Transcriptomics of Bronchoalveolar Lavage Cells Identifies New Molecular Endotypes of Sarcoidosis
Bibliographic record
Abstract
ABSTRACT Sarcoidosis is a multisystem granulomatous disease of unknown origin with a variable and often unpredictable course and pattern of organ involvement. In this study we sought to identify specific bronchoalveolar lavage (BAL) cell gene expression patterns indicative of distinct disease phenotypic traits. RNA sequencing by Ion Torrent Proton was performed on BAL cells obtained from 215 well characterized patients with pulmonary sarcoidosis enrolled in the multicenter Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study. Weighted Gene Co-expression Network Analysis (WGCNA) and non-parametric statistics were used to analyze genome wide BAL transcriptome. Validation of results was performed using a microarray expression data set of an independent sarcoidosis cohort (Freiburg, Germany (n=50)). Our supervised analysis found associations between distinct transcriptional programs and major pulmonary phenotypic manifestations of sarcoidosis including; TH1 and TH17 pathways associated with hilar lymphadenopathy; TGFB1 and MTOR signaling with parenchymal involvement, and IL7 and IL2 with airway involvement. Our unsupervised analysis revealed gene modules that uncovered four potential sarcoidosis endotypes including hilar lymphadenopathy with increased acute T cell immune response; extraocular organ involvement with PI3K activation pathways; chronic and multiorgan disease with increased immune response pathways; and multiorgan with increased IL-1 and IL-18 immune and inflammatory responses. We validated the occurrence of these endotypes using gene expression, pulmonary function tests and cell differentials from Freiburg. Taken together our results identify BAL gene expression programs that characterize major pulmonary sarcoidosis phenotypes and suggest the presence of distinct disease molecular endotypes. Take home message Genome wide BAL transcriptomics identified novel gene expression profiles associated with distinct phenotypic traits in sarcoidosis and is suggestive of the presence of novel molecular and clinical sarcoidosis endotypes that could help with further understanding of this heterogenous disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".