Thickness in entorhinal and subicular cortex predicts episodic memory decline in mild cognitive impairment

A multivariate model of time to conversion from mild cognitive impairment to Alzheimer's disease

The present study was aimed at determining which combination of demographic, genetic, cognitive, neurophysiological, and neuroanatomical factors may predict differences in time to progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). To this end, a sample of 121 MCIs was followed up during a 5-year period. According to their clinical outcome, MCIs were divided into two subgroups: (i) the "progressive" MCI group (n = 46; mean time to progression 17 ± 9.73 months) and (ii) the "stable" MCI group (n = 75; mean time of follow-up 31.37 ± 14.58 months). Kaplan-Meier survival analyses were applied to explore each variable's relationship with the progression to AD. Once potential predictors were detected, Cox regression analyses were utilized to calculate a parsimonious model to estimate differences in time to progression. The final model included three variables (in order of relevance): left parahippocampal volume (corrected by intracranial volume, LP_ ICV), delayed recall (DR), and left inferior occipital lobe individual alpha peak frequency (LIOL_IAPF). Those MCIs with LP_ICV volume, DR score, and LIOL_IAPF value lower than the defined cutoff had 6 times, 5.5 times, and 3 times higher risk of progression to AD, respectively. Besides, when the categories of the three variables were "unfavorable" (i.e., values below the cutoff), 100% of cases progressed to AD at the end of follow-up. Our results highlighted the relevance of neurophysiological markers as predictors of conversion (LIOL_IAPF) and the importance of multivariate models that combine markers of different nature to predict time to progression from MCI to dementia.

Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology

Cognitive decline is a severe concern of patients with mild cognitive impairment. Also, in patients with temporal lobe epilepsy, memory problems are a frequently encountered problem with potential progression. On the background of a unifying hypothesis for cognitive decline, we merged knowledge from dementia and epilepsy research in order to identify biomarkers with a high predictive value for cognitive decline across and beyond these groups that can be fed into intelligent systems. We prospectively assessed patients with temporal lobe epilepsy (N = 9), mild cognitive impairment (N = 19), and subjective cognitive complaints (N = 4) and healthy controls (N = 18). All had structural cerebral MRI, EEG at rest and during declarative verbal memory performance, and a neuropsychological assessment which was repeated after 18 months. Cognitive decline was defined as significant change on neuropsychological subscales. We extracted volumetric and shape features from MRI and brain network measures from EEG and fed these features alongside a baseline testing in neuropsychology into a machine learning framework with feature subset selection and 5-fold cross validation. Out of 50 patients, 27 had a decline over time in executive functions, 23 in visual-verbal memory, 23 in divided attention, and 7 patients had an increase in depression scores. The best sensitivity/specificity for decline was 72%/82% for executive functions based on a feature combination from MRI volumetry and EEG partial coherence during recall of memories; 95%/74% for visual-verbal memory by combination of MRI-wavelet features and neuropsychology; 84%/76% for divided attention by combination of MRI-wavelet features and neuropsychology; and 81%/90% for increase of depression by combination of EEG partial directed coherence factor at rest and neuropsychology. Combining information from EEG, MRI, and neuropsychology in order to predict neuropsychological changes in a heterogeneous population could create a more general model of cognitive performance decline.

Early Detection of Alzheimer's Disease Using Magnetic Resonance Imaging: A Novel Approach Combining Convolutional Neural Networks and Ensemble Learning

