Guillain–Barré syndrome and anti-ganglioside antibodies: a clinician-scientist’s journey
Bibliographic record
Abstract
Guillain-Barré syndrome (GBS) is the most frequent cause of acute flaccid paralysis. Having seen my first GBS patient in 1989, I have since then dedicated my time in research towards understanding the pathogenesis of GBS. Along with several colleagues, we identified IgG autoantibodies against ganglioside GM1 in two patients with GBS subsequent to Campylobacter jejuni enteritis. We proceeded to demonstrate molecular mimicry between GM1 and bacterial lipo-oligosaccharide of C. jejuni isolated from a patient with GBS. Our group then established a disease model for GBS by sensitization with GM1 or GM1-like lipo-oligosaccharide. With this, a new paradigm that carbohydrate mimicry can cause autoimmune disorders was demonstrated, making GBS the first proof of molecular mimicry in autoimmune disease. Patients with Fisher syndrome, characterized by ophthalmoplegia and ataxia, can develop the disease after an infection by C. jejuni. We showed that the genetic polymorphism of C. jejuni sialyltransferase, an enzyme essential to the biosynthesis of ganglioside-like lipo-oligosaccharides determines whether patients develop GBS or Fisher syndrome. This introduces another paradigm that microbial genetic polymorphism can determine the clinical phenotype of human autoimmune diseases. Similarities between the clinical presentation of Fisher syndrome and Bickerstaff brainstem encephalitis have caused debate as to whether they are in fact the same disease. We demonstrated that IgG anti-GQ1b antibodies were common to both, suggesting that they are part of the same disease spectrum. We followed this work by clarifying the nosological relationship between the various clinical presentations within the anti-GQ1b antibody syndrome. In this review, I wanted to share my journey from being a clinician to a clinician-scientist in the hopes of inspiring younger clinicians to follow a similar path.
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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 | 0.020 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.009 | 0.023 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.022 | 0.042 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".