Correlations between FDG PET glucose uptake-MRI gray matter volume scores and apolipoprotein E ε4 gene dose in cognitively normal adults: a cross-validation study using voxel-based multi-modal partial least squares

Harmonizing florbetapir and PiB PET measurements of cortical Aβ plaque burden using multiple regions-of-interest and machine learning techniques: An alternative to the Centiloid approach

INTRODUCTION

Machine learning (ML) can optimize amyloid (Aβ) comparability among positron emission tomography (PET) radiotracers. Using multi-regional florbetapir (FBP) measures and ML, we report better Pittsburgh compound-B (PiB)/FBP harmonization of mean-cortical Aβ (mcAβ) than Centiloid.

METHODS

PiB-FBP pairs from 92 subjects in www.oasis-brains.org and 46 in www.gaain.org/centiloid-project were used as the training/testing sets. FreeSurfer-extracted FBP multi-regional Aβ and actual PiB mcAβ in the training set were used to train ML models generating synthetic PiB mcAβ. The correlation coefficient (R) between the synthetic/actual PiB mcAβ in the testing set was assessed.

RESULTS

In the testing set, the synthetic/actual PiB mcAβ correlation R = 0.985 (R2  = 0.970) using artificial neural network was significantly higher (p ≤ 6.6e-4) than the FBP/PiB correlation R = 0.927 (R2  = 0.860), improving total variance percentage (R2 ) from 86% to 97%. Other ML models such as partial least square, ensemble, and relevance vector regressions also improved R (p = 9.677e-05 /0.045/0.0017).

DISCUSSION

ML improved mcAβ comparability. Additional studies are needed for the generalizability to other amyloid tracers, and to tau PET. Highlights Centiloid is a calibration of the amyloid scale, not harmonization. Centiloid unifies the amyloid scale without improving inter-tracer association (R2 ). Machine learning (ML) can harmonize the amyloid scale by improving R2 . ML harmonization maps multi-regional florbetapir SUVRs to PiB mean-cortical SUVR. Artificial neural network ML increases Centiloid R2 from 86% to 97%.

APOE ɛ4 exacerbates age-dependent deficits in cortical microstructure

The apolipoprotein E ɛ4 allele is the primary genetic risk factor for the sporadic type of Alzheimer's disease. However, the mechanisms by which apolipoprotein E ɛ4 are associated with neurodegeneration are still poorly understood. We applied the Neurite Orientation Dispersion Model to characterize the effects of apolipoprotein ɛ4 and its interactions with age and education on cortical microstructure in cognitively normal individuals. Data from 1954 participants were included from the PREVENT-Dementia and ALFA (ALzheimer and FAmilies) studies (mean age = 57, 1197 non-carriers and 757 apolipoprotein E ɛ4 carriers). Structural MRI datasets were processed with FreeSurfer v7.2. The Microstructure Diffusion Toolbox was used to derive Orientation Dispersion Index maps from diffusion MRI datasets. Primary analyses were focused on (i) the main effects of apolipoprotein E ɛ4, and (ii) the interactions of apolipoprotein E ɛ4 with age and education on lobar and vertex-wise Orientation Dispersion Index and implemented using Permutation Analysis of Linear Models. There were apolipoprotein E ɛ4 × age interactions in the temporo-parietal and frontal lobes, indicating steeper age-dependent Orientation Dispersion Index changes in apolipoprotein E ɛ4 carriers. Steeper age-related Orientation Dispersion Index declines were observed among apolipoprotein E ɛ4 carriers with lower years of education. We demonstrated that apolipoprotein E ɛ4 worsened age-related Orientation Dispersion Index decreases in brain regions typically associated with atrophy patterns of Alzheimer's disease. This finding also suggests that apolipoprotein E ɛ4 may hasten the onset age of dementia by accelerating age-dependent reductions in cortical Orientation Dispersion Index.

Effect of APOE ε4 genotype on amyloid-β, glucose metabolism, and gray matter volume in cognitively normal individuals and amnestic mild cognitive impairment

BACKGROUND AND PURPOSE

The presence of apolipoprotein E ε4 (APOE ε4) is associated with an increased risk of developing Alzheimer disease (AD). The aim of this study was to assess the effects of APOE ε4 on amyloid-β (Aβ) pathology, glucose metabolism, and gray matter (GM) volume and their longitudinal changes in healthy control (HC) and amnestic mild cognitive impairment (aMCI).

METHODS

We included 50 HCs and 109 aMCI patients from the Alzheimer's Disease Neuroimaging Initiative phase 2/GO based on availability of baseline T1-weighted magnetic resonance imaging, ¹⁸ F-florbetapir positron emission tomography (PET), and ¹⁸ F-fluorodeoxyglucose (FDG) PET. Of these, 35 HCs and 67 aMCI patients who underwent 24-month scans were included for follow-up study.

RESULTS

Voxelwise analysis revealed that APOE ε4 carriers exhibited greater baseline Aβ deposition than APOE ε4 noncarriers in both diagnostic groups. However, there was no significant difference between APOE ε4 noncarriers and APOE ε4 carriers in terms of ¹⁸ F-FDG PET standardized uptake value ratio and GM volume. Region of interest-based analysis showed statistically significant greater Aβ deposition in APOE ε4 carriers than APOE ε4 noncarriers only in aMCI patients. Furthermore, APOE ε4 carriers generally exhibited a greater magnitude and spatial extent of longitudinal changes in Aβ deposition than APOE ε4 noncarriers in both diagnostic groups.

