Autoimmune Neurology
Find out how our suite of autoimmune movement disorder testing can help diagnose PDE10A autoimmunity in patients who present with hyperkinetic movement disorders.
Learn how GFAP testing is emerging as a biomarker to support diagnosis, monitoring, and prognosis in neurological diseases.
Learn how our autoimmune/paraneoplastic evaluation for encephalopathy uses CSF testing to confirm an autoimmune GFAP meningoencephalomyelitis diagnosis.
Autoimmune encephalitis (AE) is a rare but serious condition, and accurate diagnosis is critical. Misdiagnosis can lead to unnecessary treatments, delayed care, and preventable complications.
Autoimmune neurology testing has evolved beyond limited paraneoplastic evaluations to phenotype-specific panels that identify clinically relevant antibodies. This phenotype-specific approach significantly improves diagnostic accuracy, reduces false positives, and helps guide faster, more personalized treatment for complex neurological diseases.
Learn more about how our movement disorders testing can help diagnose testicular cancer-associated paraneoplastic encephalitis.
Learn more about how our testing protocol is useful in the diagnosis of sorbitol dehydrogenase (SORD) deficiency.
Find out how we use glycine receptor Ab as a marker of stiff-person syndrome spectrum disorder.
Learn more about the risks of false positives with AQP4 ELISA methodology in CNS demyelinating disease testing.
Learn how a phenotype-specific autoimmune neurology evaluation diagnosed a treatable autoimmune encephalitis condition that was missed with a traditional paraneoplastic evaluation.
Find out how our testing uses neurofascin 155 IgG4 antibodies as a specific marker of chronic inflammatory demyelinating polyradiculoneuropathy.
Learn more about our CNS demyelinating disease testing through this case study focused on MOG-IgG as a marker of acute disseminated encephalomyelitis.
This webinar will discuss how autoimmune neurology testing has changed with expanding antibody discovery and why a patient-first, phenotype-specific approach improves test selection and interpretation.