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Record W4308957814 · doi:10.1002/acr2.11510

Anti–<scp>Valosin‐Containing</scp> Protein (<scp>VCP</scp>/p97) Autoantibodies in Inclusion Body Myositis and Other Inflammatory Myopathies

2022· article· en· W4308957814 on OpenAlexaff
Adam Amlani, May Y. Choi, Katherine A Buhler, Marie Hudson, Mark A. Tarnopolsky, Lauren Brady, Heinrike Schmeling, Mark G. Swain, Cory Stingl, Ann M. Reed, Marvin J. Fritzler

Bibliographic record

VenueACR Open Rheumatology · 2022
Typearticle
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsMcMaster University Medical CentreMcGill UniversityJewish General HospitalUniversity of Calgary
Fundersnot available
KeywordsInclusion body myositisMedicinePolymyositisAutoantibodyMyositisAntibodyDermatomyositisGlycogen storage disease type IIJuvenile dermatomyositisPathologyImmunologyInternal medicineDiseaseEnzyme replacement therapy

Abstract

fetched live from OpenAlex

OBJECTIVE: The rationale for this study was based on reports that valosin-containing protein (VCP) mutations are found in hereditary inclusion body myositis (IBM) and VCP was detected in rimmed vacuoles of sporadic IBM (sIBM) muscle biopsies. Autoantibodies to VCP have not been reported in sIBM or other inflammatory myopathies (IIMs). The aim of this study was to determine the frequency and clinical significance of anti-VCP antibodies in sIBM and other IIMs. METHODS: Sera were collected from 73 patients with sIBM and 383 comparators or controls, including patients with IIM (n = 69), those with juvenile dermatomyositis (JDM) (n = 67), those with juvenile idiopathic arthritis (JIA) (n = 47), those with primary biliary cholangitis (PBC) (n = 105), controls that were age matched to patients with sIBM (similarly aged controls [SACs]) (n = 63), and healthy controls (HCs) (n = 32). Immunoglobulin G antibodies to VCP were detected by addressable laser bead immunoassay using a full-length recombinant human protein. RESULTS: Among patients with sIBM, 26.0% (19/73) were positive for anti-VCP. The frequency in disease controls was 15.0% (48/320). Among SACs, the frequency was 1.6% (1/63), and in HCs 0% (0/32). Frequencies were 17.5% (11/63) for IIM, 25.7% (27/105) for PBC, 3.0% (2/67) for JDM, and 17.0% (8/47) for JIA. The sensitivity, specificity, positive predictive value, and negative predictive value of anti-VCP for sIBM were 26.0%, 87.2%, 28.4%, and 85.9%, respectively. Of patients with sIBM, 15.1% (11/73) were positive for both anti-VCP and anti-cytosolic 5'-nucleotidase 1A (NT5c1A). Eleven percent of patients (8/73) were positive for anti-VCP, but negative for anti-NT5c1A. CONCLUSION: Anti-VCP has low sensitivity and moderate specificity for sIBM but may help fill the seronegative gap in sIBM. Further studies are needed to determine whether anti-VCP is a biomarker for a clinical phenotype that may have clinical value.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.007
Research integrity0.0000.001
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 head0.011
GPT teacher head0.263
Teacher spread0.252 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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