Abstract:

Autoimmune encephalitis (AE) is a group of immune-mediated inflammatory diseases of the central nervous system, characterized by diverse and complex clinical manifestations, posing challenges for early diagnosis and risk assessment. Specific autoantibody testing plays a central role in the classification and diagnosis of AE. However, in clinical scenarios where antibody testing is limited or antibodies are negative (30%-50% of AE cases are antibody-negative AE), relying solely on antibody detection is often insufficient to meet the diagnostic and treatment needs of AE. In recent years, research on non-antibody biomarkers, including soluble biomarkers in blood and cerebrospinal fluid, imaging changes, and genetic susceptibility, has rapidly advanced. These studies not only deepen the understanding of AE pathobiology but also provide a potential basis for auxiliary diagnosis, treatment response evaluation, and individualized treatment in clinical practice. Nevertheless, the validation of non-antibody biomarkers remains limited, detection standards are not yet unified, and their clinical application still faces multiple challenges. Future research should leverage large-scale prospective cohorts, integrate artificial intelligence and other advanced technologies, and systematically investigate the value of dynamic changes in non-antibody biomarkers and multi-marker combined assessment in early diagnosis, treatment monito-ring, and prognosis evaluation of AE, thereby promoting the clinical translation of precision diagnosis and treatment for AE.

Key words: Autoimmune encephalitis, Early diagnosis, Prognosis, Biomarkers