{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T15:19:56Z","timestamp":1778167196781,"version":"3.51.4"},"reference-count":78,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T00:00:00Z","timestamp":1778025600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medicina"],"abstract":"<jats:p>Autoimmune encephalitis is an increasingly recognized cause of encephalitis. Detection of disease-specific antibodies is the cornerstone of diagnosis. Despite growing clinical awareness and the routine availability of antibody assays in most centers, diagnosis remains challenging due to diverse clinical presentations, the low diagnostic yield of commercial antibody kits, difficulties in interpreting antibody results, and a substantial proportion of paraclinically silent patients. This narrative review summarizes current diagnostic approaches to autoimmune encephalitis, with particular emphasis on antibody detection strategies, the diagnostic yield of different techniques, serum vs. cerebrospinal fluid testing, and the diagnostic value of supportive cerebrospinal fluid biomarkers. In addition, we discuss patients with seronegative or paraclinically silent disease, in whom diagnosis relies primarily on clinical criteria and the exclusion of alternative etiologies. Finally, we outline future perspectives, including advanced immunological techniques and machine learning-based diagnostic models, which may facilitate earlier identification and more accurate classification of autoimmune encephalitis. Improved integration of clinical assessment with cerebrospinal fluid biomarkers and novel analytical tools may reduce diagnostic delay and support the timely initiation of immunotherapy, ultimately improving neurological outcomes.<\/jats:p>","DOI":"10.3390\/medicina62050896","type":"journal-article","created":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T14:05:46Z","timestamp":1778162746000},"page":"896","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Current and Future Biomarkers in the Diagnosis of Autoimmune Encephalitis: A Review of Biomarker Detection Techniques and Their Performance"],"prefix":"10.3390","volume":"62","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2042-4378","authenticated-orcid":false,"given":"Patricija","family":"Pla\u010denyt\u0117","sequence":"first","affiliation":[{"name":"Faculty of Medicine, Vilnius University, LT-03101 Vilnius, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nata\u0161a","family":"Giedraitien\u0117","sequence":"additional","affiliation":[{"name":"Clinic of Neurology and Neurosurgery, Faculty of Medicine, Institute of Clinical Medicine, Vilnius University, LT-03101 Vilnius, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mantas","family":"Vai\u0161vilas","sequence":"additional","affiliation":[{"name":"Clinic of Neurology and Neurosurgery, Faculty of Medicine, Institute of Clinical Medicine, Vilnius University, LT-03101 Vilnius, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"31","DOI":"10.17925\/ENR.2013.08.01.31","article-title":"Autoimmune Encephalitis","volume":"8","author":"Leypoldt","year":"2013","journal-title":"Eur. 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