Clinical relevance of brain atrophy subtypes categorization in memory clinics

Staging of progressive supranuclear palsy-Richardson syndrome using MRI brain charts for the human lifespan

Brain charts for the human lifespan have been recently proposed to build dynamic models of brain anatomy in normal aging and various neurological conditions. They offer new possibilities to quantify neuroanatomical changes from preclinical stages to death, where longitudinal MRI data are not available. In this study, we used brain charts to model the progression of brain atrophy in progressive supranuclear palsy-Richardson syndrome. We combined multiple datasets (n = 8170 quality controlled MRI of healthy subjects from 22 cohorts covering the entire lifespan, and n = 62 MRI of progressive supranuclear palsy-Richardson syndrome patients from the Four Repeat Tauopathy Neuroimaging Initiative (4RTNI)) to extrapolate lifetime volumetric models of healthy and progressive supranuclear palsy-Richardson syndrome brain structures. We then mapped in time and space the sequential divergence between healthy and progressive supranuclear palsy-Richardson syndrome charts. We found six major consecutive stages of atrophy progression: (i) ventral diencephalon (including subthalamic nuclei, substantia nigra, and red nuclei), (ii) pallidum, (iii) brainstem, striatum and amygdala, (iv) thalamus, (v) frontal lobe, and (vi) occipital lobe. The three structures with the most severe atrophy over time were the thalamus, followed by the pallidum and the brainstem. These results match the neuropathological staging of tauopathy progression in progressive supranuclear palsy-Richardson syndrome, where the pathology is supposed to start in the pallido-nigro-luysian system and spreads rostrally via the striatum and the amygdala to the cerebral cortex, and caudally to the brainstem. This study supports the use of brain charts for the human lifespan to study the progression of neurodegenerative diseases, especially in the absence of specific biomarkers as in PSP.

Machine learning in Alzheimer's disease drug discovery and target identification

Alzheimer's disease (AD) stands as a formidable neurodegenerative ailment that poses a substantial threat to the elderly population, with no known curative or disease-slowing drugs in existence. Among the vital and time-consuming stages in the drug discovery process, disease modeling and target identification hold particular significance. Disease modeling allows for a deeper comprehension of disease progression mechanisms and potential therapeutic avenues. On the other hand, target identification serves as the foundational step in drug development, exerting a profound influence on all subsequent phases and ultimately determining the success rate of drug development endeavors. Machine learning (ML) techniques have ushered in transformative breakthroughs in the realm of target discovery. Leveraging the strengths of large dataset analysis, multifaceted data processing, and the exploration of intricate biological mechanisms, ML has become instrumental in the quest for effective AD treatments. In this comprehensive review, we offer an account of how ML methodologies are being deployed in the pursuit of drug discovery for AD. Furthermore, we provide an overview of the utilization of ML in uncovering potential intervention strategies and prospective therapeutic targets for AD. Finally, we discuss the principal challenges and limitations currently faced by these approaches. We also explore the avenues for future research that hold promise in addressing these challenges.

Retrospective Evaluation of Neuropathologic Proxies of the Minimal Atrophy Subtype Compared With Corticolimbic Alzheimer Disease Subtypes

BACKGROUND AND OBJECTIVES

Alzheimer disease (AD) is neuropathologically classified into 3 corticolimbic subtypes based on the neurofibrillary tangle distribution throughout the hippocampus and association cortices: limbic predominant, typical, and hippocampal sparing. In vivo, a fourth subtype, dubbed "minimal atrophy," was identified using structural MRI. The objective of this study was to identify a neuropathologic proxy for the neuroimaging-defined minimal atrophy subtype.

METHODS

We applied 2 strategies in the Florida Autopsied Multi-Ethnic (FLAME) cohort to evaluate a neuropathologic proxy for the minimal atrophy subtype. In the first strategy, we selected AD cases with a Braak tangle stage IV (Braak IV) because of the relative paucity of neocortical tangle involvement compared with Braak >IV. Braak IV cases were compared with the 3 AD subtypes. In the alternative strategy, typical AD was stratified by brain weight and cases having a relatively high brain weight (>75th percentile) were defined as minimal atrophy.