CONCLUSIONS

Our findings suggest a differential effect of APOE ε4 on Aβ pathology, glucose metabolism, and GM volume. Studying APOE ε4-related brain changes with neuroimaging biomarkers in preclinical AD offers an opportunity to further our understanding of the pathophysiology of AD at an early stage.

Molecular imaging of the association between serotonin degeneration and beta-amyloid deposition in mild cognitive impairment

BACKGROUND

Degeneration of the serotonin system has been observed in Alzheimer's disease (AD) and in mild cognitive impairment (MCI). In transgenic amyloid mouse models, serotonin degeneration is detected prior to widespread cortical beta-amyloid (Aβ) deposition, also suggesting that serotonin degeneration may be observed in preclinical AD.

METHODS

The differences in the distribution of serotonin degeneration (reflected by the loss of the serotonin transporter, 5-HTT) relative to Aβ deposition was measured with positron emission tomography in a group of individuals with MCI and a group of healthy older adults. A multi-modal partial least squares (mmPLS) algorithm was applied to identify the spatial covariance pattern between 5-HTT availability and Aβ deposition.

RESULTS

Forty-five individuals with MCI and 35 healthy older adults were studied, 22 and 27 of whom were included in the analyses who were "amyloid positive" and "amyloid negative", respectively. A pattern of lower cortical, subcortical and limbic 5-HTT availability and higher cortical Aβ deposition distinguished the MCI from the healthy older control participants. Greater expression of this pattern was correlated with greater deficits in memory and executive function in the MCI group, not in the control group.

CONCLUSION

A spatial covariance pattern of lower 5-HTT availability and Aβ deposition was observed to a greater extent in an MCI group relative to a control group and was associated with cognitive impairment in the MCI group. The results support the application of mmPLS to understand the neurochemical changes associated with Aβ deposition in the course of preclinical AD.

APOE4 Status and Cognitive Function in Middle-aged and Elderly People

Introduction

APOE is one of the prominent genes involved in the increased risk of developing Alzheimer's disease, but its effect on cognition in patients who are not yet diagnosed with dementia or mild cognitive impairment is relatively understudied. We aimed to examine the effect of ApoE4 on cognitive performance in unimpaired middle-aged and elderly persons.

Materials and methods

Our study included 51 cognitively unimpaired participants divided into ApoE4 positive patients and controls by APOE genotyping. The following clinical and demographic characteristics were collected: age, gender, education, social status, BMI, history of medical or psychiatric disorders. Patients with current anxiety or depressive disorders were excluded. Cognitive function was evaluated using MMSE, Rey Auditory-Verbal Learning Test, Rey Complex Figure test, TMT A and B and verbal fluency test. The two groups were matched for age, sex, and education. Categorial data was analyzed using Chi-Square and continuous data using Student-T test (parametric variables) or Mann-Whitney test (non-parametric variables). Statistical significance was considered at p≤.05.

Results

There were 11 (21.6%) ApoE4 positive patients and 40 (78.4%) controls. There were no significant differences between the groups regarding socio-demographic and clinical characteristics. The ApoE4 positive group performed slightly worse on cognitive evaluations compared to controls but only the mean scores of the Rey Complex Figure Test - Memory reached statistical significance (p=.019).

Conclusion

Cognitive evaluation generally rendered lower scores in the ApoE4 group compared to the control group. However, only visual memory impairment scores were significantly lower in the ApoE4 positive individuals than in controls.

Positron emission tomography imaging of serotonin degeneration and beta-amyloid deposition in late-life depression evaluated with multi-modal partial least squares

Depression in late-life is associated with increased risk of cognitive decline and development of all-cause dementia. The neurobiology of late-life depression (LLD) may involve both neurochemical and neurodegenerative mechanisms that are common to depression and dementia. Transgenic amyloid mouse models show evidence of early degeneration of monoamine systems. Informed by these preclinical data, the hypotheses were tested that a spatial covariance pattern of higher beta-amyloid (Aβ) and lower serotonin transporter availability (5-HTT) in frontal, temporal, and parietal cortical regions would distinguish LLD patients from healthy controls and the expression of this pattern would be associated with greater depressive symptoms. Twenty un-medicated LLD patients who met DSM-V criteria for major depression and 20 healthy controls underwent PET imaging with radiotracers for Aβ ([11C]-PiB) and 5-HTT ([11C]-DASB). A voxel-based multi-modal partial least squares (mmPLS) algorithm was applied to the parametric PET images to determine the spatial covariance pattern between the two radiotracers. A spatial covariance pattern was identified, including higher Aβ in temporal, parietal and occipital cortices associated with lower 5-HTT in putamen, thalamus, amygdala, hippocampus and raphe nuclei (dorsal, medial and pontine), which distinguished LLD patients from controls. Greater expression of this pattern, reflected in summary 5-HTT/Aβ mmPLS subject scores, was associated with higher levels of depressive symptoms. The mmPLS method is a powerful approach to evaluate the synaptic changes associated with AD pathology. This spatial covariance pattern should be evaluated further to determine whether it represents a biological marker of antidepressant treatment response and/or cognitive decline in LLD patients.

