Abnormal large-scale resting-state functional networks in anti-N-methyl-D-aspartate receptor encephalitis

Xiarong Gong; Libo Wang; Yuanyuan Guo; Yingzi Ma; Wei Li; Juanjuan Zhang; Meiling Chen; Jiaojian Wang; Qiang Meng; Kexuan Chen; Yanghua Tian

doi:10.3389/fnins.2024.1455131

Abnormal large-scale resting-state functional networks in anti-N-methyl-D-aspartate receptor encephalitis

Front Neurosci. 2024 Aug 19:18:1455131. doi: 10.3389/fnins.2024.1455131. eCollection 2024.

Authors

Xiarong Gong^#^{1

2}, Libo Wang^#³, Yuanyuan Guo^#⁴, Yingzi Ma^{5

6}, Wei Li^{5

6}, Juanjuan Zhang⁴, Meiling Chen⁷, Jiaojian Wang^{5

6}, Qiang Meng⁸, Kexuan Chen⁹, Yanghua Tian¹⁰

Affiliations

¹ Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China.
² Department of MR, The First People's Hospital of Yunnan Province, Kunming, China.
³ The Second People's Hospital of Yuxi, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.
⁴ Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
⁵ State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China.
⁶ Yunnan Key Laboratory of Primate Biomedical Research, Kunming, China.
⁷ Department of Clinical Psychology, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.
⁸ Department of Neurology, The First People's Hospital of Yunnan Province, Kunming, China.
⁹ Medical School, Kunming University of Science and Technology, Kunming, China.
¹⁰ Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.

^# Contributed equally.

Abstract

Background: Patients with anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis often experience severe symptoms. Resting-state functional MRI (rs-fMRI) has revealed widespread impairment of functional networks in patients. However, the changes in information flow remain unclear. This study aims to investigate the intrinsic functional connectivity (FC) both within and between resting-state networks (RSNs), as well as the alterations in effective connectivity (EC) between these networks.

Methods: Resting-state functional MRI (rs-fMRI) data were collected from 25 patients with anti-NMDAR encephalitis and 30 healthy controls (HCs) matched for age, sex, and educational level. Changes in the intrinsic functional connectivity (FC) within and between RSNs were analyzed using independent component analysis (ICA). The functional interaction between RSNs was identified by granger causality analysis (GCA).

Results: Compared to HCs, patients with anti-NMDAR encephalitis exhibited lower performance on the Wisconsin Card Sorting Test (WCST), both in terms of correct numbers and correct categories. Additionally, these patients demonstrated decreased scores on the Montreal Cognitive Assessment (MoCA). Neuroimaging studies revealed abnormal intra-FC within the default mode network (DMN), increased intra-FC within the visual network (VN) and dorsal attention network (DAN), as well as increased inter-FC between VN and the frontoparietal network (FPN). Furthermore, aberrant effective connectivity (EC) was observed among the DMN, DAN, FPN, VN, and somatomotor network (SMN).

Conclusion: Patients with anti-NMDAR encephalitis displayed noticeable deficits in both memory and executive function. Notably, these patients exhibited widespread impairments in intra-FC, inter-FC, and EC. These results may help to explain the pathophysiological mechanism of anti-NMDAR encephalitis.

Keywords: GCA; ICA; anti-N-methyl-D-aspartate receptor encephalitis; effective connectivity; functional connectivity; resting-state fMRI.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study was supported by the Natural Science Foundation of Yunnan Province (202102AA100053) and Yunnan Fundamental Research Projects (Nos. 202201BE070001-004 and 202101AT070235); Kunming University of Science and Technology & The Second People’s Hospital of Yuxi Joint Special Project on Medical Research (KUST-YX2022001 and KUST-YX2022003); Kunming University of Science and Technology & People’s Hospital of Lijiang Joint Special Project on Medical Research (KUST-LJ2022002Y); Kunming University of Science and Technology & The First People’s Hospital of Yunnan Province Joint Special Project on Medical Research (KUST-KH2022024Y); The Program of Yunnan Clinical Research Center for Geriatric Diseases (Grant No. 2023A1010128); The Yunnan Provincial Clinical Research Center for Geriatric Diseases (Grant No. 2023YJZX-LN20); Yunnan Provincial Science and Technology Department Science and Technology Plan Kunming Medical University Joint Project (202101AY070001-245 and 202401AY070001-116); Yunnan Health Training Project of High Level Talents (no. L-2017013,H-2019070); and Ten thousand Talents Program-Famous Doctor Project of Yunnan Province (no. YNWR-MY-2018-018).