Cell epigenetics & communication in systemic sclerosis and localized scleroderma skin disease

细胞表观遗传学

基本信息

批准号：
10404143
负责人：
ROBERT A. LAFYATIS
金额：
$ 30.21万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-20 至 2027-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10404143
关键词：
Adult Aftercare Automobile Driving Binding Biological Assay Biological Markers Biopsy Blood Vessels CCL18 gene Cells Child Chromatin Chromatin Structure Cicatrix Clinical Collection Communication Computing Methodologies Contracture Cutaneous Cutaneous sclerosis DNA Data Data Set Dermal Diffuse Drug Targeting Epigenetic Process FOSL2 gene FOXP1 gene Fibroblasts Gene Expression Genes Genome HIF1A gene IL6 gene Immune In Vitro Inflammatory Interleukin-6 Interstitial Lung Diseases Joints Lead Light Link Localized scleroderma Lung Lung diseases MADH3 gene Macrophage Activation Measures Mediator of activation protein Methodology Molecular Morbidity - disease rate Myelogenous Myeloid Cells Myofibroblast Pain Pathogenesis Pathway interactions Patients Phenotype Population Predictive Factor Process Profibrotic signal Regulon Rheumatism Role SFRP4 gene STAT1 gene Sampling Severity of illness Signal Transduction Skin Small Nuclear RNA Source Systemic Scleroderma Systemic disease Systems Biology THBS1 gene Transposase connective tissue growth factor cytokine differential expression drug development epigenome functional disability insight interest knock-down macrophage mortality novel predictive marker progenitor single cell analysis single-cell RNA sequencing skin disorder skin fibrosis tocilizumab tool transcription factor transcriptome transcriptomics translational study

项目摘要

Skin fibrosis in systemic sclerosis (SSc) leads to significant morbidity resulting from disfiguring, painful and itchy skin, and joint contractures. We have recently shown by single cell RNA-sequencing (scRNA-seq) that SSc dermal fibroblasts (expressing increased THBS1, PRSS23) and dermal myofibroblasts (also expressing increased SFRP4, ADAM12, TNFSF18 and CTGF) arise from SFRP2-expressing progenitors found in healthy control skin. These studies provide a framework for understanding the profibrotic drivers of these cell states. Transcription factors (TFs) are pivotal in regulating gene expression and provide a powerful landmark for these cell states. Using SCENIC, a computational method developed for detecting TF-associated regulatory networks (regulons) in single cell datasets, we identified putative TFs driving myofibroblast differentiation: FOXP1, HIF1A, IRF7, STAT1 and FOSL2. Additionally, in preliminary results we employed Assay for Transposase Accessible Chromatin by Sequencing (scATAC-seq) data supporting the importance of these TFs in SSc myofibroblast differentiation. In our first aim, we will assess the importance of these TFs in further multiome studies, and confirm their roles in myofibroblast differentiation by measuring the effects of TF knock-down on fibroblast transcriptome and epigenome. Markers of macrophage activation correlate strongly with the main clinical measure of skin disease severity, the modified Rodnan skin score (MRSS), suggesting that macrophages deliver profibrotic signals to drive myofibroblast differentiation. Recent studies in SSc-ILD have confirmed IL-6 in pathogenesis of lung disease and we see its downstream target CCL18 also upregulated in skin macrophages. In our second aim, we will use a novel system biology methodology, CausER, to analyze latent factors regulating the macrophage-fibroblast interaction and generate snRNA-seq data before and after tocilizumab to better understand the role of IL-6 in activating profibrotic macrophages in SSc skin. We expect that this will inform the similar process occurring in SSc-interstitial lung disease. Localized scleroderma (LS) continues to cause disfiguring and functional disabilities in children as well as adults. Our preliminary results implicate IFNg as activating macrophages and fibroblasts in LS skin. In aim 3, using similar approaches to study of SSc, we will compare the immune and non-immune cell populations in LS to SSc skin. First, we will combine our existing LS (n=14), SSc (n=27) and healthy control (n=14) scRNA-seq datasets, and examine differences in fibroblast and myeloid cell transcriptome-phenotypes and differentially expressed genes. Then as in aim 2, we will employ CausER to identify latent factors regulating the interaction between these cells. We will then identify TFs regulating myeloid and fibroblast phenotypes using SCENIC and multiome. We expect these studies of LS to provide new insights into the cytokines and intracellular pathways activating myofibroblasts that lead to skin fibrosis in these patients. The proposed studies will be strongly supported by clinical and biosample collection through Core B and the systems biology expertise by Drs. Singh and Das in core C.

