Precision Medicine in Sarcoidosis

摘要 结节病是一种病因不明的全身性炎症性疾病， 肉芽肿在受影响的器官，主要是在肺部。大约30%的结节病患者进展 然而，对疾病易感性或复原力的驱动因素仍然知之甚少。 对未定义抗原的炎症反应被假定为肉芽肿形成的病因， 发病机制已被认为涉及基因-病原体相互作用，但分析单个基因或 微生物还没有被证明适用于诊断所有形式的结节病。而不是一个人。 在某些情况下，疾病可以代表包括病原体的生物体群落之间的相互作用。 肺部微生物组（生活在我们体内和体表的生物群落）和宿主免疫反应。我们提出 了解微生物组/宿主相互作用将为精确医学方法提供策略 结节病这项提案通过研究肺与肺之间的相互作用来解决这一重大差距。 使用多组学方法研究结节病的微生物组、宿主免疫和临床反应--一个关键的 创新战略。我们的初步数据支持我们的新假设。首先我们发现了 微生物组，区分结节病患者与对照组。第二，我们的研究结果表明， 与肺功能下降相关的疾病严重程度的生物标志物。第三，循环分析 无论何种组学分析，出现的主题是结节病的特征是： 与细胞凋亡和自噬相关的通路，这与我们观察到的细胞凋亡减少是一致的。 外周血淋巴细胞丰富和功能性免疫无能。这些数据使我们的总体 假设：以凋亡和自噬为特征的肺部微生物组和宿主免疫相互作用 影响结节病临床进程的途径。这一假设将通过一项观察性前瞻性研究进行检验。 在5个时间点对结节病患者进行验证研究，以促进时间序列分析。目标1和2 分别关注与结节病临床病程相关的肺部微生物组或宿主免疫反应。 在目标3中使用这些数据，将基于宏基因组和 宿主免疫相互作用我们的多组学策略的新颖性和重要性在于构建模型， 精准医学疗法，将生物信息学策略应用于针对特定患者的方法。的 这项研究的长期意义在于确定结节病进展或消退的途径， 建立这些调查结果的数据库，以进一步开发更精确、可测试的模型。

ABSTRACT Sarcoidosis is a systemic inflammatory disease of unknown etiology characterized by non-caseating granulomas in affected organs, primarily in the lungs. Approximately 30% of patients with sarcoidosis progress to debilitating disease; however, the drivers of susceptibility or resilience to disease remain poorly understood. An inflammatory response to an undefined antigen is postulated as the etiology of granuloma formation, and the pathogenesis has been suggested to involve gene-pathogen interaction, yet analysis of single genes or microbes has not proven applicable to diagnosis of all forms of sarcoidosis. Indeed, rather than a single organism, the disease may represent an interaction between the community of organisms that comprise the lung microbiome (community of organisms that live in and on us) and the host immune response. We propose that understanding the microbiome/host interaction will suggest strategies for precision medicine approaches to sarcoidosis. This proposal addresses this significant gap by investigating interactions between the lung microbiome, host immune and clinical responses in sarcoidosis using multiomics approaches – a critically innovative strategy. Our preliminary data support our novel hypotheses. First, we identified distinct lung microbiomes that differentiated patients with sarcoidosis versus controls. Second, our results identified biomarkers of disease severity that were associated with decreased lung function. Third, a recurrent analytic theme that emerged, regardless of the type of -omic analysis, was that sarcoidosis is characterized by pathways related to apoptosis and autophagy, which is consistent with our observation of decreased abundance of peripheral lymphocytes and functional immune anergy. These data led us to our Overall Hypothesis: Lung microbiome and host immune interactions characterized by apoptosis and autophagy pathways influence sarcoidosis clinical course. This hypothesis will be tested by an observational prospective and validation study of sarcoidosis patients at 5 time points to facilitate time series analyses. Aims 1 and 2 focus on lung microbiome or host immune responses, respectively, in relation to clinical course of sarcoidosis. Using these data in Aim 3, predictive models will be constructed based on integrated data of metagenomic and host-immune interactions. The novelty and significance of our multiomics strategy is to construct models for precision medicine therapies to harness bioinformatic strategies into focused, patient-specific approaches. The long-term significance of this study is to define pathways for sarcoidosis progression or resolution, and to develop database of these findings to further develop more precise, testable, models.