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Record W4322757630 · doi:10.1002/art.42489

Anti–Neutrophil Extracellular Trap Antibodies in Antiphospholipid Antibody–Positive Patients: Results From the Antiphospholipid Syndrome Alliance for Clinical Trials and <scp>InternatiOnal</scp> Networking Clinical Database and Repository

2023· article· en· W4322757630 on OpenAlexaff
Yu Zuo, Sherwin Navaz, Alex Tsodikov, Katarína Kmeťová, Lyndsay Kluge, Claire K. Hoy, Srilakshmi Yalavarthi, Danieli Andrade, Maria G. Tektonidou, Savino Sciascia, Vittorio Pengo, Guillermo Ruiz‐Irastorza, H. Michael Belmont, Maria Gerosa, Paul R. Fortin, Guilherme Ramires de Jesús, D. Ware Branch, Laura Andréoli, Esther Rodríguez-Almaraz, Michelle Petri, Ricard Cervera, Rohan Willis, David R. Karp, Quan‐Zhen Li, Hannah Cohen, María Laura Bertolaccini, Doruk Erkan, Jason S. Knight

Bibliographic record

VenueArthritis & Rheumatology · 2023
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversité Laval
FundersNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesWeill Cornell Medical College
KeywordsNeutrophil extracellular trapsAutoantibodyAntiphospholipid syndromeAntibodyImmunologyMedicineBiomarkerAntigenBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: This study aimed to elucidate the presence, antigen specificities, and potential clinical associations of anti-neutrophil extracellular trap (anti-NET) antibodies in a multinational cohort of antiphospholipid (aPL) antibody-positive patients who did not have lupus. METHODS: Anti-NET IgG/IgM levels were measured in serum samples from 389 aPL-positive patients; 308 patients met the classification criteria for antiphospholipid syndrome. Multivariate logistic regression with best variable model selection was used to determine clinical associations. For a subset of the patients (n = 214), we profiled autoantibodies using an autoantigen microarray platform. RESULTS: We found elevated levels of anti-NET IgG and/or IgM in 45% of the aPL-positive patients. High anti-NET antibody levels are associated with more circulating myeloperoxidase (MPO)-DNA complexes, which are a biomarker of NETs. When considering clinical manifestations, positive anti-NET IgG was associated with lesions affecting the white matter of the brain, even after adjusting for demographic variables and aPL profiles. Anti-NET IgM tracked with complement consumption after controlling for aPL profiles; furthermore, patient serum samples containing high levels of anti-NET IgM efficiently deposited complement C3d on NETs. As determined by autoantigen microarray, positive testing for anti-NET IgG was significantly associated with several autoantibodies, including those recognizing citrullinated histones, heparan sulfate proteoglycan, laminin, MPO-DNA complexes, and nucleosomes. Anti-NET IgM positivity was associated with autoantibodies targeting single-stranded DNA, double-stranded DNA, and proliferating cell nuclear antigen. CONCLUSION: These data reveal high levels of anti-NET antibodies in 45% of aPL-positive patients, where they potentially activate the complement cascade. While anti-NET IgM may especially recognize DNA in NETs, anti-NET IgG species appear to be more likely to target NET-associated protein antigens.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.085
GPT teacher head0.403
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations42
Published2023
Admission routes1
Has abstractyes

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