Mini-Forum: Multivariate Approaches in Neuroimaging: Assessing the Connectome of Alzheimer's Disease (Guest Editors: Juan Manuel Górriz, Eugenio Iglesias-González, Javier Ramírez)
Pages 693-695
Introduction
Juan Manuel Górriz, Eugenio Iglesias-González, Javier Ramírez
Multivariate Approaches in Neuroimaging: Assessing the Connectome of Alzheimer’s Disease
Pages 697-711
Will Penny, Jorge Iglesias-Fuster, Yakeel T. Quiroz, Francisco Javier Lopera, Maria A. Bobes
Dynamic Causal Modeling of Preclinical Autosomal-Dominant Alzheimer’s Disease
Abstract: Dynamic causal modeling (DCM) is a framework for making inferences about changes in brain connectivity using neuroimaging data. We fitted DCMs to high-density EEG data from subjects performing a semantic picture matching task. The subjects are carriers of the PSEN1 mutation, which leads to early onset Alzheimer’s disease, but at the time of EEG acquisition in 1999, these subjects were cognitively unimpaired. We asked 1) what is the optimal model architecture for explaining the event-related potentials in this population, 2) which connections are different between this Presymptomatic Carrier (PreC) group and a Non-Carrier (NonC) group performing the same task, and 3) which network connections are predictive of subsequent Mini-Mental State Exam (MMSE) trajectories. We found 1) a model with hierarchical rather than lateral connections between hemispheres to be optimal, 2) that a pathway from right inferotemporal cortex (IT) to left medial temporal lobe (MTL) was preferentially activated by incongruent items for subjects in the PreC group but not the NonC group, and 3) that increased effective connectivity among left MTL, right IT, and right MTL was predictive of subsequent MMSE scores.
Pages 713-729
Francisco Jesus Martinez-Murcia, Juan Manuel Górriz, Javier Ramírez, Fermín Segovia, Diego Salas-Gonzalez, Diego Castillo-Barnes, Andrés Ortiz for the Alzheimer’s Disease Neuroimaging Initiative
Assessing Mild Cognitive Impairment Progression using a Spherical Brain Mapping of Magnetic Resonance Imaging
Abstract: Background: The early diagnosis of Alzheimer's Disease (AD), particularly in its prodromal stage, mild cognitive impairment (MCI), still remains a challenge. Many computational tools have been developed to successfully explore and predict the disease progression. In this context, the Spherical Brain Mapping (SBM) proved its ability in detecting differences between AD and aged subjects without symptoms of dementia. Being a very visual tool, its application in predicting MCI conversion to AD could be of great help to understand neurodegeneration and the disease progression. Objective: In this work, we aim at predicting the conversion of MCI affected subjects to AD more than 6 months in advance of their conversion session and understanding the progression of the disease by predicting neuropsychological test outcomes from MRI data. Methods: In order to do so, SBM is applied to a series of MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The resulting spherical brain maps show statistical and morphological information of the brain in a bidimensional plane, performing at the same time a significant feature reduction that provides a feature vector used in classification analysis. Results: The study achieves up to 92.3% accuracy in the AD versus normal controls (CTL) detection, and up to a 77.6% in detection a of MCI conversions when trained with AD and CTL subjects. The prediction of neuropsychological test outcomes achieved R2 rates up to more than 0.5. Significant regions according to t-test and correlation analysis match reported brain areas in the literature. Conclusion: The results prove that Spherical Brain Mapping offers good ability to predict conversion patterns and cognitive state, at the same time that provides an additional aid for visualizing a two-dimensional abstraction map of the brain.
Pages 731-746
Martin Dyrba, Michel J. Grothe, Abdolreza Mohammadi, Harald Binder, Thomas Kirste, Stefan J. Teipel, the Alzheimer’s Disease Neuroimaging Initiative
Comparison of Different Hypotheses Regarding the Spread of Alzheimer’s Disease Using Markov Random Fields and Multimodal Imaging
Abstract: Alzheimer’s disease (AD) is characterized by a cascade of pathological processes that can be assessed in vivo using different neuroimaging methods. Recent research suggests a systematic sequence of pathogenic events on a global biomarker level, but little is known about the associations and dependencies of distinct lesion patterns on a regional level. Markov random fields are a probabilistic graphical modeling approach that represent the interaction between individual random variables by an undirected graph. We propose the novel application of this approach to study the interregional associations and dependencies between multimodal imaging markers of AD pathology and to compare different hypotheses regarding the spread of the disease. We retrieved multimodal imaging data from 577 subjects enrolled in the Alzheimer’s Disease Neuroimaging Initiative. Mean amyloid load (AV45-PET), glucose metabolism (FDG-PET), and gray matter volume (MRI) were calculated for the six principle nodes of the default mode network—a functional network of brain regions that appears to be preferentially targeted by AD. Multimodal Markov random field models were developed for three different hypotheses regarding the spread of the disease: the “intraregional evolution model”, the “trans-neuronal spread” hypothesis, and the “wear-and-tear” hypothesis. The model likelihood to reflect the given data was evaluated using tenfold cross-validation with 1,000 repetitions. The most likely graph structure contained the posterior cingulate cortex as main hub region with edges to various other regions, in accordance with the “wear-and-tear” hypothesis of disease vulnerability. Probabilistic graphical models facilitate the analysis of interactions between several variables in a network model and therefore afford great potential to complement traditional multiple regression analyses in multimodal neuroimaging research.
