Resting-state functional connectivity and amyloid burden influence longitudinal cortical thinning in the default mode network in preclinical Alzheimer's disease

Machine learning based on functional and structural connectivity in mild cognitive impairment

OBJECTIVE

Alzheimer's disease (AD) is a chronic, degenerative neurological disorder characterized by progressive cognitive decline and mental behavioral abnormalities. Mild cognitive impairment (MCI) is regarded as a transitional stage in the progression from normal elderly individuals to patients with AD. While studies have identified abnormalities in brain connectivity in patients with MCI, including functional and structural connectivity, accurately identifying patients with MCI in clinical screening remains challenging. We hypothesized that utilizing machine learning (ML) based on both functional and structural connectivity could yield meaningful results in distinguishing between patients with MCI and normal elderly individuals, so as to provide valuable information for early diagnosis and precise evaluation of patients with MCI.

METHODS

Following clinical criteria, we recruited 32 patients with MCI for the patient group, and 32 normal elderly individuals for the control group. All subjects underwent examinations for resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI). Subsequently, significant functional and structural connectivity features were selected and combined with a support vector machine for classification of the patient and control groups.

RESULTS

We observed significantly different functional connectivity in the frontal lobe and putamen between the MCI group and normal controls. The results based on functional connectivity features demonstrated a classification accuracy of 71.88% and an area under the curve (AUC) value of 0.78. In terms of structural connectivity, we found that decreased fractional anisotropy in patients with MCI was significantly associated with Montreal Cognitive Assessment scores, specifically in regions such as the precuneus and cingulate gyrus. The classification results using the structural connectivity feature yielded an accuracy of 92.19% and an AUC value of 0.99. Lastly, combining functional and structural connectivity features resulted in a classification accuracy and AUC value of 93.75% and 0.99, respectively.

CONCLUSIONS

In this study, we demonstrated a high classification performance, underscoring the potential of both brain functional and structural connectivity in distinguishing patients with MCI from normal elderly individuals. Furthermore, the integration of functional connectivity and structural connectivity features indicated that utilizing rs-fMRI and DTI could enhance the accuracy and specificity of identifying patients with MCI compared with relying on a single neuroimaging technique.

Subclinical epileptiform discharges in Alzheimer's disease are associated with increased hippocampal blood flow

BACKGROUND

In epilepsy, the ictal phase leads to cerebral hyperperfusion while hypoperfusion is present in the interictal phases. Patients with Alzheimer's disease (AD) have an increased prevalence of epileptiform discharges and a study using intracranial electrodes have shown that these are very frequent in the hippocampus. However, it is not known whether there is an association between hippocampal hyperexcitability and regional cerebral blood flow (rCBF). The objective of the study was to investigate the association between rCBF in hippocampus and epileptiform discharges as measured with ear-EEG in patients with Alzheimer's disease. Our hypothesis was that increased spike frequency may be associated with increased rCBF in hippocampus.

METHODS

A total of 24 patients with AD, and 15 HC were included in the analysis. Using linear regression, we investigated the association between rCBF as measured with arterial spin-labelling MRI (ASL-MRI) in the hippocampus and the number of spikes/sharp waves per 24 h as assessed by ear-EEG.

RESULTS

No significant difference in hippocampal rCBF was found between AD and HC (p-value = 0.367). A significant linear association between spike frequency and normalized rCBF in the hippocampus was found for patients with AD (estimate: 0.109, t-value = 4.03, p-value < 0.001). Changes in areas that typically show group differences (temporal-parietal cortex) were found in patients with AD, compared to HC.

CONCLUSIONS

Increased spike frequency was accompanied by a hemodynamic response of increased blood flow in the hippocampus in patients with AD. This phenomenon has also been shown in patients with epilepsy and supports the hypothesis of hyperexcitability in patients with AD. The lack of a significant difference in hippocampal rCBF may be due to an increased frequency of epileptiform discharges in patients with AD.

