Impact of type 2 diabetes mellitus on differential cerebellar volume reduction in Alzheimer's disease trajectory

BackgroundAlzheimer's disease (AD) is a neurodegenerative disorder linked to cognitive decline. Type 2 diabetes mellitus (T2DM) is a known risk factor for AD and may contribute to cerebellar atrophy, but their relationship remains unclear.ObjectiveThis study investigated the impact of T2DM on cerebellar gray matter (GM) volume across normal cognition (NC), preclinical AD, and AD mild cognitive impairment (AD MCI) groups to explore its role in AD progression.MethodsMedical records of patients visiting St. Vincent's Hospital (September 2019-April 2024) were analyzed. Cerebellar GM volume was analyzed using voxel-based morphometry with SPM12. Group differences in cerebellar GM volume were assessed using rank analysis of covariance. Spearman's partial correlation was used to explore associations between cerebellar GM volume and cognitive function, and HbA1c levels in patients with T2DM.ResultsAD MCI patients with T2DM showed greater GM atrophy, particularly in the posterior lobe. In NC, T2DM was associated with Vermis VI volume reduction, while preclinical AD showed increased Left VIIIb volume. Amyloid-β positive (Aβ+) group has negative correlation HbA1c level and right Crus I volume. Cerebellar GM volume correlated with cognitive scores, particularly episodic memory in AD MCI patients with T2DM.ConclusionsT2DM and AD pathology contribute to cerebellar changes linked to cognitive decline. Managing T2DM may mitigate its impact on AD progression.

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Publication Details

Journal
Journal of Alzheimer s Disease
Published
2025-06-27
DOI
https://doi.org/10.1177/13872877251352208
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
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article

Impact of type 2 diabetes mellitus on differential cerebellar volume reduction in Alzheimer's disease trajectory

Hyun Kook Lim, Hyukjin Yoon, Dong Woo Kang, Yoo Hyun Um et al.
Journal of Alzheimer s Disease
Advanced Neuroimaging Techniques and Applications
article

Impact of type 2 diabetes mellitus on differential cerebellar volume reduction in Alzheimer's disease trajectory

Hyun Kook Lim, Hyukjin Yoon, Dong Woo Kang, Yoo Hyun Um, Sheng‐Min Wang, Jong‐Hyun Jeong, Suhyung Kim, Sunghwan Kim
article en

Abstract

BackgroundAlzheimer's disease (AD) is a neurodegenerative disorder linked to cognitive decline. Type 2 diabetes mellitus (T2DM) is a known risk factor for AD and may contribute to cerebellar atrophy, but their relationship remains unclear.ObjectiveThis study investigated the impact of T2DM on cerebellar gray matter (GM) volume across normal cognition (NC), preclinical AD, and AD mild cognitive impairment (AD MCI) groups to explore its role in AD progression.MethodsMedical records of patients visiting St. Vincent's Hospital (September 2019-April 2024) were analyzed. Cerebellar GM volume was analyzed using voxel-based morphometry with SPM12. Group differences in cerebellar GM volume were assessed using rank analysis of covariance. Spearman's partial correlation was used to explore associations between cerebellar GM volume and cognitive function, and HbA1c levels in patients with T2DM.ResultsAD MCI patients with T2DM showed greater GM atrophy, particularly in the posterior lobe. In NC, T2DM was associated with Vermis VI volume reduction, while preclinical AD showed increased Left VIIIb volume. Amyloid-β positive (Aβ+) group has negative correlation HbA1c level and right Crus I volume. Cerebellar GM volume correlated with cognitive scores, particularly episodic memory in AD MCI patients with T2DM.ConclusionsT2DM and AD pathology contribute to cerebellar changes linked to cognitive decline. Managing T2DM may mitigate its impact on AD progression.

Journal of Alzheimer s DiseaseVol. 106(4)
The Catholic University of Korea St. Vincent's Hospital (KR), The Catholic University of Korea Yeouido St. Mary's Hospital (KR), The Catholic University of Korea Seoul St. Mary's Hospital (KR), Catholic University of Korea (KR)
Good health and well-being
Openalex Percentile: Top 77%
Advanced Neuroimaging Techniques and Applications
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