Molecular characterisation of progressive pulmonary sarcoidosis: protocol for a longitudinal multi-centre study to develop peripheral blood circulating biomarkers for predicting pulmonary sarcoidosis progression.
Sarcoidosis is a heterogeneous granulomatous disease with highly variable clinical trajectories, yet no validated biomarkers exist to distinguish progressive sarcoidosis (P-sarcoidosis) from non-progressive disease (NP-sarcoidosis). This lack of tractable biomarkers limits early risk stratification and impedes therapeutic decision-making. Preliminary data from our group suggest that P-sarcoidosis and NP-sarcoidosis may be differentiated by blood-derived and peripheral blood mononuclear cell (PBMC)-derived molecular signatures, as well as ex vivo granuloma biogenesis in response to putative disease-causing antigens. This protocol describes a multi-omic study aimed at identifying mechanistically grounded, clinically translatable biomarkers that distinguish P-sarcoidosis from NP-sarcoidosis.
We will perform an integrative proteomic and transcriptomic analysis across three biological compartments: ex vivo granuloma model, PBMCs and plasma. Participants with clinically adjudicated P-sarcoidosis or NP-sarcoidosis will provide blood samples for multi-omic profiling. P-sarcoidosis versus NP-sarcoidosis phenotype will be assessed based on changes in spirometry, diffusing capacity for carbon monoxide, chest radiography and need for treatment for pulmonary symptoms. Patient-reported outcomes will also be recorded. Data-driven computational approaches will be used to identify molecular pathways associated with granuloma formation and disease persistence and to develop a classifier that distinguishes P-sarcoidosis from NP-sarcoidosis. Rigorous internal validation, feature-selection procedures and statistical controls for high-dimensional data will be applied. Candidate biomarkers emerging from multi-compartment integration will be prioritised based on biological coherence, reproducibility and clinical feasibility.
The study protocol has been approved by the Biomedical Research Alliance of New York, serving as a single Institutional Review Board (IRB) for the project (IRB # 23-02-503), as well as at National Jewish Health (IRB# HS-4091), University of Minnesota (STUDY00020121/SITE00002051) and The Ohio State University (IRB# 2023X0140). All participants will provide informed consent prior to enrolment. Results will be disseminated through peer-reviewed publications, scientific conferences and presentations to patients and advocacy groups. De-identified datasets and analytic workflows will be shared in accordance with institutional policies and data-sharing agreements.
We will perform an integrative proteomic and transcriptomic analysis across three biological compartments: ex vivo granuloma model, PBMCs and plasma. Participants with clinically adjudicated P-sarcoidosis or NP-sarcoidosis will provide blood samples for multi-omic profiling. P-sarcoidosis versus NP-sarcoidosis phenotype will be assessed based on changes in spirometry, diffusing capacity for carbon monoxide, chest radiography and need for treatment for pulmonary symptoms. Patient-reported outcomes will also be recorded. Data-driven computational approaches will be used to identify molecular pathways associated with granuloma formation and disease persistence and to develop a classifier that distinguishes P-sarcoidosis from NP-sarcoidosis. Rigorous internal validation, feature-selection procedures and statistical controls for high-dimensional data will be applied. Candidate biomarkers emerging from multi-compartment integration will be prioritised based on biological coherence, reproducibility and clinical feasibility.
The study protocol has been approved by the Biomedical Research Alliance of New York, serving as a single Institutional Review Board (IRB) for the project (IRB # 23-02-503), as well as at National Jewish Health (IRB# HS-4091), University of Minnesota (STUDY00020121/SITE00002051) and The Ohio State University (IRB# 2023X0140). All participants will provide informed consent prior to enrolment. Results will be disseminated through peer-reviewed publications, scientific conferences and presentations to patients and advocacy groups. De-identified datasets and analytic workflows will be shared in accordance with institutional policies and data-sharing agreements.
Authors
Bhargava Bhargava, Crouser Crouser, Barkes Barkes, Weise Weise, Perlman Perlman, Epperson Epperson, Griffin Griffin, Jagtap Jagtap, Mehta Mehta, Li Li, Leach Leach, Maier Maier
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