Apolipoprotein E and Alzheimer's Disease: Findings, Hypotheses, and Potential Mechanisms

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder that involves dysregulation of many cellular and molecular processes. It is notoriously difficult to develop therapeutics for AD due to its complex nature. Nevertheless, recent advancements in imaging technology and the development of innovative experimental techniques have allowed researchers to perform in-depth analyses to uncover the pathogenic mechanisms of AD. An important consideration when studying late-onset AD is its major genetic risk factor, apolipoprotein E4 (apoE4). Although the exact mechanisms underlying apoE4 effects on AD initiation and progression are not fully understood, recent studies have revealed critical insights into the apoE4-induced deficits that occur in AD. In this review, we highlight notable studies that detail apoE4 effects on prominent AD pathologies, including amyloid-β, tau pathology, neuroinflammation, and neural network dysfunction. We also discuss evidence that defines the physiological functions of apoE and outlines how these functions are disrupted in apoE4-related AD. Expected final online publication date for the Annual Review of Pathology: Mechanisms of Disease, Volume 17 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Donor-Specific Transcriptomic Analysis of Alzheimer's Disease-Associated Hypometabolism Highlights a Unique Donor, Ribosomal Proteins and Microglia

Alzheimer's disease (AD) starts decades before clinical symptoms appear. Low-glucose utilization in regions of the cerebral cortex marks early AD. To identify these regions, we conducted a voxel-wise meta-analysis of previous studies conducted with positron emission tomography that compared AD patients with healthy controls. The resulting map marks hypometabolism in the posterior cingulate, middle frontal, angular gyrus, and middle and inferior temporal regions. Using the Allen Human Brain Atlas, we identified genes that show spatial correlation across the cerebral cortex between their expression and this hypometabolism. Of the six brains in the Atlas, one demonstrated a strong spatial correlation between gene expression and hypometabolism. Previous neuropathological assessment of this brain from a 39-year-old male noted a neurofibrillary tangle in the entorhinal cortex. Using the transcriptomic data, we estimate lower proportions of neurons and more microglia in the hypometabolic regions when comparing this donor's brain with the other five donors. Within this single brain, signal recognition particle (SRP)-dependent cotranslational protein targeting genes, which encode primarily cytosolic ribosome proteins, are highly expressed in the hypometabolic regions. Analyses of human and mouse data show that expression of these genes increases progressively across AD-associated states of microglial activation. In addition, genes involved in cell killing, chronic inflammation, ubiquitination, tRNA aminoacylation, and vacuole sorting are associated with the hypometabolism map. These genes suggest disruption of the protein life cycle and neuroimmune activation. Taken together, our molecular characterization reveals a link to AD-associated hypometabolism that may be relevant to preclinical stages of AD.

Longitudinal [18F]FDG-PET/CT analysis of the glucose metabolism in ApoE-deficient mice

Background

Strong line of evidence suggests that the increased risk to develop AD may at least be partly mediated by cholesterol metabolism. A key regulator of cholesterol transport is the Apolipoprotein E4 (ApoE4), which plays a fundamental role in neuronal maintenance and repair. Impaired function of ApoE4 may contribute to altered cerebral metabolism leading to higher susceptibility to neurodegeneration.

Methods

To determine a possible link between ApoE function and alterations in AD in the brain of Apolipoprotein E-deficient mice (ApoE−/−) in a longitudinal manner metabolic and neurochemical parameters were analyzed. Cortical metabolism was measured by 2-deoxy-2-[¹⁸F]fluoroglucose ([¹⁸F]FDG)-PET/CT and proton magnetic resonance spectroscopy (¹H-MRS) served to record neurochemical status.

Results

By using [¹⁸F]FDG-PET/CT, we showed that brain metabolism declined significantly stronger with age in ApoE−/− versus wild type (wt) mice. This difference was particularly evident at the age of 41 weeks in almost each analyzed brain region. In contrast, the ¹H-MRS-measured N-acetylaspartate to creatine ratio, a marker of neuronal viability, did not decline with age and did not differ between ApoE−/− and wt mice.

Conclusion

In summary, this longitudinal in vivo study shows for the first time that ApoE−/− mice depict cerebral hypometabolism without neurochemical alterations.

