ANTI-DSDNA ANTIBODY ISOTYPES IN SYSTEMIC LUPUS ERYTHEMATOSUS: THE NEGLECTED DIAGNOSTIC PARAMETERS
Notice bibliographique
Résumé
PV038 / #485 Poster Topic: AS04 - Biomarkers Background/Purpose In systemic lupus erythematosus (SLE) many different organs are affected by an immune response including the skin, blood, muscles, heart, lung or kidneys making the range of symptoms vary widely. SLE occurs in about 0.1% of the general population and is predominant in females, especially in the age between 20 and 40 years, and may be linked to the hormone estrogen. Anti-double-stranded DNA (dsDNA) antibodies are highly specific for the disease and can be found in 30-40% of patients. Perform a comprehensive literature search to identify all relevant available published data for demonstration of the State-of-the-Art (medicine and technology, SOTA), the Scientific Validity (SV) of the analyte and the Clinical Performance (CP) of anti-dsDNA autoantibodies. Methods Systematic literature search, evaluation and documentation was done by applying PRISMA method. The search strings are assembled with the use of Boolean operators and search was restricted to peer-reviewed literature and systematic reviews. Results In total 22 publications have been identified as significant for SOTA, SV and CP of anti-dsDNA antibodies. The reviewed literature concludes that anti-dsDNA antibodies are specific and pathogenic biomarkers for monitoring SLE. IgG anti-dsDNA antibodies are the gold standard for diagnosing and monitoring SLE, especially in patients with kidney involvement (lupus nephritis) being the most common and severe organ manifestation. These antibodies can bind to self-antigens or immune complexes and accumulate in the glomerular and tubular basement membranes. Defective clearance of apoptotic cells may trigger the production of anti-dsDNA antibodies. Anti-dsDNA IgA and IgG show a strong association with disease activity, and the IgA isotype is additionally associated with several symptoms of skin involvement. However, the IgA isotype has no association with nephritis and arthritis and may therefore define a distinct subset of SLE patients. The presence of IgM anti-dsDNA antibodies shows a negative correlation with various parameters indicating lupus nephritis. Due to the contrary roles of IgG and IgM anti-dsDNA Isotypes in the pathogenesis of Lupus Nephritis, there is strong scientific evidence to use the IgG/ IgM Isotype ratio for prediction of nephritis (IgG/IgM >0.8 nephritis; IgG/IgM <0.8 no nephritis) also considered as replacement for kidney biopsy. Anti-dsDNA isotype evaluation in ELISA might indeed improve diagnostic accuracy, and multiple isotype detection (IgG, IgA, IgM) could enhance sensitivity in detecting the disease. Conclusions Almost all patients with renal problems show anti-dsDNA antibodies and they are also suitable for disease monitoring, since anti-dsDNA antibody concentration increases before disease flares but there is still some controversy. But even though anti-dsDNA antibodies have been established as one of the American College of Rheumatology (ACR) and Systemic Lupus International Collaborating Clinics’ criteria for diagnosing SLE, IgA and IgM anti-dsDNA isotypes are not included in follow-up routine of the patients. The combination of analysis of different anti-dsDNA isotypes (IgG, IgA, IgM) provides a more nuanced perspective on SLE disease. It not only enables more precise diagnosis, but also better monitoring of disease activity and progression, especially when distinguishing between organ involvement and tracking treatment courses. Overall, the analysis of anti-dsDNA antibody isotypes could provide a tailored and more precise diagnostic strategy in clinical practice, which may be particularly important in the monitoring of lupus nephritis and the specific treatment of SLE patients.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,021 | 0,077 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,011 | 0,012 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».