The hippocampus as a structural and functional network epicentre for distant cortical thinning in neurocognitive aging

Alterations in grey matter (GM) and white matter (WM) are associated with memory impairment across the neurocognitive aging spectrum and theorised to spread throughout brain networks. Functional and structural connectivity (FC,SC) may explain widespread atrophy. We tested the effect of SC and FC to the hippocampus on cortical thickness (CT) of connected areas. In 419 (223 F) participants (agemean=73 ± 8) from the Alzheimer's Disease Neuroimaging Initiative, cortical regions associated with memory (Rey Auditory Verbal Learning Test) were identified using Lasso regression. Two structural equation models (SEM), for SC and resting-state FC, were fitted including CT areas, and SC and FC to the left and right hippocampus (LHIP,RHIP). LHIP (β=-0.150,p=<.001) and RHIP (β=-0.139,p=<.001) SC predicted left temporopolar/rhinal CT; RHIP SC predicted right temporopolar/rhinal CT (β=-0.191,p=<.001). LHIP SC predicted right fusiform/parahippocampal (β=-0.104,p=.011) and intraparietal sulcus/superior parietal CT (β=0.101,p=.028). Increased RHIP FC predicted higher left inferior parietal CT (β=0.132,p=.042) while increased LHIP FC predicted lower right fusiform/parahippocampal CT (β=-0.97; p=.023). The hippocampi may be epicentres for cortical thinning through disrupted connectivity.

Hub overload and failure as a final common pathway in neurological brain network disorders

Understanding the concept of network hubs and their role in brain disease is now rapidly becoming important for clinical neurology. Hub nodes in brain networks are areas highly connected to the rest of the brain, which handle a large part of all the network traffic. They also show high levels of neural activity and metabolism, which makes them vulnerable to many different types of pathology. The present review examines recent evidence for the prevalence and nature of hub involvement in a variety of neurological disorders, emphasizing common themes across different types of pathology. In focal epilepsy, pathological hubs may play a role in spreading of seizure activity, and removal of such hub nodes is associated with improved outcome. In stroke, damage to hubs is associated with impaired cognitive recovery. Breakdown of optimal brain network organization in multiple sclerosis is accompanied by cognitive dysfunction. In Alzheimer's disease, hyperactive hub nodes are directly associated with amyloid-beta and tau pathology. Early and reliable detection of hub pathology and disturbed connectivity in Alzheimer's disease with imaging and neurophysiological techniques opens up opportunities to detect patients with a network hyperexcitability profile, who could benefit from treatment with anti-epileptic drugs.

Repetitive transcranial magnetic stimulation regulates effective connectivity patterns of brain networks in the spectrum of preclinical Alzheimer's disease

Objectives

Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are considered as the spectrum of preclinical Alzheimer's disease (AD), with abnormal brain network connectivity as the main neuroimaging feature. Repetitive transcranial magnetic stimulation (rTMS) has been proven to be an effective non-invasive technique for addressing neuropsychiatric disorders. This study aims to explore the potential of targeted rTMS to regulate effective connectivity within the default mode network (DMN) and the executive control network (CEN), thereby improving cognitive function.

Methods

This study included 86 healthy controls (HCs), 72 SCDs, and 86 aMCIs. Among them, 10 SCDs and 11 aMCIs received a 2-week rTMS course of 5-day, once-daily. Cross-sectional analysis with the spectral dynamic causal model (spDCM) was used to analyze the DMN and CEN effective connectivity patterns of the three groups. Afterwards, longitudinal analysis was conducted on the changes in effective connectivity patterns and cognitive function before and after rTMS for SCD and aMCI, and the correlation between them was analyzed.

Results

Cross-sectional analysis showed different effective connectivity patterns in the DMN and CEN among the three groups. Longitudinal analysis showed that the effective connectivity pattern of the SCD had changed, accompanied by improvements in episodic memory. Correlation analysis indicated a negative relationship between effective connectivity from the left angular gyrus (ANG) to the anterior cingulate gyrus and the ANG.R to the right middle frontal gyrus, with visuospatial and executive function, respectively. In patients with aMCI, episodic memory and executive function improved, while the effective connectivity pattern remained unchanged.

Conclusion

This study demonstrates that PCUN-targeted rTMS in SCD regulates the abnormal effective connectivity patterns in DMN and CEN, thereby improving cognition function. Conversely, in aMCI, the mechanism of improvement may differ. Our findings further suggest that rTMS is more effective in preventing or delaying disease progression in the earlier stages of the AD spectrum.

Clinical Trial Registration

http://www.chictr.org.cn, ChiCTR2000034533.

How the intrinsic functional connectivity patterns of the semantic network support semantic processing

Semantic processing, a core of language comprehension, involves the activation of brain regions dispersed extensively across the frontal, temporal, and parietal cortices that compose the semantic network. To comprehend the functional structure of this semantic network and how it prepares for semantic processing, we investigated its intrinsic functional connectivity (FC) and the relation between this pattern and semantic processing ability in a large sample from the Human Connectome Project (HCP) dataset. We first defined a well-studied brain network for semantic processing, and then we characterized the within-network connectivity (WNC) and the between-network connectivity (BNC) within this network using a voxel-based global brain connectivity (GBC) method based on resting-state functional magnetic resonance imaging (fMRI). The results showed that 97.73% of the voxels in the semantic network displayed considerably greater WNC than BNC, demonstrating that the semantic network is a fairly encapsulated network. Moreover, multiple connector hubs in the semantic network were identified after applying the criterion of WNC > 1 SD above the mean WNC of the semantic network. More importantly, three of these connector hubs (i.e., the left anterior temporal lobe, angular gyrus, and orbital part of the inferior frontal gyrus) were reliably associated with semantic processing ability. Our findings suggest that the three identified regions use WNC as the central mechanism for supporting semantic processing and that task-independent spontaneous connectivity in the semantic network is essential for semantic processing.

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.

Individual-specific functional connectivity improves prediction of Alzheimer's disease's symptoms in elderly people regardless of APOE ε4 genotype

To date, reliable biomarkers remain unclear that could link functional connectivity to patients' symptoms for detecting and predicting the process from normal aging to Alzheimer's disease (AD) in elderly people with specific genotypes. To address this, individual-specific functional connectivity is constructed for elderly participants with/without APOE ε4 allele. Then, we utilize recursive feature selection-based machine learning to reveal individual brain-behavior relationships and to predict the symptom transition in different genotypes. Our findings reveal that compared with conventional atlas-based functional connectivity, individual-specific functional connectivity exhibits higher classification and prediction performance from normal aging to AD in both APOE ε4 groups, while no significant performance is detected when the data of two genotyping groups are combined. Furthermore, individual-specific between-network connectivity constitutes a major contributor to assessing cognitive symptoms. This study highlights the essential role of individual variation in cortical functional anatomy and the integration of brain and behavior in predicting individualized symptoms.

Amyloid-β Accumulation in Relation to Functional Connectivity in Aging: a Longitudinal Study

The brain undergoes many changes at pathological and functional levels in healthy aging. This study employed a longitudinal and multimodal imaging dataset from the OASIS-3 study (n=300) and explored possible relationships between amyloid beta (Aβ) accumulation and functional brain organization over time in healthy aging. We used positron emission tomography (PET) with Pittsburgh compound-B (PIB) to quantify the Aβ accumulation in the brain and resting-state functional MRI (rs-fMRI) to measure functional connectivity (FC) among brain regions. Each participant had at least 2 to 3 follow-up visits. A linear mixed-effect model was used to examine longitudinal changes of Aβ accumulation and FC throughout the whole brain. We found that the limbic and frontoparietal networks had a greater annual Aβ accumulation and a slower decline in FC in aging. Additionally, the amount of the Aβ deposition in the amygdala network at baseline slowed down the decline in its FC in aging. Furthermore, the functional connectivity of the limbic, default mode network (DMN), and frontoparietal networks accelerated the Aβ propagation across their functionally highly connected regions. The functional connectivity of the somatomotor and visual networks accelerated the Aβ propagation across the brain regions in the limbic, frontoparietal, and DMN networks. These findings suggested that the slower decline in the functional connectivity of the functional hubs may compensate for their greater Aβ accumulation in aging. The Aβ propagation from one brain region to the other may depend on their functional connectivity strength.

Default mode network failure and neurodegeneration across aging and amnestic and dysexecutive Alzheimer's disease

From a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer's disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals (N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer's disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic (N = 8) or dysexecutive (N = 10) Alzheimer's disease from the normative cohort at the patient level, as well as between Alzheimer's disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer's disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer's disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer's disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer's disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer's disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer's disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials.

