Combining genome, function, and phenotype to define the cell type specific gene regulatory architecture of idiopathic pulmonary fibrosis

结合基因组、功能和表型来定义特发性肺纤维化的细胞类型特异性基因调控架构

• 批准号: 10541161
• 负责人: Nicholas Eli Banovich
• 金额: $ 70.13万
• 依托单位: TRANSLATIONAL GENOMICS RESEARCH INST
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-01-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10541161
• 关键词: Address; Adult; Affect; Alleles; American; Architecture; Area; Automobile Driving; Back; Bioinformatics; Biological Assay; Cell Count; Cell Culture System; Cells; Cellular biology; Characteristics; Chromium; Clinical; Clinical Trials; Collagen; Computing Methodologies; Data; Data Set; Development; Diagnosis; Disease; Disease Outcome; Disease Pathway; Disease Progression; Distal; Elderly; Environmental Risk Factor; FDA approved; Gene Expression; Gene Expression Profile; Genes; Genetic; Genetic Transcription; Genetic Variation; Genome; Genomics; Genotype; Graph; Heterogeneity; Human; In Vitro; Individual; Interstitial Lung Diseases; Length; Lung; MUC5B gene; Mediator; Messenger RNA; Molecular; Molecular Biology; Molecular Profiling; Mutation; Organoids; Outcome; Pathogenesis; Pathologic; Pathology; Pathway Analysis; Pathway interactions; Patients; Pattern; Peripheral Blood Mononuclear Cell; Phase; Phenotype; Primary Cell Cultures; Process; Production; Pulmonary Fibrosis; Quality of life; Regulator Genes; Resolution; Respiratory Failure; Role; Sampling; Single Nucleotide Polymorphism; Structure of parenchyma of lung; System; Technology; Telomerase; Validation; Variant; Work; candidate identification; cell type; clinical care; clinical heterogeneity; clinically relevant; disease heterogeneity; disease natural history; disease phenotype; gene regulatory network; genetic predictors; genetic variant; genome wide association study; genome-wide; idiopathic pulmonary fibrosis; improved; innovation; mRNA sequencing; middle age; new technology; novel; peripheral blood; programs; pulmonary function; single-cell RNA sequencing; success; targeted treatment; telomere; transcriptome; transcriptomics

Project Summary Idiopathic pulmonary fibrosis (IPF) is the most common and severe form of interstitial lung disease. IPF occurs in middle-aged and older adults and affects over 50,000 Americans each year. Most IPF patients die from respiratory failure within five years of diagnosis. The current therapies target downstream disease mechanisms, and while they modestly slow the decline in lung function, they have not been shown to improve survival or quality of life for IPF patients. There is considerable heterogeneity of clinical outcomes among IPF patients, and we believe this heterogeneity is due to distinct mechanisms and programs involved in disease initiation that culminate in a common a pathology of end-stage lung fibrosis. As such, the development of transformative treatments hinges on our ability to better understand and target “upstream” disease mechanisms. However, progress to this end has been held back by the limited study of the cell types and molecular changes initiating IPF pathogenesis. Novel technologies have recently been developed that enable quantification of mRNA levels in individual cells to be performed in a parallel, high throughput manner (scRNA- seq). Our proposed studies will leverage these technologies and the heterogeneity of the disease within the IPF lung to determine the mechanisms and mediators that underlie the early pathogenesis of IPF. We will use scRNA-seq to determine the gene expression profiles and programs in non-fibrotic control lungs (n=50), and paired, differentially affected regions of IPF lungs (n=100, paired distal, more fibrotic, vs. proximal, less fibrotic samples). We will use computational methods to group cells into putative cell types based on transcriptional similarity and canonical marker gene expression. We will then quantify the relative abundance of each cell type in these different disease states, and use innovative bioinformatic approaches to determine the gene expression programs that drive different phases of disease pathogenesis. Then, to determine the role of genetic variation in regulating these disease pathways, we will utilize the inter-individual genetic variation present in our sample to identify single nucleotide polymorphisms that are associated with gene expression changes (eQTLs) in each independent cell type. Next, to begin to interrogate the mechanisms underlying disease heterogeneity, we will determine cell-type specific gene expression changes that are associated with genetic predictors of disease outcome (MUC5B genotype, peripheral blood telomere length). Finally, we will define novel disease endotypes based on cell type specific gene expression patterns. The localization and spatial patterns of identified genes will be determined using matched FFPE samples, and key findings will be validated in primary cell/organoid culture systems. This work will generate the most comprehensive molecular characterization of healthy and IPF lungs, and promises to answer fundamental questions about cell types, genetic variants, and gene expression changes driving the idiopathic pulmonary fibrosis pathogenesis.

