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Record W4408508497 · doi:10.1093/brain/awaf102

Large-scale profiling of antibody reactivity to glycolipids in patients with Guillain-Barré syndrome

2025· article· en· W4408508497 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBrain · 2025
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsUniversity of TorontoUniversity Health NetworkUniversity of Calgary
FundersGrifolsFonds de dotation CSL Behring pour la rechercheAxencia Galega de InnovaciónCSL BehringUniversity of GlasgowErasmus Medisch CentrumGBS/CIDP Foundation InternationalWellcome Trust
KeywordsGlycolipidGuillain-Barre syndromeAntibodyGangliosideImmunologyAntigenMedicinePolyradiculoneuropathyBiologyBiochemistry

Abstract

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Guillain-Barré syndrome is an acute polyradiculoneuropathy in which preceding infections often elicit the production of antibodies that target peripheral nerve antigens, principally gangliosides. Anti-ganglioside antibodies are thought to play a key role in the clinical diversity of the disease and can be helpful in clinical practice. Extensive research into clinical associations of individual anti-ganglioside antibody specificities has been performed. Recent research has highlighted glycolipid complexes, glycolipid combinations that may alter antibody binding, as targets. In this study, we investigated antibody reactivity patterns to glycolipids and glycolipid complexes using combinatorial array, in relation to clinical features in Guillain-Barré syndrome. In total, 1413 patients from the observational International Guillain-Barré syndrome Outcome Study (0-91 years, 60.3% male) and 1061 controls (healthy, family, infectious, vaccination, other neurological disease) were included. Acute-phase sera from patients were screened for IgM, IgG, and IgA reactivity against 15 glycolipids and one phospholipid and their heteromeric complexes, similarly to archived control sera. Antibody specificities and reactivity patterns were analysed in relation to clinical features. Of all patients, 1309 (92.6%) were positive for at least one anti-glycolipid (complex) antibody. Anti-GM1 and anti-GQ1b (complex) antibodies best distinguished motor Guillain-Barré syndrome and Miller Fisher syndrome from controls, with antibodies to glycolipid complexes outperforming antibodies to single glycolipids. Three models consisting of anti-glycolipid (complex) antibodies distinguished patients with Guillain-Barré syndrome, the motor variant, and Miller Fisher syndrome from controls with high sensitivity and specificity, performing better than antibodies to single glycolipids used in clinical practice. Seven patient clusters with particular antibody reactivity patterns were identified. These clusters were distinguished by geographical region, clinical variants, preceding Campylobacter jejuni infection, electrophysiological subtypes, the Medical Research Council sum score at study entry, and the ability to walk 10 m unaided at 26 weeks. Two patient clusters with distinct anti-GM1 (complex) reactivity (broad versus restricted) differed in frequency of the axonal subtype. In cumulative incidence analyses, 15 anti-glycolipid (complex) antibodies were associated with the time required to regain the ability to walk 10 m unaided. After adjustment for known prognostic factors, IgG anti-GQ1b:GM4, GQ1b:PS and GQ1b:Sulfatide remained associated with faster recovery. Addition of anti-glycolipid antibodies to clinical prognostic models slightly improved their discriminative capacity, though insufficiently to improve the models. Measurement of anti-glycolipid antibodies by combinatorial array increases the diagnostic yield compared to assaying single glycolipids, identifies clinically relevant antibody reactivity patterns to glycolipids and glycolipid complexes, and may be useful in outcome prediction in Guillain-Barré syndrome.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.259
Teacher spread0.255 · 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