A Residual Marker of Cognitive Reserve Is Associated with Resting-State Intrinsic Functional Connectivity Along the Alzheimer's Disease Continuum

BACKGROUND

Cognitive reserve (CR) explains inter-individual differences in the impact of the neurodegenerative burden on cognitive functioning. A residual model was proposed to estimate CR more accurately than previous measures. However, associations between residual CR markers (CRM) and functional connectivity (FC) remain unexplored.

OBJECTIVE

To explore the associations between the CRM and intrinsic network connectivity (INC) in resting-state networks along the neuropathological-continuum of Alzheimer's disease (ADN).

METHODS

Three hundred eighteen participants from the DELCODE cohort were stratified using cerebrospinal fluid biomarkers according to the A(myloid-β)/T(au)/N(eurodegeneration) classification. CRM was calculated utilizing residuals obtained from a multilinear regression model predicting cognition from markers of disease burden. Using an independent component analysis in resting-state fMRI data, we measured INC of resting-state networks, i.e., default mode network (DMN), frontoparietal network (FPN), salience network (SAL), and dorsal attention network. The associations of INC with a composite memory score and CRM and the associations of CRM with the seed-to-voxel functional connectivity of memory-related were tested in general linear models.

RESULTS

CRM was positively associated with INC in the DMN in the entire cohort. The A+T+N+ group revealed an anti-correlation between the SAL and the DMN. Furthermore, CRM was positively associated with anti-correlation between memory-related regions in FPN and DMN in ADN and A+T/N+.

CONCLUSION

Our results provide evidence that INC is associated with CRM in ADN defined as participants with amyloid pathology with or without cognitive symptoms, suggesting that the neural correlates of CR are mirrored in network FC in resting-state.

Longitudinal Spatial Relationships Between Atrophy and Hypometabolism Across the Alzheimer's Disease Continuum

BACKGROUND

The A/T/N framework allows for the assessment of pathology-specific markers of MRI-derived structural atrophy and hypometabolism on 18FDG-PET. However, how these measures relate to each other locally and distantly across pathology-defined A/T/N groups is currently unclear.

OBJECTIVE

To determine the regions of association between atrophy and hypometabolism in A/T/N groups both within and across time points.

METHODS

We examined multivariate multimodal neuroimaging relationships between MRI and 18FDG-PET among suspected non-Alzheimer's disease pathology (SNAP) (A-T/N+; n = 14), Amyloid Only (A+T-N-; n = 24) and Probable AD (A+T+N+; n = 77) groups. Sparse canonical correlation analyses were employed to model spatially disjointed regions of association between MRI and 18FDG-PET data. These relationships were assessed at three combinations of time points -cross-sectionally, between baseline visits and between month 12 (M-12) follow-up visits, as well as longitudinally between baseline and M-12 follow-up.

RESULTS

In the SNAP group, spatially overlapping relationships between atrophy and hypometabolism were apparent in the bilateral temporal lobes when both modalities were assessed at the M-12 timepoint. Amyloid-Only subjects showed spatially discordant distributed atrophy-hypometabolism relationships at all time points assessed. In Probable AD subjects, local correlations were evident in the bilateral temporal lobes when both modalities were assessed at baseline and at M-12. Across groups, hypometabolism at baseline correlated with non-local, or distant, atrophy at M-12.

CONCLUSION

These results support the view that local concordance of atrophy and hypometabolism is the result of a tau-mediated process driving neurodegeneration.

The human functional connectome in neurodegenerative diseases: relationship to pathology and clinical progression

INTRODUCTION

Neurodegenerative diseases can be considered as 'disconnection syndromes,' in which a communication breakdown prompts cognitive or motor dysfunction. Mathematical models applied to functional resting-state MRI allow for the organization of the brain into nodes and edges, which interact to form the functional brain connectome.

AREAS COVERED

The authors discuss the recent applications of functional connectomics to neurodegenerative diseases, from preclinical diagnosis, to follow up along with the progressive changes in network organization, to the prediction of the progressive spread of neurodegeneration, to stratification of patients into prognostic groups, and to record responses to treatment. The authors searched PubMed using the terms 'neurodegenerative diseases' AND 'fMRI' AND 'functional connectome' OR 'functional connectivity' AND 'connectomics' OR 'graph metrics' OR 'graph analysis.' The time range covered the past 20 years.

EXPERT OPINION

Considering the great pathological and phenotypical heterogeneity of neurodegenerative diseases, identifying a common framework to diagnose, monitor and elaborate prognostic models is challenging. Graph analysis can describe the complexity of brain architectural rearrangements supporting the network-based hypothesis as unifying pathogenetic mechanism. Although a multidisciplinary team is needed to overcome the limit of methodologic complexity in clinical application, advanced methodologies are valuable tools to better characterize functional disconnection in neurodegeneration.

Subjective cognitive decline may mediate the occurrence of postoperative delirium by P-tau undergoing total hip replacement: The PNDABLE study

OBJECTIVE

We again investigated the relationship between subjective cognitive decline (SCD) and postoperative delirium (POD) with a larger sample queue. We also determined whether SCD could cause the occurrence of POD through cerebrospinal fluid (CSF) biomarkers.

METHODS

A prospective, observational cohort study was implemented in the Qingdao Municipal Hospital Affiliated with Qingdao University. This study recruited 1,471 qualified patients affiliated with the Perioperative Neurocognitive Disorder And Biomarker Lifestyle (PNDABLE) study scheduled for total hip replacement under combined spinal and epidural anesthesia from June 2020 to May 2022. The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) were used to assess the cognitive level of the patients the day before surgery. Pittsburgh sleeps quality index (PSQI) scale was used to assess sleep status. Patients were divided into the SCD group and the non-SCD (NSCD) group based on the Subjective Cognitive Decline Scale (SCDS). CSF was collected after a successful spinal-epidural combined puncture, and amyloid-β40 (Aβ40), amyloid-β42 (Aβ42), total tau (T-tau), and phosphorylated tau (P-Tau) in CSF were analyzed by enzyme-linked immunosorbent assays. After the surgery, the incidence of POD was determined by the Confusion Assessment Scale (CAM), and Memorial Delirium Assessment Scale (MDAS) score was used to determine the severity of POD. Logistic regression and sensitivity analyses were performed to determine the relationship between CSF biomarkers, SCD, and POD. The mediating effect was used to analyze the function of specific CSF biomarkers in the relationship between SCD and POD. The risk factors of SCD were also separately verified by logistic regression and sensitivity analysis models.

RESULTS

The total incidence rate of POD was 19.60% (n = 225/1148), which was 29.3% (n = 120/409) in the SCD group and 14.2% (n = 105/739) in the NSCD group. We comprehensively considered the effect of covariates such as age, hypertension, and diabetes. Multivariate logistic regression analysis showed that SCD (OR = 1.467, 95%CI: 1.015-2.120, p = 0.042) and P-tau (OR = 1.046, 95%CI: 1.028-1.063, p < 0.001) were risk factors for POD. The sensitivity analysis results were consistent with the above results. Mediation analysis showed that the relationship between SCD and POD was partially mediated by P-tau, which accounted for 31.25% (P-tau, IE = 4.279 × 10-2, p < 0.001). For SCD, the results of logistic regression analysis models showed that age (OR = 1.035, 95% CI: 1.020-1.049, p < 0.001), higher preoperative PSQI score (OR = 1.047, 95%CI: 1.014-1.080, p = 0.005), and P-tau (OR = 1.015, 95%CI: 1.002-1.028, p = 0.021) were risk factors for SCD, and subsequent sensitivity analysis confirmed this result after adjustment for ASA grade, height, and weight.

CONCLUSION

Patients with SCD are more likely to develop POD undergoing total hip replacement, and SCD can mediate the occurrence of POD via P-tau.

CLINICAL TRIAL REGISTRATION

This study was registered at China Clinical Trial Registry (Chictr2000033439).

Static and dynamic functional connectivity variability of the anterior-posterior hippocampus with subjective cognitive decline

Background

Subjective cognitive decline (SCD) is a putative Alzheimer’s disease (AD) precursor without objective neuropsychological deficits. The hippocampus plays an important role in cognitive function and emotional responses and is generally aberrant in SCD. However, previous studies have mainly focused on static functional connectivity (sFC) by resting-state functional magnetic resonance imaging (fMRI) in SCD individuals, and it remains unclear whether hippocampal dynamic functional connectivity (dFC) changes exist in SCD and whether those changes are associated with subtle changes in cognitive function or affect.