Early detection is critical for effective management of Alzheimer's disease (AD) and screening for mild cognitive impairment (MCI) is common practice. Among several deep-learning techniques that have been applied to assessing structural brain changes on magnetic resonance imaging (MRI), convolutional neural network (CNN) has gained popularity due to its superb efficiency in automated feature learning with the use of a variety of multilayer perceptrons. Meanwhile, ensemble learning (EL) has shown to be beneficial in the robustness of learning-system performance via integrating multiple models. Here, we proposed a classifier ensemble developed by combining CNN and EL, i.e., the CNN-EL approach, to identify subjects with MCI or AD using MRI: i.e., classification between (1) AD and healthy cognition (HC), (2) MCIc (MCI patients who will convert to AD) and HC, and (3) MCIc and MCInc (MCI patients who will not convert to AD). For each binary classification task, a large number of CNN models were trained applying a set of sagittal, coronal, or transverse MRI slices; these CNN models were then integrated into a single ensemble. Performance of the ensemble was evaluated using stratified fivefold cross-validation method for 10 times. The number of the intersection points determined by the most discriminable slices separating two classes in a binary classification task among the sagittal, coronal, and transverse slice sets, transformed into the standard Montreal Neurological Institute (MNI) space, acted as an indicator to assess the ability of a brain region in which the points were located to classify AD. Thus, the brain regions with most intersection points were considered as those mostly contributing to the early diagnosis of AD. The result revealed an accuracy rate of 0.84 ± 0.05, 0.79 ± 0.04, and 0.62 ± 0.06, respectively, for classifying AD vs. HC, MCIc vs. HC, and MCIc vs. MCInc, comparable to previous reports and a 3D deep learning approach (3D-SENet) based on a more state-of-the-art and popular Squeeze-and-Excitation Networks model using channel attention mechanism. Notably, the intersection points accurately located the medial temporal lobe and several other structures of the limbic system, i.e., brain regions known to be struck early in AD. More interestingly, the classifiers disclosed multiple patterned MRI changes in the brain in AD and MCIc, involving these key regions. These results suggest that as a data-driven method, the combined CNN and EL approach can locate the most discriminable brain regions indicated by the trained ensemble model while the generalization ability of the ensemble model was maximized to successfully capture AD-related brain variations early in the disease process; it can also provide new insights into understanding the complex heterogeneity of whole-brain MRI changes in AD. Further research is needed to examine the clinical implication of the finding, capability of the advocated CNN-EL approach to help understand and evaluate an individual subject's disease status, symptom burden and progress, and the generalizability of the advocated CNN-EL approach to locate the most discriminable brain regions in the detection of other brain disorders such as schizophrenia, autism, and severe depression, in a data-driven way.

Subregional Hippocampal Thickness Abnormalities in Older Adults with a History of Heavy Cannabis Use

Background and Aims: Legalization of cannabis (CB) for both medicinal and, in some states, recreational use, has given rise to increasing usage rates across the country. Of particular concern are indications that frequent CB use may be selectively harmful to the developing adolescent brain compared with adult-onset usage. However, the long-term effects of heavy, adolescent CB use on brain structure and cognitive performance in late-life remain unknown. A critical brain region is the hippocampus (HC), where there is a striking intersection between high concentrations of cannabinoid 1 (CB1) receptors and age-related pathology.

Design: We investigated whether older adults (average age=66.6+7.2 years old) with a history of early life CB use show morphological differences in hippocampal subregions compared with older, nonusers.

Methods: We performed high-resolution magnetic resonance imaging combined with computational techniques to assess cortical thickness of the medial temporal lobe, neuropsychological testing, and extensive drug use histories on 50 subjects (24 formerly heavy cannabis users [CB+ group] abstinent for an average of 28.7 years, 26 nonusers [CB− group]). We investigated group differences in hippocampal subregions, controlling for age, sex, and intelligence (as measured by the Wechsler Test of Adult Reading), years of education, and cigarette use.

Results: The CB+ subjects exhibited thinner cortices in subfields cornu ammonis 1 [CA1; F(1,42)=9.96, p=0.0003], and CA2, 3, and the dentate gyrus [CA23DG; F(1,42)=23.17, p<0.0001], and in the entire HC averaged over all subregions [F(1,42)=8.49, p=0.006].

Conclusions: Negative effects of chronic adolescent CB use on hippocampal structure are maintained well into late life. Because hippocampal cortical loss underlies and exacerbates age-related cognitive decline, these findings have profound implications for aging adults with a history of early life usage.

Clinical Trial Registration: ClinicalTrials.gov # NCT01874886.