Intrinsic functional connectivity, CSF biomarker profiles and their relation to cognitive function in mild cognitive impairment

Mild cognitive impairment (MCI) often precedes Alzheimer's Dementia (AD), and in a high proportion of individuals affected by MCI, there are already neuropathological processes ongoing that become more evident when patients progress to AD. Accordingly, there is a need for reliable biomarkers to distinguish between normal aging and incipient AD. Recent research suggests that, in addition to established biomarkers such as CSF Aß42, total tau and hyperphosphorylated tau, resting state connectivity established by functional magnetic resonance imaging might also be a feasible biomarker for prodromal stages of AD. In order to explore this possibility, we investigated resting state functional connectivity as well as cerebrospinal fluid (CSF) biomarker profiles in patients with MCI (n = 30; age 66.43 ± 7.06 years) and cognitively healthy controls (n = 38; age 66.89 ± 7.12 years). CSF Aß42, total tau and hyperphosphorylated tau concentrations were correlated with measures of cognitive performance (immediate and delayed recall, global cognition, processing speed). Moreover, MCI-related alterations in intrinsic functional connectivity within the default mode network were investigated using functional resting state MRI. As expected, MCI patients showed decreased CSF Aß42 and increased total tau concentrations. These alterations were associated with cognitive performance. However, there were no differences between MCI patients and cognitively healthy controls regarding intrinsic functional connectivity. In conclusion, our results indicate that CSF protein profiles seem to be more closely related to cognitive decline than alterations in resting state activity. Thus, resting state connectivity might not be a reliable biomarker for early stages of AD.

Imaging Biomarkers of Neurodegeneration in Alzheimer's Disease: Distinct Contributions of Cortical MRI Atrophy and FDG-PET Hypometabolism

BACKGROUND

Neurodegeneration biomarkers are routinely used in the diagnosis of Alzheimer's disease (AD).

OBJECTIVE

To evaluate the respective contributions of two neuroimaging biomarkers, structural MRI and 18FDG-PET, in the assessment of neurodegeneration in AD dementia.

METHODS

Patients with mild AD dementia diagnosed based on clinical and cerebrospinal fluid criteria and cognitively healthy subjects, from the Marseille cohort ADAge with cognitive, structural MRI and 18FDG-PET assessments, were included. Extent of atrophy on MRI and of hypometabolism on 18FDG-PET were individually evaluated in each patient using a voxel-based analysis on whole-brain approach and compared to healthy subjects. Patients were divided in distinct groups according to their atrophy extent on the one hand and to their hypometabolism extent on the other, then, to their imaging profile combining the extent of the two biomarkers.

RESULTS

Fifty-two patients were included. The MMSE score was significantly lower in the "Extensive hypometabolism" group than in the "Limited hypometabolism" group (respectively 19.5/30 versus 23/30). A lower Innotest Amyloid Tau Index was associated with an extensive hypometabolism (p = 0.04). There were more patients with low educational level in the "Extensive atrophy" group, while a higher educational level was more found in the "Limited atrophy" group (p = 0.005).

CONCLUSION

18FDG-PET hypometabolism extent is associated with the pathological processes and clinical severity of AD, while MRI atrophy seems to be influenced by the cognitive reserve. In the context of mild AD dementia, these two biomarkers of neurodegeneration are thus not interchangeable and require to be considered in combination rather than in isolation.

Radiogenomics for Precision Medicine With a Big Data Analytics Perspective

Precision medicine promises better healthcare delivery by improving clinical practice. Using evidence-based substratification of patients, the objective is to achieve better prognosis, diagnosis, and treatment that will transform existing clinical pathways toward optimizing care for the specific needs of each patient. The wealth of today's healthcare data, often characterized as big data, provides invaluable resources toward new knowledge discovery that has the potential to advance precision medicine. The latter requires interdisciplinary efforts that will capitalize the information, know-how, and medical data of newly formed groups fusing different backgrounds and expertise. The objective of this paper is to provide insights with respect to the state-of-the-art research in precision medicine. More specifically, our goal is to highlight the fundamental challenges in emerging fields of radiomics and radiogenomics by reviewing the case studies of Cancer and Alzheimer's disease, describe the computational challenges from a big data analytics perspective, and discuss standardization and open data initiatives that will facilitate the adoption of precision medicine methods and practices.

Diagnostic utility of 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) in asymptomatic subjects at increased risk for Alzheimer's disease

PURPOSE

To assess the clinical utility of 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) for detection of early signs of neurodegeneration in conditions of increased risk for Alzheimer's disease (AD) as defined by: subjective cognitive decline (SCD), evidence of cerebral amyloid-pathology, apolipoprotein E (APOE) ε4-positive genotype, or autosomal dominant forms of AD (ADAD) in asymptomatic stages.

METHODS

A comprehensive literature search was conducted using the PICO model to extract evidence from relevant studies. An expert panel then voted using the Delphi method on three different diagnostic scenarios.

RESULTS

The level of empirical study evidence for the use of FDG-PET to detect meaningful early signs of neurodegeneration was considered to be poor for ADAD and lacking for SCD and asymptomatic persons at risk, based on APOE ε4-positive genotype or cerebral amyloid pathology. Consequently, and consistent with current diagnostic criteria, panelists decided not to recommend routine clinical use of FDG-PET in these situations and to currently mainly reserve it for research purposes.

CONCLUSION

Currently, there is limited evidence on which to base recommendations regarding the clinical routine use of FDG-PET to detect diagnostically meaningful early signs of neurodegeneration in asymptomatic subjects with ADAD, with APOE ε4-positive genotype, or with cerebral amyloid pathology, and in subjects with SCD. Future prospective studies are warranted and in part already ongoing, aiming to assess the added value of FDG-PET in this context beyond research applications.

Effects of APOE-ε4 allele load on brain morphology in a cohort of middle-aged healthy individuals with enriched genetic risk for Alzheimer's disease

INTRODUCTION

Apolipoprotein E (APOE)-ε4 is the major genetic risk factor for Alzheimer's disease. However, the dose-dependent impact of this allele on brain morphology of healthy individuals remains unclear.