Methods

Seventy SCD patients and 65 healthy controls were recruited. Demographic data, comprehensive neuropsychology assessments, and resting-state fMRI data were collected. The bilateral anterior and posterior hippocampi were selected as seeds to investigate the static and dynamic functional connectivity alterations in SCD.

Results

Compared to healthy controls, subjects with SCD exhibited: (1) decreased sFC between the left caudal hippocampus and left precuneus; (2) decreased dFC variability between the bilateral caudal hippocampus and precuneus; (3) increased dFC variability between the bilateral rostral hippocampus and caudate nucleus; and (4) increased dFC variability between the left rostral hippocampus and left olfactory cortex. Additionally, the attention scores were positively correlated with dFC variability between the left posterior hippocampus and left precuneus, and the dFC variability between the bilateral anterior hippocampus and caudate nucleus was positively correlated with depression scores and negatively correlated with global cognition scores.

Conclusion

SCD individuals exhibited abnormal sFC and dFC in the anterior-posterior hippocampus, and abnormal dFC was more widespread than abnormal sFC. A combination of sFC and dFC provides a new perspective for exploring the brain pathophysiological mechanisms in SCD and offers potential neuroimaging biomarkers for the early diagnosis and intervention of AD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01066-9.

Disrupted olfactory functional connectivity in patients with late-life depression

BACKGROUND

Odor identification (OI) impairment increases the risk of Alzheimer's disease and brain abnormalities in patients with late-life depression (LLD). However, it remains unclear whether abnormal functional connectivity (FC) of olfactory regions is involved in the relationship between OI impairment and dementia risk in LLD patients. The current study aims to explore the olfactory FC patterns of LLD patients and how olfactory FCs mediate the relationship between OI and cognition.

METHODS

A total of 150 participants underwent resting-state functional magnetic resonance imaging and psychometric and olfactory assessments. The primary and secondary olfactory regions were selected as regions of interest to investigate olfactory FC patterns and their association with OI and cognitive performance in LLD patients.

RESULTS

Compared with LLD patients without OI impairment and normal controls, LLD patients with OI impairment exhibited increased FC between the left orbital frontal cortex (OFC) and left calcarine gyrus, between the left OFC and right lingual gyrus, between the right OFC and right rectus gyrus, and decreased FC between the right piriform cortex and right superior parietal lobule. Additionally, these abnormal FCs were associated with scores of OI, global cognition and language function. Finally, the FC between the right piriform cortex and right superior parietal lobule exhibited a partially mediated effect on the relationship between OI and MMSE scores.

LIMITATIONS

The present study did not exclude the possible effect of drugs.

CONCLUSION

LLD patients with OI impairment exhibited more disrupted olfactory FC (a decrease in the primary olfactory cortex and an increase in the secondary olfactory cortex) than LLD patients with intact OI, and these abnormal FCs may serve as potential targets for neuromodulation in LLD patients to prevent them from developing dementia.

Disrupted coupling between salience network segregation and glucose metabolism is associated with cognitive decline in Alzheimer's disease - A simultaneous resting-state FDG-PET/fMRI study

•

Hybrid PET/MRI was used to explore network segregation and glucose metabolism in AD.

•

DMN, CEN, and SN showed reduced segregation in AD.

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In salience network, segregation coupled with glucose metabolism in CN group.

•

The coupled segregation and glucose metabolism in CN disappeared in MCI and AD.

•

Reduced segregation and hypometabolism were associated with cognitive impairments.

The aberrant organization and functioning of three core neurocognitive networks (NCNs), i.e., default-mode network (DMN), central executive network (CEN), and salience network (SN), are among the prominent features in Alzheimer’s disease (AD). The dysregulation of both intra- and inter-network functional connectivities (FCs) of the three NCNs contributed to AD-related cognitive and behavioral abnormalities. Brain functional network segregation, integrating intra- and inter-network FCs, is essential for maintaining the energetic efficiency of brain metabolism. The association of brain functional network segregation, together with glucose metabolism, with age-related cognitive decline was recently shown. Yet how these joint functional-metabolic biomarkers relate to cognitive decline along with mild cognitive impairment (MCI) and AD remains to be elucidated. In this study, under the framework of the triple-network model, we performed a hybrid FDG-PET/fMRI study to evaluate the concurrent changes of resting-state brain intrinsic FCs and glucose metabolism of the three NCNs across cognitively normal (CN) (N = 24), MCI (N = 21), and AD (N = 21) groups. Lower network segregation and glucose metabolism were observed in all three NCNs in patients with AD. More interestingly, in the SN, the coupled relationship between network segregation and glucose metabolism existed in the CN group (r = 0.523, p = 0.013) and diminished in patients with MCI (r = 0.431, p = 0.065) and AD (r = 0.079, p = 0.748). Finally, the glucose metabolism of the DMN (r = 0.380, p = 0.017) and the network segregation of the SN (r = 0.363, p = 0.023) were significantly correlated with the general cognitive status of the patients. Our findings suggest that the impaired SN segregation and its uncoupled relationship with glucose metabolism contribute to the cognitive decline in AD.

Network-wise concordance of multimodal neuroimaging features across the Alzheimer's disease continuum

Background

Concordance between cortical atrophy and cortical glucose hypometabolism within distributed brain networks was evaluated among cerebrospinal fluid (CSF) biomarker-defined amyloid/tau/neurodegeneration (A/T/N) groups.

Method

We computed correlations between cortical thickness and fluorodeoxyglucose metabolism within 12 functional brain networks. Differences among A/T/N groups (biomarker normal [BN], Alzheimer's disease [AD] continuum, suspected non-AD pathologic change [SNAP]) in network concordance and relationships to longitudinal change in cognition were assessed.

Results

Network-wise markers of concordance distinguish SNAP subjects from BN subjects within the posterior multimodal and language networks. AD-continuum subjects showed increased concordance in 9/12 networks assessed compared to BN subjects, as well as widespread atrophy and hypometabolism. Baseline network concordance was associated with longitudinal change in a composite memory variable in both SNAP and AD-continuum subjects.

Conclusions

Our novel study investigates the interrelationships between atrophy and hypometabolism across brain networks in A/T/N groups, helping disentangle the structure-function relationships that contribute to both clinical outcomes and diagnostic uncertainty in AD.

Vascular Health Is Associated With Functional Connectivity Decline in Higher-Order Networks of Older Adults

Background

Poor vascular health may impede brain functioning in older adults, thus possibly increasing the risk of cognitive decline and Alzheimer’s disease (AD). The emerging link between vascular risk factors (VRF) and longitudinal decline in resting-state functional connectivity (RSFC) within functional brain networks needs replication and further research in independent cohorts.

Method

We examined 95 non-demented older adults using the IMAP+ cohort (Caen, France). VRF were assessed at baseline through systolic and diastolic blood pressure, body-mass-index, and glycated hemoglobin (HbA1c) levels. Brain pathological burden was measured using white matter hyperintensity (WMH) volumes, derived from FLAIR images, and cortical β-Amyloid (Aβ) deposition, derived from florbetapir-PET imaging. RSFC was estimated from functional MRI scans within canonical brain networks at baseline and up to 3 years of follow-up. Linear mixed-effects models evaluated the independent predictive value of VRF on longitudinal changes in network-specific and global RSFC as well as a potential association between these RSFC changes and cognitive decline.

Results

We replicate that RSFC increased over time in global RSFC and in the default-mode, salience/ventral-attention and fronto-parietal networks. In contrast, higher diastolic blood pressure levels were independently associated with a decrease of RSFC over time in the default-mode, salience/ventral-attention, and fronto-parietal networks. Moreover, higher HbA1c levels were independently associated with a reduction of the observed RSFC increase over time in the salience/ventral-attention network. Both of these associations were independent of brain pathology related to Aβ load and WMH volumes. The VRF-related changes in RSFC over time were not significantly associated with longitudinal changes in cognitive performance.

Conclusion

Our longitudinal findings corroborate that VRF promote RSFC alterations over time within higher-order brain networks, irrespective of pathological brain burden. Altered RSFC in large-scale cognitive networks may eventually increase the vulnerability to aging and AD.

