Comprehensive Proteomic Classifier for the Molecular Characterization of Pulmonary Sarcoidosis

PROJECT SUMMARY
The primary goal of this study is to construct predictive models (classifiers) of pulmonary sarcoidosis and
progressive (P) vs. non-progressive (NP) disease that will ultimately serve to improve outcomes of pulmonary
sarcoidosis. We have assembled a unique investigative team with expertise in proteomics, immunology,
genomics, sarcoidosis clinical care, as well as bioinformatics and statistics. Sarcoidosis is a diagnostically
challenging immune-mediated systemic disease. It results in significant morbidity and mortality, primarily due to
progressive pulmonary disease, although the factors that drive pulmonary disease and P vs. NP disease are
unknown. The strategies to treat pulmonary sarcoidosis, including the triggers to initiate treatment, are non-
specific; treatment usually relies on suppressing the immune system with corticosteroids and is associated with
considerable side-effects. Transcriptional changes in the lung and blood have defined a signature of P disease
in cross-sectional studies. Since proteins are the main effectors of cellular function and their alterations result in
disruption of biologic systems and disease development, they are a logical source of biomarkers. Our preliminary
data from bronchoalveolar lavage fluid and cells demonstrate significant proteome wide alterations in pulmonary
sarcoidosis vs controls and P vs NP disease. We hypothesize that effective markers of disease and those
distinguishing progressive from non-progressive disease will reflect biological processes active in
disease and progression. Secondarily, by characterizing cellular proteins, global phosphorylation events and
cell-specific RNA expression, we will define known proteins/gene/pathways such as the PI3K/Akt/mTOR and
other serine-threonine kinase signaling mechanisms as well as novel pathogenic proteins/genes, such as
endocytic and aryl hydrocarbon receptor signaling, which will have implications for mechanism and therapy. We
will use high-resolution mass spectrometry (MS), advanced bioinformatics and computational tools in well-
phenotyped sarcoidosis patients. In Aim 1, we will determine a disease-specific classifier for diagnosing
sarcoidosis using a Discovery Cohort of sarcoidosis cases and diseased and healthy controls (already recruited)
for the development and Validation Cohort (recruited for this study) of sarcoidosis cases and controls to verify
and optimize the classifier performance. In Aim 2, we will identify a protein classifier of P vs NP disease using
the same approach as in Aim 2. In Aim 3 we will use a novel single-cell RNA-sequencing approach, CITE-seq
to identify transcription from specific cells, and integrate it with protein changes, including examination of global
phosphorylation events to identify kinase signaling and discover cell-specific cellular proteins/genes associated
with disease and progression in a subset of our Validation Cohort. At the end of this study, we will have defined
diagnostic biomarkers of disease and progression that can be translated easily to the clinic. We will also gain
insights into the sarcoidosis pulmonary proteins and transcripts that may serve as potential therapeutic targets
and provide potential mechanistic information with future study.

Grant Number: 7R01HL153613-05
NIH Institute/Center: NIH
Principal Investigator: Maneesh Bhargava