TRIAL REGISTRATION

The study is registered at clinicaltrials.gov (NCT04436341).

Longitudinal default mode sub-networks in the language and visual variants of Alzheimer's disease

Disruption of the default mode network is a hallmark of Alzheimer's disease, which has not been extensively examined in atypical phenotypes. We investigated cross-sectional and 1-year longitudinal changes in default mode network sub-systems in the visual and language variants of Alzheimer's disease, in relation to age and tau. Sixty-one amyloid-positive Alzheimer's disease participants diagnosed with posterior cortical atrophy (n = 33) or logopenic progressive aphasia (n = 28) underwent structural MRI, resting-state functional MRI and [18F]flortaucipir PET. One-hundred and twenty-two amyloid-negative cognitively unimpaired individuals and 60 amyloid-positive individuals diagnosed with amnestic Alzheimer's disease were included as controls and as a comparison group, respectively, and had structural and resting-state functional MRI. Forty-one atypical Alzheimer's disease participants, 26 amnestic Alzheimer's disease participants and 40 cognitively unimpaired individuals had one follow-up functional MRI ∼1-2 years after the baseline scan. Default mode network connectivity was calculated using the dual regression method for posterior, ventral, anterior ventral and anterior dorsal sub-systems derived from independent component analysis. A global measure of default mode network connectivity, the network failure quotient, was also calculated. Linear mixed-effects models and voxel-based analyses were computed for each connectivity measure. Both atypical and amnestic Alzheimer's disease participants had lower cross-sectional posterior and ventral and higher anterior dorsal connectivity and network failure quotient relative to cognitively unimpaired individuals. Age had opposite effects on connectivity in Alzheimer's disease participants and cognitively unimpaired individuals. While connectivity declined with age in cognitively unimpaired individuals, younger Alzheimer's disease participants had lower connectivity than the older ones, particularly in the ventral default mode network. Greater baseline tau-PET uptake was associated with lower ventral and anterior ventral default mode network connectivity in atypical Alzheimer's disease. Connectivity in the ventral default mode network declined over time in atypical Alzheimer's disease, particularly in older participants, with lower tau burden. Voxel-based analyses validated the findings of higher anterior dorsal default mode network connectivity, lower posterior and ventral default mode network connectivity and decline in ventral default mode network connectivity over time in atypical Alzheimer's disease. Visuospatial symptoms were associated with default mode network connectivity disruption. In summary, default mode connectivity disruption was similar between atypical and amnestic Alzheimer's disease variants, and discriminated Alzheimer's disease from cognitively unimpaired individuals, with decreased posterior and increased anterior connectivity and with disruption more pronounced in younger participants. The ventral default mode network declined over time in atypical Alzheimer's disease, suggesting a shift in default mode network connectivity likely related to tau pathology.

A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles

Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.

Resting-state functional connectivity changes in older adults with sleep disturbance and the role of amyloid burden

Sleep and related disorders could lead to changes in various brain networks, but little is known about the role of amyloid β (Aβ) burden-a key Alzheimer's disease (AD) biomarker-in the relationship between sleep disturbance and altered resting state functional connectivity (rsFC) in older adults. This cross-sectional study examined the association between sleep disturbance, Aβ burden, and rsFC using a large-scale dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sample included 489 individuals (53.6% cognitively normal, 32.5% mild cognitive impairment, and 13.9% AD) who had completed sleep measures (Neuropsychiatric Inventory), PET Aβ data, and resting-state fMRI scans at baseline. Within and between rsFC of the Salience (SN), the Default Mode (DMN) and the Frontal Parietal network (FPN) were compared between participants with sleep disturbance versus without sleep disturbance. The interaction between Aβ positivity and sleep disturbance was evaluated using the linear regressions, controlling for age, diagnosis status, gender, sedatives and hypnotics use, and hypertension. Although no significant main effect of sleep disturbance was found on rsFC, a significant interaction term emerged between sleep disturbance and Aβ burden on rsFC of SN (β = 0.11, P = 0.006). Specifically, sleep disturbance was associated with SN hyperconnectivity, only with the presence of Aβ burden. Sleep disturbance may lead to altered connectivity in the SN when Aβ is accumulated in the brain. Individuals with AD pathology may be at increased risk for sleep-related aberrant rsFC; therefore, identifying and treating sleep problems in these individuals may help prevent further disease progression.

Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight

Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.

Depression Is Associated with the Aberration of Resting State Default Mode Network Functional Connectivity in Patients with Amyloid-Positive Mild Cognitive Impairment

Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia, and a significant number of individuals with MCI progress to develop dementia. Depression is prevalent in MCI patients and has been found to influence the disease progression of MCI. The default mode network (DMN), a brain network associated with Alzheimer's disease (AD), and its functional connectivity might be a neurological mechanism linking depression and AD. However, the relationship between depression, DMN functional connectivity, and cerebral beta-amyloid (Aβ) pathology remains unclear. This study aimed to investigate DMN functional connectivity differences in Aβ-positive MCI patients with depression compared to those without depression. A total of 126 Aβ-positive MCI patients were included, with 66 having depression and 60 without depression. The results revealed increased functional connectivity in the anterior DMN in the depression group compared to the non-depression group. The functional connectivity of the anterior DMN positively correlated with depression severity but not with Aβ deposition. Our findings suggest that depression influences DMN functional connectivity in Aβ-positive MCI patients, and the depression-associated DMN functional connectivity aberrance might be an important neural mechanism linking depression, Aβ pathology, and disease progression in the trajectory of AD.

Amyloid β-based therapy for Alzheimer's disease: challenges, successes and future

Amyloid β protein (Aβ) is the main component of neuritic plaques in Alzheimer's disease (AD), and its accumulation has been considered as the molecular driver of Alzheimer's pathogenesis and progression. Aβ has been the prime target for the development of AD therapy. However, the repeated failures of Aβ-targeted clinical trials have cast considerable doubt on the amyloid cascade hypothesis and whether the development of Alzheimer's drug has followed the correct course. However, the recent successes of Aβ targeted trials have assuaged those doubts. In this review, we discussed the evolution of the amyloid cascade hypothesis over the last 30 years and summarized its application in Alzheimer's diagnosis and modification. In particular, we extensively discussed the pitfalls, promises and important unanswered questions regarding the current anti-Aβ therapy, as well as strategies for further study and development of more feasible Aβ-targeted approaches in the optimization of AD prevention and treatment.

Application of data harmonization and tract-based spatial statistics reveals white matter structural abnormalities in pediatric patients with focal cortical dysplasia

Our study assessed diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) in pediatric subjects with epilepsy secondary to Focal Cortical Dysplasia (FCD) to improve our understanding of structural network changes associated with FCD related epilepsy. We utilized a data harmonization (DH) approach to minimize confounding effects induced by MRI protocol differences. We also assessed correlations between DTI metrics and neurocognitive measures of the fluid reasoning index (FRI), verbal comprehension index (VCI), and visuospatial index (VSI). Data (n = 51) from 23 FCD patients and 28 typically developing controls (TD) scanned clinically on either 1.5T, 3T, or 3T-wide-bore MRI were retrospectively analyzed. Tract-based spatial statistics (TBSS) with threshold-free cluster enhancement and permutation testing with 100,000 permutations were used for statistical analysis. To account for imaging protocol differences, we employed non-parametric data harmonization prior to permutation testing. Our analysis demonstrates that DH effectively removed MRI protocol-based differences typical in clinical acquisitions while preserving group differences in DTI metrics between FCD and TD subjects. Furthermore, DH strengthened the association between DTI metrics and neurocognitive indices. Fractional anisotropy, MD, and RD metrics showed stronger correlation with FRI and VSI than VCI. Our results demonstrate that DH is an integral step to reduce the confounding effect of MRI protocol differences during the analysis of white matter tracts and highlights biological differences between FCD and healthy control subjects. Characterization of white matter changes associated with FCD-related epilepsy may better inform prognosis and treatment approaches.