Medial Temporal Lobe Networks in Alzheimer's Disease: Structural and Molecular Vulnerabilities

The medial temporal lobe (MTL) is connected to the rest of the brain through two main networks: the anterior-temporal (AT) and the posterior-medial (PM) systems. Given the crucial role of the MTL and networks in the physiopathology of Alzheimer's disease (AD), the present study aimed at (1) investigating whether MTL atrophy propagates specifically within the AT and PM networks, and (2) evaluating the vulnerability of these networks to AD proteinopathies. To do that, we used neuroimaging data acquired in human male and female in three distinct cohorts: (1) resting-state functional MRI (rs-fMRI) from the aging brain cohort (ABC) to define the AT and PM networks (n = 68); (2) longitudinal structural MRI from Alzheimer's disease neuroimaging initiative (ADNI)GO/2 to highlight structural covariance patterns (n = 349); and (3) positron emission tomography (PET) data from ADNI3 to evaluate the networks' vulnerability to amyloid and tau (n = 186). Our results suggest that the atrophy of distinct MTL subregions propagates within the AT and PM networks in a dissociable manner. Brodmann area (BA)35 structurally covaried within the AT network while the parahippocampal cortex (PHC) covaried within the PM network. In addition, these networks are differentially associated with relative tau and amyloid burden, with higher tau levels in AT than in PM and higher amyloid levels in PM than in AT. Our results also suggest differences in the relative burden of tau species. The current results provide further support for the notion that two distinct MTL networks display differential alterations in the context of AD. These findings have important implications for disease spread and the cognitive manifestations of AD.SIGNIFICANCE STATEMENT The current study provides further support for the notion that two distinct medial temporal lobe (MTL) networks, i.e., anterior-temporal (AT) and the posterior-medial (PM), display differential alterations in the context of Alzheimer's disease (AD). Importantly, neurodegeneration appears to occur within these networks in a dissociable manner marked by their covariance patterns. In addition, the AT and PM networks are also differentially associated with relative tau and amyloid burden, and perhaps differences in the relative burden of tau species [e.g., neurofibriliary tangles (NFTs) vs tau in neuritic plaques]. These findings, in the context of a growing literature consistent with the present results, have important implications for disease spread and the cognitive manifestations of AD in light of the differential cognitive processes ascribed to them.

Distinct Functional and Metabolic Alterations of DMN Subsystems in Alzheimer's Disease: A Simultaneous FDG-PET/fMRI Study

The default mode network (DMN) dysfunction has been widely identified in Alzheimer's disease (AD). Increasing evidence has shown that the functional heterogeneity of DMN has been associated with distinct cognitive functions. The pathophysiological changes of these two DMN subsystems, i.e., anterior DMN (aDMN) and posterior DMN (pDMN), also showed different patterns in the AD patients. Yet the underlying metabolic mechanism remains not clear. In this work, we performed a simultaneous FDG-PET/fMRI study, to investigate the distinct functional and metabolic alterations of DMN subsystems in AD. Significantly decreased functional connectivity strength (FCS) in pDMN but not aDMN was found in AD patients. The retaining connectivity in aDMN might represent a compensatory strategy. Concurrently, significant glucose hypometabolism was shown in pDMN and aDMN of AD patients, respectively. Moreover, the reduction of FCS in pDMN was positively correlated with MMSE score of patients. Our study suggests that resting state functional connectivity and glucose metabolism changed differently in the aDMN and pDMN of AD. Our findings brought new insights in understanding the underlying metabolism changes along with functional alterations in AD.

Simultaneous PET/fMRI Detects Distinctive Alterations in Functional Connectivity and Glucose Metabolism of Precuneus Subregions in Alzheimer's Disease

As a central hub in the interconnected brain network, the precuneus has been reported showing disrupted functional connectivity and hypometabolism in Alzheimer's disease (AD). However, as a highly heterogeneous cortical structure, little is known whether individual subregion of the precuneus is uniformly or differentially involved in the progression of AD. To this end, using a hybrid PET/fMRI technique, we compared resting-state functional connectivity strength (FCS) and glucose metabolism in dorsal anterior (DA_pcu), dorsal posterior (DP_pcu) and ventral (V_pcu) subregions of the precuneus among 20 AD patients, 23 mild cognitive impairment (MCI) patients, and 27 matched cognitively normal (CN) subjects. The sub-parcellation of precuneus was performed using a K-means clustering algorithm based on its intra-regional functional connectivity. For the whole precuneus, decreased FCS (p = 0.047) and glucose hypometabolism (p = 0.006) were observed in AD patients compared to CN subjects. For the subregions of the precuneus, decreased FCS was found in DP_pcu of AD patients compared to MCI patients (p = 0.011) and in V_pcu for both MCI (p = 0.006) and AD (p = 0.008) patients compared to CN subjects. Reduced glucose metabolism was found in DP_pcu of AD patients compared to CN subjects (p = 0.038) and in V_pcu of AD patients compared to both MCI patients (p = 0.045) and CN subjects (p < 0.001). For both FCS and glucose metabolism, DA_pcu remained relatively unaffected by AD. Moreover, only in V_pcu, disruptions in FCS (r = 0.498, p = 0.042) and hypometabolism (r = 0.566, p = 0.018) were significantly correlated with the cognitive decline of AD patients. Our results demonstrated a distinctively disrupted functional and metabolic pattern from ventral to dorsal precuneus affected by AD, with V_pcu and DA_pcu being the most vulnerable and conservative subregion, respectively. Findings of this study extend our knowledge on the differential roles of precuneus subregions in AD.

Current directions in tau research: Highlights from Tau 2020

Studies supporting a strong association between tau deposition and neuronal loss, neurodegeneration, and cognitive decline have heightened the allure of tau and tau-related mechanisms as therapeutic targets. In February 2020, leading tau experts from around the world convened for the first-ever Tau2020 Global Conference in Washington, DC, co-organized and cosponsored by the Rainwater Charitable Foundation, the Alzheimer's Association, and CurePSP. Representing academia, industry, government, and the philanthropic sector, presenters and attendees discussed recent advances and current directions in tau research. The meeting provided a unique opportunity to move tau research forward by fostering global partnerships among academia, industry, and other stakeholders and by providing support for new drug discovery programs, groundbreaking research, and emerging tau researchers. The meeting also provided an opportunity for experts to present critical research-advancing tools and insights that are now rapidly accelerating the pace of tau research.

Longitudinal Changes in Hippocampal Network Connectivity in Alzheimer's Disease

Objective

The hippocampus is connected to 2 distinct cortical brain networks, the posterior–medial and the anterior–temporal networks, involving different medial temporal lobe (MTL) subregions. The aim of this study was to assess the functional alterations of these 2 networks, their changes over time, and links to cognition in Alzheimer's disease.

Methods

We assessed MTL connectivity in 53 amyloid‐β–positive patients with mild cognitive impairment and AD dementia and 68 healthy elderly controls, using resting‐state functional magnetic resonance imaging, cross‐sectionally and longitudinally. First, we compared the functional connectivity of the posterior–medial and anterior–temporal networks within the control group to highlight their specificities. Second, we compared the connectivity of these networks between groups, and between baseline and 18‐month follow‐up in patients. Third, we assessed the association in the connectivity changes between the 2 networks, and with cognitive performance.

Results

We found decreased connectivity in patients specifically between the hippocampus and the posterior–medial network, together with increased connectivity between several MTL subregions and the anterior–temporal network. Moreover, changes in the posterior–medial and anterior–temporal networks were interrelated such that decreased MTL–posterior–medial connectivity was associated with increased MTL–anterior–temporal connectivity. Finally, both MTL–posterior–medial decrease and MTL–anterior–temporal increase predicted cognitive decline.

Interpretation

Our findings demonstrate that longitudinal connectivity changes in the posterior–medial and anterior–temporal hippocampal networks are linked together and that they both contribute to cognitive decline in Alzheimer's disease. These results shed light on the critical role of the posterior–medial and anterior–temporal networks in Alzheimer's disease pathophysiology and clinical symptoms. ANN NEUROL 2021;90:391–406

Evaluation of the early-phase [18F]AV45 PET as an optimal surrogate of [18F]FDG PET in ageing and Alzheimer's clinical syndrome

Dual-phase [18F]AV45 positron emission tomography (PET) is highly promising in the assessment of neurodegenerative diseases, allowing to obtain information on both neurodegeneration (early-phase; eAV45) and amyloid deposition (late-phase; lAV45) which are highly complementary; yet eAV45 needs further evaluation. This study aims at validating eAV45 as an optimal proxy of [18F]FDG PET in a large mixed-population of healthy ageing and Alzheimer's clinical syndrome participants (n = 191) who had [18F]FDG PET, eAV45 and lAV45 scans. We found early time frame 0-4 min to give maximal correlation with [18F]FDG PET and minimal correlation with lAV45. Moreover, maximal overlap of [18F]FDG PET versus eAV45 associations with clinical diagnosis and cognition was obtained with pons scaling. Across reference regions, classification performance between clinical subgroups was similar for both eAV45 and [18F]FDG PET. These findings highlight the optimal use of eAV45 to assess neurodegeneration as a validated proxy of [18F]FDG PET. On top of this purpose, this study showed that combined [18F]AV45 PET dual-biomarker even outperformed [18F]FDG PET or lAV45 alone.