METHODS

We analyzed gray matter volumes (GMvs) in a sample of 533 healthy middle-aged individuals with a substantial representation of ε4-carriers (207 heterozygotes and 65 homozygotes).

RESULTS

We found APOE-ε4 additive GMv reductions in the right hippocampus, caudate, precentral gyrus, and cerebellar crus. In these regions, the APOE genotype interacted with age, with homozygotes displaying lower GMv after the fifth decade of life. APOE-ε4 was also associated to greater GMv in the right thalamus, left occipital gyrus, and right frontal cortex.

DISCUSSION

Our data indicate that APOE-ε4 exerts additive effects on GMv in regions relevant for Alzheimer's disease pathophysiology already in healthy individuals. These findings elucidate the mechanisms underlying the increased Alzheimer's disease risk in ε4-carriers, suggesting a dose-dependent disease vulnerability on the brain structure level.

Multimodal Classification of Mild Cognitive Impairment Based on Partial Least Squares

In recent years, increasing attention has been given to the identification of the conversion of mild cognitive impairment (MCI) to Alzheimer's disease (AD). Brain neuroimaging techniques have been widely used to support the classification or prediction of MCI. The present study combined magnetic resonance imaging (MRI), 18F-fluorodeoxyglucose PET (FDG-PET), and 18F-florbetapir PET (florbetapir-PET) to discriminate MCI converters (MCI-c, individuals with MCI who convert to AD) from MCI non-converters (MCI-nc, individuals with MCI who have not converted to AD in the follow-up period) based on the partial least squares (PLS) method. Two types of PLS models (informed PLS and agnostic PLS) were built based on 64 MCI-c and 65 MCI-nc from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The results showed that the three-modality informed PLS model achieved better classification accuracy of 81.40%, sensitivity of 79.69%, and specificity of 83.08% compared with the single-modality model, and the three-modality agnostic PLS model also achieved better classification compared with the two-modality model. Moreover, combining the three modalities with clinical test score (ADAS-cog), the agnostic PLS model (independent data: florbetapir-PET; dependent data: FDG-PET and MRI) achieved optimal accuracy of 86.05%, sensitivity of 81.25%, and specificity of 90.77%. In addition, the comparison of PLS, support vector machine (SVM), and random forest (RF) showed greater diagnostic power of PLS. These results suggested that our multimodal PLS model has the potential to discriminate MCI-c from the MCI-nc and may therefore be helpful in the early diagnosis of AD.

Multi-modal discriminative dictionary learning for Alzheimer's disease and mild cognitive impairment

BACKGROUND AND OBJECTIVE

The differentiation of mild cognitive impairment (MCI), which is the prodromal stage of Alzheimer's disease (AD), from normal control (NC) is important as the recent research emphasis on early pre-clinical stage for possible disease abnormality identification, intervention and even possible prevention.

METHODS

The current study puts forward a multi-modal supervised within-class-similarity discriminative dictionary learning algorithm (SCDDL) we introduced previously for distinguishing MCI from NC. The proposed new algorithm was based on weighted combination and named as multi-modality SCDDL (mSCDDL). Structural magnetic resonance imaging (sMRI), fluorodeoxyglucose (FDG) positron emission tomography (PET) and florbetapir PET data of 113 AD patients, 110 MCI patients and 117 NC subjects from the Alzheimer's disease Neuroimaging Initiative database were adopted for classification between MCI and NC, as well as between AD and NC.

RESULTS

Adopting mSCDDL, the classification accuracy achieved 98.5% for AD vs. NC and 82.8% for MCI vs. NC, which were superior to or comparable with the results of some other state-of-the-art approaches as reported in recent multi-modality publications.

CONCLUSIONS

The mSCDDL procedure was a promising tool in assisting early diseases diagnosis using neuroimaging data.

Heterogeneous multimodal biomarkers analysis for Alzheimer's disease via Bayesian network

By 2050, it is estimated that the number of worldwide Alzheimer's disease (AD) patients will quadruple from the current number of 36 million, while no proven disease-modifying treatments are available. At present, the underlying disease mechanisms remain under investigation, and recent studies suggest that the disease involves multiple etiological pathways. To better understand the disease and develop treatment strategies, a number of ongoing studies including the Alzheimer's Disease Neuroimaging Initiative (ADNI) enroll many study participants and acquire a large number of biomarkers from various modalities including demographic, genotyping, fluid biomarkers, neuroimaging, neuropsychometric test, and clinical assessments. However, a systematic approach that can integrate all the collected data is lacking. The overarching goal of our study is to use machine learning techniques to understand the relationships among different biomarkers and to establish a system-level model that can better describe the interactions among biomarkers and provide superior diagnostic and prognostic information. In this pilot study, we use Bayesian network (BN) to analyze multimodal data from ADNI, including demographics, volumetric MRI, PET, genotypes, and neuropsychometric measurements and demonstrate our approach to have superior prediction accuracy.

