Is the Alzheimer's disease cortical thickness signature a biological marker for memory?

A novel neuroimaging signature for ADRD risk stratification in the community

INTRODUCTION

Early risk stratification for clinical dementia could lead to preventive therapies. We identified and validated a magnetic resonance imaging (MRI) signature for Alzheimer's disease (AD) and related dementias (ARDR).

METHODS

An MRI ADRD signature was derived from cortical thickness maps in Framingham Heart Study (FHS) participants with AD dementia and matched controls. The signature was related to the risk of ADRD and cognitive function in FHS. Results were replicated in the University of California Davis Alzheimer's Disease Research Center (UCD-ADRC) cohort.

RESULTS

Participants in the bottom quartile of the signature had more than three times increased risk for ADRD compared to those in the upper three quartiles (P < 0.001). Greater thickness in the signature was related to better general cognition (P < 0.01) and episodic memory (P = 0.01). Results replicated in UCD-ADRC.

DISCUSSION

We identified a robust neuroimaging biomarker for persons at increased risk of ADRD. Other cohorts will further test the validity of this biomarker.

More Similar than Different: Memory, Executive Functions, Cortical Thickness, and Glucose Metabolism in Biomarker-Positive Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia

Background

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are typically associated with very different clinical and neuroanatomical presentations; however, there is increasing recognition of similarities.

Objective

To examine memory and executive functions, as well as cortical thickness, and glucose metabolism in AD and bvFTD signature brain regions.

Methods

We compared differences in a group of biomarker-defined participants with Alzheimer's disease and a group of clinically diagnosed participants with bvFTD. These groups were also contrasted with healthy controls (HC).

Results

As expected, memory functions were generally more impaired in AD, followed by bvFTD, and both clinical groups performed more poorly than the HC group. Executive function measures were similar in AD compared to bvFTD for motor sequencing and go/no-go, but bvFTD had more difficulty with a set shifting task. Participants with AD showed thinner cortex and lower glucose metabolism in the angular gyrus compared to bvFTD. Participants with bvFTD had thinner cortex in the insula and temporal pole relative to AD and healthy controls, but otherwise the two clinical groups were similar for other frontal and temporal signature regions.

Conclusions

Overall, the results of this study highlight more similarities than differences between AD and bvFTD in terms of cognitive functions, cortical thickness, and glucose metabolism. Further research is needed to better understand the mechanisms mediating this overlap and how these relationships evolve longitudinally.

MicroRNA expression in extracellular vesicles as a novel blood-based biomarker for Alzheimer's disease

INTRODUCTION

Brain cell-derived small extracellular vesicles (sEVs) in blood offer unique cellular and molecular information related to the onset and progression of Alzheimer's disease (AD). We simultaneously enriched six specific sEV subtypes from the plasma and analyzed a selected panel of microRNAs (miRNAs) in older adults with/without cognitive impairment.

METHODS

Total sEVs were isolated from the plasma of participants with normal cognition (CN; n = 11), mild cognitive impairment (MCI; n = 11), MCI conversion to AD dementia (MCI-AD; n = 6), and AD dementia (n = 11). Various brain cell-derived sEVs (from neurons, astrocytes, microglia, oligodendrocytes, pericytes, and endothelial cells) were enriched and analyzed for specific miRNAs.

RESULTS

miRNAs in sEV subtypes differentially expressed in MCI, MCI-AD, and AD dementia compared to the CN group clearly distinguished dementia status, with an area under the curve (AUC) > 0.90 and correlated with the temporal cortical region thickness on magnetic resonance imaging (MRI).

DISCUSSION

miRNA analyses in specific sEVs could serve as a novel blood-based molecular biomarker for AD.

HIGHLIGHTS

Multiple brain cell-derived small extracellular vesicles (sEVs) could be isolated simultaneously from blood. MicroRNA (miRNA) expression in sEVs could detect Alzheimer's disease (AD) with high specificity and sensitivity. miRNA expression in sEVs correlated with cortical region thickness on magnetic resonance imaging (MRI). Altered expression of miRNAs in sEVCD31 and sEVPDGFRβ suggested vascular dysfunction. miRNA expression in sEVs could predict the activation state of specific brain cell types.

