Sialic Acid Binding Ig-Like Lectin 1 is a Biomarker of Disease Activity in Autoimmune Inflammatory Myopathies
Bibliographic record
Abstract
Objectives Sialic acid binding Ig-like lectin 1 (SIGLEC1) is an adhesion molecule expressed on monocytes and macrophages, a surrogate marker for the Type I Interferon pathway, and a candidate biomarker for several autoimmune diseases. This study aimed to investigate serum SIGLEC1 levels as a novel biomarker for (1) disease activity in autoimmune inflammatory myopathies (AIM); and (2) clinical AIM manifestations. Methods AIM patients enrolled in a multisite study registry with routine venipuncture samples bio-banked at baseline visits were included. Baseline clinical data were utilized. Sera were tested for SIGLEC1 using a capture immunoassay (Aviva Systems Biology, San Diego CA). The physician global disease activity assessment (PGA), which ranges from 0 (no disease activity) to 10 (very severe disease), was used to rate overall disease activity in AIM patients classified as having active (PGA ≥2) or inactive (PGA <2) disease. Patients were also classified as having active or inactive disease for 6 individual organ systems included in the myositis disease activity assessment visual analog scales tool (MYOACT): constitutional, cutaneous, skeletal, gastrointestinal, pulmonary, and cardiac. SIGLEC1 concentrations (ng/mL) were compared between patients with active and inactive diseases and those with and without AIM-specific manifestations using t-test. Results 87 AIM patients (32.2% male, median age 57.0±19 years) with dermatomyositis (DM, n=38), polymyositis (PM, n=7), antisynthetase syndrome (AS, n=2), immune-mediated necrotizing myopathy (IMNM, n=5), inclusion body myositis (IBM, n=10), overlap (n=20), and other myopathies (n=4) were included. Higher SIGLEC1 concentration differentiated active from inactive disease in AIM (mean difference 2.7 ng/mL, 95% CI 0.7-4.8, p<0.05) (Figure 1), and DM (mean difference 4.0 ng/mL, 95% CI 0.3-7.5, p<0.05). Higher SIGLEC1 concentrations were found among patients with cutaneous (mean difference 1.7 ng/mL, 95% CI 0.1-3.4), skeletal (mean difference 2.0 ng/mL, 95% CI 0.1-3.9), and gastrointestinal (mean difference 2.2 ng/mL, 95% CI 0.5-3.9) involvement compared to patients without these features. Figure 1 Serum SIGLEC1 levels in AIM patients separated by PGA score: active (PGA≥2) and inactive (PGA<2). Horizontal bars show median values; asterisks (**) represent significant results (p<0.01). T-test was used to compare groups. PGA, physician global assessment; SIGLEC1, sialic acid binding Ig-like lectin 1. Conclusion SIGLEC1 is a promising biomarker for assessing disease activity in AIM, particularly DM, and is associated with the presence of cutaneous, skeletal, and gastrointestinal clinical features. The candidacy of SIGLEC1 as a novel AIM biomarker requires further investigation and validation in a larger cohort of AIM patients. Future studies are underway to validate these findings and evaluate SIGLEC1 as a predictor of overall AIM disease activity during the course of the 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".