Social, environmental, and epigenetic drivers of atopic dermatitis disease course
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PROJECT SUMMARY/ABSTRACT This is an application for a K23 award for Dr. Katrina Abuabara, a dermatologist, sociologist and epidemiologist at the University of California, San Francisco. Dr. Abuabara is establishing herself as an investigator in the patient-oriented clinical research of atopic dermatitis (eczema). This K23 award will provide Dr. Abuabara with the support necessary to: (1) become an expert at patient-oriented research in atopic dermatitis; (2) combine exposure and risk factor data with genomic and clinical measures; (3) implement advanced methods for longitudinal data analysis; (4) implement bioinformatics for the analysis and presentation of genomic data; and (5) develop an independent clinical research career. To achieve these goals, Dr. Abuabara has assembled a mentoring team comprised of a primary mentor, Dr. Lindsey Criswell, an epigenetic epidemiologist and clinical investigator studying heterogeneous autoimmune disease, and two co-mentors: Dr. Chuck McCulloch, a biostatistician and expert in longitudinal data analysis, and Dr. Pui-Yan Kwok, a dermatologist and human geneticist. Atopic dermatitis affects 10% of the U.S. population across their lifespans from early childhood through elder age, yet varies in severity and disease activity. Some patients have mild disease and others have disease so severe that its impact on quality of life is akin to type 1 diabetes or cystic fibrosis. The disease also waxes and wanes; patients may have periods without active disease that range from days to decades. Research on the variability in the natural history of the disease course is necessary to identify drivers of disease activity and to design personalized intervention strategies. Dr. Abuabara proposes to use electronic medical record and detailed questionnaire data repeated at multiple time points to identify subgroups of individuals with distinct patterns of disease activity (Aim 1), examine which early life exposures, including social and physical environments, are most predictive of disease (Aim 2), and finally test the hypothesis that the effect(s) of these exposures are transmitted via methylation changes to the DNA (Aims 3 and 4). The results will inform future studies examining whether epigenetic changes can be used as predictive biomarkers to identify patients likely to have a more severe course or those who are more likely to respond to treatments.