Surface-based correlates of cognition along the Alzheimer's continuum in a memory clinic population

Composite cognitive measures in large-scale studies with biomarker data for amyloid and tau have been widely used to characterize Alzheimer's disease (AD). However, little is known about how the findings from these studies translate to memory clinic populations without biomarker data, using single measures of cognition. Additionally, most studies have utilized voxel-based morphometry or limited surface-based morphometry such as cortical thickness, to measure the neurodegeneration associated with cognitive deficits. In this study, we aimed to replicate and extend the biomarker, composite study relationships using expanded surface-based morphometry and single measures of cognition in a memory clinic population. We examined 271 clinically diagnosed symptomatic individuals with mild cognitive impairment (N = 93) and Alzheimer's disease dementia (N = 178), as well as healthy controls (N = 29). Surface-based morphometry measures included cortical thickness, sulcal depth, and gyrification index within the "signature areas" of Alzheimer's disease. The cognitive variables pertained to hallmark features of Alzheimer's disease including verbal learning, verbal memory retention, and language, as well as executive function. The results demonstrated that verbal learning, language, and executive function correlated with the cortical thickness of the temporal, frontal, and parietal areas. Verbal memory retention was correlated to the thickness of temporal regions and gyrification of the inferior temporal gyrus. Language was related to the temporal regions and the supramarginal gyrus' sulcal depth and gyrification index. Executive function was correlated with the medial temporal gyrus and supramarginal gyrus sulcal depth, and the gyrification index of temporal regions and supramarginal gyrus, but not with the frontal areas. Predictions of each of these cognitive measures were dependent on a combination of structures and each of the morphometry measurements, and often included medial temporal gyrus thickness and sulcal depth. Overall, the results demonstrated that the relationships between cortical thinning and cognition are widespread and can be observed using single measures of cognition in a clinically diagnosed AD population. The utility of sulcal depth and gyrification index measures may be more focal to certain brain areas and cognitive measures. The relative importance of temporal, frontal, and parietal regions in verbal learning, language, and executive function, but not verbal memory retention, was replicated in this clinic cohort.

Brain structure and allelic associations in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD), the most prevalent form of dementia, affects 6.5 million Americans and over 50 million people globally. Clinical, genetic, and phenotypic studies of dementia provide some insights of the observed progressive neurodegenerative processes, however, the mechanisms underlying AD onset remain enigmatic.

AIMS

This paper examines late-onset dementia-related cognitive impairment utilizing neuroimaging-genetics biomarker associations.

MATERIALS AND METHODS

The participants, ages 65-85, included 266 healthy controls (HC), 572 volunteers with mild cognitive impairment (MCI), and 188 Alzheimer's disease (AD) patients. Genotype dosage data for AD-associated single nucleotide polymorphisms (SNPs) were extracted from the imputed ADNI genetics archive using sample-major additive coding. Such 29 SNPs were selected, representing a subset of independent SNPs reported to be highly associated with AD in a recent AD meta-GWAS study by Jansen and colleagues.

RESULTS

We identified the significant correlations between the 29 genomic markers (GMs) and the 200 neuroimaging markers (NIMs). The odds ratios and relative risks for AD and MCI (relative to HC) were predicted using multinomial linear models.

DISCUSSION

In the HC and MCI cohorts, mainly cortical thickness measures were associated with GMs, whereas the AD cohort exhibited different GM-NIM relations. Network patterns within the HC and AD groups were distinct in cortical thickness, volume, and proportion of White to Gray Matter (pct), but not in the MCI cohort. Multinomial linear models of clinical diagnosis showed precisely the specific NIMs and GMs that were most impactful in discriminating between AD and HC, and between MCI and HC.

CONCLUSION

This study suggests that advanced analytics provide mechanisms for exploring the interrelations between morphometric indicators and GMs. The findings may facilitate further clinical investigations of phenotypic associations that support deep systematic understanding of AD pathogenesis.