Resting-State Functional Connectivity Changes in Older Adults with Sleep Disturbance and the Role of Amyloid Burden

Sleep and related disorders could lead to changes in various brain networks, but little is known about the role of amyloid β (Aβ) burden-a key Alzheimer's disease (AD) biomarker-in the relationship between sleep disturbance and altered resting state functional connectivity (rsFC) in older adults. This cross-sectional study examined the association between sleep disturbance, Aβ burden, and rsFC using a large-scale dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sample included 489 individuals (53.6% cognitively normal, 32.5% mild cognitive impairment, and 13.9% AD) who had completed sleep measures (Neuropsychiatric Inventory), PET Aβ data, and resting-state fMRI scans at baseline. Within and between rsFC of the Salience (SN), the Default Mode (DMN) and the Frontal Parietal network (FPN) were compared between participants with sleep disturbance versus without sleep disturbance. The interaction between Aβ positivity and sleep disturbance was evaluated using linear regressions, controlling for age, diagnosis status, gender, sedatives and hypnotics use, and hypertension. Although no significant main effect of sleep disturbance was found on rsFC, a significant interaction term emerged between sleep disturbance and Aβ burden on rsFC of SN (β=0.11, P=0.006). Specifically, sleep disturbance was associated with SN hyperconnectivity, only with the presence of Aβ burden. Sleep disturbance may lead to altered connectivity in the SN when Aβ is accumulated in the brain. Individuals with AD pathology may be at increased risk for sleep-related aberrant rsFC; therefore, identifying and treating sleep problems in these individuals may help prevent further disease progression.

Functional networks in prolonged disorders of consciousness

Prolonged disorders of consciousness (DoC) are characterized by extended disruptions of brain activities that sustain wakefulness and awareness and are caused by various etiologies. During the past decades, neuroimaging has been a practical method of investigation in basic and clinical research to identify how brain properties interact in different levels of consciousness. Resting-state functional connectivity within and between canonical cortical networks correlates with consciousness by a calculation of the associated temporal blood oxygen level-dependent (BOLD) signal process during functional MRI (fMRI) and reveals the brain function of patients with prolonged DoC. There are certain brain networks including the default mode, dorsal attention, executive control, salience, auditory, visual, and sensorimotor networks that have been reported to be altered in low-level states of consciousness under either pathological or physiological states. Analysis of brain network connections based on functional imaging contributes to more accurate judgments of consciousness level and prognosis at the brain level. In this review, neurobehavioral evaluation of prolonged DoC and the functional connectivity within brain networks based on resting-state fMRI were reviewed to provide reference values for clinical diagnosis and prognostic evaluation.

Differences in resting state functional connectivity underlie visuomotor performance declines in older adults with a genetic risk (APOE ε4) for Alzheimer’s disease

Introduction

Non-standard visuomotor integration requires the interaction of large networks in the brain. Previous findings have shown that non-standard visuomotor performance is impaired in individuals with specific dementia risk factors (family history of dementia and presence of the APOE ε4 allele) in advance of any cognitive impairments. These findings suggest that visuomotor impairments are associated with early dementia-related brain changes. The current study examined the underlying resting state functional connectivity (RSFC) associated with impaired non-standard visuomotor performance, as well as the impacts of dementia family history, sex, and APOE status.

Methods

Cognitively healthy older adults (n = 48) were tested on four visuomotor tasks where reach and gaze were increasingly spatially dissociated. Participants who had a family history of dementia or the APOE ε4 allele were considered to be at an increased risk for AD. To quantify RSFC within networks of interest, an EPI sequence sensitive to BOLD contrast was collected. The networks of interest were the default mode network (DMN), somatomotor network (SMN), dorsal attention network (DAN), ventral attention network (VAN), and frontoparietal control network (FPN).

