The Behavioral/Dysexecutive Variant of Alzheimer's Disease: A Case Series with Clinical, Neuropsychological, and FDG-PET Characterization

3D Multimodal Fusion Network With Disease-Induced Joint Learning for Early Alzheimer's Disease Diagnosis

Multimodal neuroimaging provides complementary information critical for accurate early diagnosis of Alzheimer's disease (AD). However, the inherent variability between multimodal neuroimages hinders the effective fusion of multimodal features. Moreover, achieving reliable and interpretable diagnoses in the field of multimodal fusion remains challenging. To address them, we propose a novel multimodal diagnosis network based on multi-fusion and disease-induced learning (MDL-Net) to enhance early AD diagnosis by efficiently fusing multimodal data. Specifically, MDL-Net proposes a multi-fusion joint learning (MJL) module, which effectively fuses multimodal features and enhances the feature representation from global, local, and latent learning perspectives. MJL consists of three modules, global-aware learning (GAL), local-aware learning (LAL), and outer latent-space learning (LSL) modules. GAL via a self-adaptive Transformer (SAT) learns the global relationships among the modalities. LAL constructs local-aware convolution to learn the local associations. LSL module introduces latent information through outer product operation to further enhance feature representation. MDL-Net integrates the disease-induced region-aware learning (DRL) module via gradient weight to enhance interpretability, which iteratively learns weight matrices to identify AD-related brain regions. We conduct the extensive experiments on public datasets and the results confirm the superiority of our proposed method. Our code will be available at: https://github.com/qzf0320/MDL-Net.

Behavioral and dysexecutive variant of Alzheimer's disease: Insights from structural and molecular imaging studies

Frontal variant Alzheimer's disease (AD) manifests with either behavioral or dysexecutive syndromes. Recent efforts to gain a deeper understanding of this phenotype have led to a re-conceptualization of frontal AD. Behavioral (bAD) and dysexecutive (dAD) phenotypes could be considered subtypes, as suggested by both clinical and neuroimaging studies. In this review, we focused on imaging studies to highlight specific brain patterns in these two uncommon clinical AD phenotypes. Although studies did not compare directly these two variants, a common epicenter located in the frontal cortex could be inferred. On the contrary, 18F-FDG-PET findings suggested differing metabolic patterns, with bAD showing specific involvement of frontal regions and dAD exhibiting widespread alterations. Structural MRI findings confirmed this pattern, suggesting that degeneration might involve neural circuits associated with behavioral control in bAD and attentional networks in dAD. Furthermore, molecular imaging has identified different neocortical tau distribution in bAD and dAD patients compared to typical AD patients, although the distribution is remarkably heterogeneous. In contrast, Aβ deposition patterns are less differentiated between these atypical variants and typical AD. Although preliminary, these findings underscore the complexity of AD frontal phenotypes and suggest that they represent distinct entities. Further research is essential to refine our understanding of the pathophysiological mechanisms in frontal AD.

Comparison of 18F-FDG PET and arterial spin labeling MRI in evaluating Alzheimer's disease and amnestic mild cognitive impairment using integrated PET/MR

BACKGROUND

Developing biomarkers for early stage AD patients is crucial. Glucose metabolism measured by 18F-FDG PET is the most common biomarker for evaluating cellular energy metabolism to diagnose AD. Arterial spin labeling (ASL) MRI can potentially provide comparable diagnostic information to 18F-FDG PET in patients with neurodegenerative disorders. However, the conclusions about the diagnostic performance of AD are still controversial between 18F-FDG PET and ASL. This study aims to compare quantitative cerebral blood flow (CBF) and glucose metabolism measured by 18F-FDG PET diagnostic values in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) using integrated PET/MR.

