Amyloidosis and neurodegeneration result in distinct structural connectivity patterns in mild cognitive impairment

Resting-State Brain Network Characteristics Related to Mild Cognitive Impairment: A Preliminary fNIRS Proof-of-Concept Study

BACKGROUND

This study investigates the reliability of functional near-infrared spectroscopy (fNIRS) in detecting resting-state brain network characteristics in patients with mild cognitive impairment (MCI), focusing on static resting-state functional connectivity (sRSFC) and dynamic resting-state functional connectivity (dRSFC) patterns in MCI patients and healthy controls (HCs) without cognitive impairment.

METHODS

A total of 89 MCI patients and 83 HCs were characterized using neuropsychological scales. Subject sRSFC strength and dRSFC variability coefficients were evaluated via fNIRS. The study evaluated the feasibility of using fNIRS to measure these connectivity metrics and compared resting-state brain network characteristics between the two groups. Correlations with Montreal Cognitive Assessment (MoCA) scores were also explored.

RESULTS

sRSFC strength in homologous brain networks was significantly lower than in heterologous networks (p < 0.05). A significant negative correlation was also observed between sRSFC strength and dRSFC variability at both the group and individual levels (p < 0.001). While sRSFC strength did not differentiate between MCI patients and HCs, the dRSFC variability between the dorsal attention network (DAN) and default mode network (DMN), and between the ventral attention network (VAN) and visual network (VIS), emerged as sensitive biomarkers after false discovery rate correction (p < 0.05). No significant correlation was found between MoCA scores and connectivity measures.

CONCLUSIONS

fNIRS can be used to study resting-state brain networks, with dRSFC variability being more sensitive than sRSFC strength for discriminating between MCI patients and HCs. The DAN-DMN and VAN-VIS regions were found to be particularly useful for the identification of dRSFC differences between the two groups.

CLINICAL TRIAL REGISTRATION

ChiCTR2200057281, registered on 6 March, 2022; https://www.chictr.org.cn/showproj.html?proj=133808.

Identification and cognitive function prediction of Alzheimer's disease based on multivariate pattern analysis of hippocampal volumes

BACKGROUND

Alzheimer's disease (AD) is strongly associated with slowly progressive hippocampal atrophy. Elucidating the relationships between local morphometric changes and disease status for early diagnosis could be aided by machine learning algorithms trained on neuroimaging datasets.

OBJECTIVE

This study intended to propose machine learning models for the accurate identification and cognitive function prediction across the AD severity spectrum based on structural magnetic resonance imaging (sMRI) of the bilateral hippocampi.

METHODS

The high-resolution sMRI data of 120 AD dementia patients, 232 amnestic mild cognitive impairment (aMCI) patients, and 206 healthy controls (HCs) were included from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The classification capacity and cognitive predict ability of hippocampal volume was evaluated by multiple pattern analysis using the support vector machine (SVM) and relevance vector regression (RVR) application of the Pattern Recognition for Neuroimaging Toolbox, separately. For validation, the analyses were performed using a biomarker-based regrouping method and another independent local dataset.

RESULTS

The SVM application produced a total accuracy of 94.17%, 80.85%, and 70.74% and area under receiver operating characteristic curves of 0.97, 0.87, and 0.72 between HC versus AD dementia, HC versus aMCI, and aMCI versus AD dementia classification, respectively. The RVR application significantly predicted the baseline and mean cognitive function at three years of follow-up. Qualitatively consistent results were obtained using different regrouping method and the local dataset.

CONCLUSIONS

The machine learning methods based on the bilateral hippocampi distinguished across the AD severity spectrum and predicted the baseline and the longitudinal cognitive function with greater accuracy.

A novel method for PET connectomics guided by fibre-tracking MRI: Application to Alzheimer's disease

