102 M-Phase Phosphoprotein 1 (MPP-1) Autoantibodies as a Potential Biomarker for Cranial Neuropathies in an International SLE Inception Cohort
Bibliographic record
Abstract
Objectives We previously reported in a single centre prevalent SLE cohort that antibodies against the cytokinesis-associated protein M-Phase Phosphoprotein 1 (anti-MPP-1) were associated with SLE-related cranial neuropathy (CN), a rare manifestation of neuropsychiatric SLE (NPSLE). The purpose of this study was to assess whether anti-MPP-1 is a biomarker for CN or other NPSLE manifestations using an international SLE inception cohort. Methods SLE patients fulfilling the updated 1997 ACR classification criteria for SLE were included. Anti-MPP-1 antibody testing was performed on baseline samples (within 15 months of diagnosis) or first annual assessment using an addressable laser bead immunoassay (ALBIA) with purified recombinant human protein with results expressed as median florescence units (MFU). Based on healthy controls, a dilution of ≥1:500 MFU was considered positive. NPSLE manifestations occurring over the first 5 years of follow up were documented annually based on ACR case definitions using published NPSLE attribution rules1). The frequency of anti-MPP- 1 positivity between patients with versus without each of the 19 NPSLE manifestations was compared using univariate logistic regression. For any NPSLE manifestations where anti-MPP-1 positivity differed between patients with versus without the manifestation, baseline demographic and clinical characteristics were compared using t-tests and two-sample tests of proportions. For NPSLE manifestations associated with anti-MPP-1 positivity in the univariate analysis, multivariable logistic regression analysis using penalized maximum likelihood estimates was then performed to assess the relationship between anti-MPP-1 and the NPSLE manifestation, adjusting for age at anti-MPP-1 testing, female, White race/ethnicity, and significantly different baseline clinical characteristics. Results Seven hundred and ninety-five SLE patients were assessed; 29.8% were anti-MPP-1 positive, 88.7% female, and 52.1% White. The frequency of anti-MPP-1 positivity differed only for those with versus without CN (70.0% vs. 29.3%; odds ratio [OR] 5.16, 95%CI 1.44, 18.54) (table 1). Compared to patients without CN (n=785), patients with CN (n=10) were more likely to fulfill the ACR hematologic (difference: 23.9%, 95%CI 5.0%, 42.8%) and antinuclear antibody criteria (difference: 4.3%, 95%CI 2.9%, 5.8%) (table 2). In the multivariate analysis, anti-MPP-1 remained associated with CN (OR 5.24, 95%CI 1.44, 19.09) after adjusting for age at anti-MPP-1 testing, female, White race/ethnicity, hematologic disorder, and antinuclear antibody (table 3). Conclusion Anti-MPP-1 is a potential biomarker for CN. Although anti-MPP-1 is differentially expressed in a variety of neurological cells and tissues, the link to a pathogenic role requires further study. References Hanly, J. G., Urowitz, M. B., Gordon, C., et al. Ann Rheum Dis. 2020; 79(3): 356–362. Ainiala H , Hietaharju A , Loukkola J , et al . Arthritis Rheum 2001 ;45: 419–23.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".