Project 1

尽管随着生物制剂的出现，重症哮喘(SA)的治疗取得了许多进展，但仍有 由于对潜在的免疫和分子异常的了解不完全，仍然存在挑战。 为此，我们分析了重症患者的支气管肺泡灌洗(BAL)细胞。 哮喘研究计划(SARP)以及P01资助的IMSA(重症患者的免疫机制 哮喘)计划。此外，我们还利用Bulk RNA-seq方法研究了这些细胞的转录组。首字母 对SARP队列的研究表明，35-40%的SA患者的BAL细胞具有高的1型 (T1)/干扰素-g免疫标志和干扰素-g激活的STAT1在合作所致的激素不敏感中的作用 与糖皮质激素受体(GR)有关。IMSA队列中41名受试者的BAL细胞质量 细胞学/细胞学和下游生物信息学分析允许将SA患者分成两组 (PGS)、pg2和pG3，表现出不同的免疫学特征。Pg2组表现出更高的先天水平 免疫应答以FceRI+IL-4+细胞为主，而PG3以淋巴细胞为主 以干扰素-g+CD4+和CD8+T细胞数量增加为特征，其中包括组织驻留记忆 (TRM)细胞。免疫细胞通过其转录片段的去卷积与基因模块相联系。 数据使用我们的新算法ICLite。模块相关基因表达提示FceRI-和 IL-7信号在pg2和共刺激分子阳性的先天细胞产生细胞因子中的作用 PG3中TRMS产生干扰素-g的调控。在临床上，对SA患者的治疗反应 尽管接受治疗的患者有相似的生物标志物图谱，但生物学上的dupilumab也强调了异质性。 因此，鉴于对具有特定免疫表型的SA患者的不同免疫表型的新见解 转录本签名，我们现在有机会以精细的分辨率、免疫学和 从分子上讲，dupilumab如何不同地影响局部免疫(Proj.1)和上皮性(投影2)表型 在表现出相似生物标记物特征但对治疗没有相似反应的患者中。总而言之， 这些数据允许我们假设有两种不同的免疫机制，一种是由FceRI+先天调节的 免疫细胞与呼吸道上皮细胞结合，第二个通过T细胞，它们对 上皮细胞共同决定SA。为了解决这一假设，项目1的具体目标是： 目的1.用CITE-SEQ和TCR-SEQ在高分辨率下表征呼吸道免疫细胞并确定其影响 杜匹罗单抗对免疫表型的影响。目的2.确定诱发先天免疫细胞驱动的SA的机制 使用一种新的真菌蛋白酶驱动的模型进行表型分析。目标3.确定调节T1高的机制 使用已建立的HDM+环二核苷酸驱动模型的适应性免疫反应。总体而言， 研究结果将在单细胞水平上限定免疫反应和治疗反应的异质性 利用新的实验模型建立驱动不同免疫表型的关键分子/途径。

Despite many advancements in the treatment of severe asthma (SA) with the advent of biologics, there still remain challenges because of incomplete understanding of the underlying immune and molecular aberrations. Towards this end, we analyzed the bronchoalveolar lavage (BAL) cells of patients enrolled in the severe asthma research program (SARP) and also of those in the P01-funded IMSA (Immune Mechanisms in Severe Asthma) program. In addition, we studied the transcriptome of these cells using bulk RNA-seq methods. Initial studies of the SARP cohort revealed that the BAL cells in 35-40% of SA patients harbor a high Type 1 (T1)/IFN-g immune signature and implicated IFN-g-activated STAT1 in steroid insensitivity due to co-operation with the glucocorticoid receptor (GR). Subjecting the BAL cells of 41 subjects in the IMSA cohort to mass cytometry/CyTOF and downstream bioinformatic analysis allowed clustering of the SA patients into two groups (PGs), PG2 and PG3, displaying distinct immune profiles. The PG2 group showed a heightened innate immune response dominated by FceRI+IL-4+ cells while PG3 was a lymphocyte-dominated group characterized by increased numbers of IFN-g+ CD4+ and CD8+ T cells, which included tissue-resident memory (TRM) cells. The immune cells were associated with gene modules by deconvolution of their transcriptomic data using our novel algorithm, ICLite. Module-associated gene expression suggests importance of FceRI- and IL-7-signaling in cytokine production by innate cells in PG2 and of co-stimulatory molecules in positive regulation of IFN-g production from TRMs in PG3. In the clinic, response to treatment of SA patients with the biologic, dupilumab, also highlights heterogeneity despite similar biomarker profiles of the treated patients. Thus, given the novel insight gained about distinct immune phenotypes of SA patients with specific transcriptomic signatures, we now have the opportunity to determine in fine resolution, immunologically and molecularly, how dupilumab differentially impacts the local immune (Proj. 1) and epithelial (Proj. 2) phenotypes in patients who show similar biomarker profiles and yet do not respond similarly to treatment. Collectively, these data allow us to hypothesize that two distinct immune mechanisms, one regulated by FceRI+ innate immune cells in conjunction with airway epithelial cells, and the second by T cells, with their impact on epithelial cells, collectively determines SA. To address this hypothesis, the specific aims of Project 1 are to: Aim 1. Characterize airway immune cells in high-resolution by CITE-seq and TCR-seq and determine impact of dupilumab on immune phenotype. Aim 2. Determine mechanisms that induce innate immune cell-driven SA phenotype using a novel fungal protease-driven model. Aim 3. Determine mechanisms that regulate a T1high adaptive immune response using an established HDM+cyclic dinucleotide-driven model. Collectively, the findings will qualify heterogeneity in immune response and response to therapy at the single cell level and establish key molecules/pathways that drive distinct immune phenotypes using novel experimental models.