This study introduces a novel brain connectome matrix, track-weighted PET connectivity (twPC) matrix, which combines positron emission tomography (PET) and diffusion magnetic resonance imaging data to compute a PET-weighted connectome at the individual subject level. The new method is applied to characterise connectivity changes in the Alzheimer's disease (AD) continuum. The proposed twPC samples PET tracer uptake guided by the underlying white matter fibre-tracking streamline point-to-point connectivity calculated from diffusion MRI (dMRI). Using tau-PET, dMRI and T1-weighted MRI from the Alzheimer's Disease Neuroimaging Initiative database, structural connectivity (SC) and twPC matrices were computed and analysed using the network-based statistic (NBS) technique to examine topological alterations in early mild cognitive impairment (MCI), late MCI and AD participants. Correlation analysis was also performed to explore the coupling between SC and twPC. The NBS analysis revealed progressive topological alterations in both SC and twPC as cognitive decline progressed along the continuum. Compared to healthy controls, networks with decreased SC were identified in late MCI and AD, and networks with increased twPC were identified in early MCI, late MCI and AD. The altered network topologies were mostly different between twPC and SC, although with several common edges largely involving the bilateral hippocampus, fusiform gyrus and entorhinal cortex. Negative correlations were observed between twPC and SC across all subject groups, although displaying an overall reduction in the strength of anti-correlation with disease progression. twPC provides a new means for analysing subject-specific PET and MRI-derived information within a hybrid connectome using established network analysis methods, providing valuable insights into the relationship between structural connections and molecular distributions. PRACTITIONER POINTS: New method is proposed to compute patient-specific PET connectome guided by MRI fibre-tracking. Track-weighted PET connectivity (twPC) matrix allows to leverage PET and structural connectivity information. twPC was applied to dementia, to characterise the PET nework abnormalities in Alzheimer's disease and mild cognitive impairment.

Structural Network Topology Reveals Higher Brain Resilience in Individuals with Preclinical Alzheimer's Disease

Introduction: The diagnosis of Alzheimer's disease (AD) requires the presence of amyloid and tau pathology, but it remains unclear how they affect the structural network in the pre-clinical stage. We aimed to assess differences in topological properties in cognitively normal (CN) individuals with varying levels of amyloid and tau pathology, as well as their association with AD pathology burden. Methods: A total of 68 CN individuals were included and stratified by normal/abnormal (-/+) amyloid (A) and tau (T) status based on positron emission tomography results, yielding three groups: A-T- (n = 19), A+T- (n = 28), and A+T+ (n = 21). Topological properties were measured from structural connectivity. Group differences and correlations with A and T were evaluated. Results: Compared with the A-T- group, the A+T+ group exhibited changes in the structural network topology. At the global level, higher assortativity was shown in the A+T+ group and was correlated with greater tau burden (r = 0.29, p = 0.02), while no difference in global efficiency was found across the three groups. At the local level, the A+T+ group showed disrupted topological properties in the left hippocampus compared with the A-T- group, characterized by lower local efficiency (p < 0.01) and a lower clustering coefficient (p = 0.014). Conclusions: The increased linkage in the higher level architecture of the white matter network reflected by assortativity may indicate increased brain resilience in the early pathological state. Our results encourage further investigation of the topological properties of the structural network in pre-clinical AD.

An Exploratory Study of Sleep-Wake Differences of Autonomic Activity in Patients with Mild Cognitive Impairment: The Role of Melatonin as a Modulating Factor

Purpose

The objective of the present study was to assess sleep-wake differences of autonomic activity in patients with mild cognitive impairment (MCI) compared to control subjects. As a post-hoc objective, we sought to evaluate the mediating effect of melatonin on this association.

Patients and Methods

A total of 22 MCI patients (13 under melatonin treatment) and 12 control subjects were included in this study. Sleep-wake periods were identified by actigraphy and 24hr-heart rate variability measures were obtained to study sleep-wake autonomic activity.

Results

MCI patients did not show any significant differences in sleep-wake autonomic activity when compared to control subjects. Post-hoc analyses revealed that MCI patients not taking melatonin displayed lower parasympathetic sleep-wake amplitude than controls not taking melatonin (RMSSD -7 ± 1 vs 4 ± 4, p = 0.004). In addition, we observed that melatonin treatment was associated with greater parasympathetic activity during sleep (VLF 15.5 ± 0.1 vs 15.1 ± 0.1, p = 0.010) and in sleep-wake differences in MCI patients (VLF 0.5 ± 0.1 vs 0.2 ± 0.0, p = 0.004).

Conclusion

These preliminary findings hint at a possible sleep-related parasympathetic vulnerability in patients at prodromal stages of dementia as well as a potential protective effect of exogenous melatonin in this population.

Diffusion tensor tractography of the fornix in cerebral amyloid angiopathy, mild cognitive impairment and Alzheimer's disease

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The fornix was delineated with deterministic tractography from diffusion tensor images (DTI).

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Fornix diffusion changes were found in the fornix in CAA, AD and MCI compared to controls.

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Higher fornix diffusivity correlated with smaller hippocampal volume and larger ventricles.

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Fornix diffusion measures correlated with cognitive measures in the combined disease groups.

Purpose

Cerebral amyloid angiopathy (CAA) is a common neuropathological finding and clinical entity that occurs independently and with co-existent Alzheimer’s disease (AD) and small vessel disease. We compared diffusion tensor imaging (DTI) metrics of the fornix, the primary efferent tract of the hippocampus between CAA, AD and Mild Cognitive Impairment (MCI) and healthy controls.

