184. THE MICROBIOME OF TEMPORAL ARTERIES
Bibliographic record
Abstract
Background: Giant cell arteritis (GCA) is the most common large vessel vasculitis (LVV) in adults. Temporal arteries (TA) are the most accessible source of tissue for diagnostic confirmation. Although patients usually respond quickly to corticosteroids (CS), relapses occur frequently with CS tapering, suggesting that the underlying driver of inflammation has not been addressed. A role for microorganisms in GCA has long been suspected. Viral and bacterial agents have been implicated, however attempts at pathogen detection have failed to provide consistent results. Sequencing of the bacterial-specific 16S ribosomal RNA genes from human tissue is a sensitive and culture-independent method for both pathogen and commensal detection, allowing comprehensive and unbiased determinations of microbiomes. We describe the microbiomes of TA from GCA patients and controls. Methods: TA biopsies from patients suspected to have GCA were collected under aseptic conditions, snap-frozen (-80oC), deidentified and processed in blinded fashion at one time. 2 specimens were studied by Fluorescence in situ hybridization (FISH). Taxonomic classification of bacterial sequences was performed to the genus level and relative abundances were calculated. Microbiome differential abundances were analyzed by principal coordinate analysis (PCoA) with comparative Unifrac distances, and predicted functional profiling using PICRUSt. Results: 47 patients were enrolled (9 biopsy-positive GCA, 15 biopsy-negative GCA, 23 controls), FISH for bacterial DNA revealed signal in the arterial media but not the intima or adventitia. Beta, but not alpha, diversity differed between GCA cases and controls (p = 0.042). Importantly, there were no significant microbial differences between biopsy-positive and biopsy-negative GCA (p = 1.0). The largest differential abundances seen between GCA and control TAs included Proteobacteria (P), Bifidobacterium (g), Parasutterella (g) and Granulicatella (g) [LDA>4]. Conclusion: Temporal arteries are not sterile, but rather are inhabited by a community of bacteria. There are microbiomic differences between GCA and non-GCA TAs, but not between biopsy-positive and biopsy-negative GCA. Disclosures: This work was supported, in part, by the Fasenmyer Clinical Immunology Center (to GSH, LC and CE), the National Center for Advancing Translational Sciences (NCATS) of the NIH (UL1TR000439), and a post-graduate fellowship training grant from the UCB-Canadian Rheumatology Association-The Arthritis Society to AC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".