Metacognition, cortical thickness, and tauopathy in aging

We investigated self-rating of cognitive task performance (self-appraisal) and the difference between self-rating and actual task performance (appraisal discrepancy) in cognitively healthy older adults and their relationship with cortical thickness and Alzheimer's disease (AD) biomarkers, amyloid and tau. All participants (N = 151) underwent neuropsychological testing and 1.5T structural magnetic resonance imaging. A subset (N = 66) received amyloid-PET with [11C] PiB and tau-PET with [18F] Flortaucipir. We found that worse performers had lower self-appraisal ratings, but still overestimated their performance, consistent with the Dunning-Kruger effect. Self-appraisal rating and appraisal discrepancy revealed distinct relationships with cortical thickness and AD pathology. Greater appraisal discrepancy, indicating overestimation, was related to thinning of inferior-lateral temporal, fusiform, and rostral anterior cingulate cortices. Lower self-appraisal was associated with higher entorhinal and inferior temporal tau. These results suggest that overestimation could implicate structural atrophy beyond AD pathology, while lower self-appraisal could indicate early behavioral alteration due to AD pathology, supporting the notion of subjective cognitive decline prior to objective deficits.

A novel computer adaptive word list memory test optimized for remote assessment: Psychometric properties and associations with neurodegenerative biomarkers in older women without dementia

Introduction

This study established the psychometric properties and preliminary validity of the Stricker Learning Span (SLS), a novel computer adaptive word list memory test designed for remote assessment and optimized for smartphone use.

Methods

Women enrolled in the Mayo Clinic Specialized Center of Research Excellence (SCORE) were recruited via e-mail or phone to complete two remote cognitive testing sessions. Convergent validity was assessed through correlation with previously administered in-person neuropsychological tests (n = 96, ages 55-79) and criterion validity through associations with magnetic resonance imaging measures of neurodegeneration sensitive to Alzheimer's disease (n = 47).

Results

SLS performance significantly correlated with the Auditory Verbal Learning Test and measures of neurodegeneration (temporal meta-regions of interest and entorhinal cortical thickness, adjusting for age and education). Test-retest reliabilities across two sessions were 0.71-0.76 (two-way mixed intraclass correlation coefficients).

Discussion

The SLS is a valid and reliable self-administered memory test that shows promise for remote assessment of aging and neurodegenerative disorders.

Concordance of Alzheimer’s Disease Subtypes Produced from Different Representative Morphological Measures: A Comparative Study

Background: Gray matter (GM) density and cortical thickness (CT) obtained from structural magnetic resonance imaging are representative GM morphological measures that have been commonly used in Alzheimer’s disease (AD) subtype research. However, how the two measures affect the definition of AD subtypes remains unclear. Methods: A total of 180 AD patients from the ADNI database were used to identify AD subgroups. The subtypes were identified via a data-driven strategy based on the density features and CT features, respectively. Then, the similarity between the two features in AD subtype definition was analyzed. Results: Four distinct subtypes were discovered by both density and CT features: diffuse atrophy AD, minimal atrophy AD (MAD), left temporal dominant atrophy AD (LTAD), and occipital sparing AD. The matched subtypes exhibited relatively high similarity in atrophy patterns and neuropsychological and neuropathological characteristics. They differed only in MAD and LTAD regarding the carrying of apolipoprotein E ε2. Conclusions: The results verified that different representative morphological GM measurement methods could produce similar AD subtypes. Meanwhile, the influences of apolipoprotein E genotype, asymmetric disease progression, and their interactions should be considered and included in the AD subtype definition. This study provides a valuable reference for selecting features in future studies of AD subtypes.

Investigating Associations Between Inflammatory Biomarkers, Gray Matter, Neurofilament Light and Cognitive Performance in Healthy Older Adults

Background: Exploring biological variables that may serve as indicators of the development and progression of cognitive decline is currently a high-priority research area. Recent studies have demonstrated that during normal aging, individuals experience increased inflammation throughout the brain and body, which may be linked to cognitive impairment and reduced gray matter volume in the brain. Neurofilament light polypeptide (NfL), which is released into the circulation following neuronal damage, has been proposed as a biomarker for neurodegenerative diseases, and may also have utility in the context of normal aging. The present study tested associations between age, peripheral levels of the pro-inflammatory cytokine IL-6, peripheral NfL, brain volume, and cognitive performance in a sample of healthy adults over 60 years old.

