Large-scale networks changes in Wilson’s disease associated with neuropsychiatric impairments: a resting-state functional magnetic resonance imaging study

• Published in: BMC psychiatry 2023-11, Vol.23 (1), p.1-805, Article 805
• Main Authors: Wang, Anqin, Dong, Ting, Wei, Taohua, Wu, Hongli, Yang, Yulong, Ding, Yufeng, Li, Chuanfu, Yang, Wenming
• Format: Article
• Language: English
• Subjects: Analysis; Brain damage; Brain mapping; Brain research; Cognitive ability; Copper; Cortex (parietal); Development and progression; Diagnosis; Functional magnetic resonance imaging; Independent component analysis; Magnetic resonance imaging; Medical imaging; Mental disorders; Motor task performance; Neural networks; Neuroimaging; Patients; Prefrontal cortex; Psychiatry; Registration; Resting-state networks; Wilson's disease
• ISSN: 1471-244X; 1471-244X
• DOI: 10.1186/s12888-023-05236-3

Background In Wilson's disease (WD) patients, network connections across the brain are disrupted, affecting multidomain function. However, the details of this neuropathophysiological mechanism remain unclear due to the rarity of WD. In this study, we aimed to investigate alterations in brain network connectivity at the whole-brain level (both intra- and inter-network) in WD patients through independent component analysis (ICA) and the relationship between alterations in these brain network functional connections (FCs) and clinical neuropsychiatric features to understand the underlying pathophysiological and central compensatory mechanisms. Methods Eighty-five patients with WD and age- and sex-matched 85 healthy control (HC) were recruited for resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We extracted the resting-state networks (RSNs) using the ICA method, analyzed the changes of FC in these networks and the correlation between alterations in FCs and clinical neuropsychiatric features. Results Compared with HC, WD showed widespread lower connectivity within RSNs, involving default mode network (DMN), frontoparietal network (FPN), somatomotor network (SMN), dorsal attention network (DAN), especially in patients with abnormal UWDRS scores. Furthermore, the decreased FCs in the left medial prefrontal cortex (L_ MPFC), left anterior cingulate gyrus (L_ACC), precuneus (PCUN)within DMN were negatively correlated with the Unified Wilson's Disease Rating Scale-neurological characteristic examination (UWDRS-N), and the decreased FCs in the L_MPFC, PCUN within DMN were negatively correlated with the Unified Wilson's Disease Rating Scale-psychiatric symptoms examination (UWDRS-P). We additionally discovered that the patients with WD exhibited significantly stronger FC between the FPN and DMN, between the DAN and DMN, and between the FPN and DAN compared to HC. Conclusions We have provided evidence that WD is a disease with widespread dysfunctional connectivity in resting networks in brain, leading to neurological features and psychiatric symptoms (e.g. higher-order cognitive control and motor control impairments). The alter intra- and inter-network in the brain may be the neural underpinnings for the neuropathological symptoms and the process of injury compensation in WD patients. Keywords: Wilson's disease, Independent component analysis, Resting-state networks