Identification of a SmD3 epitope with a single symmetrical dimethylation of an arginine residue as a specific target of a subpopulation of anti-Sm antibodies
Bibliographic record
Abstract
Anti-Sm antibodies, identified in 1966 by Tan and Kunkel, are highly specific serological markers for systemic lupus erythrematosus (SLE). Anti-Sm reactivity is found in 5-30% of SLE patients, depending on the autoantibody detection system and the racial background of the SLE population. The Sm autoantigen complex comprises at least nine different polypeptides. All of these core proteins can serve as targets of the anti-Sm B-cell response, but most frequently the B and D polypeptides are involved. Because the BB'Sm proteins share cross-reactive epitopes (PPPGMRPP) with U1 specific ribonucleoproteins, which are more frequently targeted by antibodies that are present in patients with mixed connective tissue disease, the SmD polypeptides are regarded as the Sm autoantigens that are most specific to SLE. It was recently shown that the polypeptides D1, D3 and BB' contain symmetrical dimethylarginine, which is a component of a major autoepitope within the carboxyl-terminus of SmD1. In one of those studies, a synthetic dimethylated peptide of SmD1 (amino acids 95-119) exhibited significantly increased immunoreactivity as compared with unmodified SmD1 peptide. Using immobilized peptides, we confirmed that the dimethylated arginine residues play an essential role in the formation of major SmD1 and SmD3 autoepitopes. Moreover, we demonstrated that one particular peptide of SmD3 represents a more sensitive and more reliable substrate for the detection of a subclass of anti-Sm antibodies. Twenty-eight out of 176 (15.9%) SLE patients but only one out of 449 (0.2%) control individuals tested positive for the anti-SmD3 peptide (SMP) antibodies in a new ELISA system. These data indicate that anti-SMP antibodies are exclusively present in sera from SLE patients. Thus, anti-SMP detection using ELISA represents a new serological marker with which to diagnose and discriminate between systemic autoimmune disorders.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".