Identification of biologically relevant subtypes of hidradenitis suppurativa

项目摘要 化脓性汗腺炎（HS）是一种被忽视的，流行的，慢性的，耻辱化的，和衰弱的疾病， 最近被列为NIAMS研究的重点。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，有些人因反复爆发疖子而寻求医疗保健 却从未得到诊断这种“隐藏人群”给设计研究带来了挑战， 都是可推广的。精准医疗计划和资源为快速提高我们的 了解HS的生物学原因，并改善HS患者接受的护理。比如说 NIH在开发将遗传数据与EHR联系起来的数据库方面进行了大量投资 包括NHGRI资助的eMERGE网络和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组成部分， 既作为招聘网站，也作为数据和研究中心（5U01HG008680，1OT2OD026556）。接合 愿意贡献纵向数据的研究参与者是精准医学的主要障碍 举措公众使用互联网和社交媒体获取和交流与健康有关的信息 创造了快速有效地聚集大型纵向队列的机会，但重要的是， 与传统研究方法和最佳做法准则的不同之处尚待制定。哥伦比亚 大学是在这些方法的开发和应用的前沿。的一大挑战 实施精准医疗源于那些有着相同诊断但有不同生物学原因的患者 疾病。HS患者的合并症负担很高，我们假设， 倾向于在个体患者中一起存在的基因可用于鉴定生物学相关的疾病亚型。这里 我们将使用三种方法来识别患者的合并症模式， 在EHR中进行的研究结果的普遍性，并使用遗传数据进行生物学验证 合并症，并解决潜在疾病相关性的因果关系。生物医学信息学培训， 基于互联网的调查研究将允许申请人使用EHR数据和互联网资源进行组装 队列进行这些研究，并补充她以前在流行病学，生物统计学，分子生物学， 生物学和人类遗传学，提供跨几个领域的流畅性，这对提高精度至关重要 医学倡议。完成本建议书将实现申请人的长期目标， 培训的目的是在皮肤病治疗中实施精准医学。

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.