Cerebral changes and cognitive impairment after an ischemic heart disease: a multimodal MRI study

Three to 6 months after an acute coronary syndrome (ACS), cognitive impairment is observed in more than 30 % of the patients, mainly in executive functioning. The aim of this study was to investigate, using multimodal MRI, cerebral anatomo-functional substratum of executive dysfunction. Thirty-three patients were recruited 4 ± 1 months after a first ACS. Executive functions were evaluated with the Trail-Making-Test-B (TMTB) at baseline (ie 4 ± 1 months after ACS) and 6 months later (ie 10 ± 1 months after ACS). Using both time-points, we identified 3 groups of patients according to normative data based on age, gender and education level: 15 'cognitively normal' patients without impairment at each follow-up, 10 'transient impaired' patients with an impairment only at baseline and 8 'impairing' patients with an impairment only at follow-up. We explored, in the whole-brain, the structural integrity using Voxel-Based Morphometry and Tract-Based Spatial Statistics and the resting-state functional connectivity using Network-Based Statistics. No structural difference was observed between impaired and cognitively normal patients. At the functional level, compared to the 'cognitively normal' group, the 'transient impaired' patients presented an increased functional connectivity in a network centered on middle-orbito-frontal regions, whereas the 'impairing' patients presented only a non-significant decrease of functional connectivity. Executive dysfunction in ACS patients is associated to functional but no structural characteristics, particularly to an increased functional connectivity in cognitive networks in transient impaired patients. Further studies with larger sample size are needed to confirm these results and to determine if these patients could be at higher risk for developing permanent cognitive disorders.

Hippocampal thinning linked to longer TOMM40 poly-T variant lengths in the absence of the APOE ε4 variant

INTRODUCTION

The translocase of outer mitochondrial membrane 40 (TOMM40), which lies in linkage disequilibrium with apolipoprotein E (APOE), has received attention more recently as a promising gene in Alzheimer's disease (AD) risk. TOMM40 influences AD pathology through mitochondrial neurotoxicity, and the medial temporal lobe (MTL) is the most likely brain region for identifying early manifestations of AD-related morphology changes.

METHODS

In this study, we examined the effects of TOMM40 using high-resolution magnetic resonance imaging in 65 healthy, older subjects with and without the APOE ε4 AD-risk variant.

RESULTS

Examining individual subregions within the MTL, we found a significant relationship between increasing poly-T lengths of the TOMM40 variant and thickness of the entorhinal cortex only in subjects who did not carry the APOE ε4 allele.

DISCUSSION

Our data provide support for TOMM40 variant repeat length as an important contributor to AD-like MTL pathology in the absence of APOE ε4.

Family History of Alzheimer's Disease and Cortical Thickness in Patients With Dementia

A first-degree family history of Alzheimer's disease reflects genetic risks for the neurodegenerative disorder. Recent imaging data suggest localized effects of genetic risks on brain structure in healthy people. It is unknown whether this association can also be found in patients who already have dementia. Our aim was to investigate whether family history risk modulates regional medial temporal lobe cortical thickness in patients with Alzheimer's disease. We performed high-resolution magnetic resonance imaging and cortical unfolding data analysis on 54 patients and 53 nondemented individuals. A first-degree family history of Alzheimer's disease was associated with left hemispheric cortical thinning in the subiculum among patients and controls. The contribution of Alzheimer's disease family history to regional brain anatomy changes independent of cognitive impairment may reflect genetic risks that modulate onset and clinical course of the disease.

An Alzheimer's Disease Genetic Risk Score Predicts Longitudinal Thinning of Hippocampal Complex Subregions in Healthy Older Adults

