Alpha Actinin is Specifically Recognized by Multiple Sclerosis Autoantibodies Isolated Using an N-Glucosylated Peptide Epitope
Bibliographic record
Abstract
Sophisticated approaches have recently led to the identification of novel autoantigens associated with Multiple Sclerosis (MuS), e.g. neurofascin, contactin, CNPase, and other T-cell receptor membrane anchored proteins. These putative antigens, although differing from the conventional myelin derivatives, are conceptually based on an animal model of experimental autoimmune encephalomyelitis. In this report we describe the identification of putative antigens based on their recognition by autoantibodies isolated from MuS patient serum. In a previous work from this laboratory we have shown that a peptide probe, named CSF114(Glc), specifically identifies serum autoantibodies in a subset of MuS patients, representing ∼30% of the patient population. The autoantibodies, purified from MuS patients' sera (six), through CSF114(Glc) affinity chromatography, detected three immunoreactive protein bands present in the rat brain. Proteomic analysis of the immunoreactive bands, involving MALDI and MS/MS techniques, revealed the presence of four proteins distinguishable by their mass: alpha fodrin, alpha actinin 1, creatine kinase, and CNPase. The immunoreactive profile of these rat brain proteins was compared with that of commercially available standard proteins by challenging against either CSF114(Glc) purified MuS autoantibodies, or monoclonal antibodies. Further discrimination among the rat brain proteins was provided by the following procedure: whereas monoclonal antibodies recognized all rat brain proteins, isolated MuS specific antibodies recognize only alpha actinin 1 as a putative antigen. In fact, alpha actinin 1 displayed a robust immunoreactive response against all MuS patients' sera examined, whereas the other three bands were not consistently detectable. Thus, alpha actinin 1, a cytoskeleton protein implicated in inflammatory/degenerative autoimmune diseases (lupus nephritis and autoimmune hepatitis) might be regarded as a novel MuS autoantigen, perhaps a prototypic biomarker for the inflammatory/degenerative process typical of the disease.
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".