Methods: Of the 273 individuals who participated in this study, 173 had useable neuroimaging data, a subset of whom had useable blood data (used for quantifying IL-6 and NfL) and completed a cognitive task. Gray matter (GM) thickness values were extracted from brain areas of interest using Freesurfer. Regression models were used to test relationships between IL-6, NfL, GM, and cognitive performance. To test putative functional relationships between these variables, exploratory path analytic models were estimated, in which the relationship between age, IL-6, and working memory performance were linked via four different operationalizations of brain health: (1) a latent GM variable composed of several regions linked to cognitive impairment, (2) NfL alone, (3) NfL combined with the GM latent variable, and (4) the hippocampus alone.

Results: Regression models showed that IL-6 and NfL were significantly negatively associated with GM volume and that GM was positively associated with cognitive performance. The path analytic models indicated that age and cognitive performance are linked by GM in the hippocampus as well as several other regions previously associated with cognitive impairment, but not by NfL alone. Peripheral IL-6 was not associated with age in any of the path models.

Conclusions: Results suggest that among healthy older adults, there are several GM regions that link age and cognitive performance. Notably, NfL alone is not a sufficient marker of brain changes associated with aging, inflammation, and cognitive performance.

Impacts of Kidney Dysfunction and Cerebral Cortical Thinning on Cognitive Change in Elderly Population

BACKGROUND

Cerebral cortical thickness is a neuroimaging biomarker to predict cognitive decline, and kidney dysfunction (KD) is associated with cortical thinning.

OBJECTIVE

This study aimed to investigate the effects of KD and cortical thinning on cognitive change in a prospective cohort study.

METHODS

A total of 244 non-demented participants were recruited from elderly health checkup program and received cognitive exams including Montreal Cognitive Assessment (MoCA) and different cognitive domains at baseline and three biannual follow-ups afterwards. KD was defined as having either glomerular filtration rate <60 ml/min/1.73 m2 or proteinuria. Cortical thickness of global, lobar, and Alzheimer's disease (AD) signature area were derived from magnetic resonance imaging at baseline, and cortical thinning was defined as the lowest tertile of cortical thickness. Generalized linear mixed models were applied to evaluate the effects of KD and cortical thinning on cognitive changes.

RESULTS

KD was significantly associated with the decline in attention function (β= -0.29). Thinning of global (β= -0.06), AD signature area (β= -0.06), temporal (β= -0.06), and parietal lobes (β= -0.06) predicted poor verbal fluency over time, while temporal lobe thinning also predicted poor MoCA score (β= -0.19). KD modified the relationship between thinning of global, frontal, and limbic, and change of logical memory function (pinteraction < 0.05). When considering jointly, participants with both KD and cortical thinning had greatest decline in attention function compared with those without KD or cortical thinning (β= -0.51, ptrend = 0.008).

CONCLUSIONS

KD and cortical thinning have joint effect on cognitive decline, especially the attention function. Reverse associations may exist between cortical thinning and memory function in participants with KD, though the results should be interpreted cautiously as an exploratory analysis.

A robust brain signature region approach for episodic memory performance in older adults

The brain signature concept aims to characterize brain regions most strongly associated with an outcome of interest. Brain signatures derive their power from data-driven searches that select features based solely on performance metrics of prediction or classification. This approach has important potential to delineate biologically relevant brain substrates for prediction or classification of future trajectories. Recent work has used exploratory voxel-wise or atlas-based searches, with some using machine learning techniques to define salient features. These have shown undoubted usefulness, but two issues remain. The preponderance of recent work has been aimed at categorical rather than continuous outcomes, and it is rare for non-atlas reliant voxel-based signatures to be reported that would be useful for modelling and hypothesis testing. We describe a cross-validated signature region model for structural brain components associated with baseline and longitudinal episodic memory across cognitively heterogeneous populations including normal, mild impairment and dementia. We used three non-overlapping cohorts of older participants: from the UC Davis Aging and Diversity cohort (n = 255; mean age 75.3 ± 7.1 years; 128 cognitively normal, 97 mild cognitive impairment, 30 demented and seven unclassified); from Alzheimer's Disease Neuroimaging Initiative (ADNI) 1 (n = 379; mean age 75.1 ± 7.2; 82 cognitively normal, 176 mild cognitive impairment, 121 Alzheimer's dementia); and from ADNI2/GO (n = 680; mean age 72.5 ± 7.1; 220 cognitively normal, 381 mild cognitive impairment and 79 Alzheimer's dementia). We used voxel-wise regression analysis, correcting for multiple comparisons, to generate an array of regional masks corresponding to different association strength levels of cortical grey matter with baseline memory and brain atrophy with memory change. Cognitive measures were episodic memory using Spanish and English Neuropsychological Assessment Scales instruments for UC Davis and ADNI-Mem for ADNI 1 and ADNI2/GO. Performance metric was the adjusted R2 coefficient of determination of each model explaining outcomes in two cohorts other than where it was computed. We compared within-cohort performances of signature models against each other and against other recent signature models of episodic memory. Findings were: (i) two independently generated signature region of interest models performed similarly in a third separate cohort; (ii) a signature region of interest generated in one imaging cohort replicated its performance level when explaining cognitive outcomes in each of other, separate cohorts; and (iii) this approach better explained baseline and longitudinal memory than other recent theory-driven and data-driven models. This suggests our approach can generate signatures that may be easily and robustly applied for modelling and hypothesis testing in mixed cognition cohorts.

