Association of impaired fasting glucose and Type 2 Diabetes Mellitus with brain volume changes in Alzheimer’s Disease patients analyzed by MRI: a retrospective study

Wang, Weiwei; Wong, Leongtim; Shi, Lin; Luo, Yishan; Liang, Zhanhua; Dong, Chunbo; Song, Qingwei; Liu, Tieli; Zhang, Qing; Liu, Ailian; Miao, Yanwei; Wu, Jianlin

doi:10.7717/peerj.9801

Cited by 4 publications

(4 citation statements)

References 52 publications

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“…Similar to our research design, in structural MRI studies comparing AD patients with and without T2DM, it was reported that patients with AD and DM had significantly higher cortical atrophy caused by nonvascular mechanisms (Biessels et al, 2006) and significantly reduced pons volume (Wang et al, 2020). This research identified a significant impairment of the left SLF in AD patients with T2DM with DTI.…”

Section: Discussionsupporting

confidence: 84%

Diabetes‐related clinical and microstructural white matter changes in patients with Alzheimer's disease

Sumbul‐Sekerci,

Velioglu,

Sekerci

2024

Brain and Behavior

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AimAlthough there exists substantial epidemiological evidence indicating an elevated risk of dementia in individuals with diabetes, our understanding of the neuropathological underpinnings of the association between Type‐2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) remains unclear. This study aims to unveil the microstructural brain changes associated with T2DM in AD and identify the clinical variables contributing to these changes.MethodsIn this retrospective study involving 64 patients with AD, 31 individuals had concurrent T2DM. The study involved a comparative analysis of diffusion tensor imaging (DTI) images and clinical features between patients with and without T2DM. The FSL FMRIB software library was used for comprehensive preprocessing and tractography analysis of DTI data. After eddy current correction, the “bedpost” model was utilized to model diffusion parameters. Linear regression analysis with a stepwise method was used to predict the clinical variables that could lead to microstructural white matter changes.ResultsWe observed a significant impairment in the left superior longitudinal fasciculus (SLF) among patients with AD who also had T2DM. This impairment in patients with AD and T2DM was associated with an elevation in creatine levels.ConclusionThe white matter microstructure in the left SLF appears to be sensitive to the impairment of kidney function associated with T2DM in patients with AD. The emergence of AD in association with T2DM may be driven by mechanisms distinct from the typical AD pathology. Compromised renal function in AD could potentially contribute to impaired white matter integrity.

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Section: Discussionsupporting

confidence: 84%

Diabetes‐related clinical and microstructural white matter changes in patients with Alzheimer's disease

Sumbul‐Sekerci,

Velioglu,

Sekerci

2024

Brain and Behavior

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“…Different from other research software, AccuBrain ® is a fully automatic cloud-based computational tool, with no need for parameter settings during use ( Abrigo et al, 2019 ). More technical characteristics and their comparison with other automatic brain image segmentation methods were described in detail in previous work ( Gao et al, 2020 ; Wang et al, 2020 ). This tool has been validated to be more accurate, objective, and easier to implement and has been widely used in various neurological and mental diseases ( Wang et al, 2019 ; Zhao et al, 2019 ; Dou et al, 2020 ; Mai et al, 2021 ; Yu et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

Brain Volumetric Alterations in Preclinical HIV-Associated Neurocognitive Disorder Using Automatic Brain Quantification and Segmentation Tool

Shi

Wang

et al. 2021

Front. Neurosci.