Variants at 21 genetic loci have been associated with an increased risk for Alzheimer's disease (AD). An important unresolved question is whether multiple genetic risk factors can be combined to increase the power to detect changes in neuroimaging biomarkers for AD. We acquired high-resolution structural images of the hippocampus in 66 healthy, older human subjects. For 45 of these subjects, longitudinal 2-year follow-up data were also available. We calculated an additive AD genetic risk score for each participant and contrasted this with a weighted risk score (WRS) approach. Each score included APOE (apolipoprotein E), CLU (clusterin), PICALM (phosphatidylinositol binding clathrin assembly protein), and family history of AD. Both unweighted risk score (URS) and WRS correlated strongly with the percentage change in thickness across the whole hippocampal complex (URS: r = -0.40; p = 0.003; WRS: r = -0.25, p = 0.048), driven by a strong relationship to entorhinal cortex thinning (URS: r = -0.35; p = 0.009; WRS: r = -0.35, p = 0.009). By contrast, at baseline the risk scores showed no relationship to thickness in any hippocampal complex subregion. These results provide compelling evidence that polygenic AD risk scores may be especially sensitive to structural change over time in regions affected early in AD, like the hippocampus and adjacent entorhinal cortex. This work also supports the paradigm of studying genetic risk for disease in healthy volunteers. Together, these findings will inform clinical trial design by supporting the idea that genetic prescreening in healthy control subjects can be useful to maximize the ability to detect an effect on a longitudinal neuroimaging endpoint, like hippocampal complex cortical thickness.

Topological Properties of Large-Scale Cortical Networks Based on Multiple Morphological Features in Amnestic Mild Cognitive Impairment

Previous studies have demonstrated that amnestic mild cognitive impairment (aMCI) has disrupted properties of large-scale cortical networks based on cortical thickness and gray matter volume. However, it is largely unknown whether the topological properties of cortical networks based on geometric measures (i.e., sulcal depth, curvature, and metric distortion) change in aMCI patients compared with normal controls because these geometric features of cerebral cortex may be related to its intrinsic connectivity. Here, we compare properties in cortical networks constructed by six different morphological features in 36 aMCI participants and 36 normal controls. Six cortical features (3 volumetric and 3 geometric features) were extracted for each participant, and brain abnormities in aMCI were identified by cortical network based on graph theory method. All the cortical networks showed small-world properties. Regions showing significant differences mainly located in the medial temporal lobe and supramarginal and right inferior parietal lobe. In addition, we also found that the cortical networks constructed by cortical thickness and sulcal depth showed significant differences between the two groups. Our results indicated that geometric measure (i.e., sulcal depth) can be used to construct network to discriminate individuals with aMCI from controls besides volumetric measures.

Hippocampal Subfield Atrophy in Multi-Domain but Not Amnestic Mild Cognitive Impairment

BACKGROUND/AIMS

To investigate differences in hippocampal (HP) subfields and the adjoining perirhinal and entorhinal cortices (PRC and ERC) between amnestic mild cognitive impairment (aMCI) and multi-domain amnestic MCI (mdMCI) patients, and controls.

METHODS

Nineteen patients characterized as aMCI were compared with 24 mdMCI patients and 31 controls by means of an automatic HP segmentation procedure.

RESULTS

We found significant atrophy of the PRC and ERC in aMCI relative to controls, whereas a more pronounced pattern of atrophy in most subfields, including total HP volume, was found in the mdMCI group. The mdMCI group also had a significant cornu ammonis sector 4 region with dentate gyrus, subiculum and total HP atrophy relative to aMCI.

CONCLUSION

The aMCI group showed atrophy in the PRC and ERC, whereas significantly more affection of the HP subfields was evident in mdMCI. The mdMCI group may thus represent clinical progression relative to aMCI coupled with HP subfield affection.

Altered memory-related functional connectivity of the anterior and posterior hippocampus in older adults at increased genetic risk for Alzheimer's disease

The hippocampal complex is affected early in Alzheimer's disease (AD). Increasingly, altered functional connectivity of the hippocampus is recognized as an important feature of preclinical AD. Carriers of the APOEɛ4 allele are at an increased risk for AD, which could lead to altered hippocampal connectivity even in healthy older adults. To test this hypothesis, we used a paired-associates memory task to examine differences in task-dependent functional connectivity of the anterior and posterior hippocampus in nondemented APOEɛ4 carriers (n = 34, 18F) and noncarriers (n = 46, 31F). We examined anterior and posterior portions of the hippocampus separately to test the theory that APOEɛ4-mediated differences would be more pronounced in the anterior region, which is affected earlier in the AD course. This study is the first to use a psychophysiological interaction approach to query the context-dependent connectivity of subregions of the hippocampus during a memory task in adults at increased genetic risk for AD. During encoding, APOEɛ4 carriers had lower functional connectivity change compared to baseline between the anterior hippocampus and right precuneus, anterior insula and cingulate cortex. During retrieval, bilateral supramarginal gyrus and right precuneus showed lower functional connectivity change with anterior hippocampus in carriers. Also during retrieval, carriers showed lower connectivity change in the posterior hippocampus with auditory cortex. In each case, APOEɛ4 carriers showed strong negative connectivity changes compared to noncarriers where positive connectivity change was measured. These differences may represent prodromal functional changes mediated in part by APOEɛ4 and are consistent with the anterior-to-posterior theory of AD progression in the hippocampus.

