Disrupted resting-state brain functional network properties in non-neuropsychiatric systemic lupus erythematosus patients

被引:4
作者
Tan, Xiangliang [1 ]
Liu, Xiaojin [2 ,3 ]
Han, Kai [4 ]
Zhao, Ling [3 ]
Niu, Meiqi [3 ]
Yao, Qiaoli [1 ]
Huang, Qin [5 ]
Zhong, Miao [3 ]
Mei, Yingjie [6 ]
Huang, Ruiwang [3 ,8 ]
Xu, Yikai [1 ,7 ]
机构
[1] Southern Med Univ, Nanfang Hosp, Dept Med Imaging Ctr, Guangzhou 510515, Peoples R China
[2] Beijing Normal Univ, Ctr Educ Sci & Technol, Zhuhai, Peoples R China
[3] South China Normal Univ, Ctr Study Appl Psychol, Sch Psychol, Key Lab Mental Hlth & Cognit Sci Guangdong Prov, Guangzhou, Peoples R China
[4] Southern Med Univ, Nanfang Hosp, Dept Dermatol, Guangzhou, Peoples R China
[5] Southern Med Univ, Nanfang Hosp, Dept Rheumatol, Guangzhou, Peoples R China
[6] Philips Healthcare, Guangzhou, Peoples R China
[7] Southern Med Univ, Key Lab Mental Hlth, Minist Educ, Guangzhou, Peoples R China
[8] South China Normal Univ, Sch Psychol, Guangzhou 510631, Peoples R China
基金
中国国家自然科学基金;
关键词
Systemic lupus erythematosus; resting-state functional MRI; functional connectivity; default mode network; frontal-parietal network; DEFAULT-MODE NETWORK; MATTER STRUCTURAL NETWORKS; WORKING-MEMORY IMPAIRMENT; PARKINSONS-DISEASE; CONNECTIVITY; FMRI; DEPRESSION; CORTEX;
D O I
10.1177/09612033231160725
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Introduction Previous fMRI studies revealed that the abnormal functional connectivity (FC) was related to cognitive impairment in patients with SLE. However, it remains unclear how the disease severity affects the functional topological organization of the whole-brain network in SLE patients without neuropsychiatric symptoms (non-NPSLE). Objective We aim to examine the impairment of the whole-brain functional network in SLE patients without neuropsychiatric symptoms (non-NPSLE), which may improve the understanding of neural mechanism in SLE. Methods We acquired resting-state fMRI data from 32 non-NPSLE patients and 32 healthy controls (HC), constructed their whole-brain functional network, and then estimated the topological properties including global and nodal parameters by using graph theory. Meanwhile, we also investigated the differences in intra- and inter-network FC between the non-NPSLE patients and the HC. Results The non-NPSLE patients showed significantly lower clustering coefficient, global and local efficiency, but higher characteristic path length than the HC. The non-NPSLE patients had significantly lower nodal strength in two regions, ventromedial prefrontal cortex (vmPFC) and anterior PFC (aPFC) than the HC. We found the non-NPSLE patients had significantly lower intra-network FC within frontal-parietal network (FPN) and within default mode network (DMN), and significantly lower inter-network FC between DMN and FPN than the HC. The intra-network FC within DMN was negatively correlated with systemic lupus erythematosus disease activity index (SLEDAI). Conclusion Abnormal whole-brain functional network properties and abnormal intra- and inter-network FC may be related to cognitive impairment and disease degree in the non-NPSLE patients. Our findings provide a network perspective to understand the neural mechanisms of SLE.
引用
收藏
页码:538 / 548
页数:11
相关论文
共 44 条
  • [1] Resting state fMRI in Alzheimer's disease: beyond the default mode network
    Agosta, Federica
    Pievani, Michela
    Geroldi, Cristina
    Copetti, Massimiliano
    Frisoni, Giovanni B.
    Filippi, Massimo
    [J]. NEUROBIOLOGY OF AGING, 2012, 33 (08) : 1564 - 1578
  • [2] Asghar MA., 2018, J RHEUMATOL, V12
  • [3] The effects of disease activity, inflammation, depression and cognitive fatigue on resting state fMRI in systemic lupus erythematosus
    Barraclough, Michelle
    McKie, Shane
    Parker, Ben
    Elliott, Rebecca
    Bruce, Ian N.
    [J]. RHEUMATOLOGY, 2022, 61 (SI) : SI39 - SI47
  • [4] The effects of disease activity on neuronal and behavioural cognitive processes in systemic lupus erythematosus
    Barraclough, Michelle
    McKie, Shane
    Parker, Ben
    Elliott, Rebecca
    Bruce, Ian N.
    [J]. RHEUMATOLOGY, 2022, 61 (01) : 195 - 204
  • [5] Altered cognitive function in systemic lupus erythematosus and associations with inflammation and functional and structural brain changes
    Barraclough, Michelle
    Mckie, Shane
    Parker, Ben
    Jackson, Alan
    Pemberton, Philip
    Elliott, Rebecca
    Bruce, Ian N.
    [J]. ANNALS OF THE RHEUMATIC DISEASES, 2019, 78 (07) : 934 - 940
  • [6] CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING
    BENJAMINI, Y
    HOCHBERG, Y
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) : 289 - 300
  • [7] Resting state network functional connectivity abnormalities in systemic lupus erythematosus: correlations with neuropsychiatric impairment
    Bonacchi, Raffaello
    Rocca, Maria A.
    Ramirez, Giuseppe A.
    Bozzolo, Enrica P.
    Canti, Valentina
    Preziosa, Paolo
    Valsasina, Paola
    Riccitelli, Gianna C.
    Meani, Alessandro
    Moiola, Lucia
    Rovere-Querini, Patrizia
    Manfredi, Angelo A.
    Filippi, Massimo
    [J]. MOLECULAR PSYCHIATRY, 2021, 26 (07) : 3634 - 3645
  • [8] Default mode network changes in multiple sclerosis: a link between depression and cognitive impairment?
    Bonavita, S.
    Sacco, R.
    Esposito, S.
    d'Ambrosio, A.
    Della Corte, M.
    Corbo, D.
    Docimo, R.
    Gallo, A.
    Lavorgna, L.
    Cirillo, M.
    Bisecco, A.
    Esposito, F.
    Tedeschi, G.
    [J]. EUROPEAN JOURNAL OF NEUROLOGY, 2017, 24 (01) : 27 - 36
  • [9] The brain's default network - Anatomy, function, and relevance to disease
    Buckner, Randy L.
    Andrews-Hanna, Jessica R.
    Schacter, Daniel L.
    [J]. YEAR IN COGNITIVE NEUROSCIENCE 2008, 2008, 1124 : 1 - 38
  • [10] Abnormal topological organization in systemic lupus erythematosus: a resting-state functional magnetic resonance imaging analysis
    Cao, Zheng-Ye
    Wang, Na
    Jia, Jie-Ting
    Zhang, Hong-Ying
    Shang, Song-An
    Hu, Jing-Jing
    Xu, Yuan
    Wu, Jing-Tao
    [J]. BRAIN IMAGING AND BEHAVIOR, 2021, 15 (01) : 14 - 24