RESULTS

Braak IV cases (n = 37) differed from AD subtypes (limbic predominant [n = 174], typical [n = 986], and hippocampal sparing [n = 187] AD) in having the least years of education (median 12 years, group-wise p < 0.001) and the highest brain weight (median 1,140 g, p = 0.002). Braak IV cases most resembled the limbic predominant cases owing to their high proportion of APOE ε4 carriers (75%, p < 0.001), an amnestic syndrome (100%, p < 0.001), as well as older age of cognitive symptom onset and death (median 79 and 85 years, respectively, p < 0.001). Only 5% of Braak IV cases had amygdala-predominant Lewy bodies (the lowest frequency observed, p = 0.017), whereas 32% had coexisting pathology of Lewy body disease, which was greater than the other subtypes (p = 0.005). Nearly half (47%) of the Braak IV samples had coexisting limbic predominant age-related TAR DNA-binding protein 43 encephalopathy neuropathologic change. Cases with a high brain weight (n = 201) were less likely to have amygdala-predominant Lewy bodies (14%, p = 0.006) and most likely to have Lewy body disease (31%, p = 0.042) compared with those with middle (n = 455) and low (n = 203) brain weight.

DISCUSSION

The frequency of Lewy body disease was increased in both neuropathologic proxies of the minimal atrophy subtype. We hypothesize that Lewy body disease may underlie cognitive decline observed in minimal atrophy cases.

Beyond the amyloid cascade: An update of Alzheimer's disease pathophysiology

Alzheimer's disease (AD) is a multi-etiology disease. The biological system of AD is associated with multidomain genetic, molecular, cellular, and network brain dysfunctions, interacting with central and peripheral immunity. These dysfunctions have been primarily conceptualized according to the assumption that amyloid deposition in the brain, whether from a stochastic or a genetic accident, is the upstream pathological change. However, the arborescence of AD pathological changes suggests that a single amyloid pathway might be too restrictive or inconsistent with a cascading effect. In this review, we discuss the recent human studies of late-onset AD pathophysiology in an attempt to establish a general updated view focusing on the early stages. Several factors highlight heterogenous multi-cellular pathological changes in AD, which seem to work in a self-amplifying manner with amyloid and tau pathologies. Neuroinflammation has an increasing importance as a major pathological driver, and perhaps as a convergent biological basis of aging, genetic, lifestyle and environmental risk factors.

Bidirectional Mapping Perception-enhanced Cycle-consistent Generative Adversarial Network for Super-resolution of Brain MRI images

As an effective tool for visualizing neurodegeneration, high-resolution structural magnetism facilitates quantitative image analysis and clinical applications. Super-resolution reconstruction technology allows to improve the resolution of images without upgrading the scanning hardware. However, existing super-resolution techniques relied on paired image data sets and lacked further quantitative analysis of the generated images. In this study, we proposed a semi-supervised generative adversarial network (GAN) model for super-resolution of brain MRI, and the synthetic images were evaluated using various quantitative measures. This model adopted the cycle-consistency structure to allow for a mixture of unpaired data for training. Perceptual loss was further introduced into the model to preserve detailed texture features at high frequencies. 363 subjects with both high-resolution (HR) and low-resolution (LR) scans and 217 subjects with HR scans only were used for model derivation, training, and validation. We extracted multiple voxel-based and surface-based morphological features of the synthetic and real 3D HR images for comparison. We further evaluated the synthetic images in the differential diagnosis of diseases. Our model achieved superior mean absolute error (0.049±0.021), mean squared error (0.0059±0.0043), peak signal-to-noise ratio (29.41±3.71), structural similarity index measure (0.914±0.048). Eight morphological metrics, both voxel-based and surface-based, showed significant agreement (P<0.0001). The gap of accuracy in disease diagnosis between synthetic and real HR images was within 5% and significantly outperformed the LR images. Our proposed model enables the reconstruction of HR MRI and could be used accurately for image quantification.Clinical relevance- Quantitative evaluation of the synthetic high-resolution images was used to determine whether the synthetic images have sufficient realism and diversity.