Structural brain aging and speech production: a surface-based brain morphometry study

While there has been a growing number of studies examining the neurofunctional correlates of speech production over the past decade, the neurostructural correlates of this immensely important human behaviour remain less well understood, despite the fact that previous studies have established links between brain structure and behaviour, including speech and language. In the present study, we thus examined, for the first time, the relationship between surface-based cortical thickness (CT) and three different behavioural indexes of sublexical speech production: response duration, reaction times and articulatory accuracy, in healthy young and older adults during the production of simple and complex meaningless sequences of syllables (e.g., /pa-pa-pa/ vs. /pa-ta-ka/). The results show that each behavioural speech measure was sensitive to the complexity of the sequences, as indicated by slower reaction times, longer response durations and decreased articulatory accuracy in both groups for the complex sequences. Older adults produced longer speech responses, particularly during the production of complex sequence. Unique age-independent and age-dependent relationships between brain structure and each of these behavioural measures were found in several cortical and subcortical regions known for their involvement in speech production, including the bilateral anterior insula, the left primary motor area, the rostral supramarginal gyrus, the right inferior frontal sulcus, the bilateral putamen and caudate, and in some region less typically associated with speech production, such as the posterior cingulate cortex.

Imaging markers of structural and functional brain changes that precede cognitive symptoms in risk for Alzheimer's disease

Neuroimaging has rapidly advanced investigations into dysfunction both within and emanating from the hippocampus in early Alzheimer's disease . Focusing on prodromal subjects, we will discuss structural changes to hippocampal subregions, alterations to functional activity both within the hippocampus and elsewhere in the cortex, as well as changes to structural white matter connectivity and changes to functionally correlated patterns during memory performance. We present ample evidence that asymptomatic subjects demonstrate substantial identifiable brain changes before the onset of cognitive decline, but suggest there is significant work yet to be accomplished before applying these findings to individual patients.

Pomegranate juice augments memory and FMRI activity in middle-aged and older adults with mild memory complaints

Despite increasing emphasis on the potential of dietary antioxidants in preventing memory loss and on diet as a precursor of neurological health, rigorous studies investigating the cognitive effects of foods and their components are rare. Recent animal studies have reported memory and other cognitive benefits of polyphenols, found abundantly in pomegranate juice. We performed a preliminary, placebo-controlled randomized trial of pomegranate juice in older subjects with age-associated memory complaints using memory testing and functional brain activation (fMRI) as outcome measures. Thirty-two subjects (28 completers) were randomly assigned to drink 8 ounces of either pomegranate juice or a flavor-matched placebo drink for 4 weeks. Subjects received memory testing, fMRI scans during cognitive tasks, and blood draws for peripheral biomarkers before and after the intervention. Investigators and subjects were all blind to group membership. After 4 weeks, only the pomegranate group showed a significant improvement in the Buschke selective reminding test of verbal memory and a significant increase in plasma trolox-equivalent antioxidant capacity (TEAC) and urolithin A-glucuronide. Furthermore, compared to the placebo group, the pomegranate group had increased fMRI activity during verbal and visual memory tasks. While preliminary, these results suggest a role for pomegranate juice in augmenting memory function through task-related increases in functional brain activity.

Small-World Properties in Mild Cognitive Impairment and Early Alzheimer's Disease: A Cortical Thickness MRI Study

BACKGROUND

Small-world network consists of networks with local specialization and global integration. Our objective is to detect small-world properties alteration based on cortical thickness in mild cognitive impairment (MCI) including stables and converters, and early Alzheimer's disease (AD) compared to controls.