Pages 747-764
Fon Powell, Duygu Tosun, Roksana Sadeghi, Michael Weiner, Ashish Raj for the Alzheimer’s Disease Neuroimaging Initiative
Preserved Structural Network Organization Mediates Pathology Spread in Alzheimer’s Disease Spectrum Despite Loss of White Matter Tract Integrity
Abstract: Models of Alzheimer’s disease (AD) hypothesize stereotyped progression via white matter (WM) fiber connections, most likely via trans-synaptic transmission of toxic proteins along neuronal pathways. An important question in the field is whether and how organization of fiber pathways is affected by disease. It remains unknown whether fibers act as conduits of degenerative pathologies, or if they also degenerate with the gray matter network. This work uses graph theoretic modeling in a longitudinal design to investigate the impact of WM network organization on AD pathology spread. We hypothesize if altered WM network organization mediates disease progression, then a previously published network diffusion model will yield higher prediction accuracy using subject-specific connectomes in place of a healthy template connectome. Neuroimaging data in 124 subjects from ADNI were assessed. Graph topology metrics show preserved network organization in patients compared to controls. Using a published diffusion model, we further probe the effect of network alterations on degeneration spread in AD. We show that choice of connectome does not significantly impact the model’s predictive ability. These results suggest that, despite measurable changes in integrity of specific fiber tracts, WM network organization in AD is preserved. Further, there is no difference in the mediation of putative pathology spread between healthy and AD-impaired networks. This conclusion is somewhat at variance with previous results, which report global topological disturbances in AD. Our data indicates the combined effect of edge thresholding, binarization, and inclusion of subcortical regions to network graphs may be responsible for previously reported effects.
Pages 765-779
Fermín Segovia, Manuel Gómez-Río, Raquel Sánchez-Vañó, Juan Manuel Górriz, Javier Ramírez, Eva Triviño-Ibáñez, Cristóbal Carnero Pardo, María Dolores Martínez Lozano, Pablo Sopena-Novales
Usefulness of Dual-Point Amyloid PET Scans in Appropriate Use Criteria: A Multicenter Study
Abstract: Background: Biomarkers of neurodegeneration play a major role in the diagnosis of Alzheimer’s disease (AD). Information on both amyloid-β accumulation, e.g., from amyloid positron emission tomography (PET), and downstream neuronal injury, e.g., from 18F-fluorodeoxyglucose (FDG) PET, would ideally be obtained in a single procedure. Objective: On the basis that the parallelism between brain perfusion and glucose metabolism is well documented, the objective of this work is to evaluate whether brain perfusion estimated in a dual-point protocol of 18F-florbetaben (FBB) PET can be a surrogate of FDG PET in appropriate use criteria (AUC) for amyloid PET. Methods: This study included 47 patients fulfilling international AUC for amyloid PET. FDG PET, early FBB (pFBB) PET (0-10 min post injection), and standard FBB (sFBB) PET (90-110 min post injection) scans were acquired. Results of clinical subjective reports and of quantitative region of interest (ROI)-based analyses were compared between procedures using statistical techniques such as Pearson's correlation coefficients and t-tests. Results: pFBB and FDG visual reports on the 47 patients showed good agreement (κ> 0.74); ROI quantitative analysis indicated that both data modalities are highly correlated; and the t-test analysis does not reject the null hypothesis that data from pFBB and FDG examinations comes from independent random samples from normal distributions with equal means and variances. Conclusions: A good agreement was found between pFBB and FDG data as obtained by subjective visual and quantitative analyses. Dual-point FBB PET scans could offer complementary information (similar to that from FDG PET and FBB PET) in a single procedure, considering pFBB as a surrogate of FDG.
Pages 781-791
Janusch Blautzik*, Sebastian Kotz*, Matthias Brendel, Julia Sauerbeck, Franziska Vettermann, Yaroslav Winter, Peter Bartenstein, Kazunari Ishii, Axel Rominger, for the Alzheimer’s Disease Neuroimaging Initiative *These authors contributed equally to this work.
Relationship Between Body Mass Index, ApoE4 Status, and PET-Based Amyloid and Neurodegeneration Markers in Amyloid-Positive Subjects with Normal Cognition or Mild Cognitive Impairment
Abstract: Body weight loss in late-life is known to occur at a very early stage of Alzheimer’s disease (AD). Apolipoprotein E4 (ApoE4) represents a major genetic risk factor for AD and is linked to an increased cortical amyloid-β (Aβ) accumulation. Since the relationship between body weight, ApoE4, and AD pathology is poorly investigated, we aimed to evaluate whether ApoE4 allelic status modifies the association of body mass index (BMI) with markers of AD pathology. A total of 368 Aβ-positive cognitively healthy or mild cognitive impaired subjects had undergone [18F]-AV45-PET, [18F]-FDG-PET, and T1w-MRI examinations. Composite cortical [18F]-AV45 uptake and [18F]-FDG uptake in posterior cingulate cortex were calculated as surrogates of cortical Aβ load and glucose metabolism, respectively. Multiple linear regressions were performed to assess the relationships between these PET biomarkers with BMI, present cognitive performance, and cognitive changes over time. Multivariate analysis of covariance was conducted to test for statistical differences between ApoE4/BMI categories on the PET markers and cognitive scores. In carriers of the ApoE4 allele only, BMI was inversely associated with cortical amlyoid load (β=-0.193, p<0.005) and recent cognitive decline (β=-0.209, p<0.05), and positively associated with cortical glucose metabolism in an AD-vulnerable region (β=0.145, p<0.05). ApoE4/BMI category analyses demonstrated lower Aβ load, higher posterior cingulate glucose metabolism, improved cognitive performance, and lower progression of cognitive decline in obese ApoE4 carriers. The effect of ApoE4 in promoting the accumulation of cortical amyoid, which may itself be a driver for weight loss, may be moderated by altering leptin signaling in the hypothalamus.