Imaging Techniques in Alzheimer's Disease: A Review of Applications in Early Diagnosis and Longitudinal Monitoring

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting many individuals worldwide with no effective treatment to date. AD is characterized by the formation of senile plaques and neurofibrillary tangles, followed by neurodegeneration, which leads to cognitive decline and eventually death.

INTRODUCTION

In AD, pathological changes occur many years before disease onset. Since disease-modifying therapies may be the most beneficial in the early stages of AD, biomarkers for the early diagnosis and longitudinal monitoring of disease progression are essential. Multiple imaging techniques with associated biomarkers are used to identify and monitor AD.

AIM

In this review, we discuss the contemporary early diagnosis and longitudinal monitoring of AD with imaging techniques regarding their diagnostic utility, benefits and limitations. Additionally, novel techniques, applications and biomarkers for AD research are assessed.

FINDINGS

Reduced hippocampal volume is a biomarker for neurodegeneration, but atrophy is not an AD-specific measure. Hypometabolism in temporoparietal regions is seen as a biomarker for AD. However, glucose uptake reflects astrocyte function rather than neuronal function. Amyloid-β (Aβ) is the earliest hallmark of AD and can be measured with positron emission tomography (PET), but Aβ accumulation stagnates as disease progresses. Therefore, Aβ may not be a suitable biomarker for monitoring disease progression. The measurement of tau accumulation with PET radiotracers exhibited promising results in both early diagnosis and longitudinal monitoring, but large-scale validation of these radiotracers is required. The implementation of new processing techniques, applications of other imaging techniques and novel biomarkers can contribute to understanding AD and finding a cure.

CONCLUSIONS

Several biomarkers are proposed for the early diagnosis and longitudinal monitoring of AD with imaging techniques, but all these biomarkers have their limitations regarding specificity, reliability and sensitivity. Future perspectives. Future research should focus on expanding the employment of imaging techniques and identifying novel biomarkers that reflect AD pathology in the earliest stages.

Genome-wide association study identifies susceptibility loci of brain atrophy to NFIA and ST18 in Alzheimer's disease

To identify genetic variants influencing cortical atrophy in Alzheimer's disease (AD), we performed genome-wide association studies (GWAS) of mean cortical thicknesses in 17 AD-related brain. In this study, we used neuroimaging and genetic data of 919 participants from the Alzheimer's Disease Neuroimaging Initiative cohort, which include 268 cognitively normal controls, 488 mild cognitive impairment, 163 AD individuals. We performed GWAS with 3,041,429 single nucleotide polymorphisms (SNPs) for cortical thickness. The results of GWAS indicated that rs10109716 in ST18 (ST18 C2H2C-type zinc finger transcription factor) and rs661526 in NFIA (nuclear factor I A) genes are significantly associated with mean cortical thicknesses of the left inferior frontal gyrus and left parahippocampal gyrus, respectively. The rs661526 regulates the expression levels of NFIA in the substantia nigra and frontal cortex and rs10109716 regulates the expression levels of ST18 in the thalamus. These results suggest a crucial role of identified genes for cortical atrophy and could provide further insights into the genetic basis of AD.

