CO4 - Bronchoalveolar Lavage Protein Panel to Detect Beryllium Sensitization and Chronic Beryllium Disease
Maneesh Bhargava (United States)1; Brian Vestal (United States)2; Danielle O Weise (United States)3; Timothy J Griffin (United States)3; Pratik D Jagtap (United States)3; Joshua Macaluso (United States)2; L Ealine Epperson (United States)2; Margaret Mroz (United States)2; Lisa A Maier (United States)2; Li Li (United States)2;
1 - The Ohio State University; 2 - National Jewish Health; 3 - Univeristy of Minnesota;
Keywords: Beryllium health effects; diagnosis; proteomics;
Select the theme: Challenges in Sarcoidosis Diagnosis and Staging
Type: Original Papers
Presentation: Oral Communication

Introduction: Chronic beryllium disease (CBD) is a cell-mediated granulomatous lung disease that mimics pulmonary sarcoidosis. Diagnosis of CBD and its precursor, beryllium sensitization (BeS), relies on biopsy and demonstration of an abnormal immune response to beryllium via the BeLPT, which is performed in few laboratories.

Objectives: To identify biomarkers distinguishing healthy controls (HC) from BeS and CBD

Materials and Methods: Bronchoalveolar lavage fluid (BALF) from 25 HC, 50 BeS, and 50 CBD cases was processed to enrich for medium- and low-abundance proteins, followed by trypsin digestion and Strap–based sample cleanup. Peptide preparations were analyzed on an Orbitrap Eclipse using data-independent acquisition mass spectrometry. Spectral datasets were processed with EncyclopeDIA for protein inference and quantification. Differential abundance modeling was performed with the proDA method, which handles missing values probabilistically. We used variable selection algorithms with 5-fold cross-validation to build models that identify the class labels HC, BeS, or CBD. 

Results: BeS and CBD participants were older, more likely to be male, and have smoked than HC. Compared with BeS, CBD was associated with lower BAL macrophages (74.2 ± 18.2 vs 88.8 ± 9.02%) and higher lymphocytes (24.1 ± 18.0 vs 9.14 ± 7.78%), with no differences in spirometry. Of 2,063 high‑confidence proteins identified at a 1% FDR, 1,799 proteins with less than 25% missing values across samples were retained for analysis. A BALF protein‑only model achieved an AUC of 0.91 for distinguishing HC from BeS and 0.98 for HC from CBD. For discrimination between BeS and CBD, a LASSO‑based classifier incorporating age, sex, and BAL cell counts achieved an AUC of 0.80, which improved to 0.89 with the addition of BALF proteins. A BALF protein‑only model also performed robustly for distinguishing BeS from CBD (AUC = 0.88).

Conclusions: These findings suggest a less invasive diagnostic alternative for BeS and CBD, potentially reducing reliance on lung biopsy and/or BeLPT.