Comprehensive proteomic classifier for molecular characterisation of pulmonary sarcoidosis: protocol for a longitudinal multi-centre study to evaluate bronchoalveolar fluid and cell diagnostic and prognostic biomarkers of pulmonary sarcoidosis.
Sarcoidosis is a multisystem disorder with variable presentation and disease course. Diagnosis requires the exclusion of other causes of granulomatous inflammation. Current clinical management is often fraught with diagnostic uncertainy and the lack of tools to predict pulmonary disease progression. To address these challenges, we designed a study using data from bronchoalveolar lavage (BAL) fluid and cells to develop diagnostic and prognostic tools in patients with pulmonary sarcoidosis.
This multicentre study will include discovery and validation cohorts of healthy controls, interstitial lung disease controls and pulmonary sarcoidosis cases from three study sites. Sarcoidosis participants will be grouped into progressive and non-progressive pulmonary disease based on changes in pulmonary function testing, chest radiographs or treatment requirements. The discovery cohort consists of participants with existing BAL fluid, BAL cells, and clinical datasets; the validation cohort will be prospectively enrolled and participants will consent for BAL collection from either a clinical or research bronchoscopy. Untargeted proteomic profiling of BALF along with statistical modelling with variable selection techniques will generate a classifier for diagnosis and prognosis. Targeted proteomics using parallel reaction monitoring-mass spectrometry will be used for internal and external validation. Additionally, BAL cell single-cell gene-expression analysis using Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) will be integrated with proteome-wide data to elucidate cell-specific pathways implicated in the development and progression of sarcoidosis.
The study will be conducted in accordance with Good Clinical Practice and the Declaration of Helsinki. The protocol has been approved by the Biomedical Research Alliance of New York Institutional Review Board (IRB), which serves as the single IRB across all study sites. The findings of this study will be presented as abstracts at scientific meetings and summarised in peer-reviewed journal manuscripts.
This multicentre study will include discovery and validation cohorts of healthy controls, interstitial lung disease controls and pulmonary sarcoidosis cases from three study sites. Sarcoidosis participants will be grouped into progressive and non-progressive pulmonary disease based on changes in pulmonary function testing, chest radiographs or treatment requirements. The discovery cohort consists of participants with existing BAL fluid, BAL cells, and clinical datasets; the validation cohort will be prospectively enrolled and participants will consent for BAL collection from either a clinical or research bronchoscopy. Untargeted proteomic profiling of BALF along with statistical modelling with variable selection techniques will generate a classifier for diagnosis and prognosis. Targeted proteomics using parallel reaction monitoring-mass spectrometry will be used for internal and external validation. Additionally, BAL cell single-cell gene-expression analysis using Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) will be integrated with proteome-wide data to elucidate cell-specific pathways implicated in the development and progression of sarcoidosis.
The study will be conducted in accordance with Good Clinical Practice and the Declaration of Helsinki. The protocol has been approved by the Biomedical Research Alliance of New York Institutional Review Board (IRB), which serves as the single IRB across all study sites. The findings of this study will be presented as abstracts at scientific meetings and summarised in peer-reviewed journal manuscripts.
Authors
Bhargava Bhargava, Weise Weise, Barkes Barkes, Jagtap Jagtap, Mehta Mehta, Lock Lock, Kakoty Kakoty, Perlman Perlman, Dincer Dincer, Restrepo Restrepo, Griffin Griffin, Fingerlin Fingerlin, Li Li, King-Biggs King-Biggs, Maier Maier
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