Machine learning based on the multimodal connectome can predict the preclinical stage of Alzheimer's disease: a preliminary study

OBJECTIVES

Subjective cognitive decline (SCD) may be a preclinical stage of Alzheimer's disease (AD). Neuroimaging studies suggest that abnormal brain connectivity plays an important role in the pathophysiology of SCD. However, most previous studies focused on single modalities only. Multimodal combinations can more effectively utilize various information and little is known about their diagnostic value in SCD.

METHODS

One hundred ten SCD individuals and well-matched healthy controls (HCs) were recruited in this study (the primary sample: 35 SCD and 36 HC; the validation sample: 21 SCD and 18 HC). Multimodal imaging data were used to construct functional, anatomical, and morphological networks, respectively. These networks were used in combination with a multiple kernel learning-support vector machine to predict SCD individuals. We validated our model on another independent sample. Multiple linear regression (MLR) analyses were conducted to investigate the relationships among network metrics, cognition, and pathological biomarkers.

RESULTS

We found that the characteristics identified from the multimodal network were primarily located in the default mode network (DMN) and salience network (SN), achieving an accuracy of 88.73% (an accuracy of 79.49% for an independent sample) based on the integration of the three modalities. MLR analyses showed that increased AV45 SUVRs were significantly associated with impaired memory function, the enhanced functional connectivity, and the decreased morphological connectivity.

CONCLUSION

This study suggests that abnormal multimodal connections within DMN and SN can be used as effective biomarkers to identify SCD and provide insight into understanding the pathophysiological mechanisms underlying SCD.

KEY POINTS

• Multimodal brain networks improve the detection accuracy of SCD. • Abnormal connections within DMN and SN can be used as effective biomarkers for the identification of SCD.

A Systematic Review of the Association between Amyloid-β and τ Pathology with Functional Connectivity Alterations in the Alzheimer Dementia Spectrum Utilizing PET Scan and rsfMRI

The association between functional connectivity (FC) alterations with amyloid-β (Aβ) and τ protein depositions in Alzheimer dementia is a subject of debate in the current literature. Although many studies have suggested a declining FC accompanying increased Aβ and τ concentrations, some investigations have contradicted this hypothesis. Therefore, this systematic review was conducted to sum up the current literature in this regard. The PROSPERO guideline for systematic reviews was applied for development of a research protocol, and this study was initiated after getting the protocol approval. Studies were screened, and those investigating FC measured by resting-state functional MRI and Aβ and τ protein depositions using amyloid and τ positron emission tomography were included. We categorized the included studies into 3 groups methodologically, addressing the question using global connectivity analysis (examining all regions of interest across the brain based on a functional atlas), seed-based connectivity analysis, or within-networks connectivity analysis. The quality of the studies was assessed using the Newcastle-Ottawa Scale. Among 31 included studies, 14 found both positive and negative correlations depending on the brain region and stage of the investigated disease, while 7 showed an overall negative correlation, 8 indicated an overall positive correlation, and 2 found a nonsignificant association between protein deposition and FC. The investigated regions were illustrated using tables. The posterior default mode network, one of the first regions of amyloid accumulation, and the temporal lobe, the early τ deposition region, are the 2 most investigated regions where inconsistencies exist. In conclusion, our study indicates that transneuronal spreading of τ and the amyloid hypothesis can justify higher FC related to higher protein depositions when global connectivity analysis is applied. However, the discrepancies observed when investigating the brain locally could be due to the varying manifestations of the amyloid and τ overload compensatory mechanisms in the brain at different stages of the disease with hyper- and hypoconnectivity cycles that can occur repeatedly. Nevertheless, further studies investigating both amyloid and τ deposition simultaneously while considering the stage of Alzheimer dementia are required to assess the accuracy of this hypothesis.

Vascular risk factors are associated with a decline in resting-state functional connectivity in cognitively unimpaired individuals at risk for Alzheimer's disease: Vascular risk factors and functional connectivity changes

Resting-state functional connectivity is suggested to be cross-sectionally associated with both vascular burden and Alzheimer's disease (AD) pathology. However, evidence is lacking regarding longitudinal changes in functional connectivity. This study includes 247 cognitively unimpaired individuals with a family history of sporadic AD (185 women/ 62 men; mean [SD] age of 63 [5.3] years). Plasma total-, HDL-, and LDL-cholesterol and systolic and diastolic blood pressure were measured at baseline. Global (whole-brain) brain functional connectivity and connectivity from canonical functional networks were computed from resting-state functional MRI obtained at baseline and ~3.5 years of annual follow-ups, using a predefined functional parcellation. A subsample underwent Aβ- and tau-PET (n=91). Linear mixed-effects models demonstrated that global functional connectivity increased over time across the entire sample. In contrast, higher total-cholesterol and LDL-cholesterol levels were associated with greater reduction of functional connectivity in the default-mode network over time. In addition, higher diastolic blood pressure was associated with global functional connectivity reduction. The associations were similar when the analyses were repeated using two other functional brain parcellations. Aβ and tau deposition in the brain were not associated with changes in functional connectivity over time in the subsample. These findings provide evidence that vascular burden is associated with a decrease in functional connectivity over time in older adults with elevated risk for AD. Future studies are needed to determine if the impact of vascular risk factors on functional brain changes precede the impact of AD pathology on functional brain changes.

Topographic patterns of white matter hyperintensities are associated with multimodal neuroimaging biomarkers of Alzheimer's disease

Background

White matter hyperintensities (WMH) are frequently found in Alzheimer’s disease (AD). Commonly considered as a marker of cerebrovascular disease, regional WMH may be related to pathological hallmarks of AD, including beta-amyloid (Aβ) plaques and neurodegeneration. The aim of this study was to examine the regional distribution of WMH associated with Aβ burden, glucose hypometabolism, and gray matter volume reduction.

Methods

In a total of 155 participants (IMAP+ cohort) across the cognitive continuum from normal cognition to AD dementia, FLAIR MRI, AV45-PET, FDG-PET, and T1 MRI were acquired. WMH were automatically segmented from FLAIR images. Mean levels of neocortical Aβ deposition (AV45-PET), temporo-parietal glucose metabolism (FDG-PET), and medial-temporal gray matter volume (GMV) were extracted from processed images using established AD meta-signature templates. Associations between AD brain biomarkers and WMH, as assessed in region-of-interest and voxel-wise, were examined, adjusting for age, sex, education, and systolic blood pressure.

Results

There were no significant associations between global Aβ burden and region-specific WMH. Voxel-wise WMH in the splenium of the corpus callosum correlated with greater Aβ deposition at a more liberal threshold. Region- and voxel-based WMH in the posterior corpus callosum, along with parietal, occipital, and frontal areas, were associated with lower temporo-parietal glucose metabolism. Similarly, lower medial-temporal GMV correlated with WMH in the posterior corpus callosum in addition to parietal, occipital, and fontal areas.

Conclusions

This study demonstrates that local white matter damage is correlated with multimodal brain biomarkers of AD. Our results highlight modality-specific topographic patterns of WMH, which converged in the posterior white matter. Overall, these cross-sectional findings corroborate associations of regional WMH with AD-typical Aß deposition and neurodegeneration.

Resting state functional atlas and cerebral networks in mouse lemur primates at 11.7 Tesla

Measures of resting-state functional connectivity allow the description of neuronal networks in humans and provide a window on brain function in normal and pathological conditions. Characterizing neuronal networks in animals is complementary to studies in humans to understand how evolution has modelled network architecture. The mouse lemur (Microcebus murinus) is one of the smallest and more phylogenetically distant primates as compared to humans. Characterizing the functional organization of its brain is critical for scientists studying this primate as well as to add a link for comparative animal studies. Here, we created the first functional atlas of mouse lemur brain and describe for the first time its cerebral networks. They were classified as two primary cortical networks (somato-motor and visual), two high-level cortical networks (fronto-parietal and fronto-temporal) and two limbic networks (sensory-limbic and evaluative-limbic). Comparison of mouse lemur and human networks revealed similarities between mouse lemur high-level cortical networks and human networks as the dorsal attentional (DAN), executive control (ECN), and default-mode networks (DMN). These networks were however not homologous, possibly reflecting differential organization of high-level networks. Finally, cerebral hubs were evaluated. They were grouped along an antero-posterior axis in lemurs while they were split into parietal and frontal clusters in humans.