Pages 793-806
Matthias Brendel*, Julia Sauerbeck*, Sonja Greven, Sebastian Kotz, Franziska Scheiwein, Janusch Blautzik, Andreas Delker, Oliver Pogarell, Kazunari Ishii, Peter Bartenstein, Axel Rominger, for the Alzheimer’s Disease Neuroimaging Initiative *These authors contributed equally to this work.
Serotonin Selective Reuptake Inhibitor Treatment Improves Cognition and Grey Matter Atrophy but not Amyloid Burden During Two-Year Follow-Up in Mild Cognitive Impairment and Alzheimer’s Disease Patients with Depressive Symptoms
Abstract: Late-life depression, even when of subsyndromal severity, has shown strong associations with mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Preclinical studies have suggested that serotonin selective reuptake inhibitors (SSRIs) can attenuate amyloidogenesis. Therefore, we aimed to investigate the effect of SSRI medication on amyloidosis and grey matter volume in subsyndromal depressed subjects with MCI and AD during an interval of two years. 256 cognitively affected subjects (225 MCI/ 31 AD) undergoing [18F]-AV45-PET and MRI at baseline and 2-year follow-up were selected from the ADNI database. Subjects with a positive depression item (DEP(+); n=73) in the Neuropsychiatric Inventory Questionnaire were subdivided to those receiving SSRI medication (SSRI(+); n=24) and those without SSRI treatment (SSRI(-); n=49). Longitudinal cognition (∆-ADAS), amyloid deposition rate (standardized uptake value, using white matter as reference region (SUVRWM), and changes in grey matter volume were compared using common covariates. Analyses were performed separately in all subjects and in the subgroup of amyloid-positive subjects. Cognitive performance in DEP(+)/SSRI(+) subjects (∆-ADAS: -5.0%) showed less deterioration with 2-year follow-up when compared to DEP(+)/SSRI(-) subjects (∆-ADAS: +18.6%, p<0.05), independent of amyloid SUVRWM at baseline. With SSRI treatment, the progression of grey matter atrophy was reduced (-0.9% versus -2.7%, p<0.05), notably in fronto-temporal cortex. A slight trend towards lower amyloid deposition rate was observed in DEP(+)/SSRI(+) subjects versus DEP(+)/SSRI(-). Despite the lack of effect to amyloid PET, SSRI medication distinctly rescued the declining cognitive performance in cognitively affected patients with depressive symptoms, and likewise attenuated grey matter atrophy.
Pages 807-817
Kichang Kwak, Hyuk Jin Yun, Gilsoon Park, Jong-Min Lee, for the Alzheimer’s Disease Neuroimaging Initiative
Multi-Modality Sparse Representation for Alzheimer’s Disease Classification
Abstract: Background: Alzheimer’s disease (AD) and mild cognitive impairment (MCI) are age-related neurodegenerative diseases characterized by progressive loss of memory and irreversible cognitive functions. The hippocampus, a brain area critical for learning and memory processes, is especially susceptible to damage at early stages of AD. Objective: We aimed to develop prediction model using a multi-modality sparse representation approach. Methods: We proposed a sparse representation approach to the hippocampus using structural T1-weighted magnetic resonance imaging (MRI) and 18-fluorodeoxyglucose-positron emission tomography (FDG-PET) to distinguish AD/MCI from healthy control subjects (HCs). We considered structural and function information for the hippocampus and applied a sparse patch-based approach to effectively reduce the dimensions of neuroimaging biomarkers. Results: In experiments using Alzheimer’s Disease Neuroimaging Initiative data, our proposed method demonstrated more reliable than previous classification studies. The effects of different parameters on segmentation accuracy were also evaluated. The mean classification accuracy obtained with our proposed method was 0.94 for AD/HCs, 0.82 for MCI/HCs, and 0.86 for AD/MCI. Conclusion: We extracted multi-modal features from automatically defined hippocampal regions of training subjects and found this method to be discriminative and robust for AD and MCI classification. The extraction of features in T1 and FDG-PET images is expected to improve classification performance due to the relationship between brain structure and function.
Pages 819-842
Elena Ruiz, Javier Ramirez, Juan Manuel Gorriz, Jorge Casillas for the Alzheimer’s Disease Neuroimaging Initiative
Alzheimer’s Disease Computer-Aided Diagnosis: Histogram-Based Analysis of Regional MRI Volumes for Feature Selection and Classification
Abstract: This paper proposes a novel fully automatic computer-aided diagnosis (CAD) system for the early detection of Alzheimer’s disease (AD) based on supervised machine learning methods. The novelty of the approach, which is based on histogram analysis, is twofold: 1) a feature extraction process that aims to detect differences in brain regions of interest (ROIs) relevant for the recognition of subjects with AD and 2) an original greedy algorithm that predicts the severity of the effects of AD on these regions. This algorithm takes account of the progressive nature of AD that affects the brain structure with different levels of severity, i.e., the loss of gray matter in AD is found first in memory-related areas of the brain such as the hippocampus. Moreover, the proposed feature extraction process generates a reduced set of attributes which allows the use of general-purpose classification machine learning algorithms. In particular, the proposed feature extraction approach assesses the ROI image separability between classes in order to identify the ones with greater discriminant power. These regions will have the highest influence in the classification decision at the final stage. Several experiments were carried out on segmented magnetic resonance images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) in order to show the benefits of the overall method. The proposed CAD system achieved competitive classification results in a highly efficient and straightforward way.
