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Enregistrement W3111402818 · doi:10.1093/jalm/jfaa199

Laboratory Testing of Myasthenia Gravis: New Treatments Drive Change

2020· article· en· W3111402818 sur OpenAlexaff
Hans Frykman, Pankaj Kumar

Notice bibliographique

RevueThe Journal of Applied Laboratory Medicine · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueMyasthenia Gravis and Thymoma
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMyasthenia gravisMedicineImmunology

Résumé

récupéré en direct d'OpenAlex

Myasthenia gravis (MG) is a neuromuscular disorder, mediated largely by autoantibodies (Abs), that targets functionally important proteins at the neuromuscular junction in the postsynaptic muscle membrane (1). MG is a heterogeneous disorder with regard to autoimmune profile, immunopathology, and the multifaceted immune response. Antibody testing plays a central role in confirming MG diagnosis and directing the management of MG patients. The majority (approximately 80%) of patients with generalized MG (GMG) develop antibodies against the acetylcholine receptor (AChR), whereas muscle-specific kinase (MuSK) Abs are detected in 1%–10% of patients (1–3). However, despite the progress made in serology, none of these antibodies are detected in 1%–15% of GMG patients, (i.e., sera are negative for AChR and MuSK Abs with current gold standard tests) (1–3). It is generally believed that patients with seronegative MG are most likely similar in their immunopathology to patients who are antibody positive, except that either the current testing methodologies are not sensitive enough to detect low-affinity or low-titer antibodies or the target proteins in the neuromuscular junction have not been fully identified. Substantial efforts have been made toward finding novel antibodies and developing improved detection techniques. In recent years, new antibody targets have been identified in some patients with MG against lipoprotein-receptor–related protein 4 (LRP4), agrin, collagen, antistriational muscle (Kv1.4, titin, and ryanodine receptors) and cortactin (1–3). These antibodies mostly coexist with AChR and MuSK Abs; therefore, studies are required to establish their pathogenic role in patients with MG. Antititin and anticortactin Abs are of particular interest because they are associated with more severe symptoms (1–3). Furthermore, some are not exclusively MG specific. For instance, Abs against LRP4 are reported in 1%–2% of patients with seronegative MG; however, LRP4 is also frequently detected among patients with amyotrophic lateral sclerosis (10%–23%) (4). With the introduction of new, highly effective, antigen-specific treatment options (e.g., eculizumab in patients with refractory GMG who are positive for AChR Abs and rituximab in patients who are positive for MuSK Abs), it is increasingly important to evaluate levels of the specific antibody responsible for pathogenesis in individual patients. A major advancement in the field has been the recent and ongoing development of highly sensitive and specific live cell–based assays (CBAs) for clustered AChR, MuSK, and LRP4 Abs (4). Regarding detection of AChR Abs, although the radioimmunoprecipitation assay (RIPA) has been the gold standard test for the past few years, not all clinically relevant antibodies bind well to 125I-α-bungarotoxin–labeled AChR antigens in solution (4). Typically, rapsyn-clustered AChR antigens (clustered AChR) are expressed on a HEK293 cell surface at a density similar to that at the neuromuscular junction. Clustered AChR Abs that have low affinity for soluble antigens (in standard RIPA assay) bind well to clustered AChR in its native form. In routine diagnostic settings, the clustered AChR Abs are detected in approximately 20% of patients with seronegative MG (4). The sensitivity of the clustered live CBA is increased when both the adult and fetal forms of the AChR antigens are used (2, 4). Interestingly, although the clustered CBA detects the same subclass of antibodies (IgG1 and IgG3) as standard RIPA, the patients with clustered AChR Abs have higher prevalence of ocular MG, milder disease severity, and better treatment response (2, 4). In addition, in the pediatric population, the importance of distinguishing between acquired and congenital MG makes the high-sensitivity CBA test a first-line option. In a recent study conducted at our laboratory, 16% (7/44) of children with seronegative MG tested positive for clustered live AChR Abs with a CBA (5). These 7 children with positive results have been verified as having acquired MG (5). Anti-AChR and MuSK Abs are also detected by ELISA, fluorescence immunoprecipitation assay, and dot-blot methods; however, overall sensitivity and specificity are generally lower than the gold standard RIPA assay or the live CBA (1–3). With advancements in improved diagnostics and, more important, early treatment of patients with GMG including intravenous immunoglobulin and plasma exchange, there has been a recent proposed change to MG testing algorithms. Because many treatments confound the test results (e.g., false-negative results are possible if patients have received intravenous immunoglobulin and plasma exchange within 6 weeks of their antibody test or rituximab or eculizumab within 24 weeks of their test), if the patient is under the care of an adult neurologist or ophthalmologist, we now recommend a complete reflex testing algorithm on the first pretreatment sample from a patient with suspected MG, starting with the binding and blocking assays for AChR Abs by RIPA (Fig. 1, A). The simultaneous presence of striational Abs should be tested in AChR Abs–positive sample with suspected thymoma-associated MG (optional). If AChR Abs are negative, then reflex to MuSK Abs by RIPA. If MuSK Abs tests are negative, then use concurrent testing with high-sensitivity clustered AChR Abs, MuSK Abs, and LRP4 Abs by CBA and anticortactin Abs by western blots. In the case of children, the sample should be tested directly for clustered AChR Abs by CBAs (Fig. 1, B). If AChR Abs are negative, then reflex to MuSK Abs by RIPA. If both the tests are negative, then MuSK Abs, LRP4 Abs, and anticortactin Abs tests are optional. Importantly, the algorithm-based approach does not affect the test turnaround time because the samples are simultaneously tested and reported. MG algorithm for adults’ and children’s Ab testing. Dotted lines indicate optional testing (made with http://Lucidchart.com). We foresee that in the near future, the specificity of these CBAs will convince clinicians that the assays should be part of systematic testing in the presence of seronegative generalized MG, thus stimulating laboratories to make these tests available. Availability remains an issue at the present time. Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 4 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; (c) final approval of the published article; and (d) agreement to be accountable for all aspects of the article thus ensuring that questions related to the accuracy or integrity of any part of the article are appropriately investigated and resolved. Authors’ Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest: Employment or Leadership: H. Frykman, BC Neuroimmunology Lab. Consultant or Advisory Role: None declared. Stock Ownership: H. Frykman, BC Neuroimmunology Lab. Honoraria: H. Frykman, Alexion Pharmaceuticals. Research Funding: None declared. Expert Testimony: H. Frykman, Alexion Pharmaceuticals. Patents: None declared. Acknowledgments: Authors would like to thank Alan Cashman for creating the figure. myasthenia gravis autoantibody, generalized myasthenia gravis acetylcholine receptor muscle-specific kinase lipoprotein-receptor–related protein 4 cell-based assay radioimmunoprecipitation assay

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,031
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: aucune
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,047

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,031
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,003
Communication savante0,0050,005
Science ouverte0,0010,001
Intégrité de la recherche0,0030,005
Charge utile insuffisante (le modèle a refusé de juger)0,0050,002

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.

Tête enseignante Opus0,054
Tête enseignante GPT0,277
Écart entre enseignants0,222 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2020
Routes d'admission1
Résumé présentnon

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