Changed Cerebral White Matter Structural Network Topological Characters and Its Correlation with Cognitive Behavioral Abnormalities in Narcolepsy Type 1

Abstract

In the current study we investigated topological abnormalities of the cerebral white matter networks in narcolepsy type 1 (NT1) patients and its relationship with their cognitive abnormalities using diffusion tensor imaging (DTI) technology. Methods: DTI and the Beijing version of the Montreal Cognitive Assessment (MoCA-BJ) were applied to 30 NT1 patients and 30 age-matched healthy controls. DTI studies were also carried using the 3T MRI system. Next, DTI data was used to establish a cerebral white matter network for all subjects and graph theory was applied to analyze the topological characteristics of the white matter structural network. Topographical parameters (such as local efficiency (Eloc), global efficiency (Eglob) and small-world (σ)) between NT1 patients and controls were then compared. The correlation between MoCA-BJ scores and topological parameters was also analyzed. Results: MoCA-BJ scores in NT1 patients were lower than those in the healthy controls. Compared with healthy controls, the global efficiency of the white matter network and attributes of the small world network were significantly reduced in NT1 patients. Finally, the global efficiency of the white matter structural network was related to the MoCA-BJ score of NT1 patients. Conclusion:The abnormal topological characteristics of the white matter structural network in NT1 patients may be associated with their cognitive impairment.

Psychobehavioural profile in narcolepsy type 1 with and without REM sleep behaviour disorder

“…In the NT1 adult population, executive functions and higher‐order cognition have been studied extensively, while the global cognition assessment received little‐to‐no attention (Filardi et al, 2021). In a recent study investigating the relationship between topographical abnormalities of the cerebral white matter networks and cognitive functions in NT1 patients using diffusion tensor imaging technology (Ni et al, 2022), the authors found lower MoCA scores in NT1 patients similarly to that observed in our patients. Furthermore, the MoCA score correlated with a lower global efficiency of the white matter structural network in NT1 (Ni et al, 2022).…”

“…In a recent study investigating the relationship between topographical abnormalities of the cerebral white matter networks and cognitive functions in NT1 patients using diffusion tensor imaging technology (Ni et al, 2022), the authors found lower MoCA scores in NT1 patients similarly to that observed in our patients. Furthermore, the MoCA score correlated with a lower global efficiency of the white matter structural network in NT1 (Ni et al, 2022). However, it is important to consider that MoCA is a screening tool for detecting mild cognitive impairment (MCI) (Nasreddine et al, 2005), and some studies underline the importance of validating MCI cut-offs in independent samples, because they are likely to be sample dependent and specific to the individual investigation (Martin et al, 2017;Weissberger et al, 2017).…”