Pages 843-854
Carlos Gómez, Celia Juan-Cruz, Jesús Poza, Saúl J. Ruiz-Gómez, Javier Gomez-Pilar, Pablo Núñez, María García, Alberto Fernández, Roberto Hornero
Alterations of Effective Connectivity Patterns in Mild Cognitive Impairment: An MEG Study
Abstract: Neuroimaging techniques have demonstrated over the years their ability to characterize the brain abnormalities associated with different neurodegenerative diseases. Among all these techniques, magnetoencephalography (MEG) stands out by its high temporal resolution and noninvasiveness. The aim of the present study is to explore the coupling patterns of resting-state MEG activity in subjects with mild cognitive impairment (MCI). To achieve this goal, five minutes of spontaneous MEG activity were acquired with a 148-channel whole-head magnetometer from 18 MCI patients and 26 healthy controls. Inter-channel relationships were investigated by means of two complementary coupling measures: coherence and Granger causality. Coherence is a classical method of functional connectivity, while Granger causality quantifies effective (or causal) connectivity. Both measures were calculated in the five conventional frequency bands: delta (&delta:, 1-4 Hz), theta (θ, 4-8 Hz), alpha (α, 8-13 Hz), beta (β, 13-30 Hz), and gamma (γ, 30-45Hz). Our results showed that connectivity values were lower for MCI patients than for controls in all frequency bands. However, only Granger causality revealed statistically significant differences between groups (p-values < 0.05, FDR corrected Mann-Whitney U-test), mainly in the beta band. Our results support the role of MCI as a disconnection syndrome, which elicits early alterations in effective connectivity patterns. These findings can be helpful to identify the neural substrates involved in prodromal stages of dementia.
Pages 855-869
Yudong Zhang, Shuihua Wang, Yuxiu Sui,, Ming Yang, Bin Liu, Hong Cheng, Junding Sun, Wenjuan Jia, Preetha Phillips, Juan Manuel Gorriz
Multivariate Approach for Alzheimer’s Disease Detection Using Stationary Wavelet Entropy and Predator-Prey Particle Swarm Optimization
Abstract: Background: The number of patients with Alzheimer’s disease is increasing rapidly every year. Scholars often use computer vision and machine learning methods to develop an automatic diagnosis system. Objective: In this study, we developed a novel machine learning system that can make diagnoses automatically from brain magnetic resonance images. Methods: First, the brain imaging was processed, including skull stripping and spatial normalization. Second, one axial slice was selected from the volumetric image, and stationary wavelet entropy (SWE) was done to extract the texture features. Third, a single-hidden-layer neural network was used as the classifier. Finally, a predator-prey particle swarm optimization was proposed to train the weights and biases of the classifier. Results: Our method used 4-level decomposition and yielded 13 SWE features. The classification yielded an overall accuracy of 92.73±1.03%, a sensitivity of 92.69±1.29%, and a specificity of 92.78±1.51%. The area under the curve is 0.95±0.02. Additionally, this method only cost 0.88 s to identify a subject in online stage, after its volumetric image is preprocessed. Conclusion: In terms of classification performance, our method performs better than 10 state-of-the-art approaches and the performance of human observers. Therefore, this proposed method is effective in the detection of Alzheimer’s disease.
Regular Section
Pages 871-876
Short Communication
Meng-Shan Tan, Ping Wang, Fang-Chen Ma, Jie-Qiong Li, Chen-Chen Tan, Jin-Tai Yu, Lan Tan, Alzheimer’s Disease Neuroimaging Initiative (Handling Associate Editor: Ling-Qiang Zhu)
Common Variant in PLD3 Influencing Cerebrospinal Fluid Total Tau Levels and Hippocampal Volumes in Mild Cognitive Impairment Patients from the ADNI Cohort
Abstract: Recent studies found the variants in Alzheimer’s disease (AD) risk gene PLD3 were associated with cognitive function, but its detailed mechanism before typical AD onset was unknown. Our current study examined the impact of PLD3 common variant rs11667768 on cerebrospinal fluid (CSF) total-tau and phosphorylated-tau levels and structural MRI from the ADNI database. We found rs11667768 was significantly associated with CSF total-tau levels and hippocampal volumes at baseline and six-year follow-up in the total non-demented elderly group and the mild cognitive impairment subgroup, indicating a potential role of PLD3 common variants in influencing cognitive function through changing CSF total-tau levels and hippocampal volumes.
Pages 877-884
Ophir Keret, Tzippy Shochat, Israel Steiner, Amir Glik
Non-Ashkenazi Jewish Origin is Associated with Early Onset Alzheimer's Disease
Abstract: Early-onset Alzheimer's disease (EOAD) accounts for 1-5% of Alzheimer’s disease cases and is associated with specific ethnicities. It has been our impression that non-Ashkenazi Jews have a higher rate of EOAD and we therefore explored this hypothesis. We performed a retrospective case control study of EOAD cases referred to our cognitive neurology clinic between January 1999 and December 2016. Patients (n=129) were compared to age- and geographically-matched controls generated from the Second Israeli National Health Survey (n=1,811). Data on country of origin, education, dementia family history, depression, and vascular risk factors were compared between the groups. The association of non-Ashkenazi Jewish heritage and country of origin with EOAD was calculated using a logistic multivariate regression model. The EOAD group’s mean age was 59.6±4.1 years, with a female predominance (64.3%). The EOAD group had a higher percentage of individuals of non-Ashkenazi Jewish origin (64.3% versus 51.4%, p=0.003) and of Yemenite descent in particular (16.28% versus 6.24%, p <0.001). On multiple logistic regression analysis, Yemenite Jewish origin was an independently associated with EOAD (OR 2.54, 95% CI 1.4-4.8). There were no significant differences in parameters between non-Ashkenazi and Ashkenazi Jews. Only 4.6% of EOAD cases had a positive EOAD family history. In conclusion, EOAD is over-represented among non-Ashkenazi Jews. Yemenite origin is independently associated with EOAD and the majority of patients with EOAD have no family history of Alzheimer’s disease. Further evaluation with genetic studies is warranted.
Pages 885-896
Karen Ritchie*, Isabelle Carrière*, David Howett, Li Su, Michael Hornberger, John T. O’Brien, Craig W. Ritchie, Dennis Chan *These authors contributed equally to this work.
