This project is designed to address the following hypothesis: Distinct patterns in lung microbiome are characteristic of sarcoidosis phenotypes and reflected in changes in systemic inflammatory responses as measured by peripheral changes in gene transcription. The Specific Aims are: 1. To identify peripheral blood mononuclear cell (PBMC) gene expression patterns that characterize distinct sarcoidosis phenotypes. 2. To determine whether patterns in the lung microbiome are associated with sarcoidosis severity and disease phenotypes 3. To correlate mRNA and microRNA expression patterns in sarcoidosis affected organs with changes in microbiome, clinical parameters and PBMC gene expression patterns 4. To integrate clinical, transcriptomic, and microbiome data to identify novel molecular phenotypes in sarcoidosis.
Sarcoidosis is a systemic disease characterized by the formation of granulomatous lesions, especially in the lungs, liver, skin, and lymph nodes, with a heterogeneous set of clinical manifestations and a variable course 1. Despite significant progress in the understanding of the genetic predisposition and role of immunity, it is still a challenge to explain the clinical presentation of sarcoidosis. Standard clinical assessment, imaging, and pulmonary function tests (PFTs) do not allow prediction of disease course and response to therapy. Furthermore, there are no good long-term therapies. Considering that the interactions between potential infections, changes in systemic inflammation, and patterns in lung microbiome and the different and distinct disease phenotypes in sarcoidosis are not well understood, the Sarcoidosis protocol for the Genomic Research in AAT Deficiency and Sarcoidosis (GRADS) grant (hereafter called GRADS Sarcoidosis protocol) is designed to address the following: Hypothesis Distinct patterns in lung microbiome are characteristic of sarcoidosis phenotypes and reflected in changes in systemic inflammatory responses as measured by peripheral changes in gene transcription. Specific Aims 1. To identify peripheral blood mononuclear cell (PBMC) gene expression patterns that characterize distinct sarcoidosis phenotypes. 2. To determine whether patterns in the lung microbiome are associated with sarcoidosis severity and disease phenotypes 3. To correlate mRNA and microRNA expression patterns in sarcoidosis affected organs with changes in microbiome, clinical parameters and PBMC gene expression patterns 4. To integrate clinical, transcriptomic, and microbiome data to identify novel molecular phenotypes in sarcoidosis. Focusing on accessible PBMCs should enable GRADS researchers to identify markers for disease phenotypes, severity, and outcome. Analysis of lesional transcriptomes (mRNA, microRNA and lincRNA) will add mechanistic insights. High throughput unbiased analysis of the lung microbiome will potentially identify patterns in the lung microbiome that determine disease activity and persistence, as well as response to therapy. Participants are assigned a provisional clinical phenotype upon obtaining consent at time of enrollment by the respective recruiting center. Clinical phenotypes will be reviewed, confirmed, and monitored to ensure achievement of study objectives. Participants who cannot be assigned a clinical phenotype after the initial study visit will be excluded from additional study participation.
Study Type
OBSERVATIONAL
Enrollment
368
Arizona Health Sciences Center
Tucson, Arizona, United States
University of California - San Francisco
San Francisco, California, United States
National Jewish Health
Denver, Colorado, United States
Yale University
New Haven, Connecticut, United States
Johns Hopkins University
Baltimore, Maryland, United States
University of Pennsylvania
Philadelphia, Pennsylvania, United States
University of Pittsburgh
Pittsburgh, Pennsylvania, United States
Medical University of South Caolina
Charleston, South Carolina, United States
Vanderbilt University
Nashville, Tennessee, United States
PBMC Gene Expression
To identify peripheral blood mononuclear cell (PBMC) gene expression patterns that characterize distinct sarcoidosis phenotypes, samples will be run in batches in block designs (equal numbers of phenotypes) and batches will be analyzed independently to determine reproducibility - a subset of samples will be rerun to assure continuity and established normalization algorithms will be applied 1-3. Normalized human transcript (mRNA and microRNA) levels obtained from PBMC will be related to established phenotypes as well as cross phenotype characteristics using linear models, i.e., ANOVA or linear regression using the LIMMA package (http://bioinf.wehi.edu.au) or BRB ArrayTools (http://linus.nci.nih.gov/BRB-ArrayTools.html).
Time frame: Baseline, 6 months, 12 months
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