IgG Glycosylation Changes and<i>MBL2</i>Polymorphisms: Associations with Markers of Systemic Inflammation and Joint Destruction in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To examine whether IgG glycosylation changes and MBL2 genotypes are associated with systemic inflammation and joint destruction in rheumatoid arthritis (RA). METHODS: IgG N-glycan content was determined from serum in 118 patients with RA by high-throughput glycan analysis using normal-phase high-pressure liquid chromatography. MBL2 extended genotypes (YA/YA, YA/XA, XA/XA, YA/YO, XA/YO, YO/YO) were determined. Systemic inflammation was assessed by serum levels of C-reactive protein (CRP), interleukin 6 (IL-6), and tumor necrosis factor-α (TNF-α). Joint destruction was assessed by total Sharp score (TSS) and alloplastic surgery records. RESULTS: IgG hypogalactosylation was significantly correlated to IL-6 (Spearman's rho = 0.32, p < 0.001), CRP (Spearman's rho = 0.31, p < 0.001), TSS (Spearman's rho = 0.25, p = 0.01), and alloplastic replacement of joints (Spearman's rho = 0.18, p = 0.05). In multivariate analysis including age, CRP, anticitrullinated protein antibodies (ACPA), and other confounders, IgG hypogalactosylation was significantly associated with TSS (p = 0.014) and alloplastic joint replacement (OR 76.5, p = 0.041) in patients homozygous for the high expression MBL2 genotype YA/YA, but not in carriers of lower expression genotypes. CONCLUSION: Decreased galactosylation of IgG correlated to markers of inflammation, i.e., IL-6 and CRP. Only in patients homozygous for high expression of the MBL2 genotype YA/YA was IgG hypogalactosylation associated with markers of joint destruction. Our results suggest that inflammation-associated decreased galactosylation of IgG combined with high expression MBL2 genotypes are involved in the pathophysiology of RA.
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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 | 0.000 | 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".