Sarcoidosis
Conditions
Keywords
Genomics, Microbiome, Microflora, Virome
Brief summary
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.
Detailed description
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.
Interventions
None listed
Sponsors
National Heart, Lung, and Blood Institute (NHLBI)
University of Pittsburgh
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 85 Years
Healthy volunteers
No
Inclusion criteria
1. Age between the ages of 18 and 85. 2. Have a diagnosis of sarcoidosis established by consensus criteria (ATS/ERS), confirmed by either biopsy or by manifestations consistent with acute sarcoidosis (Löfgren's syndrome) in absence of other known diagnosis. OR Have a suspected diagnosis of sarcoidosis and is scheduled to undergo a biopsy procedure to confirm a diagnosis of sarcoidosis using the same consensus criteria (ATS/ERS). 3. Able to tolerate and willing to undergo study procedures. 4. Be capable of understanding study forms. 5. Provide signed informed consent.
Exclusion criteria
1. History of comorbid condition severe enough to significantly increase risks based on investigator discretion. 2. Currently an active smoker. 3. Undergoing bronchoscopy (clinical or research) with any one of the following: 1. severe pulmonary impairment (\<50% predicted FVC, \<1 L FEV1; DLco \<40% predicted, resting hypoxemia \<92% with or without supplemental oxygen) 2. other co-morbid disease that would preclude bronchoscopy. 3. hypersensitivity to or intolerance of any of the drugs required for sedation during conscious sedation bronchoscopy. 4. Known systemic autoimmune disease such as rheumatoid arthritis, lupus, scleroderma, Sjögrens, etc. 5. Found to have an alternative interstitial lung disease during evaluation and/or screening. 6. Diagnosis of unstable cardiovascular disease including myocardial infarction in the past 6 weeks, uncontrolled congestive heart failure, or uncontrolled arrhythmia 7. Use of anticoagulation (patients on warfarin or clopidogrel will be excluded, patients on aspirin alone can be studied even with concurrent use) 8. Dementia or other cognitive dysfunction which in the opinion of the investigator would prevent the participant from consenting to the study or completing study procedures 9. Non-Sarcoidosis pulmonary disease (e.g., rheumatoid arthritis, lupus, scleroderma) that, in the opinion of the investigator, limits the interpretability of the analysis of sarcoidosis pulmonary disease 10. Primary biliary cirrhosis or autoimmune hepatitis 11. Crohn's disease 12. Chronic beryllium disease 13. Have an active bacterial or viral infection at time of screening. 14. Have an active or ongoing serious infection, including HIV, HBV and HCV 15. Active tuberculosis or are taking any medication for tuberculosis 16. Have a history of demyelinating diseases, lymphoproliferative diseases, or other malignancies other than presumed cured non-metastatic skin cancer 17. Have evidence of a likely malignancy on chest x-ray 18. Are currently pregnant at time of screening 19. Currently institutionalized (e.g., prisons, long-term care facilities) 20. Hypersensitivity to or intolerance of albuterol sulfate or propellants or excipients of the inhalers 21. History of Lung volume reduction surgery, lung resection or bronchoscopic lung volume reduction in any form. 22. History of lung or other organ transplant 23. Unable to comprehend consent document and/or questionnaires Conditional Exclusions: 1. Participants who present with an upper respiratory infection or pulmonary exacerbation, either solely participant-identified or that has been clinically treated, in the last four weeks can be rescreened for the study once the four-week window has closed. 2. Participants who present with current use of acute antibiotics or have acute antibiotics within the past four weeks can be rescreened for the study ≥28 days after discontinuing acute antibiotics. 3. Female participants who present \<3 months after giving birth will be asked to reschedule their visit until three months have passed since the birth. 4. Former smoker who quit \< 3months prior to enrollment
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| PBMC Gene Expression | Baseline, 6 months, 12 months | 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). |
Countries
United States
Outcome results
None listed