RESULTS

Analyses revealed overlapping between decreased regional rCBF and 18F-FDG PET SUVR in patients with AD compared with NC participants in the bilateral parietotemporal regions, frontal cortex, and cingulate cortex. Compared with NC participants, patients with aMCI exclusively demonstrated lower 18F-FDG PET SUVR in the bilateral temporal cortex, insula cortex, and inferior frontal cortex. Comparison of the rCBF in patients with aMCI and NC participants revealed no significant difference (P > 0.05). The ROC analysis of rCBF in the meta-ROI could diagnose patients with AD (AUC, 0.87) but not aMCI (AUC, 0.61). The specificity of diagnosing aMCI has been improved to 75.56% when combining rCBF and 18F-FDG PET SUVR.

CONCLUSION

ASL could detect similar aberrant patterns of abnormalities compared to 18F-FDG PET in patients with AD compared with NC participants but not in aMCI. The diagnostic efficiency of 18F-FDG-PET for AD and aMCI patients remained higher to ASL. Our findings support that applying 18F-FDG PET may be preferable for diagnosing AD and aMCI.

Icariin improves cognitive impairment by inhibiting ferroptosis of nerve cells

AIM

We investigated the effect and mechanism of Icariin (ICA) on improving neurobehavioral ability of mice with Alzheimer's disease (AD).

METHODS

We selected 10-month-old APP/PS1 mice (AD) and wild-type C57BL/6J mice (Normal). After intragastric administration of ICA, Morris water maze was employed to detect neurobehavioral improvements, and to assay key ferroptosis indicators and oxidative stress levels. The common target of ICA for resisting ferroptosis and AD was predicted by network pharmacology.

RESULTS

ICA could improve the neurobehavioral, memory and motor abilities of AD mice. It could lower the ferroptosis level and enhance the resistance to oxidative stress. After inhibition of MDM2, ICA could no longer improve the cognitive ability of AD mice, nor could it further inhibit ferroptosis. Network pharmacological analysis revealed that MDM2 might be the target of ICA action.

CONCLUSIONS

We found that ICA can inhibit ferroptosis of nerve cells, thereby ameliorating neural damage in mice with AD.

Longitudinal clinical, cognitive and biomarker profiles in dominantly inherited versus sporadic early-onset Alzheimer's disease

Approximately 5% of Alzheimer's disease cases have an early age at onset (<65 years), with 5-10% of these cases attributed to dominantly inherited mutations and the remainder considered as sporadic. The extent to which dominantly inherited and sporadic early-onset Alzheimer's disease overlap is unknown. In this study, we explored the clinical, cognitive and biomarker profiles of early-onset Alzheimer's disease, focusing on commonalities and distinctions between dominantly inherited and sporadic cases. Our analysis included 117 participants with dominantly inherited Alzheimer's disease enrolled in the Dominantly Inherited Alzheimer Network and 118 individuals with sporadic early-onset Alzheimer's disease enrolled at the University of California San Francisco Alzheimer's Disease Research Center. Baseline differences in clinical and biomarker profiles between both groups were compared using t-tests. Differences in the rates of decline were compared using linear mixed-effects models. Individuals with dominantly inherited Alzheimer's disease exhibited an earlier age-at-symptom onset compared with the sporadic group [43.4 (SD ± 8.5) years versus 54.8 (SD ± 5.0) years, respectively, P < 0.001]. Sporadic cases showed a higher frequency of atypical clinical presentations relative to dominantly inherited (56.8% versus 8.5%, respectively) and a higher frequency of APOE-ε4 (50.0% versus 28.2%, P = 0.001). Compared with sporadic early onset, motor manifestations were higher in the dominantly inherited cohort [32.5% versus 16.9% at baseline (P = 0.006) and 46.1% versus 25.4% at last visit (P = 0.001)]. At baseline, the sporadic early-onset group performed worse on category fluency (P < 0.001), Trail Making Test Part B (P < 0.001) and digit span (P < 0.001). Longitudinally, both groups demonstrated similar rates of cognitive and functional decline in the early stages. After 10 years from symptom onset, dominantly inherited participants experienced a greater decline as measured by Clinical Dementia Rating Sum of Boxes [3.63 versus 1.82 points (P = 0.035)]. CSF amyloid beta-42 levels were comparable [244 (SD ± 39.3) pg/ml dominantly inherited versus 296 (SD ± 24.8) pg/ml sporadic early onset, P = 0.06]. CSF phosphorylated tau at threonine 181 levels were higher in the dominantly inherited Alzheimer's disease cohort (87.3 versus 59.7 pg/ml, P = 0.005), but no significant differences were found for t-tau levels (P = 0.35). In summary, sporadic and inherited Alzheimer's disease differed in baseline profiles; sporadic early onset is best distinguished from dominantly inherited by later age at onset, high frequency of atypical clinical presentations and worse executive performance at baseline. Despite these differences, shared pathways in longitudinal clinical decline and CSF biomarkers suggest potential common therapeutic targets for both populations, offering valuable insights for future research and clinical trial design.