Results

Individuals with the ε4 allele showed abnormalities in RSFC between posterior DMN nodes that predicted poorer non-standard visuomotor performance. Specifically, multiple linear regression analyses revealed lower RSFC between the precuneus/posterior cingulate cortex and the left inferior parietal lobule as well as the left parahippocampal cortex. Presence of the APOE ε4 allele also modified the relationship between mean DAN RSFC and visuomotor control, where lower mean RSFC in the DAN predicted worse non-standard visuomotor performance only in APOE ε4 carriers. There were otherwise no effects of family history, APOE ε4 status, or sex on the relationship between RSFC and visuomotor performance for any of the other resting networks.

Conclusion

The preliminary findings provide insight into the impact of APOE ε4-related genetic risk on neural networks underlying complex visuomotor transformations, and demonstrate that the non-standard visuomotor task paradigm discussed in this study may be used as a non-invasive, easily accessible assessment tool for dementia risk.

Dual-probe fluorescence spectroscopy for sensitive quantitation of Alzheimer’s amyloid pathology

Protein misfolding is a prominent pathological hallmark of neurodegenerative disorders, including Alzheimer’s disease (AD). Studies have shown that the diversity of β sheet-rich protein deposits (such as amyloid β plaques and neurofibrillary tangles), present across different brain regions, might underlie different disease phenotypes and only certain types of aggregates might be associated with cognitive decline. Conformationally sensitive fluorescent amyloid probes have the ability to report different structures of protein aggregates by virtue of their shifting emission spectra. Here we defined the binding affinity of the fluorescent amyloid probes BSB and MCAAD to disease-relevant protein aggregates, and combined the two probes to examine formalin-fixed paraffin-embedded mouse and human brain samples. Coupled with quantitative spectral phasor analysis, the dual-probe staining approach revealed remarkable heterogeneity of protein aggregates across the samples. Distinct emission spectra were consistent with certain types of deposits present in the mouse and human brain sections. The sensitivity of this staining, imaging and analysis approach outperformed conventional immunohistochemistry with the detected spectral differences between the greater parenchyma of cognitively normal and AD cases indicating a subtle yet widespread proteopathy associated with disease. Our method offers more sensitive, objective, and quantitative examination of protein misfolding pathology using conventional tissue sections.

Level of Amyloid-β (Aβ) Binding Leading to Differential Effects on Resting State Functional Connectivity in Major Brain Networks

Introduction: Amyloid-β protein (Aβ) is one of the biomarkers for Alzheimer’s disease (AD). The recent application of interhemispheric functional connectivity (IFC) in resting-state fMRI has been used as a non-invasive diagnostic tool for early dementia. In this study, we focused on the level of Aβ accumulated and its effects on the major functional networks, including default mode network (DMN), central executive network (CEN), salience network (SN), self-referential network (SRN) and sensory motor network (SMN). Methods: 58 participants (27 Hi Aβ (HiAmy) and 31 low Aβ (LowAmy)) and 25 healthy controls (HC) were recruited. [¹⁸F]flutemetamol PET/CT was performed for diseased groups, and MRI scanning was done for all participants. Voxel-by-voxel correlation analysis was done for both groups in all networks. Results: In HiAmy, IFC was reduced in all networks except SN. A negative correlation in DMN, CEN, SRN and SMN suggests high Aβ related to IFC reduction; However, a positive correlation in SN suggests high Aβ related to an increase in IFC. In LowAmy, IFC increased in CEN, SMN, SN and SRN. Positive correlation in all major brain networks. Conclusion: The level of Aβ accumulated demonstrated differential effects on IFC in various brain networks. As the treatment to reduce Aβ plaque deposition is available in the market, it may be an option for the HiAmy group to improve their IFC in major brain networks.