What Tools Can We Use to Screen for Fall Risk in Older Patients with Mild Cognitive Impairment? Findings from the MEMENTO Cohort

OBJECTIVES

Identifying risk factors for falls can improve outcomes in older patients without cognitive decline. Yet this has not been demonstrated in older people with mild cognitive impairment (MCI). We therefore sought to better identify risk factors for falls in this particular group.

DESIGN

The analysis was conducted on the MEMENTO cohort, which is a large, French, prospective cohort.

SETTING AND PARTICIPANTS

We included older people (>65 years old) with MCI (defined from neuropsychological scores) and a Short Physical Performance Battery (SPPB) score at baseline.

METHODS

Fallers were defined as participants having fallen at least once during the study's 2-year follow-up period. We compared clinical, neuropsychological, and biological data at baseline in fallers vs nonfallers. Additional analyses were performed on the following subgroups: women, men, people aged ≥75 years.

RESULTS

Of the 1416 people included in our study, 194 (13.5%) fell at least once. A bivariate analysis showed that fallers were older, predominantly women, less independent in activities of daily living, and more apathetic. Fallers performed less well in executive function, balance, and gait tests. In a multivariable analysis, only age, gender, the number of limitations in instrumental activities of daily living, and living alone were significantly associated with falls. In a multivariable analysis of the subgroup of oldest patients and of the subgroup of men, executive function was significantly worse in fallers than in nonfallers.

CONCLUSION AND IMPLICATIONS

Our results demonstrate that easily attainable risk factors can be used to identify individuals with MCI with a higher risk of falls and for whom prevention could be beneficial. Future studies are needed to further evaluate the role of mild executive dysfunction in certain subgroups, such as men and oldest patients.

Research diagnostic criteria for mild cognitive impairment with Lewy bodies: A systematic review and meta-analysis

INTRODUCTION

Operationalized research criteria for mild cognitive impairment with Lewy bodies (MCI-LB) were published in 2020. The aim of this systematic review and meta-analysis was to review the evidence for the diagnostic clinical features and biomarkers in MCI-LB set out in the criteria.

METHODS

MEDLINE, PubMed, and Embase were searched on 9/28/22 for relevant articles. Articles were included if they presented original data reporting the rates of diagnostic features in MCI-LB.

RESULTS

Fifty-seven articles were included. The meta-analysis supported the inclusion of the current clinical features in the diagnostic criteria. Evidence for striatal dopaminergic imaging and meta-iodobenzylguanidine cardiac scintigraphy, though limited, supports their inclusion. Quantitative electroencephalogram (EEG) and fluorodeoxyglucose positron emission tomography (PET) show promise as diagnostic biomarkers.

DISCUSSION

The available evidence largely supports the current diagnostic criteria for MCI-LB. Further evidence will help refine the diagnostic criteria and understand how best to apply them in clinical practice and research.

HIGHLIGHTS

A meta-analysis of the diagnostic features of MCI-LB was carried out. The four core clinical features were more common in MCI-LB than MCI-AD/stable MCI. Neuropsychiatric and autonomic features were also more common in MCI-LB. More evidence is needed for the proposed biomarkers. FDG-PET and quantitative EEG show promise as diagnostic biomarkers in MCI-LB.

A study of linear measurement and clinical correlation of brain atrophy in Wilson's disease

Background

The aim of this study was to explore the clinical relevance of linear measures of Wilson's disease (WD).

Methods

Relative values of brain atrophy in 30 patients with WD and 30 healthy volunteers were measured and compared using a manual measurement method. Linear measurement indicators of brain atrophy in patients with and without mental disorders were also compared. In addition, correlations of patients' age, disease duration, and Unified Wilson's Disease Rating Scale (UWDRS) scores with brain atrophy indicators were determined.

Results

The results showed that the e-value, Huckman number, Evans index, and lateral ventricular body index were higher in the WD group compared with the control group. The age of patients with WD was negatively correlated with the k-value and significantly positively correlated with the brainstem index. WD duration was prominently positively correlated with the d-value and negatively correlated with the j-value. In addition, neurological function scores were significantly positively correlated with the c-value, e-value, caudate nucleus index, Huckman number, Evans index, and lateral ventricular body index. By contrast, patients with psychiatric symptoms had a higher a-value and fourth ventricular index than those without psychiatric symptoms.