Methods

Sixty-eight healthy controls, 32 CAA, 21 AD, and 26 MCI patients were recruited at two centers. Diffusion tensor images were acquired at 3 T with high spatial resolution and fluid-attenuated inversion recovery (FLAIR) to suppress cerebrospinal fluid (CSF) and minimize partial volume effects on the fornix. The fornix was delineated with deterministic tractography to yield mean diffusivity (MD), axial diffusivity (AXD), radial diffusivity (RD), fractional anisotropy (FA) and tract volume. Volumetric measurements of the hippocampus, thalamus, and lateral ventricles were obtained using T1-weighted MRI.

Results

Diffusivity (MD, AXD, and RD) of the fornix was highest in AD followed by CAA compared to controls; the MCI group was not significantly different from controls. FA was similar between groups. Fornix tract volume was ∼ 30% lower for all three patient groups compared to controls, but not significantly different between the patient groups. Thalamic and hippocampal volumes were preserved in CAA, but lower in AD and MCI compared to controls. Lateral ventricular volumes were increased in CAA, AD and MCI. Global cognition, memory, and executive function all correlated negatively with fornix diffusivity across the combined clinical group.

Conclusion

There were significant diffusion changes of the fornix in CAA, AD and MCI compared to controls, despite relatively intact thalamic and hippocampal volumes in CAA, suggesting the mechanisms for fornix diffusion abnormalities may differ in CAA compared to AD and MCI.

Altered Volume and Structural Connectivity of the Hippocampus in Alzheimer's Disease and Amnestic Mild Cognitive Impairment

Background: Hippocampal atrophy is a characteristic of Alzheimer’s disease (AD). However, alterations in structural connectivity (number of connecting fibers) between the hippocampus and whole brain regions due to hippocampal atrophy remain largely unknown in AD and its prodromal stage, amnestic mild cognitive impairment (aMCI).

Methods: We collected high-resolution structural MRI (sMRI) and diffusion tensor imaging (DTI) data from 36 AD patients, 30 aMCI patients, and 41 normal control (NC) subjects. First, the volume and structural connectivity of the bilateral hippocampi were compared among the three groups. Second, correlations between volume and structural connectivity in the ipsilateral hippocampus were further analyzed. Finally, classification ability by hippocampal volume, its structural connectivity, and their combination were evaluated.

Results: Although the volume and structural connectivity of the bilateral hippocampi were decreased in patients with AD and aMCI, only hippocampal volume correlated with neuropsychological test scores. However, positive correlations between hippocampal volume and ipsilateral structural connectivity were displayed in patients with AD and aMCI. Furthermore, classification accuracy (ACC) was higher in AD vs. aMCI and aMCI vs. NC by the combination of hippocampal volume and structural connectivity than by a single parameter. The highest values of the area under the receiver operating characteristic (ROC) curve (AUC) in every two groups were all obtained by combining hippocampal volume and structural connectivity.

Conclusions: Our results showed that the combination of hippocampal volume and structural connectivity (number of connecting fibers) is a new perspective for the discrimination of AD and aMCI.

Tau deposition and structural connectivity demonstrate differential association patterns with neurocognitive tests

Tau neurofibrillary tangles have a central role in the pathogenesis of Alzheimer’s Disease (AD). Mounting evidence indicates that the propagation of tau is assisted by brain connectivity with weakened white-matter integrity along the propagation pathways. Recent advances in tau positron emission tomography tracers and diffusion magnetic resonance imaging allow the visualization of tau pathology and white-matter connectivity of the brain in vivo. The current study aims to investigate how tau deposition and structural connectivity are associated with memory function in prodromal AD. In this study, tau accumulation and structural connectivity data from 83 individuals (57 cognitively normal participants and 26 participants with mild cognitive impairment) were associated with neurocognitive test scores. Statistical analyses were performed in 70 cortical/subcortical brain regions to determine: 1. the level of association between tau and network metrics extracted from structural connectivity and 2. the association patterns of brain memory function with tau accumulation and network metrics. The results showed that tau accumulation and network metrics were correlated in early tau deposition regions. Furthermore, tau accumulation was associated with worse performance in almost all neurocognitive tests performance evaluated in the study. In comparison, decreased network connectivity was associated with declines in the delayed memory recall in Craft Stories and Benson Figure Copy. Interaction analysis indicates that tau deposition and dysconnectivity have a synergistic effect on the delayed Benson Figure Recall. Overall, our findings indicate that both tau deposition and structural dysconnectivity are associated with neurocognitive dysfunction. They also suggest that tau-PET may have better sensitivity to neurocognitive performance than diffusion MRI-derived measures of white-matter connectivity.