Physical activity is associated with increased resting-state functional connectivity in networks predictive of cognitive decline in clinically unimpaired older adults

Introduction

Physical activity (PA) promotes resilience with respect to cognitive decline, although the underlying mechanisms are not well understood. We examined the associations between objectively measured PA and resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) across seven anatomically distributed neural networks.

Methods

rs-fcMRI, amyloid beta (Aβ) positron emission tomography (PET), PA (steps/day × 1 week), and longitudinal cognitive (Preclinical Alzheimer's Cognitive Composite) data from 167 cognitively unimpaired adults (ages 63 to 90) were used. We used linear and linear mixed-effects regression models to examine the associations between baseline PA and baseline network connectivity and between PA, network connectivity, and longitudinal cognitive performance.

Results

Higher PA was associated selectively with greater connectivity in three networks previously associated with cognitive decline (default, salience, left control). This association with network connectivity accounted for a modest portion of PA's effects on Aβ-related cognitive decline.

Discussion

Although other mechanisms are likely present, PA may promote resilience with respect to Aß-related cognitive decline, partly by increasing connectivity in a subset of cognitive networks.

Neuroprotection and Disease Modification by Astrocytes and Microglia in Parkinson Disease

Oxidative stress and neuroinflammation are common bases for disease onset and progression in many neurodegenerative diseases. In Parkinson disease, which is characterized by the degeneration of dopaminergic neurons resulting in dopamine depletion, the pathogenesis differs between hereditary and solitary disease forms and is often unclear. In addition to the pathogenicity of alpha-synuclein as a pathological disease marker, the involvement of dopamine itself and its interactions with glial cells (astrocyte or microglia) have attracted attention. Pacemaking activity, which is a hallmark of dopaminergic neurons, is essential for the homeostatic maintenance of adequate dopamine concentrations in the synaptic cleft, but it imposes a burden on mitochondrial oxidative glucose metabolism, leading to reactive oxygen species production. Astrocytes provide endogenous neuroprotection to the brain by producing and releasing antioxidants in response to oxidative stress. Additionally, the protective function of astrocytes can be modified by microglia. Some types of microglia themselves are thought to exacerbate Parkinson disease by releasing pro-inflammatory factors (M1 microglia). Although these inflammatory microglia may further trigger the inflammatory conversion of astrocytes, microglia may induce astrocytic neuroprotective effects (A2 astrocytes) simultaneously. Interestingly, both astrocytes and microglia express dopamine receptors, which are upregulated in the presence of neuroinflammation. The anti-inflammatory effects of dopamine receptor stimulation are also attracting attention because the functions of astrocytes and microglia are greatly affected by both dopamine depletion and therapeutic dopamine replacement in Parkinson disease. In this review article, we will focus on the antioxidative and anti-inflammatory effects of astrocytes and their synergism with microglia and dopamine.

Impairment of Episodic-Specific Autobiographical Memory in Individuals with Subjective Cognitive Decline and in Patients with Prodromal or Mild Alzheimer's Disease

BACKGROUND

Autobiographical memory (AM) is a personal form of memory that becomes impaired in the early, clinical stages of Alzheimer's disease (AD). In the "preclinical" phase of AD, neuropathological hallmarks are present (especially in a brain network underpinning AM), but performance on standardized neuropsychological tests is normal. Even so, some patients have subjective cognitive decline (SCD).

OBJECTIVE

The aim was to 1) investigate AM performance on two tests with different approaches in SCD, and in prodromal and mild AD, and 2) examine the association between the AM tests.

METHODS

We included 17 SCD patients with heightened risk of AD, 17 amnestic mild cognitive impairment (aMCI) patients, 17 patients with mild dementia due to AD, and 30 healthy controls. Patients were diagnosed according to international criteria, and all participants had MMSE scores≥24. AM was assessed using the Columbia Autobiographical Memory Interview-Short Form (CAMI-SF) and the Three Events Test. These tests measure the production of contextual details.