Tau and Amyloid Relationships with Resting-state Functional Connectivity in Atypical Alzheimer's Disease

The mechanisms through which tau and amyloid-beta (Aβ) accumulate in the brain of Alzheimer's disease patients may differ but both are related to neuronal networks. We examined such mechanisms on neuroimaging in 58 participants with atypical Alzheimer's disease (posterior cortical atrophy or logopenic progressive aphasia). Participants underwent Aβ-PET, longitudinal tau-PET, structural MRI and resting-state functional MRI, which was analyzed with graph theory. Regions with high levels of Aβ were more likely to be functional hubs, with a high number of functional connections important for resilience to cascading network failures. Regions with high levels of tau were more likely to have low clustering coefficients and degrees, suggesting a lack of trophic support or vulnerability to local network failures. Regions strongly functionally connected to the disease epicenters were more likely to have higher levels of tau and, less strongly, of Aβ. The regional rate of tau accumulation was associated with tau levels in functionally connected regions, in support of tau accumulation in a functional network. This study elucidates the relations of tau and Aβ to functional connectivity metrics in atypical Alzheimer's disease, strengthening the hypothesis that the spread of the 2 proteins is driven by different biological mechanisms related to functional networks.

Comparison of Amyloid β and Tau Spread Models in Alzheimer's Disease

Tau and amyloid β (Aβ), 2 key pathogenic proteins in Alzheimer's disease (AD), reportedly spread throughout the brain as the disease progresses. Models of how these pathogenic proteins spread from affected to unaffected areas had been proposed based on the observation that these proteins could transmit to other regions either through neural fibers (transneuronal spread model) or through extracellular space (local spread model). In this study, we modeled the spread of tau and Aβ using a graph theoretical approach based on resting-state functional magnetic resonance imaging. We tested whether these models predict the distribution of tau and Aβ in the brains of AD spectrum patients. To assess the models' performance, we calculated spatial correlation between the model-predicted map and the actual map from tau and amyloid positron emission tomography. The transneuronal spread model predicted the distribution of tau and Aβ deposition with significantly higher accuracy than the local spread model. Compared with tau, the local spread model also predicted a comparable portion of Aβ deposition. These findings provide evidence of transneuronal spread of AD pathogenic proteins in a large-scale brain network and furthermore suggest different contributions of spread models for tau and Aβ in AD.

Ambivert degree identifies crucial brain functional hubs and improves detection of Alzheimer's Disease and Autism Spectrum Disorder

Functional modules in the human brain support its drive for specialization whereas brain hubs act as focal points for information integration. Brain hubs are brain regions that have a large number of both within and between module connections. We argue that weak connections in brain functional networks lead to misclassification of brain regions as hubs. In order to resolve this, we propose a new measure called ambivert degree that considers the node's degree as well as connection weights in order to identify nodes with both high degree and high connection weights as hubs. Using resting-state functional MRI scans from the Human Connectome Project, we show that ambivert degree identifies brain hubs that are not only crucial but also invariable across subjects. We hypothesize that nodal measures based on ambivert degree can be effectively used to classify patients from healthy controls for diseases that are known to have widespread hub disruption. Using patient data for Alzheimer's Disease and Autism Spectrum Disorder, we show that the hubs in the patient and healthy groups are very different for both the diseases and deep feedforward neural networks trained on nodal hub features lead to a significantly higher classification accuracy with significantly fewer trainable weights compared to using functional connectivity features. Thus, the ambivert degree improves identification of crucial brain hubs in healthy subjects and can be used as a diagnostic feature to detect neurological diseases characterized by hub disruption.

Functional brain architecture is associated with the rate of tau accumulation in Alzheimer's disease

In Alzheimer's diseases (AD), tau pathology is strongly associated with cognitive decline. Preclinical evidence suggests that tau spreads across connected neurons in an activity-dependent manner. Supporting this, cross-sectional AD studies show that tau deposition patterns resemble functional brain networks. However, whether higher functional connectivity is associated with higher rates of tau accumulation is unclear. Here, we combine resting-state fMRI with longitudinal tau-PET in two independent samples including 53 (ADNI) and 41 (BioFINDER) amyloid-biomarker defined AD subjects and 28 (ADNI) vs. 16 (BioFINDER) amyloid-negative healthy controls. In both samples, AD subjects show faster tau accumulation than controls. Second, in AD, higher fMRI-assessed connectivity between 400 regions of interest (ROIs) is associated with correlated tau-PET accumulation in corresponding ROIs. Third, we show that a model including baseline connectivity and tau-PET is associated with future tau-PET accumulation. Together, connectivity is associated with tau spread in AD, supporting the view of transneuronal tau propagation.

Patient-Tailored, Connectivity-Based Forecasts of Spreading Brain Atrophy

Neurodegenerative diseases appear to progress by spreading via brain connections. Here we evaluated this transneuronal degeneration hypothesis by attempting to predict future atrophy in a longitudinal cohort of patients with behavioral variant frontotemporal dementia (bvFTD) and semantic variant primary progressive aphasia (svPPA). We determined patient-specific "epicenters" at baseline, located each patient's epicenters in the healthy functional connectome, and derived two region-wise graph theoretical metrics to predict future atrophy: (1) shortest path length to the epicenter and (2) nodal hazard, the cumulative atrophy of a region's first-degree neighbors. Using these predictors and baseline atrophy, we could accurately predict longitudinal atrophy in most patients. The regions most vulnerable to subsequent atrophy were functionally connected to the epicenter and had intermediate levels of baseline atrophy. These findings provide novel, longitudinal evidence that neurodegeneration progresses along connectional pathways and, further developed, could lead to network-based clinical tools for prognostication and disease monitoring.

Targeting age-related differences in brain and cognition with multimodal imaging and connectome topography profiling

Aging is characterized by accumulation of structural and metabolic changes in the brain. Recent studies suggest transmodal brain networks are especially sensitive to aging, which, we hypothesize, may be due to their apical position in the cortical hierarchy. Studying an open‐access healthy cohort (n = 102, age range = 30–89 years) with MRI and Aβ PET data, we estimated age‐related cortical thinning, hippocampal atrophy and Aβ deposition. In addition to carrying out surface‐based morphological and metabolic mapping experiments, we stratified effects along neocortical and hippocampal resting‐state functional connectome gradients derived from independent datasets. The cortical gradient depicts an axis of functional differentiation from sensory‐motor regions to transmodal regions, whereas the hippocampal gradient recapitulates its long‐axis. While age‐related thinning and increased Aβ deposition occurred across the entire cortical topography, increased Aβ deposition was especially pronounced toward higher‐order transmodal regions. Age‐related atrophy was greater toward the posterior end of the hippocampal long‐axis. No significant effect of age on Aβ deposition in the hippocampus was observed. Imaging markers correlated with behavioral measures of fluid intelligence and episodic memory in a topography‐specific manner, confirmed using both univariate as well as multivariate analyses. Our results strengthen existing evidence of structural and metabolic change in the aging brain and support the use of connectivity gradients as a compact framework to analyze and conceptualize brain‐based biomarkers of aging.

ASAF: altered spontaneous activity fingerprinting in Alzheimer's disease based on multisite fMRI

Several monocentric studies have noted alterations in spontaneous brain activity in Alzheimer's disease (AD), although there is no consensus on the altered amplitude of low-frequency fluctuations in AD patients. The main aim of the present study was to identify a reliable and reproducible abnormal brain activity pattern in AD. The amplitude of local brain activity (AM), which can provide fast mapping of spontaneous brain activity across the whole brain, was evaluated based on multisite rs-fMRI data for 688 subjects (215 normal controls (NCs), 221 amnestic mild cognitive impairment (aMCI) 252 AD). Two-sample t-tests were used to detect group differences between AD patients and NCs from the same site. Differences in the AM maps were statistically analyzed via the Stouffer's meta-analysis. Consistent regions of lower spontaneous brain activity in the default mode network and increased activity in the bilateral hippocampus/parahippocampus, thalamus, caudate nucleus, orbital part of the middle frontal gyrus and left fusiform were observed in the AD patients compared with those in NCs. Significant correlations (P < 0.05, Bonferroni corrected) between the normalized amplitude index and Mini-Mental State Examination scores were found in the identified brain regions, which indicates that the altered brain activity was associated with cognitive decline in the patients. Multivariate analysis and leave-one-site-out cross-validation led to a 78.49% prediction accuracy for single-patient classification. The altered activity patterns of the identified brain regions were largely correlated with the FDG-PET results from another independent study. These results emphasized the impaired brain activity to provide a robust and reproducible imaging signature of AD.