Multimodal Image Analysis in Alzheimer's Disease via Statistical Modelling of Non-local Intensity Correlations

The joint analysis of brain atrophy measured with magnetic resonance imaging (MRI) and hypometabolism measured with positron emission tomography with fluorodeoxyglucose (FDG-PET) is of primary importance in developing models of pathological changes in Alzheimer's disease (AD). Most of the current multimodal analyses in AD assume a local (spatially overlapping) relationship between MR and FDG-PET intensities. However, it is well known that atrophy and hypometabolism are prominent in different anatomical areas. The aim of this work is to describe the relationship between atrophy and hypometabolism by means of a data-driven statistical model of non-overlapping intensity correlations. For this purpose, FDG-PET and MRI signals are jointly analyzed through a computationally tractable formulation of partial least squares regression (PLSR). The PLSR model is estimated and validated on a large clinical cohort of 1049 individuals from the ADNI dataset. Results show that the proposed non-local analysis outperforms classical local approaches in terms of predictive accuracy while providing a plausible description of disease dynamics: early AD is characterised by non-overlapping temporal atrophy and temporo-parietal hypometabolism, while the later disease stages show overlapping brain atrophy and hypometabolism spread in temporal, parietal and cortical areas.

Multi-modality sparse representation-based classification for Alzheimer's disease and mild cognitive impairment

BACKGROUND AND OBJECTIVE

The discrimination of Alzheimer's disease (AD) and its prodromal stage known as mild cognitive impairment (MCI) from normal control (NC) is important for patients' timely treatment. The simultaneous use of multi-modality data has been demonstrated to be helpful for more accurate identification. The current study focused on extending a multi-modality algorithm and evaluating the method by identifying AD/MCI.

METHODS

In this study, sparse representation-based classification (SRC), a well-developed method in pattern recognition and machine learning, was extended to a multi-modality classification framework named as weighted multi-modality SRC (wmSRC). Data including three modalities of volumetric magnetic resonance imaging (MRI), fluorodeoxyglucose (FDG) positron emission tomography (PET) and florbetapir PET from the Alzheimer's disease Neuroimaging Initiative database were adopted for AD/MCI classification (113 AD patients, 110 MCI patients and 117 NC subjects).

RESULTS

Adopting wmSRC, the classification accuracy achieved 94.8% for AD vs. NC, 74.5% for MCI vs. NC, and 77.8% for progressive MCI vs. stable MCI, superior to or comparable with the results of some other state-of-the-art models in recent multi-modality researches.

CONCLUSIONS

The wmSRC method is a promising tool for classification with multi-modality data. It could be effective for identifying diseases from NC with neuroimaging data, which could be helpful for the timely diagnosis and treatment of diseases.

A FDG-PET Study of Metabolic Networks in Apolipoprotein E ε4 Allele Carriers

Recently, some studies have applied the graph theory in brain network analysis in Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI). However, relatively little research has specifically explored the properties of the metabolic network in apolipoprotein E (APOE) ε4 allele carriers. In our study, all the subjects, including ADs, MCIs and NCs (normal controls) were divided into 165 APOE ε4 carriers and 165 APOE ε4 noncarriers. To establish the metabolic network for all brain regions except the cerebellum, cerebral glucose metabolism data obtained from FDG-PET (¹⁸F-fluorodeoxyglu-cose positron emission tomography) were segmented into 90 areas with automated anatomical labeling (AAL) template. Then, the properties of the networks were computed to explore the between-group differences. Our results suggested that both APOE ε4 carriers and noncarriers showed the small-world properties. Besides, compared with APOE ε4 noncarriers, the carriers showed a lower clustering coefficient. In addition, significant changes in 6 hub brain regions were found in between-group nodal centrality. Namely, compared with APOE ε4 noncarriers, significant decreases of the nodal centrality were found in left insula, right insula, right anterior cingulate, right paracingulate gyri, left cuneus, as well as significant increases in left paracentral lobule and left heschl gyrus in APOE ε4 carriers. Increased local short distance interregional correlations and disrupted long distance interregional correlations were found, which may support the point that the APOE ε4 carriers were more similar with AD or MCI in FDG uptake. In summary, the organization of metabolic network in APOE ε4 carriers indicated a less optimal pattern and APOE ε4 might be a risk factor for AD.

Association of a neurokinin 3 receptor polymorphism with the anterior basal forebrain

The neuropeptide neurokinin 3 (NK3) and its receptor modulate cholinergic activity of the basal forebrain (BF) and are implicated in learning and memory. In Alzheimer's disease, the rs2765 single-nucleotide polymorphism (SNP) of the NK3 receptor-coding gene TACR3 was correlated with the right hippocampus volume. Here, we studied the association of the rs2765 SNP with magnetic resonance imaging-based volumes of the BF and hippocampus in a population-based sample of 1967 participants between 21 and 90 years of age. The rs2765 SNP was significantly associated with the most anterior BF volume corresponding to the medial septum/diagonal band, and with a significantly steeper age-related volume decline. The rs2765 SNP was not associated with other BF subvolumes or hippocampus volumes. Apolipoprotein E ε4 showed no correlation with any brain volume or global cognition. Our findings in a large population-based sample suggest an association of an NK3 receptor SNP with age-related decline of rostral cholinergic BF volume.