Allocentric and Egocentric Spatial Processing in Middle-Aged Adults at High Risk of Late-Onset Alzheimer’s Disease: The PREVENT Dementia Study
Abstract: Impairments in spatial processing due to hippocampal degeneration have been observed in the years immediately preceding the diagnosis of Alzheimer’s disease (AD) dementia. The demonstration of changes in spatial processing in preceding decades would provide a cognitive marker for pre-clinical AD and an outcome measure for early intervention trials. The present study examined allocentric and egocentric spatial processing in relation to future dementia risk in a middle-aged cohort. The CAIDE Dementia Risk Score (DRS) was calculated for 188 persons aged 40 to 59, of whom 94 had a parent with dementia. Participants underwent the Four Mountains Test (4MT) of allocentric spatial processing, the Virtual Reality Supermarket Trolley Task (VRSTT) of egocentric spatial processing, and 3T MRI scans. A significant negative association was found between the DRS and 4MT (Spearman correlation -0.26, p=0.0006), but not with the VRSTT. The 4MT was also found to be a better predictor of risk than tests of episodic memory, verbal fluency, or executive functioning. The results suggest that allocentric rather than egocentric processing may be a potential indicator of risk for late-onset AD, consistent with the hypothesis that the earliest cognitive changes in AD are driven by tau-related degeneration in the medial temporal lobe rather than amyloid-only deposition in the medial parietal lobe.
Pages 897-915
Roberta Lizio*, Claudio Babiloni*, Claudio Del Percio, Antonia Losurdo, Lucia Vernò, Marina De Tommaso, Anna Montemurno, Giuseppe Dalfino, Pietro Cirillo, Andrea Soricelli, Raffaele Ferri, Giuseppe Noce, Maria Teresa Pascarelli, Valentina Catania, Flavio Nobili, Francesco Famà, Francesco Orzi, Franco Giubilei, Carla Buttinelli, A. Ivano Triggiani, Giovanni B. Frisoni, Anna Maria Scisci, Nicola Mastrofilippo, Deni Aldo Procaccini, Loreto Gesualdo *These authors contributed equally to this work.
Different Abnormalities of Cortical Neural Synchronization Mechanisms in Patients with Mild Cognitive Impairment due to Alzheimer’s and Chronic Kidney Diseases: An EEG Study
Abstract: This study tested whether resting state alpha rhythms (8-13 Hz) may characterize mild cognitive impairment due to Alzheimer’s disease (ADMCI) compared with MCI due to chronic kidney disease (CKDMCI). Clinical and resting state eyes-closed electroencephalographic (rsEEG) rhythms from 40 ADMCI, 29 CKDMCI, and 45 cognitively normal elderly (Nold) subjects were available in a national archive. Age, gender, and education were matched in the three groups, and Mini-Mental State Evaluation (MMSE) score was paired in the ADMCI and CKDMCI groups. Delta (<4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz) cortical sources were estimated by eLORETA freeware and classified across individuals by area under the receiver operating characteristic curve (AUROCC). Compared with Nold group, posterior alpha 1 source activities were more reduced in ADMCI than CKDMCI group. In contrast, widespread delta source activities were greater in CKDMCI than ADMCI group. These source activities correlated with the MMSE score and correctly classified between Nold and all MCI individuals (AUROCC=0.8-0.85) and between ADMCI and CKDMCI subjects (AUROCC=0.75). These results suggest that early AD affects cortical neural synchronization at alpha frequencies underpinning brain arousal and low vigilance in the quiet wakefulness. In contrast, CKD may principally affect cortical neural synchronization at the delta frequencies. Future prospective cross-validation studies will have to test these candidate rsEEG markers for clinical applications and drug discovery.
Pages 917-930
Eelco van Duinkerken, Juliana Farme, Jesus Landeira-Fernandez, Marcia C. Dourado, Jerson Laks, Daniel C. Mograbi
Medical and Research Consent Decision-Making Capacity in Patients with Alzheimer’s Disease: A Systematic Review
Abstract: The capacity to make decisions is an important feature of daily living, which is closely linked to proper cognitive functioning. In conditions in which cognitive functioning becomes compromised, such as in Alzheimer’s disease (AD), decision-making capacity can also get affected. Especially in AD, this has important implications, since over the course of the condition many important clinical decisions have to be made. For caregivers as well as physicians, it is sometimes difficult to determine how and when to intervene in the decision-making process. The aim of this systematic literature review was to identify studies that have evaluated medical and research consent decision-making capacity in patients with AD. Studies consistently show that decision-making capabilities are impaired in patients with AD. The cognitive and neuronal correlates of this process are, however, poorly studied. The few studies that investigated correlations have shown worse cognitive performance, mainly on the MMSE, to be related to poorer decision-making capacity. As most of these correlations have been performed in groups combining patients and controls, it remains unknown if these associations are disease specific. There is a need to study more systematically the decision-making process in relation to cognitive functioning and neural correlates to be able to develop a framework of decision-making capacity in AD, ultimately aiding clinicians and caregivers to understand and evaluate those capabilities in patients.