Evidence of parietal hyperactivation in individuals with mild cognitive impairment who progressed to dementia: A longitudinal fMRI study

Hyperactivation, which is defined as a higher level of activation in patients compared to cognitively unimpaired older adults (controls; CTL), might represent an early signature of Alzheimer's Disease (AD). The goal of this study was to assess the presence and location of hyperactivation in individuals with mild cognitive impairment (MCI) who were later diagnosed with dementia, examine how hyperactivation changes longitudinally, and whether it is related to time before dementia. Forty participants, 26 with MCI and 14 CTL were enrolled in the study. Magnetic resonance imaging was used to measure functional activation while participants encoded word-pairs as well as cortical thickness and regional brain volume at study entry (Y0) and two years later (Y2). Clinical follow-up was completed every two years following study entry to identify progressors (pMCI), that is, individuals who later received a diagnosis of dementia. Task-related activation was assessed in pMCI in both hippocampi and in regions showing greater cortical thinning from Y0 to Y2 compared to CTLs. Hyperactivation was found in pMCI individuals in the right supramarginal gyrus. Persons with pMCI also showed hypoactivation in the left hippocampus and left pars opercularis. Both hyper- and hypoactivation were present at Y0 and Y2 and did not change longitudinally. Activation was not associated with time before dementia diagnosis. Smaller volume and thinner cortical thickness were associated with shorter time to diagnosis in the left hippocampus and left pars opercularis. In conclusion, hyperactivation was found in individuals who later progressed to dementia, confirming that it might represent an early biomarker to identify individuals in the prodromal phase of AD and that its understanding could contribute to elucidate the key brain mechanisms that precede dementia.

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Hyperactivation of the right parietal region was found in MCI progressors.

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Hypoactivation was found in the hippocampal and frontal regions.

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This overall pattern was specific to MCI who progressed to dementia.

Cross-sectional and longitudinal characterization of SCD patients recruited from the community versus from a memory clinic: subjective cognitive decline, psychoaffective factors, cognitive performances, and atrophy progression over time

Background

Subjective cognitive decline (SCD) defines a heterogeneous population, part of which having Alzheimer’s disease (AD). We aimed at characterizing SCD populations according to whether or not they referred to a memory clinic, by assessing the factors associated with increased AD risk.

Methods

Seventy-eight cognitively unimpaired older adults from the IMAP+ study (Caen) were included, amongst which 28 healthy controls (HC) and 50 SCD recruited from the community (SCD-community; n = 23) or from a memory clinic (SCD-clinic; n = 27). Participants underwent cognitive, psychoaffective, structural MRI, FDG-PET, and amyloid-PET assessments. They were followed up over a mean period of 2.4 ± 0.8 years. The groups were compared in terms of baseline and follow-up levels of SCD (self- and informant-reported), cognition, subclinical anxiety and depression, and atrophy progression over time. We also investigated SCD substrates within each SCD group through the correlations between self-reported SCD and other psychometric and brain measures.

Results

Compared to HC, both SCD groups showed similar cognitive performances but higher informant-reported SCD and anxiety. Compared to SCD-community, SCD-clinic showed higher informant-reported SCD, depression score, and atrophy progression over time but similar brain amyloid load. A significant increase over time was found for depression in the SCD-community and for self-reported praxis-domestic activities SCD factor in the SCD-clinic. Higher self-reported SCD correlated with (i) lower grey matter volume and higher anxiety in SCD-community, (ii) greater informant-reported SCD in SCD-clinic, and (iii) lower glucose metabolism in both SCD groups.

Conclusions

Higher subclinical depression and informant-reported SCD specifically characterize the SCD group that refers to a memory clinic. The same group appears as a frailer population than SCD-community as they show greater atrophy progression over time. Yet, both the SCD groups were quite similar otherwise including for brain amyloid load and the SCD-community showed increased depression score over time. Altogether, our findings highlight the relevance of assessing psychoaffective factors and informant-reported SCD in SCD populations and point to both differences and similarities in SCD populations referring or not to a memory clinic.

Electronic supplementary material

The online version of this article (10.1186/s13195-019-0514-z) contains supplementary material, which is available to authorized users.

Theories of Aging and the Prevalence of Alzheimer's Disease

Objective

Aging and AD are associated in some way, then it is reasonable to ask whether or not it is possible to age without AD inexorably appearing at any moment, depending on the period of life. Therefore, the goal of this review is to verify, in light of some aging theories, the prevalence of AD.

Methods

For the purpose of this manuscript, the indexers Alzheimer, aging, Alzheimer, and aging were considered; theories of aging were researched. The research was conducted using PubMed, Medline, Scopus, Elsevier, and Google Scholar.

Results

The most common subjects in the papers analyzed for this manuscript were aging and Alzheimer's disease. The association between Alzheimer and theories of aging seems inconclusive.

Conclusions

Accordingly, the general idea is that AD is associated with aging in such a way that almost all people will present this disease; however, it is plausible to consider that the increase in life expectancy will generate a high prevalence of AD. In a general sense, it seems that the theories of aging explain the origin of AD under superlative and catastrophic considerations and use more biomolecular data than social or behavioral data as the bases of analysis, which may be the problem.

Multimodal Neuroimaging in Alzheimer's Disease: Early Diagnosis, Physiopathological Mechanisms, and Impact of Lifestyle

Over the last ten years, we have conducted research in Alzheimer's disease (AD) using multimodal neuroimaging techniques to improve diagnosis, further our understanding of the pathological mechanisms underlying the disease, and support the development of innovative non-pharmacological preventive strategies. Our works emphasized the interest of hippocampal subfield volumetry in early diagnosis and the need for further development in this field including optimization, standardization, and automatization of the techniques. Also, we conducted several studies in cognitively intact at-risk elderly (e.g., subjective cognitive decline patients and APOE4 carriers) to better identify biomarkers associated with increased risk of developing AD. Regarding the physiopathological mechanisms, specific multimodal neuroimaging techniques allowed us to highlight the relevance of diaschisis, the mismatch between neurodegeneration and local Aβ deposition and the regional variation in the mechanisms underlying structural or functional alterations. Further works integrating other biomarkers known to play a role in the physiopathology of AD (tau, TDP-43, inflammation, etc.) in a longitudinal design would be useful to get a comprehensive understanding of their relative role, sequence, and causal relationships. Our works also highlighted the relevance of functional connectivity in further understanding the specificity of cognitive deficits in AD and how connectivity differentially influences the propagation of the different AD biomarkers. Finally, we conducted several studies on the links between lifestyle factors and neuroimaging biomarkers to unravel mechanisms of reserve. Further efforts are needed to better understand which lifestyle factor, or combination of factors, impact on AD pathology, and when, to help translating our knowledge to training programs that might prevent or delay brain and cognitive changes leading to AD dementia.

Functional connectivity associated with tau levels in ageing, Alzheimer's, and small vessel disease

In Alzheimer's disease, tau pathology spreads hierarchically from the inferior temporal lobe throughout the cortex, ensuing cognitive decline and dementia. Similarly, circumscribed patterns of pathological tau have been observed in normal ageing and small vessel disease, suggesting a spatially ordered distribution of tau pathology across normal ageing and different diseases. In vitro findings suggest that pathological tau may spread 'prion-like' across neuronal connections in an activity-dependent manner. Supporting this notion, functional brain networks show a spatial correspondence to tau deposition patterns. However, it remains unclear whether higher network-connectivity facilitates tau propagation. To address this, we included 55 normal aged elderly (i.e. cognitively normal, amyloid-negative), 50 Alzheimer's disease patients (i.e. amyloid-positive) covering the preclinical to dementia spectrum, as well as 36 patients with pure (i.e. amyloid-negative) vascular cognitive impairment due to small vessel disease. All subjects were assessed with AV1451 tau-PET and resting-state functional MRI. Within each group, we computed atlas-based resting-state functional MRI functional connectivity across 400 regions of interest covering the entire neocortex. Using the same atlas, we also assessed within each group the covariance of tau-PET levels among the 400 regions of interest. We found that higher resting-state functional MRI assessed functional connectivity between any given region of interest pair was associated with higher covariance in tau-PET binding in corresponding regions of interest. This result was consistently found in normal ageing, Alzheimer's disease and vascular cognitive impairment. In particular, inferior temporal tau-hotspots, as defined by highest tau-PET uptake, showed high predictive value of tau-PET levels in functionally closely connected regions of interest. These associations between functional connectivity and tau-PET uptake were detected regardless of presence of dementia symptoms (mild cognitive impairment or dementia), amyloid deposition (as assessed by amyloid-PET) or small vessel disease. Our findings suggest that higher functional connectivity between brain regions is associated with shared tau-levels, supporting the view of prion-like tau spreading facilitated by neural activity.

