Identification of biologically relevant subtypes of hidradenitis suppurativa

项目摘要 化脓性汗腺炎(HS)是一种被忽视、流行、慢性、污名化和衰弱的疾病，具有 最近被NIAMS列为优先研究对象。有证据表明，一些HS患者选择自我管理 症状仍然与医疗保健无关，一些人因反复爆发脓肿而寻求医疗护理 但从来没有得到过诊断。这种“隐藏的人群”给设计研究带来了挑战， 是可以概括的。精准医疗计划和资源提供了迅速增加我们的 了解HS的生物学原因，并改善HS患者的护理。例如， NIH已经在开发将基因数据与EHR联系起来的数据存储库方面进行了大量投资 对于数十万患者，包括NHGRI资助的Emerge Network和NIH资助的ALL 我们的研究计划。哥伦比亚大学的调查人员是这些全国性项目的重要成员， 既是招聘网站，也是数据和研究中心(5U01HG008680，1OT2OD026556)。引人入胜 愿意贡献纵向数据的研究参与者是精准医学的主要障碍 首创精神。公众利用互联网和社交媒体获取和交流与健康有关的信息 创造了快速高效地组装大型纵向队列的机会，但也存在重要的 与传统研究方法和最佳实践指南的不同之处尚未确定。哥伦比亚 大学在这些方法的开发和应用方面走在了前列。面临的一个重大挑战 实施精准医学源于诊断相同但生物原因不同的患者 疾病的威胁。HS患者有很高的合并症负担，我们假设 往往出现在单个患者身上，可以用来识别生物相关的疾病亚型。这里 我们将使用三种方法来确定患者体内的并存模式，以表征 在电子病历中进行的研究结果的概括性，并使用遗传数据进行生物学验证 并解决疾病关联背后的因果关系。生物医学信息学和 基于互联网的调查研究将允许申请者使用电子病历数据和互联网资源进行汇编 进行这些研究，并补充了她之前在流行病学、生物统计学、分子生物学方面的培训 生物学和人类遗传学，提供对提高精确度至关重要的几个领域的流畅性 医学倡议。完成这项建议将实现申请者获得高级 旨在皮肤病治疗中实施精准医学的培训。

Project Summary Hidradenitis suppurativa (HS) is a neglected, prevalent, chronic, stigmatizing, and debilitating disease that has recently been prioritized for study by NIAMS. Evidence suggests that some HS patients choose to self-manage symptoms remaining unconnected to healthcare, and some seek medical care for repeated outbreaks of boils but never receive a diagnosis. Such ‘hidden populations’ create challenges for designing research studies that are generalizable. Precision medicine initiatives and resources offer opportunities to rapidly increase our knowledge about biological causes of HS and to improve the care that HS patients receive. For example, the NIH has made considerable investments in the development of data repositories that link genetic data to EHR for hundreds of thousands of patients, including the NHGRI-funded eMERGE Network and the NIH-funded All of Us Research Program. Columbia University investigators are integral members of these nationwide programs, both as a recruitment site, as well as a data and research center (5U01HG008680, 1OT2OD026556). Engaging research participants who are willing to contribute longitudinal data is a major obstacle to precision medicine initiatives. The public’s use of the Internet and social media to obtain and exchange health-related information has created opportunities to rapidly and efficiently assemble large longitudinal cohorts, yet there are important differences from traditional research methods and best practice guidelines have yet to be developed. Columbia University is at the forefront of the development and application of these methods. A major challenge to implementing precision medicine arises from patients who share a diagnosis but have different biological causes of disease. HS patients have a high burden of comorbidities and we hypothesize that sets of comorbidities that tend to present together in individual patients can be used to identify biologically relevant disease subtypes. Here we will use three approaches to identify patterns of comorbidities within patients, to characterize the generalizability of the results from studies conducted in EHR, and to use genetic data to biologically validate comorbidities and resolve causality underlying disease associations. Training in biomedical informatics and Internet-based survey research will allow the applicant to use EHR data and Internet resources for assembling cohorts to conduct these studies, and complement her previous training in epidemiology, biostatistics, molecular biology and human genetics, providing fluency across several domains that are crucial for advancing precision medicine initiatives. Completion of this proposal will achieve the applicant’s long-term goal of obtaining advanced training aimed at implementing precision medicine in the treatment of skin disease.