Autoantibody Testing in Neuromuscular Disease: Assays, Interpretation, and Clinical Impact
This review surveys the principal autoantibodies used in diagnosing neuromuscular disorders, including paraneoplastic onconeural antibodies that can direct cancer screening. It covers current assay technologies, the importance of integrating results with electrodiagnostic findings, and the risk of false positives in low-prevalence settings. Online pre-test probability calculators are highlighted as practical tools for clinicians to improve test ordering and interpretation accuracy.
The original study
Autoantibody testing in neuromuscular medicine: assay technologies, interpretation, and clinical utility.
- Authors
- Zhang T, Mills JR, Dubey D, Klein CJ
- Journal
- Clinical biochemistry
- Type
- Journal Article, Review
- PMID
- 41633498
Original abstract
Neuromuscular autoantibody testing is an essential component in the diagnosis and management of autoimmune neuromuscular disorders. These immune-mediated diseases target antigens found in nerves, muscles, and neuromuscular junctions, and may occasionally involve the central nervous system, resulting in complex clinical presentations. Developments in antibody identification and validation have provided clinically relevant biomarkers for diagnostic, therapeutic, and prognostic purposes. Among antibody-associated neuromuscular disorders, paraneoplastic onconeural autoantibodies are of particular significance, as their presence may direct search for specific underlying malignancies. Appropriate ordering and interpretation of these tests should be integrated with clinical and electrodiagnostic (CEDX) findings. Given that these disorders are often rare, estimating an optimal pre-test probability is important to improve test accuracy and reduce false positive outcomes. Online clinical calculators are available to help clinicians determine appropriate testing strategies for some disorders. This review summarizes principal neuromuscular antibodies, current testing approaches, and the influence of laboratory data on patient care.