Discerning mild cognitive impairment and Alzheimer Disease from normal aging: morphologic characterization based on univariate and multivariate models

No relationship between fornix and cingulum degradation and within-network decreases in functional connectivity in prodromal Alzheimer's disease

INTRODUCTION

The earliest changes in the brain due to Alzheimer's disease are associated with the neural networks related to memory function. We investigated changes in functional and structural connectivity among regions that support memory function in prodromal Alzheimer's disease, i.e., during the mild cognitive impairment (MCI) stage.

METHODS

Twenty-three older healthy controls and 25 adults with MCI underwent multimodal MRI scanning. Limbic white matter tracts-the fornix, parahippocampal cingulum, retrosplenial cingulum, subgenual cingulum and uncinate fasciculus-were reconstructed in ExploreDTI using constrained spherical deconvolution-based tractography. Using a network-of-interest approach, resting-state functional connectivity time-series correlations among sub-parcellations of the default mode and limbic networks, the hippocampus and the thalamus were calculated in Conn.

ANALYSIS

Controlling for age, education, and gender between group linear regressions of five diffusion-weighted measures and of resting state connectivity measures were performed per hemisphere. FDR-corrections were performed within each class of measures. Correlations of within-network Fisher Z-transformed correlation coefficients and the mean diffusivity per tract were performed. Whole-brain graph theory measures of cluster coefficient and average path length were inspecting using the resting state data.

RESULTS & CONCLUSION

MCI-related changes in white matter structure were found in the fornix, left parahippocampal cingulum, left retrosplenial cingulum and left subgenual cingulum. Functional connectivity decreases were observed in the MCI group within the DMN-a sub-network, between the hippocampus and sub-areas -a and -c of the DMN, between DMN-c and DMN-a, and, in the right hemisphere only between DMN-c and both the thalamus and limbic-a. No relationships between white matter tract 'integrity' (mean diffusivity) and within sub-network functional connectivity were found. Graph theory revealed that changes in the MCI group was mostly restricted to diminished between-neighbour connections of the hippocampi and of nodes within DMN-a and DMN-b.

Plasma lipid peroxidation biomarkers for early and non-invasive Alzheimer Disease detection

INTRODUCTION

Alzheimer Disease (AD) standard diagnosis is based on evaluations and biomarkers that are non-specific, expensive, or requires invasive sampling. Therefore, an early, and non-invasive diagnosis is required. As regards molecular mechanisms, recent research has shown that lipid peroxidation plays an important role.

METHODS

Well-defined participants groups were recruited. Lipid peroxidation compounds were determined in plasma using a validated analytical method. Statistical studies consisted of an elastic-net-penalized logistic regression adjustment.

RESULTS

The regression model fitted to the data included six variables (lipid peroxidation biomarkers) as potential predictors of early AD. This model achieved an apparent area under the receiver operating characteristics (AUC-ROCs) of 0.883 and a bootstrap-validated AUC-ROC of 0.817. Calibration of the model showed very low deviations from real probabilities.

CONCLUSION

A satisfactory early diagnostic model has been obtained from plasma levels of 6 lipid peroxidation compounds, indicating the individual probability of suffering from early AD.

The associated volumes of sub-cortical structures and cognitive domain in patients of Mild Cognitive Impairment

This study aimed to explore the relationship between sub-cortical structures alterations and the cognitive domains in Mild Cognitive Impairment (MCI) patients, expected to find identifying sub-cortical structure markers of MCI progression to dementia. A total of 67 MCI patients (8 subjects refused to follow up) were recruited, who were divided into 21 stable MCI (sMCI) and 38 progress MCI (pMCI), according to cognitive assays. FreeSurfer software was used to perform volumetric measurements of the sub-cortical structures from 3.0 T magnetic resonance scans. Data revealed that pMCI subjects had lower scores in memory, language, executive and visual spatial compared with sMCI subjects. Compared with the sMCI group, the volume of the left thalamus, bilateral hippocampus, corpus callosum posterior and corpus callosum central was smaller in pMCI subjects. Partial correlation and general linear regression analysis showed that the left hippocampus was predicted region for memory, left thalamus was predicted region for language, executive and visual spatial. These current results suggest that the volumes of sub-cortical structures in stable MCI and progress MCI patients were heterogeneous. Among these regions, the left hippocampus was predicted region for memory, left thalamus was predicted region for language, executive and visual spatial, suggesting that these structures might be important for detecting the subtle effects of MCI patients' cognitive domain or to assess the effectiveness of therapeutic intervention for MCI.