Studying ventricular abnormalities in mild cognitive impairment with hyperbolic Ricci flow and tensor-based morphometry

Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process during an early symptomatic stage. Structural magnetic resonance imaging (MRI) measures have been the mainstay of Alzheimer's disease (AD) imaging research, however, ventricular morphometry analysis remains challenging because of its complicated topological structure. Here we describe a novel ventricular morphometry system based on the hyperbolic Ricci flow method and tensor-based morphometry (TBM) statistics. Unlike prior ventricular surface parameterization methods, hyperbolic conformal parameterization is angle-preserving and does not have any singularities. Our system generates a one-to-one diffeomorphic mapping between ventricular surfaces with consistent boundary matching conditions. The TBM statistics encode a great deal of surface deformation information that could be inaccessible or overlooked by other methods. We applied our system to the baseline MRI scans of a set of MCI subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI: 71 MCI converters vs. 62 MCI stable). Although the combined ventricular area and volume features did not differ between the two groups, our fine-grained surface analysis revealed significant differences in the ventricular regions close to the temporal lobe and posterior cingulate, structures that are affected early in AD. Significant correlations were also detected between ventricular morphometry, neuropsychological measures, and a previously described imaging index based on fluorodeoxyglucose positron emission tomography (FDG-PET) scans. This novel ventricular morphometry method may offer a new and more sensitive approach to study preclinical and early symptomatic stage AD.

More than cholesterol transporters: lipoprotein receptors in CNS function and neurodegeneration

Members of the low-density lipoprotein (LDL) receptor gene family have a diverse set of biological functions that transcend lipid metabolism. Lipoprotein receptors have broad effects in both the developing and adult brain and participate in synapse development, cargo trafficking, and signal transduction. In addition, several family members play key roles in Alzheimer's disease (AD) pathogenesis and neurodegeneration. This Review summarizes our current understanding of the role lipoprotein receptors play in CNS function and AD pathology, with a special emphasis on amyloid-independent roles in endocytosis and synaptic dysfunction.

African-American TOMM40'523-APOE haplotypes are admixture of West African and Caucasian alleles

BACKGROUND

Several studies have demonstrated a lower apolipoprotein E4 (APOE ε4) allele frequency in African-Americans, but yet an increased age-related prevalence of AD. An algorithm for prevention clinical trials incorporating TOMM40'523 (Translocase of Outer Mitochondria Membrane) and APOE depends on accurate TOMM40'523-APOE haplotypes.

METHODS

We have compared the APOE and TOMM40'523 phased haplotype frequencies of a 9.5 kb TOMM40/APOE genomic region in West African, Caucasian, and African-American cohorts.

RESULTS

African-American haplotype frequency scans of poly-T lengths connected in phase with either APOE ε4 or APOE ε3 differ from both West Africans and Caucasians and represent admixture of several distinct West African and Caucasian haplotypes. A new West African TOMM40'523 haplotype, with APOE ε4 connected to a short TOMM40'523 allele, is observed in African-Americans but not Caucasians.

CONCLUSION

These data have therapeutic implications for the age of onset risk algorithm estimates and the design of a prevention trial for African-Americans or other mixed ethnic populations.

Recognition memory is associated with altered resting-state functional connectivity in people at genetic risk for Alzheimer's disease

The apolipoprotein E ε4 (ApoE ε4) allele not only represents the strongest single genetic risk factor for sporadic Alzheimer's disease, but also imposes independent effects on brain function in healthy individuals where it has been shown to promote subtle memory deficits and altered intrinsic functional brain network connectivity. Based on previous work showing a potential relevance of the default mode network (DMN) functional connectivity for episodic memory function, we hypothesized that the ApoE ε4 genotype would affect memory performance via modulation of the DMN. We assessed 63 healthy individuals (50-80 years old), of which 20 carried the ε4 allele. All participants underwent resting-state functional magnetic resonance imaging (fMRI), high-resolution 3D anatomical MRI imaging and neuropsychological assessment. Functional connectivity analysis of resting-state activity was performed with a predefined seed region located in the left posterior cingulate cortex (PCC), a core region of the DMN. ApoE ε4 carriers performed significantly poorer than non-carriers in wordlist recognition and cued recall. Furthermore, ε4 carriers showed increased connectivity relative to ε4 non-carriers between the PCC seed region and left-hemispheric middle temporal gyrus (MTG). There was a positive correlation between recognition memory scores and resting-state connectivity in the left MTG in ε4 carriers. These results can be interpreted as compensatory mechanisms strengthening the cross-links between DMN core areas and cortical areas involved in memory processing.

APOE-epsilon4 and aging of medial temporal lobe gray matter in healthy adults older than 50 years

Atrophy of the hippocampus and surrounding temporal regions occurs in Alzheimer's disease (AD). APOE ε4, the major genetic risk factor for late-onset AD, has been associated with smaller volume in these regions before amyloidosis can be detected by AD biomarkers. To examine APOE ε4 effects in relation to aging, we performed a longitudinal magnetic resonance imaging study involving cognitively normal adults (25 APOE ε4 carriers and 31 ε3 homozygotes), initially aged 51-75 years. We used growth curve analyses, which can provide information about APOE ε4-related differences initially and later in life. Hippocampal volume was the primary outcome; nearby medial temporal regions were secondary outcomes. Brain-derived neurotrophic factor, val66met was a secondary covariate. APOE ε4 carriers had significantly smaller initial hippocampal volumes than ε3 homozygotes. Rate of hippocampal atrophy was not greater in the APOE ε4 group, although age-related atrophy was detected in the overall sample. The findings add to the growing evidence that effects of APOE ε4 on hippocampal size begin early in life, underscoring the importance of early interventions to increase reserve.

