|
1000
|
Abstract/Summary
|
-
<jats:title>Abstract</jats:title><jats:p>There is growing evidence suggesting that immunological mechanisms play a significant role in the development of psychiatric symptoms in certain patient subgroups. However, the relationship between clinical red flags for suspected autoimmune psychiatric disease and signs of central nervous system (CNS) pathology (e.g., routine cerebrospinal fluid (CSF) alterations, CNS damage markers, neurophysiological or neuroimaging findings) has received limited attention. Here, we aimed to describe the prevalence and distribution of potential CNS pathologies in psychiatric patients in relation to clinical red flags for autoimmune psychiatric disease and psychiatric symptoms. CSF routine findings and CNS damage markers; neurofilament light chain protein (NfL), glial fibrillary acidic protein (GFAP) and total Tau (t-Tau), in CSF from 127 patients with psychiatric disease preselected for suspected immunological involvement were related to recently proposed clinical red flags, psychiatric features, and MRI and EEG findings. Twenty-one percent had abnormal routine CSF findings and 27% had elevated levels of CNS damage markers. Six percent had anti-neuronal antibodies in serum and 2% had these antibodies in the CSF. Sixty-six percent of patients examined with MRI (n = 88) had alterations, mostly atrophy or nonspecific white matter lesions. Twenty-seven percent of patients with EEG recordings (n = 70) had abnormal findings. Elevated NfL levels were associated with comorbid autoimmunity and affective dysregulation symptoms. Elevated t-Tau was associated with catatonia and higher ratings of agitation/hyperactivity. Elevated GFAP was associated with acute onset, atypical presentation, infectious prodrome, tics, depressive/anxiety symptom ratings and overall greater psychiatric symptom burden. In conclusion, preselection based on suspected autoimmune psychiatric disease identifies a population with a high prevalence of CSF alterations suggesting CNS pathology. Future studies should examine the value of these markers in predicting treatment responses.</jats:p>
|
|
1000
|
Hinweis
|
-
DeepGreen-ID: fa2def08e62648f48a0761e4a3ca3cfb ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search) ;
|