Biomarkers in Alzheimer's disease: role in early and differential diagnosis and recognition of atypical variants

BACKGROUND

Development of in vivo biomarkers has shifted the diagnosis of Alzheimer's disease (AD) from the later dementia stages of disease towards the earlier stages and has introduced the potential for pre-symptomatic diagnosis. The International Working Group recommends that AD diagnosis is restricted in the clinical setting to people with specific AD phenotypes and supportive biomarker findings.

MAIN BODY

In this review, we discuss the phenotypic presentation and use of biomarkers for the early diagnosis of typical and atypical AD and describe how this can support clinical decision making, benefit patient communication, and improve the patient journey. Early diagnosis is essential to optimize the benefits of available and emerging treatments. As atypical presentations of AD often mimic other dementias, differential diagnosis can be challenging and can be facilitated using AD biomarkers. However, AD biomarkers alone are not sufficient to confidently diagnose AD or predict disease progression and should be supplementary to clinical assessment to help inform the diagnosis of AD.

CONCLUSIONS

Use of AD biomarkers with incorporation of atypical AD phenotypes into diagnostic criteria will allow earlier diagnosis of patients with atypical clinical presentations that otherwise would have been misdiagnosed and treated inappropriately. Early diagnosis is essential to guide informed discussion, appropriate care and support, and individualized treatment. It is hoped that disease-modifying treatments will impact the underlying AD pathology; thus, determining the patient's AD phenotype will be a critical factor in guiding the therapeutic approach and the assessment of the effects of interventions.

Frontal variant Alzheimer's disease: A systematic narrative synthesis

BACKGROUND

Frontal variant Alzheimer's disease (fvAD) is considered a rare form of Alzheimer's disease (AD) which may be misdiagnosed as behavioural variant frontotemporal dementia (bvFTD). The literature has tended to conflate behavioural and executive dysfunction in fvAD cohorts and uses both AD diagnostic criteria and bvFTD diagnostic criteria to classify fvAD cohorts. The primary aim of this narrative synthesis was to summarise neuropsychological findings in fvAD cohorts in the context of established AD pathology.

METHODS

EMBASE, PsycINFO, PROQUEST and MEDLINE databases were searched for studies eligible for inclusion. Studies with both neuropsychological and biomarker evidence were included in the final narrative synthesis.

RESULTS

Ten studies were reviewed, including samples totalling 342 fvAD participants, 178 typical AD participants and 250 bvFTD participants. The review revealed areas worthy of further investigation that may aid differential diagnosis, including the degree of executive dysfunction in fvAD cohorts relative to bvFTD cohorts, the onset of behavioural and cognitive symptomatology, and similarities between fvAD and typical AD cognitive profiles.

CONCLUSION

There was insufficient neuropsychological evidence to clearly differentiate fvAD and bvFTD cognitive phenotypes, however, the review has highlighted distinctive features of the two disorders that may guide differential diagnosis in future research. Moreover, the review has highlighted issues involving disparate diagnostic criteria used to classify fvAD cohorts, contributing to variation in findings.