Spatial patterns of correlation between cortical amyloid and cortical thickness in a tertiary clinical population with memory deficit

To estimate regional Alzheimer disease (AD) pathology burden clinically, analysis methods that enable tracking brain amyloid or tau positron emission tomography (PET) with magnetic resonance imaging (MRI) measures are needed. We therefore developed a robust MRI analysis method to identify brain regions that correlate linearly with regional amyloid burden in congruent PET images. This method was designed to reduce data variance and improve the sensitivity of the detection of cortical thickness-amyloid correlation by using whole brain modeling, nonlinear image coregistration, and partial volume correction. Using this method, a cross-sectional analysis of 75 tertiary memory clinic AD patients was performed to test our hypothesis that regional amyloid burden and cortical thickness are inversely correlated in medial temporal neocortical regions. Medial temporal cortical thicknesses were not correlated with their regional amyloid burden, whereas cortical thicknesses in the lateral temporal, lateral parietal, and frontal regions were inversely correlated with amyloid burden. This study demonstrates the robustness of our technique combining whole brain modeling, nonlinear image coregistration, and partial volume correction to track the differential correlation between regional amyloid burden and cortical thinning in specific brain regions. This method could be used with amyloid and tau PET to assess corresponding cortical thickness changes.

Dynamic association between AT(N) profile and cognition mediated by cortical thickness in Alzheimer's continuum

BACKGROUND

The recently-proposed National Institute on Aging and Alzheimer's Association research framework organizes Alzheimer's disease (AD) biomarkers based on amyloid/tau/neurodegeneration (AT(N)). This study investigated the mediating effect of structural change in brain MRI on changes in cognitive function according to initial AT(N) profiles.

METHODS

We included 576 subjects (cognitively unimpaired (N = 136), mild cognitive impairment (N = 294), dementia (N = 146)) from the Alzheimer's disease Neuroimaging Initiative study. The parallel-process latent growth curve model was applied to test the mediational effect of cortical thickness growth trajectory between the initial AT(N) profiles and cognitive growth trajectory.

RESULTS

In Alzheimer's continuum, only the A + T + (N)+ profile showed a mediational effect of the cortical thickness growth trajectory. A + T - (N)- was not sufficient to induce direct or indirect effects on cognitive dysfunction, and A + T + (N)- showed a significant direct path from an altered cortical thickness to cognitive decline.

CONCLUSION

The sequential effect between changes in brain MRI and cognition varied by baseline AT(N) profile, suggesting the dynamic changes in the relationships among biomarkers in the current cascade model.

Engagement in Lifestyle Activities is Associated with Increased Alzheimer's Disease-Associated Cortical Thickness and Cognitive Performance in Older Adults

The aim of this study was to examine the association between lifestyle activities, including physical, cognitive, and social activities, and Alzheimer’s disease (AD) signature cortical thickness, as well as to examine the mediating role of AD signature cortical thickness in lifestyle activities and cognitive function in community-dwelling healthy older adults. Participants were 1026 older adults who met the study inclusion criteria. The physical, cognitive, and social activities of daily life were assessed using a self-reporting questionnaire. AD signature cortical thickness was determined using FreeSurfer software. Cognitive function was evaluated using the National Center for Geriatrics and Gerontology-Functional Assessment Tool. Path analysis (based on structural equation modeling (SEM)) of cognitive activities indicated that the direct path from cognitive activities to cognitive function was significant (p < 0.001), as was the direct path from AD signature cortical thickness to cognitive function (p < 0.001). Physical (p < 0.05) or social activities (p < 0.05) had a direct effect on cognitive function. However, AD signature cortical thickness did not mediate the relationship between physical or social activities and cognitive function. Our findings suggest that higher levels of cognitive activities later in life have a significant and positive direct effect on cognitive function. Additionally, AD signature cortical thickness significantly mediates the relationship between cognitive activities and cognitive function.

Precuneus-Dominant Degeneration of Parietal Lobe Is at Risk of Epilepsy in Mild Alzheimer's Disease

Introduction: Alzheimer's disease (AD) is the leading cause of cognitive decline. Epilepsy is a frequent comorbid condition of AD. While previous studies analyzed the risk factors of AD-related epileptic seizures, we still lack biomarkers of epilepsy in mild AD cases.

