Predictive Models of Beryllium Sensitization and Chronic Beryllium Disease

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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.