Predictive Models of Beryllium Sensitization and Chronic Beryllium Disease

铍致敏和慢性铍病的预测模型

• 批准号: 10736862
• 负责人: Maneesh Bhargava
• 金额: $ 241.35万
• 依托单位: NATIONAL JEWISH HEALTH
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-10 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10736862
• 关键词: Antigens; Beryllium; Bioinformatics; Biological; Biological Models; Biopsy; Bronchoalveolar Lavage; Bronchoalveolar Lavage Fluid; CD4 Positive T Lymphocytes; Cells; Certification; Cessation of life; Chronic berylliosis; Clinical; Clinical Data; Computational Biology; Coupled; Coupling; Data; Data Set; Diagnosis; Disease; Early Diagnosis; Enrollment; Evaluation; Exhibits; Fibrosis; Future; Gene Expression; Gene Proteins; General Population; Genetic Predisposition to Disease; Genetic Transcription; Genomics; Goals; Granulomatous; HLA-DPB1 gene; Health; Immune; Immune response; Impairment; In Vitro; Individual; Industry; Link; Lung; Lung diseases; Lymphocyte; Macrophage; Mass Spectrum Analysis; Mediating; Metals; Modeling; Morbidity - disease rate; Nature; Organ; Other Genetics; Pathogenicity; Pathway interactions; Patients; Performance; Persons; Population; Proteins; Proteome; Proteomics; Public Health; Pulmonary Inflammation; Quality of life; Regulation; Research; Research Personnel; Resolution; Respiratory Failure; Risk; Sampling; Signal Transduction; Sirtuins; Structure; System; Testing; Translating; Validation; Variant; Work; Workplace; clinical care; cohort; diagnostic tool; follow-up; follower of religion Jewish; genetic variant; granulomatous lung disease; improved; innovation; lymphocyte proliferation; mortality; novel; predictive modeling; programmed cell death protein 1; protein expression; rapid detection; recruit; single-cell RNA sequencing; transcriptome; transcriptome sequencing

PROJECT SUMMARY/ABSTRACT Beryllium (Be) is used in a several industries and US is the largest exporter of Be in the world. Despite mitigation strategies, Be exposure at workplace results in Be sensitization (BeS) and Chronic Beryllium Disease (CBD). CBD is an important understudied organ-specific immune-mediated disease characterized by granulomatous lung inflammation, fibrosis, and death. Hence, CBD is a public health concern resulting in promulgation of new exposures standards recently. BeS develops in up to 20% of Be-exposed individuals and progresses to CBD 50-100% of these at-risk individuals. The goal of this study is to define the novel lung compartment-specific gene-protein pathways, which will narrow the existing gap in understanding of Be lung disease and form the basis of a clinically viable models (classifiers) to identify BeS, CBD and predict progression of BeS to CBD. This projects hypothesis is that systematic characterization of lung compartment- specific changes will identify novel pathways linked to BeS, CBD and the progression of BeS to CBD. The investigators posit that the proteins in these pathways would provide clinically viable models (classifiers) that will discriminate between healthy controls, BeS, and CBD. In Aim 1, the study will determine the systems level, lung compartment-specific, gene-protein changes linked to BeS and CBD by analyzing BAL cells from a Discovery Cohort (CBD=50, BeS=50, healthy controls=25). This aim will Identify the transcriptional and global protein changes using contemporary high-resolution mass-spectrometry coupled with advanced computational biology and bioinformatics. A combination of single cell RNA sequencing and innovative expression deconvolution will define cell-specific transcriptional changes implicated in BeS and CBD. Furthermore, the research team will integrate transcription and protein expression to identify the biological pathways associated with Be-induced lung disease. The study uses the same Discovery Cohort, and an independent Validation Cohort of subjects already enrolled in Aim 2, to develop and validate a comprehensive BAL fluid classifier of BeS and CBD. Specifically, the Discovery Cohort will be used to construct and internally validate a multicomponent classifier that discriminates healthy controls. In addition, this classifier will be externally validated in the Validation Cohort of CBD (n=50), BeS (n=50), and healthy controls (n=25). In Aim 3, the study evaluates the stability of the classifier of BeS and CBD and develops predictive models of progression from BeS to CBD in subjects with longitudinal clinical data and BAL fluid already available. A group of BeS cases who on follow-up developed CBD will be compared to BeS cases who do not develop CBD to build a model that predicts BeS progression. At the completion of this project, the study findings will be poised to translate to clinical care for the rapid detection of CBD and BeS. Further, it will identify novel pathways associated with Be lung disease that can be tested in future structure-function studies in model systems of Be lung disease.

项目总结/摘要 铍（Be）被广泛应用于多个行业，美国是世界上最大的铍出口国。尽管 缓解策略，在工作场所的Be暴露导致Be敏感（BeS）和慢性铍中毒 疾病（CBD）。CBD是一种重要的未充分研究的器官特异性免疫介导的疾病，其特征在于 肉芽肿性肺部炎症、纤维化和死亡。因此，CBD是一个公共卫生问题， 新的风险暴露标准的颁布。高达20%的铍暴露个体会出现铍硫综合征， 这些高危人群中有50-100%进展为CBD。本研究的目的是确定新肺 区室特异性基因-蛋白质通路，这将缩小现有的差距，了解肺 疾病和形式的基础上，临床可行的模型（分类），以确定BeS，CBD和预测 BeS向CBD的发展。这个项目的假设是，肺室的系统表征- 具体的变化将确定与BeS，CBD和BeS到CBD的进展有关的新途径。的 研究人员认为，这些途径中的蛋白质将提供临床上可行的模型（分类器）， 将区分健康对照、BeS和CBD。在目标1中，研究将确定系统级别， 肺室特异性，基因蛋白质的变化与BeS和CBD通过分析BAL细胞从一个 发现队列（CBD=50，BeS=50，健康对照=25）。这一目标将确定转录和全球 蛋白质的变化使用当代高分辨率质谱结合先进的计算 生物学和生物信息学。单细胞RNA测序和创新表达的结合 解卷积将定义涉及BeS和CBD的细胞特异性转录变化。而且 研究小组将整合转录和蛋白质表达，以确定相关的生物途径 铍诱发的肺病该研究使用相同的发现队列和独立的验证 已入组目标2的受试者队列，以开发和验证一种全面的BAL液体分类器， BeS和CBD。具体而言，发现队列将用于构建和内部验证 多组分分类器，用于区分健康对照。此外，该分类器将在外部 在CBD（n=50）、BeS（n=50）和健康对照（n=25）的验证队列中验证。目标3：研究 评估了BeS和CBD分类器的稳定性，并开发了从 在具有纵向临床数据和BAL液可用的受试者中，将BeS改为CBD。一组BeS病例 将后续开发CBD的患者与未开发CBD的BeS病例进行比较，以建立模型 能预测BeS进程在这个项目完成后，研究结果将转化为 用于临床快速检测CBD和BeS。此外，它将确定与Be相关的新途径， 肺疾病，可以在未来的结构-功能研究中进行测试，在模型系统的Be肺病。