Purpose: The aim of our study was to analyze the correlations between neuropsychology, cortical thickness, and brain volumetric measurements in mild Alzheimer patients with concomitant epileptic seizures.

Materials and methods: We selected mild AD patients from our database to examine them with structural magnetic resonance imaging, 24 h electroencephalography, and detailed neuropsychology. We made the diagnosis of epilepsy based on epileptology data including neurophysiology. We retrospectively analyzed the neuropsychology pattern, clinical and epidemiologic features, cortical thickness, and volumetric values of mild AD patients with and without overt clinical seizures using covariance weighted general linear model.

Results: We found epileptic seizures in 26% of mild AD patients. Patients with seizures performed worse in visuo-spatial scores than patients without (p = 0.003). Patients with seizures had smaller parietal thickness (p = 0.018), being associated to reduced thickness of left (p = 0.007), and right precunei (p = 0.005). The visuo-spatial performance positively and strongly correlated with the thickness of the parietal lobe (r = 0.67; p = 0.002) and with the volume of the precuneus (r = 0.612; p = 0.005).

Conclusion: Epileptic seizures are common even in mild AD. We found that a prominent deficit in visuo-spatial skills is a red flag for epileptic seizures in the initial phase of AD, indicating the early involvement of parietal lobe in the neurodegenerative process. Because our findings suggest that the degeneration of precuneus is a sensitive marker of seizures associated to mild AD, clinicians need to pay special attention to the pattern of atrophy shown by structural MRI. Our results confirm previous data suggesting that epileptic seizures might be associated to a faster progressing type of AD with the early degeneration of posterior cortical areas.

The Geometry of the Generalized Gamma Manifold and an Application to Medical Imaging

The Fisher information metric provides a smooth family of probability measures with a Riemannian manifold structure, which is an object in information geometry. The information geometry of the gamma manifold associated with the family of gamma distributions has been well studied. However, only a few results are known for the generalized gamma family that adds an extra shape parameter. The present article gives some new results about the generalized gamma manifold. This paper also introduces an application in medical imaging that is the classification of Alzheimer’s disease population. In the medical field, over the past two decades, a growing number of quantitative image analysis techniques have been developed, including histogram analysis, which is widely used to quantify the diffuse pathological changes of some neurological diseases. This method presents several drawbacks. Indeed, all the information included in the histogram is not used and the histogram is an overly simplistic estimate of a probability distribution. Thus, in this study, we present how using information geometry and the generalized gamma manifold improved the performance of the classification of Alzheimer’s disease population.

The personalized Alzheimer's disease cortical thickness index predicts likely pathology and clinical progression in mild cognitive impairment

Introduction

An Alzheimer's disease (AD) biomarker adjusted for age-related brain changes should improve specificity for AD-related pathological burden.

Methods

We calculated a brain-age-adjusted “personalized AD cortical thickness index” (pADi) in mild cognitive impairment patients from the Alzheimer's Disease Neuroimaging Initiative. We performed receiver operating characteristic analysis for discrimination between patients with and without cerebrospinal fluid evidence of AD and logistic regression in an independent sample to determine if a dichotomized pADi predicted conversion to AD dementia.

Results

Receiver operating characteristic area under the curve was 0.69 and 0.72 in the two samples. Three empirical methods identified the same cut-point for pADi in the discovery sample. In the validation sample, 83% of pADi+ mild cognitive impairment patients were cerebrospinal fluid AD biomarker positive. pADi+ mild cognitive impairment patients (n = 63, 38%) were more likely to progress to AD dementia after 1 (odds ratio = 2.9) and 3 (odds ratio = 2.6) years.

Discussion

The pADi is a personalized, magnetic resonance imaging–derived AD biomarker that predicts progression to dementia.

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The personalized AD cortical thickness index (pADi) is a personalized magnetic resonance imaging–derived, brain-age-adjusted Alzheimer's disease (AD) biomarker.

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The pADi accurately identifies mild cognitive impairment patients with cerebrospinal fluid markers of AD.

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The pADi was consistent across two independent samples with 1.5T and 3T magnetic resonance imaging data.

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An optimal cut-point predicted progression to AD dementia over 1 or 3 years.

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The pADi can identify mild cognitive impairment likely due to AD in individual patients.