How Many Alzheimer-Perusini's Atypical Forms Do We Still Have to Discover?

Alzheimer-Perusini's (AD) disease represents the most spread dementia around the world and constitutes a serious problem for public health. It was first described by the two physicians from whom it took its name. Nowadays, we have extensively expanded our knowledge about this disease. Starting from a merely clinical and histopathologic description, we have now reached better molecular comprehension. For instance, we passed from an old conceptualization of the disease based on plaques and tangles to a more modern vision of mixed proteinopathy in a one-to-one relationship with an alteration of specific glial and neuronal phenotypes. However, no disease-modifying therapies are yet available. It is likely that the only way to find a few "magic bullets" is to deepen this aspect more and more until we are able to draw up specific molecular profiles for single AD cases. This review reports the most recent classifications of AD atypical variants in order to summarize all the clinical evidence using several discrimina (for example, post mortem neurofibrillary tangle density, cerebral atrophy, or FDG-PET studies). The better defined four atypical forms are posterior cortical atrophy (PCA), logopenic variant of primary progressive aphasia (LvPPA), behavioral/dysexecutive variant and AD with corticobasal degeneration (CBS). Moreover, we discuss the usefulness of such classifications before outlining the molecular-genetic aspects focusing on microglial activity or, more generally, immune system control of neuroinflammation and neurodegeneration.

Impact of dysexecutive syndrome in quality of life in Alzheimer disease: What we know now and where we are headed

Alzheimer's disease (AD) is a common form of dementia that leads to multiple repercussions in the patient's life. This condition's clinical characteristics include loss of memory, temporal and spatial disorientation, language or executive dysfunction, and subsequent decline of social function. Dysexecutive syndrome (DS), the second most frequent neuropsychological dysfunction in AD, affects multiple brain areas and causes cognitive, behavioral, and emotional difficulties. We aimed to analyze the association between DS and AD and elucidate possible lack of evidence that may urge further research on this theme. Especially when dealing with such a disabling disease, where new findings can directly imply a better prognosis.

Neuropsychological Assessment in the Distinction Between Biomarker Defined Frontal-Variant of Alzheimer's Disease and Behavioral-Variant of Frontotemporal Dementia

BACKGROUND

Frontal-variant of Alzheimer's disease (fvAD) was purposed for patients with AD pathology that, despite the typical amnestic presentation, show early and progressive deterioration of behavior and executive functions, closely resembling the behavioral-variant of frontotemporal dementia (bvFTD). This leads to a challenging differential diagnosis where neuropsychological evaluation and in vivo pathological evidence are essential.

OBJECTIVE

To evaluate the contribution of a comprehensive neuropsychological assessment (NP) battery in distinguishing between fvAD-dementia and bvFTD supported by cerebrospinal fluid (CSF) biomarkers.

METHODS

We included 40 patients with a baseline NP profile with prominent early executive and/or behavioral dysfunction, who meet both diagnosis of bvFTD and fvAD-dementia, according to international criteria. All patients underwent comprehensive NP assessment and CSF-AD biomarker evaluation. Neuropsychological domains as well as clinical and sociodemographic features, and APOE genotype were compared between groups.

RESULTS

21 patients (52.5%) met the biological criteria for AD (decreased Aβ42 together with increased T-tau or P-tau in CSF) and were therefore classified as fvAD (mean age was 64.57, with 47.6% female). There were no differences between groups regarding age/age-at-onset, gender, or educational level. Regarding neuropsychological profile, performances in language and memory functions were equivalent in both groups. Significant differences were found in visuo-constructional abilities (p = 0.004), Trail Making Test A (p < 0.001), and Raven's Colored Progressive Matrices (p = 0.019), with fvAD patients showing worst performances.

CONCLUSION

In patients with an early prominent frontal profile, a higher impairment in attention and visuo-spatial functions, signaling additional right hemisphere fronto-parietal dysfunction, point towards a diagnosis of fvAD-dementia and may be useful in clinical practice.

