Transcriptomic Analysis and High-dimensional Phenotypic Mapping of Mononuclear Phagocytes in Mesenteric Lymph Nodes Reveal Differences Between Ulcerative Colitis and Crohn’s Disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: Crohn's disease [CD] and ulcerative colitis [UC] are distinct forms of inflammatory bowel disease. Heterogeneity of HLA-DR+SIRPα + mononuclear phagocytes [MNPs], including macrophages [MΦ], monocyte-derived [Mono] cells, and dendritic cells [DCs], was reported in gut tissue but not yet investigated in mesenteric lymph nodes [MLNs] of IBD patients. We here compared the phenotype, function, and molecular profile of HLA-DR+SIRPα + MNPs in CD and UC MLNs. METHODS: Cell distribution, morphology, immune function, and transcriptomic [bulk RNAseq] and high-dimensional protein expression profiles [CyTOF] of HLA-DR+SIRPα + MNPs were examined in MLNs of UC [n = 14], CD [n = 35], and non-IBD [n = 12] patients. RESULTS: Elevated frequencies of CD14+CD64+CD163+ [Mono/MΦ-like] MNPs displaying monocyte/MΦ morphology and phagocytic function were a distinct feature of UC MLNs. In CD, the proportion of CD14-CD64-CD163- [DC-like] cells was augmented relative to Mono/MΦ-like cells; DC-like cells drove naïve T cell proliferation, Th1 polarisation, and Th17 TCM plasticity. Gene expression profile corroborated the nature of DC-like cells, best represented by BTLA, SERPINF, IGJ and, of Mono/MΦ-like cells, defined by CD163, MARCO, MAFB, CD300E, S100A9 expression. CyTOF analysis showed that CD123+ plasmacytoid cells predominated over conventional DCs in DC-like cells. Four CD163+ clusters were revealed in Mono/MΦ-like cells, two of which were enriched in MARCO-CD68dimHLA-DRdim monocyte-like cells and MARCOhiCD68hiHLA-DRhi Mɸ, whose proportion increased in UC relative to CD. CONCLUSIONS: Defining the landscape of MNPs in MLNs provided evidence for expansion of CD163+ Mono/MΦ-like cells in UC only, highlighting a distinction between UC and CD, and thus the potential contribution of monocyte-like cells in driving colitis.
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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".