Commonalities and distinctions between the type 2 diabetes mellitus and Alzheimer's disease: a systematic review and multimodal neuroimaging meta-analysis

Hao Xie; Ying Yu; Yang Yang; Qian Sun; Ze-Yang Li; Min-Hua Ni; Si-Ning Li; Pan Dai; Yan-Yan Cui; Xin-Yu Cao; Nan Jiang; Li-Juan Du; Wen Gao; Jia-Jun Bi; Lin-Feng Yan; Guang-Bin Cui

doi:10.3389/fnins.2023.1301778

Commonalities and distinctions between the type 2 diabetes mellitus and Alzheimer's disease: a systematic review and multimodal neuroimaging meta-analysis

Front Neurosci. 2023 Dec 6:17:1301778. doi: 10.3389/fnins.2023.1301778. eCollection 2023.

Authors

Hao Xie^#¹, Ying Yu^#¹, Yang Yang^#¹, Qian Sun¹, Ze-Yang Li¹, Min-Hua Ni¹, Si-Ning Li^{1

2}, Pan Dai^{1

2}, Yan-Yan Cui^{1

3}, Xin-Yu Cao^{1

4}, Nan Jiang¹, Li-Juan Du¹, Wen Gao⁵, Jia-Jun Bi⁵, Lin-Feng Yan¹, Guang-Bin Cui¹

Affiliations

¹ Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), Xi'an, Shaanxi, China.
² Faculty of Medical Technology, Xi'an Medical University, Xi'an, Shaanxi, China.
³ Faculty of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China.
⁴ Faculty of Medical Technology, Medical School of Yan'an University, Yan'an, Shaanxi, China.
⁵ Student Brigade, Fourth Military Medical University, Xi'an, Shaanxi, China.

^# Contributed equally.

Abstract

Background: Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are aging related diseases with high incidence. Because of the correlation of incidence rate and some possible mechanisms of comorbidity, the two diseases have been studied in combination by many researchers, and even some scholars call AD type 3 diabetes. But the relationship between the two is still controversial.

Methods: This study used seed-based d mapping software to conduct a meta-analysis of the whole brain resting state functional magnetic resonance imaging (rs-fMRI) study, exploring the differences in amplitude low-frequency fluctuation (ALFF) and cerebral blood flow (CBF) between patients (AD or T2DM) and healthy controls (HCs), and searching for neuroimaging evidence that can explain the relationship between the two diseases.

Results: The final study included 22 datasets of ALFF and 22 datasets of CBF. The results of T2DM group showed that ALFF increased in both cerebellum and left inferior temporal gyrus regions, but decreased in left middle occipital gyrus, right inferior occipital gyrus, and left anterior central gyrus regions. In the T2DM group, CBF increased in the right supplementary motor area, while decreased in the middle occipital gyrus and inferior parietal gyrus. The results of the AD group showed that the ALFF increased in the right cerebellum, right hippocampus, and right striatum, while decreased in the precuneus gyrus and right superior temporal gyrus. In the AD group, CBF in the anterior precuneus gyrus and inferior parietal gyrus decreased. Multimodal analysis within a disease showed that ALFF and CBF both decreased in the occipital lobe of the T2DM group and in the precuneus and parietal lobe of the AD group. In addition, there was a common decrease of CBF in the right middle occipital gyrus in both groups.

Conclusion: Based on neuroimaging evidence, we believe that T2DM and AD are two diseases with their respective characteristics of central nervous activity and cerebral perfusion. The changes in CBF between the two diseases partially overlap, which is consistent with their respective clinical characteristics and also indicates a close relationship between them.

Systematic review registration: PROSPERO [CRD42022370014].

Keywords: Alzheimer’s disease; coordinated-based meta-analysis; functional magnetic resonance imaging; functional neuroimaging; type 2 diabetes mellitus.

Publication types

Review

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Key Research and Development Projects of Shaanxi (Grant number 2023-YBSF-331) and “Rapid response” research project of Air Force Military Medical University (Grant number 2023KXKT025).