RESULTS

Significant group effects were found for the Three Events Test and the CAMI-SF. All patient groups produced significantly fewer contextual details than the controls on the Three Events Test. On CAMI-SF, the aMCI and mild AD groups were able to answer fewer questions or gave significantly less detailed answers than the other groups. The SCD patients performed below the controls on CAMI-SF, but the difference was not significant.

CONCLUSION

AM may be impaired in very early AD, even in the phases where standardized episodic memory tests show no decline.

The Amyloid-β Pathway in Alzheimer's Disease

Breakthroughs in molecular medicine have positioned the amyloid-β (Aβ) pathway at the center of Alzheimer's disease (AD) pathophysiology. While the detailed molecular mechanisms of the pathway and the spatial-temporal dynamics leading to synaptic failure, neurodegeneration, and clinical onset are still under intense investigation, the established biochemical alterations of the Aβ cycle remain the core biological hallmark of AD and are promising targets for the development of disease-modifying therapies. Here, we systematically review and update the vast state-of-the-art literature of Aβ science with evidence from basic research studies to human genetic and multi-modal biomarker investigations, which supports a crucial role of Aβ pathway dyshomeostasis in AD pathophysiological dynamics. We discuss the evidence highlighting a differentiated interaction of distinct Aβ species with other AD-related biological mechanisms, such as tau-mediated, neuroimmune and inflammatory changes, as well as a neurochemical imbalance. Through the lens of the latest development of multimodal in vivo biomarkers of AD, this cross-disciplinary review examines the compelling hypothesis- and data-driven rationale for Aβ-targeting therapeutic strategies in development for the early treatment of AD.

Update on neuroimaging in Alzheimer's disease

PURPOSE OF REVIEW

The purpose of this review was to discuss the contribution of the most recent neuroimaging studies to our understanding of the mechanisms underlying Alzheimer's disease.

RECENT FINDINGS

Studies have applied cross-sectional and longitudinal positron emission tomography (PET), structural and resting-state functional magnetic resonance imaging to primarily investigate (1) how Alzheimer's disease pathological hallmarks like tau and amyloid-beta build up and spread across the brain at different disease stage and in different disease phenotypes and (2) how the spreading of these proteins is related to atrophy, to neuronal network disruption and to neuroinflammation.

SUMMARY

The findings of these studies offer insight on the mechanisms that drive the pathological and clinical progression of Alzheimer's disease, highlighting their multifactorial nature, which is a crucial aspect for the development of disease-modifying therapeutics and can be captured with multimodal imaging approaches.

Altered basal forebrain BOLD signal variability at rest in posttraumatic stress disorder: A potential candidate vulnerability mechanism for neurodegeneration in PTSD

Individuals with posttraumatic stress disorder (PTSD) are at increased risk for the development of various forms of dementia. Nevertheless, the neuropathological link between PTSD and neurodegeneration remains unclear. Degeneration of the human basal forebrain constitutes a pathological hallmark of neurodegenerative diseases, such as Alzheimer's and Parkinson's disease. In this seed-based resting-state (rs-)fMRI study identifying as outcome measure the temporal BOLD signal fluctuation magnitude, a seed-to-voxel analyses assessed temporal correlations between the average BOLD signal within a bilateral whole basal forebrain region-of-interest and each whole-brain voxel among individuals with PTSD (n = 65), its dissociative subtype (PTSD+DS) (n = 38) and healthy controls (n = 46). We found that compared both with the PTSD and healthy controls groups, the PTSD+DS group exhibited increased BOLD signal variability within two nuclei of the seed region, specifically in its extended amygdaloid region: the nucleus accumbens and the sublenticular extended amygdala. This finding is provocative, because it mimics staging models of neurodegenerative diseases reporting allocation of neuropathology in early disease stages circumscribed to the basal forebrain. Here, underlying candidate etiopathogenetic mechanisms are neurovascular uncoupling, decreased connectivity in local- and large-scale neural networks, or disrupted mesolimbic dopaminergic circuitry, acting indirectly upon the basal forebrain cholinergic pathways. These abnormalities may underpin reward-related deficits representing a putative link between persistent traumatic memory in PTSD and anterograde memory deficits in neurodegeneration. Observed alterations of the basal forebrain in the dissociative subtype of PTSD point towards the urgent need for further exploration of this region as a potential candidate vulnerability mechanism for neurodegeneration in PTSD.