White matter microstructure in late middle-age: Effects of apolipoprotein E4 and parental family history of Alzheimer's disease

INTRODUCTION

Little is still known about the effects of risk factors for Alzheimer's disease (AD) on white matter microstructure in cognitively healthy adults. The purpose of this cross-sectional study was to assess the effect of two well-known risk factors for AD, parental family history and APOE4 genotype.

METHODS

This study included 343 participants from the Wisconsin Registry for Alzheimer's Prevention, who underwent diffusion tensor imaging (DTI). A region of interest analysis was performed on fractional anisotropy maps, in addition to mean, radial, and axial diffusivity maps, aligned to a common template space using a diffeomorphic, tensor-based registration method. The analysis focused on brain regions known to be affected in AD including the corpus callosum, superior longitudinal fasciculus, fornix, cingulum, and uncinate fasciculus. Analyses assessed the impact of APOE4, parental family history of AD, age, and sex on white matter microstructure in late middle-aged participants (aged 47-76 years).

RESULTS

Both APOE4 and parental family history were associated with microstructural white matter differences. Participants with parental family history of AD had higher FA in the genu of the corpus callosum and the superior longitudinal fasciculus. We observed an interaction between family history and APOE4, where participants who were family history positive but APOE4 negative had lower axial diffusivity in the uncinate fasciculus, and participants who were both family history positive and APOE4 positive had higher axial diffusivity in this region. We also observed an interaction between APOE4 and age, whereby older participants (=65 years of age) who were APOE4 carriers, had higher MD in the superior longitudinal fasciculus and in the portion of the cingulum bundle running adjacent to the cingulate cortex, compared to non-carriers. Older participants who were APOE4 carriers also showed higher radial diffusivity in the genu compared to non-carriers. Across all participants, age had an effect on FA, MD, and axial and radial diffusivities. Sex differences were observed in FA and radial diffusivity.

CONCLUSION

APOE4 genotype, parental family history of AD, age, and sex are all associated with microstructural white matter differences in late middle-aged adults. In participants at risk for AD, alterations in diffusion characteristics-both expected and unexpected-may represent cellular changes occurring at the earliest disease stages, but further work is needed. Higher mean, radial, and axial diffusivities were observed in participants who are more likely to be experiencing later stage preclinical pathology, including participants who were both older and carried APOE4, or who were positive for both APOE4 and parental family history of AD.

Neuroimaging biomarkers for Alzheimer's disease in asymptomatic APOE4 carriers

INTRODUCTION

The E4 allele of the apolipoprotein E (APOE4) is the major known genetic risk factor for Alzheimer's disease (AD), with a dramatic increase in the risk of developing AD as the number of APOE4 alleles increases from 0 to 2. For this reason, asymptomatic APOE4 carriers as a group offer a great opportunity to search for the presence of early biomarkers for AD. The present article reviews neuroimaging studies on APOE4 carriers, focusing on cognitively normal individuals and on the main neuroimaging biomarkers for AD, i.e. atrophy with structural MRI, hypometabolism with FDG-PET, and amyloid deposition with amyloid-PET imaging.

STATE OF THE ART

There are a great number of studies on the effect of APOE4 on brain structures, and they tend to show significant atrophy in APOE4 carriers compared to non-carriers especially in regions susceptible to AD pathology such as the hippocampus. However, results are rather discrepant which suggests that the effect of APOE4 on brain structure is subtle. As for FDG-PET metabolism, the few available studies show decreased metabolism, again especially in AD-sensitive regions such as posterior associative parietal areas, with a dose-dependent effect (i.e. worsening as the number of APOE4 alleles increases). Finally, there is a unanimous and major effect of APOE4 on amyloid deposition with an increase in Aβ load as the number of APOE4 alleles increases and a decrease in the age of predicted amyloid-positivity in APOE4 carriers. This graded effect of APOE4 on atrophy, hypometabolism, and amyloid deposition is consistent with multimodal neuroimaging studies suggestive of a predominant effect of APOE4 on amyloid rather than tau-related injury and on brain metabolism rather than brain structure. Neuroimaging studies also suggest that APOE4 effects may be mediated by both Aβ-dependent and Aβ-independent pathological processes. This contradicts the view that Aβ pathology is a necessary upstream event to neuronal injury in AD.

PERSPECTIVES AND CONCLUSION

Future studies should tell whether the mechanisms and sequences evidenced in carriers are comparable to those found in non-carriers, but it is likely that APOE4 not only influences the risk for AD, but also modulates the pathophysiological cascade. Altogether, APOE4 carriers offer a great opportunity to investigate brain changes in the asymptomatic stages of AD and to further our understanding of the pathophysiology of the disease, although precaution is needed for interpretation in AD at large.