Morphological Biomarker Differentiating MCI Converters from Nonconverters: Longitudinal Evidence Based on Hemispheric Asymmetry

Identifying subjects with mild cognitive impairment (MCI) who may probably progress to Alzheimer's disease (AD) is important for better understanding the disease mechanisms and facilitating early treatments. In addition to the direct volumetric and thickness measurement based on high-resolution magnetic resonance imaging (MRI), hemispheric asymmetry could be a potential index to detect morphological variations in MCI patients with a high risk of conversion to AD. The present study collected a set of longitudinal MRI data from 53 MCI converters and nonconverters and investigated the asymmetry differences between groups. Asymmetry variation was observed in the medial temporal lobe, especially in the entorhinal cortex, between converters and nonconverters 3 years before the former developed AD. The proposed asymmetry analysis was observed to be sensitive to detect morphological changes between groups as compared to the methods of voxel-based morphometry (VBM) and thickness measurement. Hemispheric asymmetry in specific brain regions as a neuroimaging biomarker can provide helpful information for prediction of MCI conversion.

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer's disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, 'shape connections' between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus.

Subcortical Shape Changes, Hippocampal Atrophy and Cortical Thinning in Future Alzheimer's Disease Patients

Efficacy of future treatments depends on biomarkers identifying patients with mild cognitive impairment at highest risk for transitioning to Alzheimer's disease. Here, we applied recently developed analysis techniques to investigate cross-sectional differences in subcortical shape and volume alterations in patients with stable mild cognitive impairment (MCI) (n = 23, age range 59–82, 47.8% female), future converters at baseline (n = 10, age range 66–84, 90% female) and at time of conversion (age range 68–87) compared to group-wise age and gender matched healthy control subjects (n = 23, age range 61–81, 47.8% female; n = 10, age range 66–82, 80% female; n = 10, age range 68–82, 70% female). Additionally, we studied cortical thinning and global and local measures of hippocampal atrophy as known key imaging markers for Alzheimer's disease. Apart from bilateral striatal volume reductions, no morphometric alterations were found in cognitively stable patients. In contrast, we identified shape alterations in striatal and thalamic regions in future converters at baseline and at time of conversion. These shape alterations were paralleled by Alzheimer's disease like patterns of left hemispheric morphometric changes (cortical thinning in medial temporal regions, hippocampal total and subfield atrophy) in future converters at baseline with progression to similar right hemispheric alterations at time of conversion. Additionally, receiver operating characteristic curve analysis indicated that subcortical shape alterations may outperform hippocampal volume in identifying future converters at baseline. These results further confirm the key role of early cortical thinning and hippocampal atrophy in the early detection of Alzheimer's disease. But first and foremost, and by distinguishing future converters but not patients with stable cognitive abilities from cognitively normal subjects, our results support the value of early subcortical shape alterations and reduced hippocampal subfield volumes as potential markers for the early detection of Alzheimer's disease.

Abnormal Changes of Brain Cortical Anatomy and the Association with Plasma MicroRNA107 Level in Amnestic Mild Cognitive Impairment

MicroRNA107 (Mir107) has been thought to relate to the brain structure phenotype of Alzheimer's disease. In this study, we evaluated the cortical anatomy in amnestic mild cognitive impairment (aMCI) and the relation between cortical anatomy and plasma levels of Mir107 and beta-site amyloid precursor protein (APP) cleaving enzyme 1 (BACE1). Twenty aMCI (20 aMCI) and 24 cognitively normal control (NC) subjects were recruited, and T1-weighted MR images were acquired. Cortical anatomical measurements, including cortical thickness (CT), surface area (SA), and local gyrification index (LGI), were assessed. Quantitative RT-PCR was used to examine plasma expression of Mir107, BACE1 mRNA. Thinner cortex was found in aMCI in areas associated with episodic memory and language, but with thicker cortex in other areas. SA decreased in aMCI in the areas associated with working memory and emotion. LGI showed a significant reduction in aMCI in the areas involved in language function. Changes in Mir107 and BACE1 messenger RNA plasma expression were correlated with changes in CT and SA. We found alterations in key left brain regions associated with memory, language, and emotion in aMCI that were significantly correlated with plasma expression of Mir107 and BACE1 mRNA. This combination study of brain anatomical alterations and gene information may shed lights on our understanding of the pathology of AD.

CLINICAL TRIAL REGISTRATION

http://www.ClinicalTrials.gov, identifier NCT01819545.