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Tingyu Cao,1 Zengguang Wang,2 Xiaodong Zhu1 1Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China; 2Department of Neurosurgery, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, People’s Republic of ChinaCorrespondence: Xiaodong Zhu, Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China, Tel +86 13312142939, Email zxd3516@tmu.edu.cn Zengguang Wang, Department of Neurosurgery, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China, Email wangzengguang@tmu.edu.cnAbstract: Bruton’s tyrosine kinase (BTK) is a central signaling node in B cells. BTK inhibition has witnessed great success in the treatment of B-cell malignancies. Additionally, in the immune system, BTK is also a prominent component linking a wide variety of immune-related pathways. Therefore, more and more studies attempting to dissect the role of BTK in autoimmune and inflammation progression have emerged in recent years. In particular, BTK expression was also found to be elevated within the central nervous system (CNS) during neuroinflammation. BTK inhibitors are capable of crossing the blood–brain barrier rapidly to modulate B cell functions, attenuate microglial activities and affect NLRP3 inflammasome pathways within the CNS to improve the outcome of diseases. Thus, BTK inhibition appears to be a promising approach to modulate dysregulated inflammation in the CNS and alleviate destruction caused by excessive inflammatory responses. This review will summarize the immunomodulatory mechanisms in which BTK is involved in the development of neurological diseases and discuss the therapeutic potential of BTK inhibition for the treatment of neuroinflammatory pathology.Keywords: BTK, BTK inhibition, BTK inhibitors, neuroinflammation

ObjectiveThe aim of this study was to investigate the correlations of plasma neurodegenerative proteins and electroencephalography (EEG) dynamic functional network (DFN) parameters with disease progression in early Parkinson’s disease (PD) with different motor subtypes, including tremor-dominant (TD) and postural instability and gait disorder (PIGD).MethodsIn our study, 33 patients with PD (21 TD and 12 PIGD) and 33 healthy controls (HCs) were enrolled. Plasma neurofilament light chain (NfL), α-synuclein (α-syn), total-tau (t-tau), β-amyloid 42 (Aβ42), and β-amyloid 40 (Aβ40) levels were measured using an ultrasensitive single-molecule array (Simoa) immunoassay. All the patients with PD underwent EEG quantified by DFN analysis. The motor and non-motor performances were evaluated by a series of clinical assessments. Subsequently, a correlation analysis of plasma biomarkers and EEG measures with clinical scales was conducted.ResultsIn the TD group, plasma NfL exhibited a significant association with MDS-UPDRS III and Montreal Cognitive Assessment (MoCA). A higher Aβ42/40 level was significantly related to a decrease in Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA) in the PIGD group. In terms of the correlation between EEG characteristic parameters and clinical outcomes, trapping time (TT) delta was positively correlated with MDS-UPDRS III and MoCA scores in the TD group, especially in the prefrontal and frontal regions. For other non-motor symptoms, there were significant direct associations of kPLI theta with HAMD and HAMA, especially in the prefrontal region, and kPLI gamma was particularly correlated with Rapid Eye Movement Sleep Behavior Disorder Screening Questionnaire (RBDSQ) scores in the prefrontal, frontal, and parietal regions in the TD group. Furthermore, there was a significant positive correlation between plasma t-tau and kPLI, and pairwise correlations were found among plasma NfL, theta TT, and MoCA scores in the TD group.ConclusionThese results provide evidence that plasma neurodegenerative proteins and EEG measures have great potential in predicting the disease progression of PD subtypes, especially for the TD subtype. A combination of these two kinds of markers may have a superposition effect on monitoring and estimating the prognosis of PD subtypes and deserves further research in larger, follow-up PD cohorts.