Functional connectivity of large-scale brain networks in patients with anti-NMDA receptor encephalitis: an observational study

Michael Peer, Harald Prüss, Inbal Ben-Dayan, Friedemann Paul*, Shahar Arzy, Carsten Finke

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

102 Scopus citations

Abstract

Background In anti-NMDA receptor (NMDAR) encephalitis, antibody-mediated dysfunction of NMDARs causes severe neuropsychiatric symptoms, including psychosis, memory deficits, and movement disorders. However, it remains elusive how antibody-mediated NMDAR dysfunction leads to these symptoms, and whether the symptoms arise from impairment in specific brain regions and the interactions between impaired regions. Methods In this observational study, we recruited 43 patients with anti-NMDAR encephalitis from a tertiary university hospital and 43 age-matched and sex-matched healthy controls without a history of neurological or psychiatric disorders, who were recruited from the general population of Berlin. We used structural and resting-state functional MRI to investigate alterations in connectivity in all participants. We did functional connectivity analyses, including large-scale network analysis, whole-brain pair-wise connectivity, and machine-learning classification, and compared the results with patients' functional impairment. Findings Although structural MRI was normal in 31 (72%) of the 43 patients, we observed widespread alterations of functional connectivity that correlated with clinical measures. These alterations included impaired hippocampal functional connectivity, decoupling of the medial temporal and the default-mode networks, and an overall impairment of frontotemporal connections. Furthermore, functional connectivity was impaired within distributed large-scale networks, including sensorimotor, frontoparietal, lateral-temporal, and visual networks. Memory impairment correlated with hippocampal and medial-temporal-lobe network connectivity, whereas schizophrenia-like symptoms were associated with functional connectivity changes in frontoparietal networks. Machine-learning analyses corroborated these findings and identified frontoparietal and frontotemporal connections as reliably discriminating features between patients and controls, yielding an overall accuracy of 81%. Interpretation This study reveals a characteristic pattern of whole-brain functional connectivity alterations in anti-NMDAR encephalitis that is well suited to explain the major clinical symptoms of the disorder. These observations advance the pathophysiological understanding of NMDAR dysfunction in the human brain and could be similarly relevant for other neuropsychiatric disorders, such as schizophrenia. Funding Deutsche Forschungsgemeinschaft, Israeli National Science Foundation, Ministry of Science and Technology of Israel, Orion Foundation, and the Agnes Ginges Center for Neurologenetics.

Original languageAmerican English
Pages (from-to)768-774
Number of pages7
JournalThe Lancet Psychiatry
Volume4
Issue number10
DOIs
StatePublished - Oct 2017

Bibliographical note

Publisher Copyright:
© 2017 Elsevier Ltd

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