Pages 931-949
Sharon S. Simon, Erich S. Tusch, Nicole C. Feng, Krister Håkansson, Abdul Mohammed, Kirk R. Daffner (Handling Associate Editor: Sharon Naismith)
Is Computerized Working Memory Training Effective in Healthy Older Adults? Evidence from a Multi-Site, Randomized Controlled Trial
Abstract: Background: Developing effective interventions to attenuate age-related cognitive decline and prevent or delay the onset of dementia are major public health goals. Computerized cognitive training (CCT) has been marketed increasingly to older adults, but its efficacy remains unclear. Working memory (WM), a key determinant of higher order cognitive abilities, is susceptible to age-related decline and a relevant target for CCT in elders. Objective: To evaluate the efficacy of CCT focused on WM compared to an active control condition in healthy older adults. Methods: Eighty-two cognitively normal adults from two sites (USA and Sweden) were randomly assigned to Cogmed Adaptive or Non-Adaptive (active control) CCT groups. Training was performed in participants’ homes, five days per week over five weeks. Changes in the performance of the Cogmed trained tasks, and in five neuropsychological tests (Trail Making Test Part A and Part B, Digit Symbol, Controlled Oral Word Association Test and Semantic Fluency) were used as outcome measures. Results: The groups were comparable at baseline. The Adaptive group showed robust gains in the trained tasks, and there was a time-by-group interaction for the Digit Symbol test, with significant improvement only after Adaptive training. In addition, the magnitude of the intervention effect was similar at both sites. Conclusion: Home-based CCT Adaptive WM training appears more effective than Non-Adaptive training in older adults from different cultural backgrounds. We present evidence of improvement in trained tasks and on a demanding untrained task dependent upon WM and processing speed. The benefits over the active control group suggest that the Adaptive CCT gains were linked to providing a continuously challenging level of WM difficulty.
Pages 951-961
Ling Gao*, Yu Jiang*, Shan Wei, Suhang Shang, Pei Li, Chen Chen, Liangjun Dang, Jin Wang, Kang Huo, Meiying Deng, Jingyi Wang, Rong Zhang, Qiumin Qu *These authors contributed equally to this work.
The Level of Plasma Amyloid-β40 Is Correlated with Peripheral Transport Proteins in Cognitively Normal Adults: A Population-Based Cross-Sectional Study
Abstract: Background: Transport proteins, soluble low-density lipoprotein receptor-related protein-1 (sLRP1), and soluble receptor of advanced glycation end products (sRAGE), play an important role in the clearance of plasma amyloid-β (Aβ). However, their relationship is not clear. Objective: The aim was to explore the relationship between plasma levels of sLRP1, sRAGE, and Aβ in a cross-sectional study. Methods: A total of 1,185 cognitively normal participants (age above 40) from a village in the suburbs of Xi’an, China were enrolled from October 8, 2014 to March 30, 2015. Plasma Aβ40, Aβ42, sLRP1, and sRAGE were tested using a commercial ELISA. Apolipoprotein E (APOE) genotyping was conducted using PCR and sequencing. The relationship between plasma levels of sLRP1, sRAGE, and Aβ was analyzed using Pearson’s correlation analysis and multiple linear regression. Results: In the total population, Log sLRP1 and Log sRAGE were positively correlated with plasma Aβ40 (r=0.103, p<0.001; r=0.064, p=0.027, respectively), but neither were associated with plasma Aβ42. After multivariable adjustment in the regression model, Log sLRP1 and Log sRAGE were still positively related with plasma Aβ40 (β=2.969, p<0.001; β=1.936, p=0.017, respectively) but not Aβ42. Furthermore, the positive correlations between transport proteins and plasma Aβ40 remained significant only in APOE ε4 non-carriers after Pearson’s analysis and multiple regression analysis after stratification by gene status. Conclusion: The concentrations of plasma sLRP1 and sRAGE had a significant impact on the level of plasma Aβ40 in cognitively normal adults, especially in APOE ε4 non-carriers. However, the mechanism by which the transport proteins are involved in peripheral Aβ clearance and the relationship between transporters and amyloid burden in the brain needs further validation.
Pages 963-976
Ivan Zaletel, Marija Schwirtlich, Milka Perović, Mirna Jovanović, Milena Stevanović, Selma Kanazir, Nela Puškaš (Handling Associate Editor: Fiorella Casamenti)
Early Impairments of Hippocampal Neurogenesis in 5xFAD Mouse Model of Alzheimer’s Disease Are Associated with Altered Expression of SOXB Transcription Factors
Abstract: Dysregulation of neurogenesis in the subgranular zone (SGZ) of the hippocampal dentate gyrus has been related to cognitive deficits and memory loss in neurodegenerative diseases, such as Alzheimer’s disease (AD). Members of the B group of SOX transcription factors play critical roles in regulating neurogenesis in the embryonic and adult nervous system, including maintaining the multipotency, renewal, and cell fate decision of neural stem/progenitor cells. The aim of the present study was to evaluate the expression patterns of selected SOXB proteins in the SGZ, of 8-week-old male and female 5xFAD mice, which represent a transgenic model of AD with a severe and very early development of amyloid pathology. Immunohistochemical analysis showed a significant decrease in the number of cells expressing SOX1, SOX2, and SOX21 transcription factors within the SGZ of 5xFAD mice in comparison to their non-transgenic counterparts which coincidences with reduced number of doublecortin immunoreactive immature neurons found in Tg males. Despite observed changes in expressional pattern of examined SOXB proteins, the proliferative capacity evaluated by the number of Ki-67 immunoreactive cells remained unaffected in transgenic mice of both genders. Based on our results, we suggest that SOXB proteins might be considered as new biomarkers for the detection of early impairments in adult neurogenesis in different animal models or/and new targets in human regenerative medicine.