Conclusion

Therefore, it can be concluded that patients with WD and those with psychiatric symptoms have more severe brain atrophy compared to normal subjects. The patient's age, disease duration, and neurological function scores were positively correlated with the severity of brain atrophy.

Validity and Performance of Blood Biomarkers for Alzheimer Disease to Predict Dementia Risk in a Large Clinic-Based Cohort

BACKGROUND AND OBJECTIVE

Blood biomarkers for Alzheimer disease (AD) have consistently proven to be associated with CSF or PET biomarkers and effectively discriminate AD from other neurodegenerative diseases. Our aim was to test their utility in clinical practice, from a multicentric unselected prospective cohort where patients presented with a large spectrum of cognitive deficits or complaints.

METHODS

The MEMENTO cohort enrolled 2,323 outpatients with subjective cognitive complaint (SCC) or mild cognitive impairment (MCI) consulting in 26 French memory clinics. Participants had neuropsychological assessments, MRI, and blood sampling at baseline. CSF sampling and amyloid PET were optional. Baseline blood Aβ42/40 ratio, total tau, p181-tau, and neurofilament light chain (NfL) were measured using a Simoa HD-X analyzer. An expert committee validated incident dementia cases during a 5-year follow-up period.

RESULTS

Overall, 2,277 individuals had at least 1 baseline blood biomarker available (n = 357 for CSF subsample, n = 649 for PET subsample), among whom 257 were diagnosed with clinical AD/mixed dementia during follow-up. All blood biomarkers but total tau were mildly correlated with their equivalence in the CSF (r = 0.33 to 0.46, p < 0.0001) and were associated with amyloid-PET status (p < 0.0001). Blood p181-tau was the best blood biomarker to identify amyloid-PET positivity (area under the curve = 0.74 [95% CI = 0.69; 0.79]). Higher blood and CSF p181-tau and NfL concentrations were associated with accelerated time to AD dementia onset with similar incidence rates, whereas blood Aβ42/40 was less efficient than CSF Aβ42/40. Blood p181-tau alone was the best blood predictor of 5-year AD/mixed dementia risk (c-index = 0.73 [95% CI = 0.69; 0.77]); its accuracy was higher in patients with clinical dementia rating (CDR) = 0 (c-index = 0.83 [95% CI = 0.69; 0.97]) than in patients with CDR = 0.5 (c-index = 0.70 [95% CI = 0.66; 0.74]). A "clinical" reference model (combining demographics and neuropsychological assessment) predicted AD/mixed dementia risk with a c-index = 0.88 [95% CI = 0.86-0.91] and performance increased to 0.90 [95% CI = 0.88; 0.92] when adding blood p181-tau + Aβ42/40. A "research" reference model (clinical model + apolipoprotein E genotype and AD signature on MRI) had a c-index = 0.91 [95% CI = 0.89-0.93] increasing to 0.92 [95% CI = 0.90; 0.93] when adding blood p181-tau + Aβ42/40. Chronic kidney disease and vascular comorbidities did not affect predictive performances.

DISCUSSION

In a clinic-based cohort of patients with SCC or MCI, blood biomarkers may be good hallmarks of underlying pathology but add little to 5-year dementia risk prediction models including traditional predictors.

Mnemonic Discrimination Performance in a Memory Clinic: A Pilot Study

BACKGROUND

Mnemonic discrimination is the behavioral ability stemming from pattern separation, which is the neural process of establishing independent and non-overlapping new memories. Over the past two decades, its assessment in various populations has contributed to a better conceptual understanding of age-related memory decline.

OBJECTIVE

To assess the clinical relevance of mnemonic discrimination in the memory clinics setting.