Multimodality imaging of neurodegenerative disorders with a focus on multiparametric magnetic resonance and molecular imaging

Neurodegenerative diseases afflict a large number of persons worldwide, with the prevalence and incidence of dementia rapidly increasing. Despite their prevalence, clinical diagnosis of dementia syndromes remains imperfect with limited specificity. Conventional structural-based imaging techniques also lack the accuracy necessary for confident diagnosis. Multiparametric magnetic resonance imaging and molecular imaging provide the promise of improving specificity and sensitivity in the diagnosis of neurodegenerative disease as well as therapeutic monitoring of monoclonal antibody therapy. This educational review will briefly focus on the epidemiology, clinical presentation, and pathologic findings of common and uncommon neurodegenerative diseases. Imaging features of each disease spanning from conventional magnetic resonance sequences to advanced multiparametric methods such as resting-state functional magnetic resonance imaging and arterial spin labeling imaging will be described in detail. Additionally, the review will explore the findings of each diagnosis on molecular imaging including single-photon emission computed tomography and positron emission tomography with a variety of clinically used and experimental radiotracers. The literature and clinical cases provided demonstrate the power of advanced magnetic resonance imaging and molecular techniques in the diagnosis of neurodegenerative diseases and areas of future and ongoing research. With the advent of combined positron emission tomography/magnetic resonance imaging scanners, hybrid protocols utilizing both techniques are an attractive option for improving the evaluation of neurodegenerative diseases.

The pattern of cortical thickness underlying disruptive behaviors in Alzheimer's disease

Background

Disruptive behaviors, including agitation, disinhibition, irritability, and aberrant motor behaviors, are commonly observed in patients with Alzheimer's disease (AD). However, the neuroanatomical basis of these disruptive behaviors is not fully understood.

Objective

To confirm the differences in cortical thickness and surface area between AD patients and healthy controls and to further investigate the features of cortical thickness and surface area associated with disruptive behaviors in patients with AD.

Methods

One hundred seventy-four participants (125 AD patients and 49 healthy controls) were recruited from memory clinics at the Peking University Institute of Sixth Hospital. Disruptive behaviors, including agitation/aggression, disinhibition, irritability/lability, and aberrant motor activity subdomain scores, were evaluated using the Neuropsychiatry Inventory. Both whole-brain vertex-based and region-of-interest-based cortical thickness and surface area analyses were automatically conducted with the CIVET pipeline based on structural magnetic resonance images. Both group-based statistical comparisons and brain-behavior association analyses were performed using general linear models, with age, sex, and education level as covariables.

Results

Compared with healthy controls, the AD patients exhibited widespread reduced cortical thickness, with the most significant thinning located in the medial and lateral temporal and parietal cortex, and smaller surface areas in the left fusiform and left inferior temporal gyrus. High total scores of disruptive behaviors were significantly associated with cortical thinning in several regions that are involved in sensorimotor processing, language, and expression functions. The total score of disruptive behaviors did not show significant associations with surface areas.

Conclusion

We highlight that disruptive behaviors in patients with AD are selectively associated with cortical thickness abnormalities in sensory, motor, and language regions, which provides insights into neuroanatomical substrates underlying disruptive behaviors. These findings could lead to sensory, motor, and communication interventions for alleviating disruptive behaviors in patients with AD.

Virtual Adversarial Training-Based Deep Feature Aggregation Network From Dynamic Effective Connectivity for MCI Identification