Pages 977-988
Jenalle E. Baker, Yen Ying Lim*, Judith Jaeger, David Ames, Nicola T. Lautenschlager, Joanne Robertson, Robert H. Pietrzak, Peter J. Snyder, Victor L. Villemagne, Christopher C. Rowe, Colin L. Masters, Paul Maruff* (Handling Associate Editor: Alden Gross) *Co-senior authors
Episodic Memory and Learning Dysfunction over an 18-Month Period in Preclinical and Prodromal Alzheimer’s Disease
Abstract: Recent meta-analyses suggest that episodic memory impairment associated with preclinical Alzheimer’s disease (AD) equates to 0.15-0.24 standard deviations below that of cognitively healthy older adults. The current study aimed to characterize impairments in verbal acquisition and recall detectable at a single assessment, and investigate how verbal learning and episodic memory deteriorates in preclinical AD. A verbal list-learning task, the International Shopping List Test (ISLT), was administered multiple times over an 18-month period, to three groups of participants: amyloid-beta negative healthy older adults (Aβ- CN; n = 50); Aβ+ positive healthy older adults (preclinical AD; n = 25); and Aβ+ positive individuals diagnosed with mild cognitive impairment (prodromal AD; n = 22). At baseline, there was no significant difference between the preclinical AD and control groups rate of acquisition, or total and delayed recall, however all indices were impaired in prodromal AD. Performance on ISLT total score improved in the control group over the 18-month period, but showed a moderate magnitude decline in the preclinical AD group (Cohen’s d = -0.63, [-1.12, -0.14]) and the prodromal AD group (Cohen’s d = -0.36, [-0.94, 0.22]). No significant impairment in acquisition associated with preclinical AD was seen at baseline. Individuals with preclinical AD showed a significantly different performance on the ISLT total score over an 18-month period, compared to those without abnormal Aβ. Individuals with prodromal AD showed substantial impairment on the ISLT at baseline and declined to a greater extent over time.
Pages 989-1000
Madia Lozupone, Francesco Panza, Marco Piccininni, Massimiliano Copetti, Rodolfo Sardone, Bruno P. Imbimbo, Eleonora Stella, Francesca D’Urso, Maria Rosaria Barulli, Petronilla Battista, Alessandra Grasso, Rosanna Tortelli, Rosa Capozzo, Francesco Coppola, Daniela Isabel Abbrescia, Antonello Bellomo, Gianluigi Giannelli, Nicola Quaranta, Davide Seripa, Giancarlo Logroscino (Handling Associate Editor: Patrick Kehoe)
Social Dysfunction in Older Age and Relationships with Cognition, Depression, and Apathy: The GreatAGE Study
Abstract: Background: Most studies focused on only one measure of social dysfunction in older age, without proper validation and distinction across different dimensions including subjectivity, structural, and functional aspects. Objective: We sought to validate the Social Dysfunction Rating Scale (SDRS) and its factorial structure, also determining the association of SDRS with cognitive functions, global psychopathology, and social deprivation. Methods: The SDRS was administered to 484 Italian community-dwelling elderly, recruited in the GreatAGE study, a population-based study on aging conducted in Castellana Grotte, Bari, Southern Italy. We determined objective and subjective psychometric properties of SDRS against the gold standard evaluation of social dysfunction according to the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders (SCID-I) criterion. Results: The SDRS showed a moderate accuracy with an optimal cut-off of 26 maximized with higher sensitivity (0.74,95% CI:0.63-0.84) than specificity (0.57,95% CI:0.50-0.64). A five-factor structure was carried out and five dimensions of SDRS were identified (loneliness; social isolation; feeling of contribution/uselessness; lack of leisure activities; anxiety for the health). Education and global cognitive functions were inversely correlated to SDRS, while a direct association with global psychopathology, depression, and apathy was found. The prevalence of higher SDRS scores was major in subjects with current psychiatric disorders versus other subjects. Conclusion: The SDRS could be a valid instrument to capture both size and quality of social dysfunction, both in subjects with psychiatric disorders and in normal subjects. Several categories of social dysfunction differed only in the degree of health deprivation, not in social or material deprivation.
Pages 1001-1010
Minghao Sun*, Yinghui Zhao*, Men Han*, Baozhu Zhang, Xiao Zhang, Qichao Zhang, Nastasia K-H Lim, Wen-An Wang, Fu-De Huang *These authors contributed equally to this work.
TTC7 and Hyccin Regulate Neuronal Aβ42 Accumulation and its Associated Neural Deficits in Aβ42-Expressing Drosophila
Abstract: Neuronal amyloid-β (Aβ) accumulation plays an important role in the pathogenesis of Alzheimer's disease (AD). The conformation and toxicity of Aβ are regulated by lipids on the plasma membrane. Previously, we found downregulation of Rolling Blackout (RBO) or phosphatidylinositol-4-kinase type IIIα (PI4KIIIα) reduces neuronal Aβ accumulation and associated neural deficits in a Drosophila model expressing Aβ42. In mammals, the homologs of RBO and PI4KIIIα were reported to form a plasma membrane-localized complex with a scaffold protein TTC7 and cytosolic protein Hyccin/FAM126A to tightly control the plasmalemmal level of phosphatidylinositol-4-phosphate. Here, we show genetic downregulation of Drosophila TTC7 and Hyccin also reduces neuronal Aβ accumulation and associated synaptic and motor defects as well as premature death in Aβ42-expressing flies, while overexpression of TTC7 and Hyccin produced the opposite effect. These results, together with our previous study, demonstrate that RBO/TTC7/PI4KIIIα/Hyccin regulate neuronal Aβ accumulation and associated neural deficits in the Drosophila model, further supporting the RBO/Efr3-PI4KIIIα complex as a potential therapeutic target for AD.