METHODS

This retrospective study was performed in 90 patients with a Mini-Mental State Examination (MMSE)>18 who consulted our memory clinic for the first time. All patients were tested with the Mnemonic Similarity Task, a freely available computerized test. Global cognitive function, executive function, visuoconstructional abilities, and verbal and visual episodic memory were also collected, together with the diagnosis after the initial clinical assessment (subjective cognitive complaint [SCC], mild cognitive impairment [MCI], or mild dementia).

RESULTS

Mnemonic discrimination performance was correlated with global cognitive function, executive function, and visual and verbal episodic memory scores, independent of age. It discriminated patients with SCC from those with MCI (amnestic or non-amnestic) with moderate accuracy (AUC = 0.77-0.78), similar to MMSE and the Frontal Assessment Battery (AUC = 0.74-0.84). Mnemonic discrimination performance did not distinguish between amnestic and non-amnestic MCI and the variability of the measure was important within groups.

CONCLUSION

Mnemonic discrimination performance involves many cognitive domains and discriminates between patients with SCC and MCI with performance equivalent to "paper-and-pencil" screening tests. Further dedicated prospective studies will determine whether this task is of interest beyond research purposes, as a diagnostic or screening tool in primary care.

Structural progression of Alzheimer’s disease over decades: the MRI staging scheme

The chronological progression of brain atrophy over decades, from pre-symptomatic to dementia stages, has never been formally depicted in Alzheimer’s disease. This is mainly due to the lack of cohorts with long enough MRI follow-ups in cognitively unimpaired young participants at baseline. To describe a spatiotemporal atrophy staging of Alzheimer’s disease at the whole-brain level, we built extrapolated lifetime volumetric models of healthy and Alzheimer’s disease brain structures by combining multiple large-scale databases (n = 3512 quality controlled MRI from 9 cohorts of subjects covering the entire lifespan, including 415 MRI from ADNI1, ADNI2 and AIBL for Alzheimer’s disease patients). Then, we validated dynamic models based on cross-sectional data using external longitudinal data. Finally, we assessed the sequential divergence between normal aging and Alzheimer’s disease volumetric trajectories and described the following staging of brain atrophy progression in Alzheimer’s disease: (i) hippocampus and amygdala; (ii) middle temporal gyrus; (iii) entorhinal cortex, parahippocampal cortex and other temporal areas; (iv) striatum and thalamus and (v) middle frontal, cingular, parietal, insular cortices and pallidum. We concluded that this MRI scheme of atrophy progression in Alzheimer’s disease was close but did not entirely overlap with Braak staging of tauopathy, with a ‘reverse chronology’ between limbic and entorhinal stages. Alzheimer’s disease structural progression may be associated with local tau accumulation but may also be related to axonal degeneration in remote sites and other limbic-predominant associated proteinopathies.

Deregulated mitochondrial microRNAs in Alzheimer's disease: Focus on synapse and mitochondria

Alzheimer's disease (AD) is the most common cause of dementia and is currently one of the biggest public health concerns in the world. Mitochondrial dysfunction in neurons is one of the major hallmarks of AD. Emerging evidence suggests that mitochondrial miRNAs potentially play important roles in the mitochondrial dysfunctions, focusing on synapse in AD progression. In this meta-analysis paper, a comprehensive literature review was conducted to identify and discuss the (1) role of mitochondrial miRNAs that regulate mitochondrial and synaptic functions; (2) the role of various factors such as mitochondrial dynamics, biogenesis, calcium signaling, biological sex, and aging on synapse and mitochondrial function; (3) how synapse damage and mitochondrial dysfunctions contribute to AD; (4) the structure and function of synapse and mitochondria in the disease process; (5) latest research developments in synapse and mitochondria in healthy and disease states; and (6) therapeutic strategies that improve synaptic and mitochondrial functions in AD. Specifically, we discussed how differences in the expression of mitochondrial miRNAs affect ATP production, oxidative stress, mitophagy, bioenergetics, mitochondrial dynamics, synaptic activity, synaptic plasticity, neurotransmission, and synaptotoxicity in neurons observed during AD. However, more research is needed to confirm the locations and roles of individual mitochondrial miRNAs in the development of AD.