项目摘要 特发性肺纤维化（IPF）是间质性肺病中最常见和最严重的形式。IPF 发生在中年和老年人，每年影响超过50，000名美国人。大多数IPF患者死亡 在确诊后五年内死于呼吸衰竭目前的治疗针对下游疾病 虽然它们适度地减缓了肺功能的下降，但它们并没有被证明可以改善 IPF患者的生存率或生活质量。IPF之间的临床结局存在相当大的异质性 我们认为这种异质性是由于疾病中涉及的不同机制和程序 其最终导致终末期肺纤维化共同病理学。因此， 变革性治疗取决于我们更好地理解和瞄准“上游”疾病的能力 机制等然而，由于对细胞类型的研究有限， 启动IPF发病机制的分子变化。最近开发了新技术， 在单个细胞中的mRNA水平的定量以平行的高通量方式（scRNA-RNA）进行。 seq）。我们提出的研究将利用这些技术和疾病的异质性， IPF肺，以确定IPF早期发病机制的机制和介质。我们将使用 scRNA-seq以确定非纤维化对照肺（n=50）中的基因表达谱和程序，以及 IPF肺的成对差异性受累区域（n=100，成对远端，纤维化程度更高，对比近端，纤维化程度更低 样品）。我们将使用计算方法，根据转录水平将细胞分组为假定的细胞类型。 相似性和典型标记基因表达。然后我们将量化每种细胞类型的相对丰度 在这些不同的疾病状态，并使用创新的生物信息学方法来确定基因 表达程序驱动疾病发病机制的不同阶段。然后，为了确定 在调节这些疾病通路的遗传变异中，我们将利用个体间的遗传变异， 存在于我们的样本中，以确定与基因表达相关的单核苷酸多态性， 在每个独立的细胞类型的变化（eQTL）。接下来，开始探究 疾病的异质性，我们将确定细胞类型特异性基因表达的变化， 疾病结局的遗传预测因子（MUC 5 B基因型、外周血端粒长度）。最后我们将 基于细胞类型特异性基因表达模式定义新的疾病内型。本地化和 将使用匹配的FFPE样本确定已识别基因的空间模式，关键发现将是 在原代细胞/类器官培养系统中验证。这项工作将产生最全面的分子 表征健康和IPF肺，并有望回答有关细胞类型的基本问题， 遗传变异和基因表达变化驱动特发性肺纤维化发病机制。

项目成果

Coming to "Grp(s)" with Senescence in the Alveolar Epithelium.

来到“Grp(s)”，肺泡上皮细胞衰老。

• DOI: 10.1164/rccm.201910-2052ed
• 发表时间: 2020
• 期刊: American journal of respiratory and critical care medicine
• 影响因子: 24.7
• 作者: Winters,NichelleI;Kropski,JonathanA
• 通讯作者: Kropski,JonathanA

A Unique Cellular Organization of Human Distal Airways and Its Disarray in Chronic Obstructive Pulmonary Disease.

人类远端气道的独特细胞组织及其在慢性阻塞性肺疾病中的混乱。

• DOI: 10.1164/rccm.202207-1384oc
• 发表时间: 2023
• 期刊: American journal of respiratory and critical care medicine
• 影响因子: 24.7
• 作者: Rustam,Samir;Hu,Yang;Mahjour,SeyedBabak;Rendeiro,AndreF;Ravichandran,Hiranmayi;Urso,Andreacarola;D'Ovidio,Frank;Martinez,FernandoJ;Altorki,NasserK;Richmond,Bradley;Polosukhin,Vasiliy;Kropski,JonathanA;Blackwell,TimothyS;Ran
• 通讯作者: Ran

Genome-Wide Association Studies in Idiopathic Pulmonary Fibrosis: Bridging the Gap between Sequence and Consequence.

特发性肺纤维化的全基因组关联研究：弥合序列和后果之间的差距。

• DOI: 10.1164/rccm.201911-2286ed
• 发表时间: 2020
• 期刊: American journal of respiratory and critical care medicine
• 影响因子: 24.7
• 作者: Spagnolo,Paolo;Kropski,JonathanA
• 通讯作者: Kropski,JonathanA

Cell type-specific and disease-associated eQTL in the human lung.

人肺中细胞类型特异性和疾病相关的 eQTL。

• DOI: 10.1101/2023.03.17.533161
• 发表时间: 2023
• 期刊: bioRxiv : the preprint server for biology
• 作者: Natri,HeiniM;DelAzodi,ChristinaB;Peter,Lance;Taylor,ChaseJ;Chugh,Sagrika;Kendle,Robert;Chung,Mei-I;Flaherty,DavidK;Matlock,BrittanyK;Calvi,CarlaL;Blackwell,TimothyS;Ware,LorraineB;Bacchetta,Matthew;Walia,Rajat;Shaver,
• 通讯作者: Shaver,

Multiplatform Single-Cell Analysis Identifies Immune Cell Types Enhanced in Pulmonary Fibrosis.

多平台单细胞分析可识别肺纤维化中增强的免疫细胞类型。

• DOI: 10.1165/rcmb.2021-0418oc
• 发表时间: 2022
• 期刊: American journal of respiratory cell and molecular biology
• 影响因子: 6.4
• 作者: Serezani,AnaPM;Pascoalino,BrunoD;Bazzano,JuliaMR;Vowell,KatherineN;Tanjore,Harikrishna;Taylor,ChaseJ;Calvi,CarlaL;McCall,AScott;Bacchetta,MatthewD;Shaver,CiaraM;Ware,LorraineB;Salisbury,MargaretL;Banovich,NicholasE