Dataset Information

Association Between Hippocampus, Thalamus, and Caudate in Mild Cognitive Impairment APOE?4 Carriers: A Structural Covariance MRI Study.

ABSTRACT: Objective: Although, the apolipoprotein E (APOE) genotype is widely recognized as one of the most important risk factors for Alzheimer's disease (AD) development, the neural mechanisms by which the ?4 allele promotes the AD occurring remain under debate. The aim of this study was to evaluate neurobiological effects of the APOE-genotype on the pattern of the structural covariance in mild cognitive impairment (MCI) subjects. Methods: We enrolled 95 MCI subjects and 49 healthy controls. According to APOE-genotype, MCI subjects were divided into three groups: APOE?4 non-carriers (MCI?4-/-, n = 55), APOE?4 heterozygous carriers (MCI?4+/-, n = 31), and APOE?4 homozygous carriers (MCI?4+/+, n = 9) while all controls were APOE?4 non-carriers. In order to explore their brain structural pattern, T1-weighted anatomical brain 1.5-T MRI scans were collected. A whole-brain voxel-based morphometry analysis was performed, and all significant regions (p < 0.05 family-wise error, whole brain) were selected as a region of interest for the structural covariance analysis. Moreover, in order to evaluate the progression of the disease, a clinical follow-up was performed for 2 years. Results: The F-test showed in voxel-based morphometry analysis a strong overall difference among the groups in the middle frontal and temporal gyri and in the bilateral hippocampi, thalami, and parahippocampal gyri, with a grading in the atrophy in these latter three structures according to the following order: MCI?4+/+ > MCI?4+/- > MCI?4-/- > controls. Structural covariance analysis revealed a strong structural association between the left thalamus and the left caudate and between the right hippocampus and the left caudate (p < 0.05 family-wise error, whole brain) in the MCI?4 carrier groups (MCI?4+/+ > MCI?4+/-), whereas no significant associations were observed in MCI?4-/- subjects. Of note, the 38% of MCIs enrolled in this study developed AD within 2 years of follow-up. Conclusion: This study improves the knowledge on neurobiological effect of APOE ?4 in early pathophysiological phenomena underlying the MCI-to-AD evolution, as our results demonstrate changes in the structural association between hippocampal formation and thalamo-striatal connections occurring in MCI ?4 carriers. Our results strongly support the role of subcortical structures in MCI ?4 carriers and open a clinical window on the role of these structures as early disease markers.

SUBMITTER: Novellino F

PROVIDER: S-EPMC6933953 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Association Between Hippocampus, Thalamus, and Caudate in Mild Cognitive Impairment APOEε4 Carriers: A Structural Covariance MRI Study.

Novellino Fabiana F López María Eugenia ME Vaccaro Maria Grazia MG Miguel Yus Y Delgado María Luisa ML Maestu Fernando F

Frontiers in neurology 20191220

<b>Objective:</b> Although, the apolipoprotein E (APOE) genotype is widely recognized as one of the most important risk factors for Alzheimer's disease (AD) development, the neural mechanisms by which the ε4 allele promotes the AD occurring remain under debate. The aim of this study was to evaluate neurobiological effects of the APOE-genotype on the pattern of the structural covariance in mild cognitive impairment (MCI) subjects. <b>Methods:</b> We enrolled 95 MCI subjects and 49 healthy control ...[more]

PMID: 31920926

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Project description:Detection and diagnosis of early and subclinical stages of Alzheimer's Disease (AD) play an essential role in the implementation of intervention and prevention strategies. Neuroimaging techniques predominantly provide insight into anatomic structure changes associated with AD. Deep learning methods have been extensively applied towards creating and evaluating models capable of differentiating between cognitively unimpaired, patients with Mild Cognitive Impairment (MCI) and AD dementia. Several published approaches apply information fusion techniques, providing ways of combining several input sources in the medical domain, which contributes to knowledge of broader and enriched quality. The aim of this paper is to fuse sociodemographic data such as age, marital status, education and gender, and genetic data (presence of an apolipoprotein E (APOE)-?4 allele) with Magnetic Resonance Imaging (MRI) scans. This enables enriched multi-modal features, that adequately represent the MRI scan visually and is adopted for creating and modeling classification systems capable of detecting amnestic MCI (aMCI). To fully utilize the potential of deep convolutional neural networks, two extra color layers denoting contrast intensified and blurred image adaptations are virtually augmented to each MRI scan, completing the Red-Green-Blue (RGB) color channels. Deep convolutional activation features (DeCAF) are extracted from the average pooling layer of the deep learning system Inception_v3. These features from the fused MRI scans are used as visual representation for the Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN) classification model. The proposed approach is evaluated on a sub-study containing 120 participants (aMCI = 61 and cognitively unimpaired = 59) of the Heinz Nixdorf Recall (HNR) Study with a baseline model accuracy of 76%. Further evaluation was conducted on the ADNI Phase 1 dataset with 624 participants (aMCI = 397 and cognitively unimpaired = 227) with a baseline model accuracy of 66.27%. Experimental results show that the proposed approach achieves 90% accuracy and 0.90 F1-Score at classification of aMCI vs. cognitively unimpaired participants on the HNR Study dataset, and 77% accuracy and 0.83 F1-Score on the ADNI dataset.

Dataset Information

Association Between Hippocampus, Thalamus, and Caudate in Mild Cognitive Impairment APOE?4 Carriers: A Structural Covariance MRI Study.

Publications

Association Between Hippocampus, Thalamus, and Caudate in Mild Cognitive Impairment APOEε4 Carriers: A Structural Covariance MRI Study.

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