target tissue at risk for breast cancer development and will improve the sensitivity of mammography for screening. The study may lead to a novel, non-invasive and economical approach to breast cancer prevention.

• Perceived Risk and Compliance with Mandatory Evacuation Order (PI: S. Weller)

  This project explores perceived risk among people who were deemed by civil defense authorities to be at major risk of serious bodily harm.  A mandatory evacuation order was issued for Galveston Island and surrounding low-lying areas in September 2008, as a force 2 to 3 hurricane approached the Gulf Coast.  When the storm hit the island, it was estimated that approximately 40% of the population had not heeded the mandatory evacuation.  The storm had an accompanied surge more typical of a force 4 to 5 storm and inundated the island with approximately 13 feet of tidal surge.  To understand how people interpret and chose to comply or not comply with a mandatory order, this study uses in-depth, open-ended interviews to elicit reasons, motives, and beliefs about what a “mandatory” evacuation means, why they would or would not comply, what they might do next time and why, and what they would like others to know who might be given a mandatory order in the future.  Subjects are paired "neighbors:" one who did and one who did not evacuate.  We hypothesize that there may be differences in understanding of risk between those who did and did not evacuate and also between those who give the orders and those who do and do not respond to orders. Our ultimate goal is to understand if there are important differences in the understanding of risk between those who issue mandatory evacuation orders and the public who is expected to respond to them.  While Gulf Coast and Eastern Seaboard areas carry summertime risk of a natural disaster due to a hurricane, the entire US carries some degree of risk due to a possible terrorist, specifically a bioterrorist attack.  Population response (and non-response) to mandatory evacuation rules raises a question about population compliance with any mandatory order.

• A Longitudinal Study of Elderly Mexican American Health (PI: K. Markides)

  The Hispanic EPESE (Established Populations for Epidemiologic Studies of the Elderly) is the largest epidemiologic study of the health of Mexican American elderly. The principal investigator of the study is Dr. Kyriakos Markides, Professor of Preventive Medicine and Community Health. Researchers at the University of Texas Medical Branch at Galveston, Texas are conducting the project in collaboration with colleagues from the University of Texas at Austin and the University of Texas Health Science Center at San Antonio. The National Institute on Aging is funding this study. The study began in the early 1990’s and was recently refunded through 2015. It is the primary source of information on the health of older Mexicans using representative samples from the Southwestern United States.

• Late Effects of Radiation in Older Gynecologic Cancer Survivors (PI: J. Freeman)

  This study is using gynecologic cancers as a model system for investigating late effects of radiation using the SEER Medicare Database. The overall objectives are to 1) construct and evaluate claims based algorithms for defining late effects of radiation related to bowel and bladder toxicities, 2) estimate the risks of these effects among older cancer survivors diagnosed from 1986-2002 and 3) examine variations in the risk by patient, physician and facility characteristics, Study findings have important implications for two groups of older adults with personal histories of cancer. For newly diagnosed patients, our risk estimates over the most recent follow-up period (2000-2005) are helpful for making decisions about current treatment options. Information over the entire study period can also be used to develop individual “Survivorship Plans” - tailored to the survivor’s personal characteristics and when she was treated - with recommended follow-up care. Such plans are critical for the effective surveillance of cancer survivors by primary care physicians, who provide much of the long term follow-up care for patients with these adverse effects. The plans can also remind and encourage survivors to report symptoms related to potential toxicities.

• Biomarker Discovery for Hepatitis C Progression Using Machine Learning Techniques (PI: H. Spratt)

  The spread of Hepatitis C virus (HCV) in the Hispanic population has caused great concern due to its advanced progression when compared with Caucasian individuals and the reduced effect of common therapy options on Hispanic patients. Little is known about the progression of HCV to liver cancer, so one of the goals of this project is to investigate biomarkers for early stage detection of liver cancer in individuals with advanced liver fibrosis due to HCV infection. Surface Enhanced Laser Desorption/Ionization (SELDI) and metabonomics experiments will be conducted on serum and urine samples from patients infected with HCV and liver cancer. The different stages of fibrosis associated with HCV will be compared to discover which proteins and metabolites are differentially expressed between individuals;  the end result will be the development of a biomarker panel for fibrosis stage determination. Also, patients proteomic and metabolomic response to therapy will be examined to determine a priori which individuals will respond well to therapy. In addition, patients with liver cancer will be compared to patients infected with HCV to develop a biomarker panel for the detection of early stage liver cancer. Classical methods of analysis such as principal component analysis, hierarchical clustering, neural networks, and receiver operating curves will be utilized as well as more sophisticated techniques such as machine learning and support vector machines. Dr. Spratt will make advances in the areas of support vector machine to create higher-quality biomarker panels for HCV infection and disease progression. The specific aims are to 1) analyze the Hepatitis C Virus data using standard techniques such as hierarchical clustering, principal component analysis, neural networks, and logistic regression to identify proteins and metabolites which are significantly differentially expressed in the various stages of fibrosis; 2) analyze the HCV data using support vector machines to more accurately develop a classifier for stage of fibrosis; 3) develop novel improvements in support vector machine methodology to obtain a higher quality, more reliable diagnostic for stage of liver fibrosis; 4) analyze patient response to disease treatment using improvements in support vector machine techniques and determine which patients are more likely to respond to therapy and which type of therapy; and 5) develop markers for distinction of cancer versus non-cancer patients with HCV from applications of machine learning.