Pages 1011-1027
Annalise M. Rahman-Filipiak, Bruno Giordani, Judith Heidebrink, Arijit Bhaumik, Benjamin M. Hampstead (Handling Associate Editor: Duke Han)
Self- and Informant-Reported Memory Complaints: Frequency and Severity in Cognitively Intact Individuals and those with Mild Cognitive Impairment and Neurodegenerative Dementias
Abstract: Background: Subjective memory complaints (SMCs) are incorporated into the diagnosis of mild cognitive impairment (MCI) and neurodegenerative dementias; however, the relative frequency of SMCs in cognitively intact older adults and those with different types of dementia is poorly understood. Similarly, the concordance between self- versus informant-reported SMCs has not been compared across different diagnostic groups. Objective: This study aimed to evaluate the frequency of self-reported (Objective 1) and informant-reported (Objective 2) SMCs in cognitively intact adults or those diagnosed with MCI or a neurodegenerative dementia. Agreement between participant and informant complaints was also evaluated (Objective 3). Methods: Baseline evaluation data were drawn from 488 participants (Mage = 70.49 years; Medu = 15.62 years) diagnosed as cognitively intact, non-amnestic MCI, amnestic single domain MCI, amnestic multi-domain MCI, possible/probable Alzheimer’s disease, dementia with Lewy bodies, or frontotemporal dementia. Participants and their informants completed the Memory Assessment Clinic Questionnaire. Results: One-way ANCOVAs controlling for age, education, and depression revealed no group differences in severity of self-reported SMCs. In contrast, informant memory ratings followed the expected clinical pattern, with comparable and most impaired ratings given to participants with any dementia diagnosis, followed by those with any MCI diagnosis, followed by cognitively intact participants. There was inconsistent agreement between self- and informant-reported SMC ratings in any of the impaired groups. Conclusions: Given greater diagnostic specificity and internal consistency of informant report, clinicians should weigh this information more heavily than self-report in the diagnostic process.
Pages 1029-1039
Nienke M.E. Scheltens, Betty M. Tijms, Martijn W. Heymans, Gil D. Rabinovici, Brendan I. Cohn-Sheehy, Bruce L. Miller, Joel H. Kramer, Steffen Wolfsgruber, Michael Wagner, Johannes Kornhuber, Oliver Peters, Philip Scheltens, Wiesje M. van der Flier; Amsterdam Dementia Cohort, Alzheimer’s Disease Neuroimaging Initiative, German Dementia Competence Network, University of San Francisco Memory and Aging Center
Prominent Non-Memory Deficits in Alzheimer’s Disease Are Associated with Faster Disease Progression
Abstract: Background: Alzheimer’s disease (AD) is a heterogeneous disorder. Objective: To investigate whether cognitive AD subtypes are associated with different rates of disease progression. Methods: We included 1,066 probable AD patients from the Amsterdam Dementia Cohort (n=290), Alzheimer’s Disease Neuroimaging Initiative (n=268), Dementia Competence Network (n=226), and University of California, San Francisco (n=282) with available follow-up data. Patients were previously clustered into two subtypes based on their neuropsychological test results: one with most prominent memory impairment (n=663) and one with most prominent non-memory impairment (n=403). We examined associations between cognitive subtype and disease progression, as measured with repeated Mini-Mental State Examination (MMSE) and Clinical Dementia Rating scale sum of boxes (CDR sob), using linear mixed models. Furthermore, we investigated mortality risk associated with subtypes using Cox proportional hazard analyses. Results: Patients were 71±9 years old; 541 (51%) were female. At baseline, pooled non-memory patients had worse MMSE scores (23.1±0.1) and slightly worse CDR sob (4.4±0.1) than memory patients (MMSE 24.0±0.1; p<0.001; CDR sob 4.1±0.1; p<0.001). During follow-up, pooled non-memory patients showed steeper annual decline in MMSE (-2.8±0.1) and steeper annual increase in CDR sob (1.8±0.1) than memory patients (MMSE -1.9±0.1; pinteraction<0.001; CDR sob 1.3±0.1; pinteraction<0.001). Furthermore, the non-memory subtype was associated with an increased risk of mortality compared with the memory subtype at trend level (HR=1.36, CI=1.00-1.85, p=0.05). Conclusions: AD patients with most prominently non-memory impairment show faster disease progression and higher risk of mortality than patients with most prominently memory impairment.
Pages 1041-1050
Angelina R. Sutin, Yannick Stephan, Antonio Terracciano
Psychological Distress, Self-Beliefs, and Risk of Cognitive Impairment and Dementia
Abstract: Depressive symptoms and a history of mental disorders are associated with increased risk for dementia. Less is known about whether other aspects of psychological distress and negative self-beliefs also increase risk. The purpose of this research is to examine 1) whether eight aspects of psychological distress and self-beliefs (anxiety, negative affect, hostility, anger-in, anger-out, hopelessness, pessimism, perceived constraints) are associated with risk of incident dementia and cognitive impairment not dementia (CIND), 2) whether the associations are independent of depressive symptoms and history of a mental health diagnosis, and 3) whether the associations are also independent of behavioral, clinical, and genetic risk factors. A total of 9,913 participants (60% female) from the Health and Retirement Study completed the baseline measures, scored in the non-impaired range of cognition at baseline, and had cognitive status assessed across the 6-8-year follow-up. Baseline measures included eight aspects of psychological distress and self-beliefs, cognitive performance, depressive symptoms, and genetic, clinical, and behavioral risk factors. Participants who scored higher on anxiety, negative affect, hostility, pessimism, hopelessness, and perceived constraints were at a 20-30% increased risk of dementia and a 10-20% increased risk of CIND. The associations held controlling for baseline depressive symptoms, history of a mental health diagnosis, clinical and behavioral risk factors, and genetic risk. Anger-in and anger-out were unrelated to risk of either dementia or CIND. Independent of the core experience of depressed affect, other aspects of negative emotionality and self-beliefs increase risk of mild and severe cognitive impairment, which suggests additional targets of intervention.
Page 1051
Book Review
Alzheimer's Disease and Dementia: What Everyone Needs to Know, by Steven R. Sabat, Oxford University Press: New York, US, 2018; 256 pp. ISBN: 9780190603113. Reviewed by Bingyu Li