METHODS

MRI scans of 13 controls, 10 MCI, and 10 with early AD were retrospectively analyzed; 11 MCI converters, 11 MCI stables, and 10 controls from the ADNI website were also included.

RESULTS

There were significantly decreased local efficiencies in patients with MCI and AD compared to controls; and MCI patients showed increased global efficiency compared to AD and controls. The MCI converters experience the worst local efficiency during the converting period to AD; the stables, however, have highest local and global efficiency.

CONCLUSIONS

The abnormal cortical thickness-based small-world properties in MCI and AD as well as the distinct patterns between two MCI subtypes suggest that small-world network analysis has the potential to better differentiate different stages of early dementia.

Cortical signatures of cognition and their relationship to Alzheimer's disease

Recent changes in diagnostic criteria for Alzheimer's disease (AD) state that biomarkers can enhance certainty in a diagnosis of AD. In the present study, we combined cognitive function and brain morphology, a potential imaging biomarker, to predict conversion from mild cognitive impairment to AD. We identified four biomarkers, or cortical signatures of cognition (CSC), from regressions of cortical thickness on neuropsychological factors representing memory, executive function/processing speed, language, and visuospatial function among participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Neuropsychological factor scores were created from a previously validated multidimensional factor structure of the neuropsychological battery in ADNI. Mean thickness of each CSC at the baseline study visit was used to evaluate risk of conversion to clinical AD among participants with mild cognitive impairment (MCI) and rate of decline on the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) score. Of 307 MCI participants, 119 converted to AD. For all domain-specific CSC, a one standard deviation thinner cortical thickness was associated with an approximately 50% higher hazard of conversion and an increase of approximately 0.30 points annually on the CDR-SB. In combined models with a domain-specific CSC and neuropsychological factor score, both CSC and factor scores predicted conversion to AD and increasing clinical severity. The present study indicated that factor scores and CSCs for memory and language both significantly predicted risk of conversion to AD and accelerated deterioration in dementia severity. We conclude that predictive models are best when they utilize both neuropsychological measures and imaging biomarkers.

Hippocampal CA1 apical neuropil atrophy and memory performance in Alzheimer's disease

Memory loss is often the first and most prominent symptom of Alzheimer's disease (AD), coinciding with the spread of neurofibrillary pathology from the entorhinal cortex (ERC) to the hippocampus. The apical dendrites of hippocampal CA1 pyramidal neurons, in the stratum radiatum/stratum lacunosum-moleculare (SRLM), are among the earliest targets of this pathology, and atrophy of the CA1-SRLM is apparent in postmortem tissue from patients with mild AD. We previously demonstrated that CA1-SRLM thinning is also apparent in vivo, using ultra-high field 7-Tesla (7T) MRI to obtain high-resolution hippocampal microstructural imaging. Here, we hypothesized that CA1-SRLM thickness would correlate with episodic memory performance among patients with mild AD. We scanned nine patients, using an oblique coronal T2-weighted sequence through the hippocampal body with an in-plane resolution of 220 μm, allowing direct visual identification of subfields - dentate gyrus (DG)/CA3, CA2, CA1, and ERC - and hippocampal strata - SRLM and stratum pyramidale (SP). We present a novel semi-automated method of measuring stratal width that correlated well with manual measurements. We performed multi-domain neuropsychological evaluations that included three tests of episodic memory, yielding composite scores for immediate recall, delayed recall, and delayed recognition memory. Strong correlations occurred between delayed recall performance and the widths of CA1-SRLM (r(2)=0.69; p=0.005), CA1-SP (r(2)=0.5; p=0.034), and ERC (r(2)=0.62; p=0.012). The correlation between CA1-SRLM width and delayed recall lateralized to the left hemisphere. DG/CA3 size did not correlate significantly with any aspect of memory performance. These findings highlight a role for 7T hippocampal microstructural imaging in revealing focal structural pathology that correlates with the central cognitive feature of AD.