Dynamic functional connectivity (dFC) network inferred from resting-state fMRI reveals macroscopic dynamic neural activity patterns for brain disease identification. However, dFC methods ignore the causal influence between the brain regions. Furthermore, due to the complex non-Euclidean structure of brain networks, advanced deep neural networks are difficult to be applied for learning high-dimensional representations from brain networks. In this paper, a group constrained Kalman filter (gKF) algorithm is proposed to construct dynamic effective connectivity (dEC), where the gKF provides a more comprehensive understanding of the directional interaction within the dynamic brain networks than the dFC methods. Then, a novel virtual adversarial training convolutional neural network (VAT-CNN) is employed to extract the local features of dEC. The VAT strategy improves the robustness of the model to adversarial perturbations, and therefore avoids the overfitting problem effectively. Finally, we propose the high-order connectivity weight-guided graph attention networks (cwGAT) to aggregate features of dEC. By injecting the weight information of high-order connectivity into the attention mechanism, the cwGAT provides more effective high-level feature representations than the conventional GAT. The high-level features generated from the cwGAT are applied for binary classification and multiclass classification tasks of mild cognitive impairment (MCI). Experimental results indicate that the proposed framework achieves the classification accuracy of 90.9%, 89.8%, and 82.7% for normal control (NC) vs. early MCI (EMCI), EMCI vs. late MCI (LMCI), and NC vs. EMCI vs. LMCI classification respectively, outperforming the state-of-the-art methods significantly.

Research Criteria for the Behavioral Variant of Alzheimer Disease: A Systematic Review and Meta-analysis

Importance

The behavioral variant of Alzheimer disease (bvAD) is characterized by early and predominant behavioral deficits caused by AD pathology. This AD phenotype is insufficiently understood and lacks standardized clinical criteria, limiting reliability and reproducibility of diagnosis and scientific reporting.

Objective

To perform a systematic review and meta-analysis of the bvAD literature and use the outcomes to propose research criteria for this syndrome.

Data Sources

A systematic literature search in PubMed/MEDLINE and Web of Science databases (from inception through April 7, 2021) was performed in duplicate.

Study Selection

Studies reporting on behavioral, neuropsychological, or neuroimaging features in bvAD and, when available, providing comparisons with typical amnestic-predominant AD (tAD) or behavioral variant frontotemporal dementia (bvFTD).

Data Extraction and Synthesis

This analysis involved random-effects meta-analyses on group-level study results of clinical data and systematic review of the neuroimaging literature. The study was performed following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines.

Main Outcomes and Measures

Behavioral symptoms (neuropsychiatric symptoms and bvFTD core clinical criteria), cognitive function (global cognition, episodic memory, and executive functioning), and neuroimaging features (structural magnetic resonance imaging, [18F]fluorodeoxyglucose-positron emission tomography, perfusion single-photon emission computed tomography, amyloid positron emission tomography, and tau positron emission tomography).

Results

The search led to the assessment of 83 studies, including 13 suitable for meta-analysis. Data were collected for 591 patients with bvAD. There was moderate to substantial heterogeneity and moderate risk of bias across studies. Cases with bvAD showed more severe behavioral symptoms than tAD (standardized mean difference [SMD], 1.16 [95% CI, 0.74-1.59]; P < .001) and a trend toward less severe behavioral symptoms compared with bvFTD (SMD, -0.22 [95% CI, -0.47 to 0.04]; P = .10). Meta-analyses of cognitive data indicated worse executive performance in bvAD vs tAD (SMD, -1.03 [95% CI, -1.74 to -0.32]; P = .008) but not compared with bvFTD (SMD, -0.61 [95% CI, -1.75 to 0.53]; P = .29). Cases with bvAD showed a nonsignificant difference of worse memory performance compared with bvFTD (SMD, -1.31 [95% CI, -2.75 to 0.14]; P = .08) but did not differ from tAD (SMD, 0.43 [95% CI, -0.46 to 1.33]; P = .34). The neuroimaging literature revealed 2 distinct bvAD neuroimaging phenotypes: an AD-like pattern with relative frontal sparing and a relatively more bvFTD-like pattern characterized by additional anterior involvement, with the AD-like pattern being more prevalent.

Conclusions and Relevance

These data indicate that bvAD is clinically most similar to bvFTD, while it shares most pathophysiological features with tAD. Based on these insights, we propose research criteria for bvAD aimed at improving the consistency and reliability of future research and aiding the clinical assessment of this AD phenotype.