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PurposeThis study aimed to determine if people living with HIV (PLWH) in preclinical human immunodeficiency virus (HIV)-associated neurocognitive disorder (HAND), with no clinical symptoms and without decreased daily functioning, suffer from brain volumetric alterations and its patterns.MethodFifty-nine male PLWH at the HAND preclinical stage were evaluated, including 19 subjects with asymptomatic neurocognitive impairment (ANI), 17 subjects with cognitive abnormality that does not reach ANI (Not reach ANI), and 23 subjects with cognitive integrity. Moreover, 23 healthy volunteers were set as the seronegative normal controls (NCs). These individuals underwent sagittal three-dimensional T1-weighted imaging (3D T1WI). Quantified data and volumetric measures of brain structures were automatically segmented and extracted using AccuBrain®. In addition, the multiple linear regression analysis was performed to analyze the relationship of volumes of brain structures and clinical variables in preclinical HAND, and the correlations of the brain volume parameters with different cognitive function states were assessed by Pearson’s correlation analysis.ResultsThe significant difference was shown in the relative volumes of the ventricular system, bilateral lateral ventricle, thalamus, caudate, and left parietal lobe gray matter between the preclinical HAND and NCs. Furthermore, the relative volumes of the bilateral thalamus in preclinical HAND were negatively correlated with attention/working memory (left: r = −0.271, p = 0.042; right: r = −0.273, p = 0.040). Higher age was associated with increased relative volumes of the bilateral lateral ventricle and ventricular system and reduced relative volumes of the left thalamus and parietal lobe gray matter. The lower CD4+/CD8+ ratio was associated with increased relative volumes of the left lateral ventricle and ventricular system. Longer disease course was associated with increased relative volumes of the bilateral thalamus. No significant difference was found among preclinical HAND subgroups in all indices, and the difference between the individual groups (Not reach ANI and Cognitive integrity groups) and NCs was also insignificant. However, there was a significant difference between ANI and NCs in the relative volumes of the bilateral caudate and lateral ventricle.ConclusionMale PLWH at the HAND preclinical stage suffer from brain volumetric alterations. AccuBrain® provides potential value in evaluating HIV-related neurocognitive dysfunction.

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“…Accu-Brain® performs brain structure segmentation based on a multi-atlas image registration scheme. The accuracy of hippocampus segmentation of AccuBrain® was validated using data from the ADNI database [36], and more technical description of AccuBrain® and its comparison with other automatic brain image segmentation schemes were described in our previous work [37][38][39]. Since the main objective of this study is to identify FTD from NC and AD, we focus on the brain regions known to be associated with cognition and behavior, including the brain parenchyma, typical subcortical structures (bilateral hippocampus, amygdala and caudate, etc.…”

Section: Fig 1 Subject Screening From the Nacc Databasementioning

confidence: 99%

An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer’s disease

Mai

Ruan

et al. 2021

Alz Res Therapy

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Background The differential diagnosis of frontotemporal dementia (FTD) and Alzheimer’s disease (AD) is difficult due to the overlaps of clinical symptoms. Structural magnetic resonance imaging (sMRI) presents distinct brain atrophy and potentially helps in their differentiation. In this study, we aim at deriving a novel integrated index by leveraging the volumetric measures in brain regions with significant difference between AD and FTD and developing an MRI-based strategy for the differentiation of FTD and AD. Methods In this study, the data were acquired from three different databases, including 47 subjects with FTD, 47 subjects with AD, and 47 normal controls in the NACC database; 50 subjects with AD in the ADNI database; and 50 subjects with FTD in the FTLDNI database. The MR images of all subjects were automatically segmented, and the brain atrophy, including the AD resemblance atrophy index (AD-RAI), was quantified using AccuBrain®. A novel MRI index, named the frontotemporal dementia index (FTDI), was derived as the ratio between the weighted sum of the volumetric indexes in “FTD dominant” structures over that obtained from “AD dominant” structures. The weights and the identification of “FTD/AD dominant” structures were acquired from the statistical analysis of NACC data. The differentiation performance of FTDI was validated using independent data from ADNI and FTLDNI databases. Results AD-RAI is a proven imaging biomarker to identify AD and FTD from NC with significantly higher values (p < 0.001 and AUC = 0.88) as we reported before, while no significant difference was found between AD and FTD (p = 0.647). FTDI showed excellent accuracy in identifying FTD from AD (AUC = 0.90; SEN = 89%, SPE = 75% with threshold value = 1.08). The validation using independent data from ADNI and FTLDNI datasets also confirmed the efficacy of FTDI (AUC = 0.93; SEN = 96%, SPE = 70% with threshold value = 1.08). Conclusions Brain atrophy in AD, FTD, and normal elderly shows distinct patterns. In addition to AD-RAI that is designed to detect abnormal brain atrophy in dementia, a novel index specific to FTD is proposed and validated. By combining AD-RAI and FTDI, an MRI-based decision strategy was further proposed as a promising solution for the differential diagnosis of AD and FTD in clinical practice.

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Association of impaired fasting glucose and Type 2 Diabetes Mellitus with brain volume changes in Alzheimer’s Disease patients analyzed by MRI: a retrospective study

Cited by 4 publications

References 52 publications

Diabetes‐related clinical and microstructural white matter changes in patients with Alzheimer's disease

Diabetes‐related clinical and microstructural white matter changes in patients with Alzheimer's disease

Brain Volumetric Alterations in Preclinical HIV-Associated Neurocognitive Disorder Using Automatic Brain Quantification and Segmentation Tool

An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer’s disease

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