Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Identification of disease phenotypes in acetylcholine receptor-antibody myasthenia gravis using proteomics-based consensus clustering.

EBioMedicine - 1 Jul 2024

Nelke Christopher, Schroeter Christina B, Barman Sumanta, Stascheit Frauke, Masanneck Lars, Theissen Lukas, Huntemann Niklas, Walli Sara, Cengiz Derya, Dobelmann Vera, Vogelsang Anna, Pawlitzki Marc, Räuber Saskia, Konen Felix F, Skripuletz Thomas, Hartung Hans-Peter, König Simone, Roos Andreas, Meisel Andreas, Meuth Sven G, Ruck Tobias

Abstract excerpt

BACKGROUND: The clinical heterogeneity of myasthenia gravis (MG), an autoimmune disease defined by antibodies (Ab) directed against the postsynaptic membrane, constitutes a challenge for patient stratification and treatment decision making. Novel strategies are needed to classify patients based on their biological phenotypes aiming to improve patient selection and treatment outcomes. METHODS: For this purpose, we...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Autoantibodies
Share to B-Lymphocytes

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Cluster Analysis

Share to Complement Activation

Share to Myasthenia Gravis

Share to Proteome

Share to Proteomics

Share to Receptors, Cholinergic

Source

Open in PubMed Open full text

Identifiers

PMID: 38959848
DOI: 10.1016/j.ebiom.2024.105231
PMCID: PMC11269806

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identification of disease phenotypes in acetylcholine receptor-antibody myasthenia gravis using proteomics-based consensus clustering.PMID 38959848Read ↗

Towards personalized management of myasthenia gravis phenotypes: From the role of multi-omics to the emerging biomarkers and therapeutic targets.Semantic proximity Read ↗

Distribution and Temporal Changes of Autoantibody-Mediated Pathogenic Mechanisms Among Acetylcholine Receptor-Positive Myasthenia Gravis PatientsSemantic proximity Read ↗

Heterogeneity of acetylcholine receptor autoantibody-mediated complement activity in patients with myasthenia gravisSemantic proximity Read ↗

Single-cell profiling of myasthenia gravis identifies a pathogenic T cell signatureSemantic proximity Read ↗

A Distinct Immunological Signature in Late‐Onset Myasthenia Gravis: Insights from an Exploratory Proteomics StudySemantic proximity Read ↗

Myasthenia gravis: from autoantibodies to therapy.Semantic proximity Read ↗

Receptor clustering and pathogenic complement activation in myasthenia gravis depend on synergy between antibodies with multiple subunit specificitiesSemantic proximity Read ↗

Peripheral immune landscape for hypercytokinemia in myasthenic crisis utilizing single-cell transcriptomicsSemantic proximity Read ↗

Identification of genetic risk loci and prioritization of genes and pathways for myasthenia gravis: a genome-wide association study.Semantic proximity Read ↗

Clinical Genomic, phenotype and epigenetic insights into the pathology, autoimmunity and weight management of patients with Myasthenia Gravis (Review).Semantic proximity Read ↗

Phenotype, Severity, and Therapy of Patients With LRP4 Antibody-Associated Myasthenia Gravis in the German Myasthenia Gravis Registry.Semantic proximity Read ↗

Protein signature of human white blood cells enables biochemical tracking of rare neurological diseasesSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.