Cortical structure and the risk for Alzheimer's disease: a bidirectional Mendelian randomization study

Progressive loss of neurons in a specific brain area is one of the manifestations of Alzheimer's disease (AD). Much effort has been devoted to investigating brain atrophy and AD. However, the causal relationship between cortical structure and AD is not clear. We conducted a bidirectional two-sample Mendelian randomization analysis to investigate the causal relationship between cortical structure (surface area and thickness of the whole cortex and 34 cortical regions) and AD risk. Genetic variants used as instruments came from a large genome-wide association meta-analysis of cortical structure (33,992 participants of European ancestry) and AD (AD and AD-by-proxy, 71,880 cases, 383,378 controls). We found suggestive associations of the decreased surface area of the temporal pole (OR (95% CI): 0.95 (0.9, 0.997), p = 0.04), and decreased thickness of cuneus (OR (95% CI): 0.93 (0.89, 0.98), p = 0.006) with higher AD risk. We also found a suggestive association of vulnerability to AD with the decreased surface area of precentral (β (SE): -43.4 (21.3), p = 0.042) and isthmus cingulate (β (SE): -18.5 (7.3), p = 0.011). However, none of the Bonferroni-corrected p values of the causal relationship between cortical structure and AD met the threshold. We show suggestive evidence of an association of the atrophy of the temporal pole and cuneus with higher AD risk. In the other direction, there was a suggestive causal relationship between vulnerability to AD and the decreased surface area of the precentral and isthmus cingulate. Our findings shed light on the associations of cortical structure with the occurrence of AD.

Ginkgo Biloba Extract Is Comparable With Donepezil in Improving Functional Recovery in Alzheimer's Disease: Results From a Multilevel Characterized Study Based on Clinical Features and Resting-State Functional Magnetic Resonance Imaging

Background: Ginkgo biloba extract (GBE) and donepezil have been reported to be effective in patients with Alzheimer’s disease (AD). Nonetheless, how these drugs impact spontaneous brain activities and how they consequently improve functional recovery are currently unclear.

Objectives: This study was to explore the efficacy of GBE vs. donepezil and their add-on efficacy on functional recovery and the adaption of spontaneous brain activities following pharmacologic treatment in patients with AD.

Methods: Patients with AD were enrolled and assigned to the GBE group (n = 50), the donepezil group (n = 50), or the combined group (n = 50). Neuropsychological assessments, including minimum mental state examination (MMSE), Alzheimer’s disease assessment scale-cognition (ADAS-Cog), instrumental activity of daily living (IADL), geriatric depression scale (GDS), neuropsychiatric inventory (NPI), and quality of life in Alzheimer’s disease (QOL-AD), were conducted at baseline, 1 month, 3 months, and 6 months. Resting-state functional magnetic resonance imaging (rs-fMRI) was collected to compare the amplitude of low-frequency fluctuation (ALFF), percent amplitude of fluctuation (PerAF), regional homogeneity (ReHo), and degree centrality (DC) at baseline and 6 months.

Results: No major significant differences were detected in all comparisons between groups across all follow-up time points. For intragroup comparison, MMSE and ADAS-Cog scores differed significantly across all follow-ups in three groups. The combined group showed significant improvement of GDS scores between baseline and 6 months (p = 0.007). The GBE group (p = 0.044) and donepezil group (p = 0.012) demonstrated significant improvement of NPI scores between baseline and 6 months. Significant correlations were observed between IADL and ALFF in the right gyrus rectus (p = 0.03) and in the left superior cerebellum gyrus (p = 0.01), between GDS and ALFF in the right middle temporal gyrus (p = 0.01), between NPI and PerAF in the left fusiform gyrus (p = 0.03), and between MMSE and ReHo in right superior frontal gyrus (p = 0.04).

Conclusion: GBE was comparable with donepezil in the improvement of functional recovery in patients with AD while the combined application of GBE and donepezil seems unnecessary. GBE-mediated improvement of functional recovery was characterized by decreased ALFF values in the right gyrus rectus and decreased PerAF values in the left fusiform gyrus. These featured variations of imaging metrics in specific brain regions may serve as biomarkers in the monitoring of the therapeutic efficacy of GBE.