系统性硬化症 (SSc) 中的皮肤纤维化会导致毁容、疼痛和瘙痒等严重并发症皮肤、关节挛缩。我们最近通过单细胞 RNA 测序 (scRNA-seq) 表明 SSc 真皮成纤维细胞（表达增加的 THBS1、PRSS23）和真皮肌成纤维细胞（也表达增加的 SFRP4、ADAM12、TNFSF18 和 CTGF）源自健康人中发现的表达 SFRP2 的祖细胞控制皮肤。这些研究为理解这些细胞状态的促纤维化驱动因素提供了一个框架。转录因子 (TF) 在调节基因表达方面发挥着关键作用，并为这些基因表达提供了强有力的里程碑。细胞状态。使用 SCENIC，一种为检测 TF 相关调控网络而开发的计算方法在单细胞数据集中，我们确定了驱动肌成纤维细胞分化的推定 TF：FOXP1、HIF1A、 IRF7、STAT1 和 FOSL2。此外，在初步结果中，我们采用了转座酶可及性分析染色质测序 (scATAC-seq) 数据支持这些 TF 在 SSc 肌成纤维细胞中的重要性差异化。在我们的第一个目标中，我们将评估这些转录因子在进一步的多组研究中的重要性，并确认通过测量 TF 敲低对成纤维细胞转录组的影响来了解它们在肌成纤维细胞分化中的作用和表观基因组。巨噬细胞活化标志物与皮肤的主要临床指标密切相关疾病严重程度，改良的 Rodnan 皮肤评分 (MRSS)，表明巨噬细胞可促进纤维化驱动肌成纤维细胞分化的信号。最近 SSc-ILD 的研究证实了 IL-6 在 SSc-ILD 发病机制中的作用肺部疾病，我们发现其下游靶点 CCL18 在皮肤巨噬细胞中也上调。在我们的第二个目标，我们将使用一种新颖的系统生物学方法 CausER 来分析调节巨噬细胞-成纤维细胞相互作用并在托珠单抗前后生成 snRNA-seq 数据，以更好地了解 IL-6 在激活 SSc 皮肤促纤维化巨噬细胞中的作用。我们希望这将告知类似的过程也发生在 SSc-间质性肺疾病中。局限性硬皮病 (LS) 继续导致儿童和成人的毁容和功能障碍。我们的初步结果表明 IFNg 激活 LS 皮肤中的巨噬细胞和成纤维细胞。在目标 3 中，使用类似的方法来研究 SSc，我们将比较 LS 和 SSc 皮肤中的免疫和非免疫细胞群。首先，我们将结合我们现有的LS (n=14)、SSc (n=27) 和健康对照 (n=14) scRNA-seq 数据集，并检查成纤维细胞和骨髓细胞转录组表型和差异表达基因。然后如目标 2 所示，我们将采用 CausER 识别调节这些细胞之间相互作用的潜在因素。然后我们将识别 TF 使用 SCENIC 和 multiome 调节骨髓细胞和成纤维细胞表型。我们期望 LS 的这些研究能够为激活肌成纤维细胞的细胞因子和细胞内途径提供新的见解，从而导致皮肤这些患者的纤维化。拟议的研究将得到临床和生物样本收集的大力支持通过核心 B 和博士的系统生物学专业知识。核心 C 中的 Singh 和 Das。