Disrupted Gray Matter Networks Associated with Cognitive Dysfunction in Cerebral Small Vessel Disease

Yian Gao; Shengpei Wang; Haotian Xin; Mengmeng Feng; Qihao Zhang; Chaofan Sui; Lingfei Guo; Changhu Liang; Hongwei Wen

doi:10.3390/brainsci13101359

Disrupted Gray Matter Networks Associated with Cognitive Dysfunction in Cerebral Small Vessel Disease

Brain Sci. 2023 Sep 22;13(10):1359. doi: 10.3390/brainsci13101359.

Authors

Yian Gao¹, Shengpei Wang^{2

3}, Haotian Xin⁴, Mengmeng Feng⁴, Qihao Zhang⁵, Chaofan Sui¹, Lingfei Guo¹, Changhu Liang⁶, Hongwei Wen⁷

Affiliations

¹ Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China.
² Research Center for Brain-Inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100040, China.
³ University of Chinese Academy of Sciences, Beijing 101408, China.
⁴ Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, No. 45 Chang-Chun St., Xicheng District, Beijing 100054, China.
⁵ Department of Radiology, Weill Cornell Medical College, New York. 407 East 61st Street, New York, NY 10044, USA.
⁶ Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jing-Wu Road No. 324, Jinan 250021, China.
⁷ Key Laboratory of Cognition and Personality (Ministry of Education), Faculty of Psychology, Southwest University, Chongqing 400715, China.

Abstract

This study aims to investigate the disrupted topological organization of gray matter (GM) structural networks in cerebral small vessel disease (CSVD) patients with cerebral microbleeds (CMBs). Subject-wise structural networks were constructed from GM volumetric features of 49 CSVD patients with CMBs (CSVD-c), 121 CSVD patients without CMBs (CSVD-n), and 74 healthy controls. The study used graph theory to analyze the global and regional properties of the network and their correlation with cognitive performance. We found that both the control and CSVD groups exhibited efficient small-world organization in GM networks. However, compared to controls, CSVD-c and CSVD-n patients exhibited increased global and local efficiency (E_glob/E_loc) and decreased shortest path lengths (L_p), indicating increased global integration and local specialization in structural networks. Although there was no significant global topology change, partially reorganized hub distributions were found between CSVD-c and CSVD-n patients. Importantly, regional topology in nonhub regions was significantly altered between CSVD-c and CSVD-n patients, including the bilateral anterior cingulate gyrus, left superior parietal gyrus, dorsolateral superior frontal gyrus, and right MTG, which are involved in the default mode network (DMN) and sensorimotor functional modules. Intriguingly, the global metrics (E_glob, E_loc, and L_p) were significantly correlated with MoCA, AVLT, and SCWT scores in the control group but not in the CSVD-c and CSVD-n groups. In contrast, the global metrics were significantly correlated with the SDMT score in the CSVD-s and CSVD-n groups but not in the control group. Patients with CSVD show a disrupted balance between local specialization and global integration in their GM structural networks. The altered regional topology between CSVD-c and CSVD-n patients may be due to different etiological contributions, which may offer a novel understanding of the neurobiological processes involved in CSVD with CMBs.

Keywords: cerebral microbleeds; cerebral small vessel disease; graph theory; gray matter networks; voxel-based morphometry.

Abstract

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