Association of plasma Aβ40/Aβ42 ratio and brain Aβ accumulation: testing a whole-brain PLS-VIP approach in individuals at risk of Alzheimer's disease

Molecular and brain regional/network-wise pathophysiological changes at preclinical stages of Alzheimer's disease (AD) have primarily been found through knowledge-based studies conducted in late-stage mild cognitive impairment/dementia populations. However, such an approach may compromise the objective of identifying the earliest spatial-temporal pathophysiological processes. We investigated 261 individuals with subjective memory complaints, a condition at increased risk of AD, to test a whole-brain, non-a-priori method based on partial least squares in unraveling the association between plasma Aβ42/Aβ40 ratio and an extensive set of brain regions characterized through molecular imaging of Aβ accumulation and cortical metabolism. Significant associations were mapped onto large-scale networks, identified through an atlas and by knowledge, to elaborate on the reliability of the results. Plasma Aβ42/40 ratio was associated with Aβ-PET uptake (but not FDG-PET) in regions generally investigated in preclinical AD such as those belonging to the default mode network, but also in regions/networks normally not accounted - including the central executive and salience networks - which likely have a selective vulnerability to incipient Aβ accumulation. The present whole-brain approach is promising to investigate early pathophysiological changes of AD to fully capture the complexity of the disease, which is essential to develop timely screening, detection, diagnostic, and therapeutic interventions.

EEG-fMRI Signal Coupling Is Modulated in Subjects With Mild Cognitive Impairment and Amyloid Deposition

Cognitive impairment indicates disturbed brain physiology which can be due to various mechanisms including Alzheimer's pathology. Combined functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) recordings (EEG-fMRI) can assess the interplay between complementary measures of brain activity and EEG changes to be localized to specific brain regions. We used a two-step approach, where we first examined changes related to a syndrome of mild cognitive impairment irrespective of pathology and then studied the specific impact of amyloid pathology. After detailed clinical and neuropsychological characterization as well as a positron emission tomography (PET) scans with the tracer 11-[C]-Pittsburgh Compound B to estimate cerebral amyloid deposition, 14 subjects with mild cognitive impairment (MCI) (mean age 75.6 SD: 8.9) according to standard criteria and 21 cognitively healthy controls (HCS) (mean age 71.8 SD: 4.2) were assessed with EEG-fMRI. Thalamo-cortical alpha-fMRI signal coupling was only observed in HCS. Additional EEG-fMRI signal coupling differences between HCS and MCI were observed in parts of the default mode network, salience network, fronto-parietal network, and thalamus. Individuals with significant cerebral amyloid deposition (amyloid-positive MCI and HCS combined compared to amyloid-negative HCS) displayed abnormal EEG-fMRI signal coupling in visual, fronto-parietal regions but also in the parahippocampus, brain stem, and cerebellum. This finding was paralleled by stronger absolute fMRI signal in the parahippocampus and weaker absolute fMRI signal in the inferior frontal gyrus in amyloid-positive subjects. We conclude that the thalamocortical coupling in the alpha band in HCS more closely reflects previous findings observed in younger adults, while in MCI there is a clearly aberrant coupling in several networks dominated by an anticorrelation in the posterior cingulate cortex. While these findings may broadly indicate physiological changes in MCI, amyloid pathology was specifically associated with abnormal fMRI signal responses and disrupted coupling between brain oscillations and fMRI signal responses, which especially involve core regions of memory: the hippocampus, para-hippocampus, and lateral prefrontal cortex.