Social, environmental, and epigenetic drivers of atopic dermatitis disease course

项目概要/摘要 这是一份K23奖的申请，获奖者是皮肤科医生、社会学家和流行病学家卡特里娜·阿布巴拉博士。 在旧金山弗朗西斯科的加州大学。Abuabara博士正在建立自己作为一个调查员在 特应性皮炎（湿疹）的患者导向临床研究。K23奖将为Abuabara博士提供 必要支持：（1）成为特应性皮炎患者导向研究专家;（2）联合收割机 暴露和风险因素数据与基因组和临床措施;（3）实施先进的方法， 纵向数据分析;（4）实施生物信息学分析和介绍基因组数据;以及 (5)发展独立的临床研究事业。为了实现这些目标，Abuabara博士召集了一个 指导团队由主要导师Lindsey Criswell博士组成，他是一位表观遗传流行病学家和临床 研究异质性自身免疫性疾病的调查员，和两位共同导师：查克·麦卡洛克博士， 生物统计学家和纵向数据分析专家，以及皮肤科医生和人类 遗传学家 特应性皮炎影响着10%的美国人口，从幼儿到老年 年龄，但不同的严重程度和疾病活动。有些病人病情轻微，有些病人有病， 严重的是，它对生活质量的影响类似于1型糖尿病或囊性纤维化。这种疾病也会加重， 衰退;患者可能有几天到几十年的无活动性疾病的时期。研究 疾病病程自然史的变异性对于确定疾病活动的驱动因素和 设计个性化的干预策略。Abuabara博士建议使用电子病历， 在多个时间点重复的详细问卷数据，以确定具有不同 疾病活动模式（目标1），检查哪些早期生活暴露，包括社会和身体 环境，最能预测疾病（目标2），最后检验这些环境的影响的假设。 暴露通过DNA的甲基化变化传递（目标3和4）。结果将告知未来 研究检查表观遗传变化是否可以用作预测生物标志物，以确定患者可能 或者那些更有可能对治疗有反应的人。

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.