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Record W4414587335 · doi:10.1101/2025.09.25.678492

Symmetrical Dimethylarginine as the Central Antigenic Determinant of Anti-Smith Autoantibodies in Systemic Lupus Erythematosus

2025· preprint· en· W4414587335 on OpenAlexfundno aff
Lars C. van Vliet, Annemarie L Dorjée

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMedicine
TopicUrticaria and Related Conditions
Canadian institutionsnot available
FundersArthritis SocietyDutch Arthritis Society
KeywordsAutoantibodyEpitopeAntibodyMolecular mimicryAutoimmunityAntigenEpitope mappingImmune systemAmino acid

Abstract

fetched live from OpenAlex

ABSTRACT Objective Systemic lupus erythematosus (SLE) is a chronic autoimmune disease causing multi-organ damage. The most specific autoantibody response in SLE, present in 20-30% of patients, targets the Sm-protein and has been shown to recognize a linear Sm-derived B cell epitope containing a post-translational modification (PTM) of arginine termed symmetrical dimethyl arginine (sDMA). As autoantibodies to other PTM-modified proteins are often promiscuous, we aimed to determine the specificity and cross-reactivity of anti-Sm antibodies. Methods Specificity and promiscuity/cross-reactivity of anti-Sm IgG were measured by ELISA in SLE patients and healthy donors using peptides containing either sDMA or unmodified arginine. Inhibition and cross-reactivity were determined using competitive ELISA and affinity purification. Recognition of endogenous EBNA1 by anti-Sm IgG was performed by Western blot using lysates of EBV-bearing lymphoblastoid cell lines. Results The sDMA residue is recognized by anti-Sm+ SLE patients regardless of the peptide amino acid sequence, with a modest impact of amino acids flanking sDMA on recognition. Most notably, IgGs targeting sDMA comprise the overall majority (∼90%) of the anti-Sm antibody repertoire and are highly cross-reactive between SmD3 108-122 and several sDMA-containing viral-derived epitopes, including full-length EBNA1. Conclusion Our data implicate that the majority of anti-Sm IgGs target the sDMA residue irrespective of its Sm-context, thus representing a prototypic anti-PTM response. These antibodies are highly promiscuous, recognizing several sDMA-modified targets, including naturally occurring viral sDMA-expressing epitopes. These findings suggest a new mechanism by which molecular mimicry of sDMA-modified viral proteins could contribute to a breach of tolerance in anti-Sm+ SLE patients. KEY MESSAGES What is already known on this topic Symmetrical dimethylarginine (sDMA) residues are present on RGG/RG repeat regions within the SmD1, SmD3, and SmB/B⍰ subunits of the Sm protein complex in vivo . The introduction of sDMA is essential for recognition of minimal antigenic epitopes spanning amino acids #95–119 on the SmD1 and #108–122 on the SmD3 subunits by a specific subset of anti-Sm autoantibodies. What this study adds We show that autoantibodies targeting sDMA residues are common in anti-Sm+ SLE patients and represent the majority of the anti-Sm autoantibody repertoire. We demonstrate that anti-sDMA autoantibodies are highly cross-reactive and can also bind to sDMA residues on other targets, including several virus-derived epitopes, thus representing a prototypic anti-modified protein antibody (AMPA) response directed against post-translationally modified proteins through symmetrical dimethylation of arginine. How this study might affect research, practice, or policy The high cross-reactivity of Sm antibodies to various sDMA-containing epitopes, combined with a dominant antigenic specificity, provides mechanistic insight in the potential link between viral infection and tolerance breach in anti-Sm+ SLE patients.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.242
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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