Distinct Subtypes of Microparticle-containing Immune Complexes Are Associated with Disease Activity, Damage, and Carotid Intima-media Thickness in Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Microparticles (MP) are small extracellular vesicles present in body fluids. MP originate from different cellular lineages, principally from platelets in blood, and may expose phosphatidylserine (PS). In systemic lupus erythematosus (SLE), MP harbor immunoglobulin G (IgG), thereby forming MP-containing immune complexes (mpIC). We aimed to verify an association between SLE disease activity, damage, and surrogate markers of atherosclerosis and MP harboring IgG, taking into account the platelet origin and PS exposure of MP. METHODS: MP expressing surface IgG, platelet antigen (CD41+), and PS were quantified using flow cytometry in plasma of 191 women with SLE. Carotid ultrasounds (US) were available in 113 patients. Spearman correlation analysis was used to analyze whether levels of MP were associated with the following outcomes: SLE Disease Activity Index 2000 (SLEDAI-2K), Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (SDI), and carotid US plaques and intima-media thickness (CIMT) as surrogates for vascular damage. RESULTS: We found CD41+ MP harboring IgG present in SLE. A positive correlation was found between SLEDAI-2K and levels of CD41+ MP harboring IgG and exposing (p = 0.027) and non-exposing PS (p = 0.001). Conversely, SDI (p = 0.024) and CIMT (p = 0.016) correlated with concentrations of CD41- MP harboring IgG and exposing PS. Associations were independent of low-density lipoprotein cholesterol level, body mass index, and antimalarial drug use. CONCLUSION: Different subtypes of mpIC are produced in SLE and are associated with distinct clinical characteristics such as disease activity and vascular damage. The assessment of MP subtypes might serve for the design of predictive markers of disease activity and vascular damage in patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".