Alzheimer's disease neuroimaging

PURPOSE OF REVIEW

The aim of this study was to discuss the contribution of neuroimaging studies to our understanding of Alzheimer's disease. We now have the capability of measuring both tau and beta-amyloid (Aβ) proteins in the brain, which together with more traditional neuroimaging modalities, has led the field to focus on using neuroimaging to better characterize disease mechanisms underlying Alzheimer's disease.

RECENT FINDINGS

Studies have utilized tau and Aβ PET, as well as [18F]fluorodeoxyglucose PET, and structural and functional MRI, to investigate the following topics: phenotypic variability in Alzheimer's disease , including how neuroimaging findings are related to clinical phenotype and age; multimodality analyses to investigate the relationships between different neuroimaging modalities and what that teaches us about disease mechanisms; disease staging by assessing neuroimaging changes in the very earliest phases of the disease in cognitively normal individuals and individuals carrying an autosomal dominant Alzheimer's disease mutation; and influence of other comorbidities and proteins to the disease process.

SUMMARY

The findings shed light on the role of tau and Aβ, as well as age and other comorbidities, in the neurodegenerative process in Alzheimer's disease. This knowledge will be crucial in the development of better disease biomarkers and targeted therapeutic approaches.

Brain and cognitive correlates of sleep fragmentation in elderly subjects with and without cognitive deficits

Introduction

Sleep disturbances are increasingly recognized as a risk factor for Alzheimer's disease. However, no study has assessed the relationships between objective sleep fragmentation (SF) and brain and cognitive integrity across different cognitive stages, from cognitively unimpaired elderly subjects to patients with subjective cognitive decline and/or mild cognitive impairment.

Methods

30 cognitively unimpaired elderly participants and 36 patients with subjective cognitive decline and/or mild cognitive impairment underwent a neuropsychological evaluation, structural MRI, ¹⁸F-fluorodeoxyglucose, and ¹⁸F-florbetapir-PET scans, and an actigraphy recording over a minimum of six consecutive nights. Multiple regression and mediation analyses were performed between SF parameters, neuroimaging data, and cognitive scores.

Results

In cognitively unimpaired elderly participants, SF intensity mediated the association between frontohippocampal hypometabolism and lower executive functioning. Moreover, to a lower extent, increased SF variability was related to thalamic atrophy and ventromedial prefrontal amyloid burden. However, in patients with subjective cognitive decline and/or mild cognitive impairment, SF no longer contributed to the expression of cognitive deficits.

Discussion

These findings suggest that SF may directly contribute to lower cognitive performance in cognitively unimpaired elderly subjects. Therefore, treating sleep disturbances before the onset of cognitive deficits may help to cope with brain alterations and maintain cognitive functioning.

Subjective cognitive decline: preclinical manifestation of Alzheimer's disease

Subjective cognitive decline (SCD), characterized by a very early and subtle cognitive decline prior to the appearance of objective cognitive impairment, is considered to be the preclinical manifestation of Alzheimer's disease (AD). Given the lack of significant abnormalities in standardized neuropsychological assessments for individuals with SCD, biochemical and neuroimaging biomarkers may be important indicators of the preclinical stage of AD. The application of various biomarkers derived from the cerebrospinal fluid and neuroimaging thus has the potential to make AD-related pathology detectable in vivo. In this review, we discuss the conceptual evolution of SCD as an entity and further elucidate characteristic cerebrospinal fluid and neuroimaging biomarkers of SCD.

Functional signature of conversion of patients with mild cognitive impairment

The entorhinal-hippocampal circuit is a strategic hub for cognition and the first site affected by Alzheimer's disease (AD). We investigated magnetic resonance imaging patterns of brain atrophy and functional connectivity in an Alzheimer's Disease Neuroimaging Initiative data set that included healthy controls, mild cognitive impairment (MCI), and patients with AD. Individuals with MCI were clinically evaluated 24 months after the first magnetic resonance imaging scan, and the cohort subdivided into sets of individuals who either did or did not convert to AD. The MCI group was also divided into patients who did show or not the presence of AD-related alterations in the cerebrospinal fluid. Patients with AD exhibited the collapse of the long-range hippocampal/entorhinal connectivity, pronounced cortical/subcortical atrophy, and a dramatic decline in cognitive performances. Patients with MCI who converted to AD or patients with MCI who showed the presence of AD-related alterations in the cerebrospinal fluid showed memory deficits, entorhinal/hippocampal hypoconnectivity, and concomitant atrophy of the two regions. Patients with MCI who did not convert to AD or patients with MCI who did not show the presence of AD-related alterations in the cerebrospinal fluid had no atrophy but showed hippocampal/entorhinal hyperconnectivity with selected neocortical/subcortical regions involved in memory processing and brain metastability. This hyperconnectivity may represent a compensatory strategy against the progression of cognitive impairment.

Disrupted interactions among the hippocampal, dorsal attention, and central-executive networks in amnestic mild cognitive impairment

Neuroimaging investigations consistently demonstrate that the neural processes involve complex interactions between the large-scale networks. Among those networks, the dorsal attention network (DAN) and the central-executive network (CEN) have been previously shown to exhibit anti-correlated activity with the default-mode network (DMN) in cognitively normal people. In amnestic mild cognitive impairment (MCI) and Alzheimer's disease, the hippocampal network (HCN)-a key memory processing system-and its interactions with other networks have gathered central interest. The current study aims to evaluate the patterns of functional architectures of the HCN with the three networks-DAN, CEN, and DMN-in amnestic MCI and normal controls (NC) to test the hypothesis that the interactions of HCN with other networks alter in MCI. We recorded the resting state functional MRI, assessed patterns of functional architectures between the four networks using dynamical causal modeling, and compared between NC and MCI. Our analysis showed that the DAN modulates the activity between the HCN and the DMN in both MCI and NC. We further uncovered that the DAN modulates the activity between the HCN and the CEN in NC, but such modulation is impaired in MCI. We found an association between impaired modulation and Montreal cognitive assessment (R = 0.349). Overall, our findings provide important insight in understanding the neuroimaging signature of amnestic MCI and/or Alzheimer's disease.

Molecular properties underlying regional vulnerability to Alzheimer's disease pathology

Amyloid deposition and neurofibrillary degeneration in Alzheimer's disease specifically affect discrete neuronal systems, but the underlying mechanisms that render some brain regions more vulnerable to Alzheimer's disease pathology than others remain largely unknown. Here we studied molecular properties underlying these distinct regional vulnerabilities by analysing Alzheimer's disease-typical neuroimaging patterns of amyloid deposition and neurodegeneration in relation to regional gene expression profiles of the human brain. Graded patterns of brain-wide vulnerability to amyloid deposition and neurodegeneration in Alzheimer's disease were estimated by contrasting multimodal amyloid-sensitive PET and structural MRI data between patients with Alzheimer's disease dementia (n = 76) and healthy controls (n = 126) enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Regional gene expression profiles were derived from brain-wide microarray measurements provided by the Allen brain atlas of the adult human brain transcriptome. In a hypothesis-driven analysis focusing on the genes coding for the amyloid precursor (APP) and tau proteins (MAPT), regional expression levels of APP were positively correlated with the severity of regional amyloid deposition (r = 0.44, P = 0.009), but not neurodegeneration (r = 0.01, P = 0.96), whereas the opposite pattern was observed for MAPT (neurodegeneration: r = 0.46, P = 0.006; amyloid: r = 0.08, P = 0.65). Using explorative gene set enrichment analysis, amyloid-vulnerable regions were found to be characterized by relatively low expression levels of gene sets implicated in protein synthesis and mitochondrial respiration. By contrast, neurodegeneration-vulnerable regions were characterized by relatively high expression levels of gene sets broadly implicated in neural plasticity, with biological functions ranging from neurite outgrowth and synaptic contact over intracellular signalling cascades to proteoglycan metabolism. At the individual gene level this data-driven analysis further corroborated the association between neurodegeneration and MAPT expression, and additionally identified associations with known tau kinases (CDK5, MAPK1/ERK2) alongside components of their intracellular (Ras-ERK) activation pathways. Sensitivity analyses showed that these pathology-specific imaging-genetic associations were largely robust against changes in some of the methodological parameters, including variation in the brain donor sample used for estimating regional gene expression profiles, and local variations in the Alzheimer's disease-typical imaging patterns when these were derived from an independent patient cohort (BioFINDER study). These findings highlight that the regionally selective vulnerability to Alzheimer's disease pathology relates to specific molecular-functional properties of the affected neural systems, and that the implicated biochemical pathways largely differ for amyloid accumulation versus neurodegeneration. The data provide novel insights into the complex pathophysiological mechanisms of Alzheimer's disease and point to pathology-specific treatment targets that warrant further exploration in independent studies.