White Matter Changes as an Independent Predictor of Alzheimer’s Disease

Article type: Research Article

Authors: Yan, Yibing^{a; b; 1} | Wu, Yue^{a; b; 1} | Xiao, Guixian^f | Wang, Lu^{a; b} | Zhou, Shanshan^{a; b; d} | Wei, Ling^{a; b; d} | Tian, Yanghua^{a; b; d; e; f} | Wu, Xingqi^{a; b; *} | Hu, Panpan^{a; b; c; d; e; *} | Wang, Kai^{a; b; c; d; e; *}

Affiliations: [a] Department of Neurology, The First Affiliated Hospital of Anhui Medical University, the School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China | [b] Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China | [c] Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China | [d] Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China | [e] Anhui Provincial Institute of Translational Medicine, Anhui Medical University, Hefei, China | [f] Department of Sleep Psychology, The Second Hospital of Anhui Medical University, Anhui Medical University, Hefei, China

Correspondence: [*] Correspondence to: Xingqi Wu, Panpan Hu, and Kai Wang, Department of Neurology, First Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China. Tel.: +86 551 62923704; Fax: +86 551 62923704; E-mails: [email protected], [email protected], [email protected].

Note: [1] These authors contributed equally to this work.

Abstract: Background:Abnormalities in white matter (WM) may be a crucial physiologic feature of Alzheimer’s disease (AD). However, neuroimaging’s ability to visualize the underlying functional degradation of the WM region in AD is unclear. Objective:This study aimed to explore the differences in amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) in the WM region of patients with AD and healthy controls (HC) and to investigate further whether these values can provide supplementary information for diagnosing AD. Methods:Forty-eight patients with AD and 46 age-matched HC were enrolled and underwent resting-state functional magnetic resonance imaging and a neuropsychological battery assessment. We analyzed the differences in WM activity between the two groups and further explored the correlation between WM activity in the different regions and cognitive function in the AD group. Finally, a machine learning algorithm was adopted to construct a classifier in detecting the clinical classification ability of the values of ALFF/ALFF in the WM. Results:Compared with HCs, patients with AD had lower WM activity in the right anterior thalamic radiation, left frontal aslant tract, and left forceps minor, which are all positively related to global cognitive function, memory, and attention function (all p < 0.05). Based on the combined WM ALFF and fALFF characteristics in the different regions, individuals not previously assessed were classified with moderate accuracy (75%), sensitivity (71%), specificity (79%), and area under the receiver operating characteristic curve (85%). Conclusion:Our results suggest that WM activity is reduced in AD and can be used for disease classification.

Keywords: Alzheimer’s disease, amplitude of low-frequency fluctuation, cognitive function, resting-state functional magnetic resonance imaging, white matter

DOI: 10.3233/JAD-221037

Journal: Journal of Alzheimer's Disease, vol. 93, no. 4, pp. 1443-1455, 2023