Accelerated Brain Aging in Mild Traumatic Brain Injury: Longitudinal Pattern Recognition with White Matter Integrity

Mild traumatic brain injury (mTBI) initiating long-term effects on white matter integrity resembles brain-aging changes, implying an aging process accelerated by mTBI. This longitudinal study aims to investigate the mTBI-induced acceleration of the brain-aging process by developing a neuroimaging model to predict brain age. The brain-age prediction model was defined using relevance vector regression based on fractional anisotropy from diffusion tensor imaging of 523 healthy individuals. The model was used to estimate the brain-predicted age difference (brain-PAD) between the chronological and estimated brain age in 116 acute mTBI patients and 63 healthy controls. Fifty patients were followed for 6 ∼ 12 months to evaluate the longitudinal changes in brain-PAD. We investigated whether brain-PAD was greater in patients of older age, post-concussion complaints, and apolipoprotein E (APOE) ɛ4 genotype, and whether it had the potential to predict neuropsychological outcomes. The brain-age prediction model predicted brain age accurately (r = 0.96). The brains of mTBI patients in the acute phase were estimated to be "older," with greater brain-PAD (2.59 ± 5.97 years) than the healthy controls (0.12 ± 3.19 years) (p < 0.05), and remained stable 6-12 month post-injury (2.50 ± 4.54 years). Patients who were older or who had post-concussion complaints, rather than APOE ɛ4 genotype, had greater brain-PADs (p < 0.001, p = 0.024). Additionally, brain-PAD in the acute phase predicted information processing speed at the 6 ∼ 12 month follow-up (r = -0.36, p = 0.01). In conclusion, mTBI accelerates the brain-aging process, and brain-PAD may be capable of evaluating aging-associated issues post-injury, such as increased risks of neurodegeneration.

Common Brain Structural Alterations Associated with Cardiovascular Disease Risk Factors and Alzheimer's Dementia: Future Directions and Implications

Recent reports suggest declines in the age-specific risk of Alzheimer's dementia in higher income Western countries. At the same time, investigators believe that worldwide trends of increasing mid-life modifiable risk factors [e.g., cardiovascular disease (CVD) risk factors] coupled with the growth of the world's oldest age groups may nonetheless lead to an increase in Alzheimer's dementia. Thus, understanding the overlap in neuroanatomical profiles associated with CVD risk factors and AD may offer more relevant targets for investigating ways to reduce the growing dementia epidemic than current targets specific to isolated AD-related neuropathology. We hypothesized that a core group of common brain structural alterations exist between CVD risk factors and Alzheimer's dementia. Two co-authors conducted independent literature reviews in PubMed using search terms for CVD risk factor burden (separate searches for 'cardiovascular disease risk factors', 'hypertension', and 'Type 2 diabetes') and 'aging' or 'Alzheimer's dementia' with either 'grey matter volumes' or 'white matter'. Of studies that reported regionally localized results, we found support for our hypothesis, determining 23 regions commonly associated with both CVD risk factors and Alzheimer's dementia. Within this context, we outline future directions for research as well as larger cerebrovascular implications for these commonalities. Overall, this review supports previous as well as more recent calls for the consideration that both vascular and neurodegenerative factors contribute to the pathogenesis of dementia.

Brain Amyloid Contribution to Cognitive Dysfunction in Early-Stage Parkinson's Disease: The PPMI Dataset

BACKGROUND

The pathological processes underlying cognitive impairment in Parkinson's disease (PD) are heterogeneous and the contribution of cerebral amyloid deposits is poorly defined, particularly in the early stages of the disease.

OBJECTIVE

To investigate regional [18F]florbetaben binding to amyloid-β (Aβ) and its contribution to cognitive dysfunction in early stage PD.

METHODS

A multicenter cohort of 48 PD patients from the Parkinson's Progression Marker Initiative (PPMI) underwent [18F]florbetaben positron emission tomography (PET) scanning. Clinical features, including demographic characteristics, motor severity, cerebrospinal fluid (CSF), and cognitive testing were systematically assessed according to the PPMI study protocol. For the purpose of this study, we analyzed various neuropsychological tests assessing all cognitive functions.

RESULTS

There were 10/48 (21%) amyloid positive PD patients (PDAβ+). Increased [18F]florbetaben uptake in widespread cortical and subcortical regions was associated with poorer performance on global cognition, as assessed by Montreal Cognitive Assessment (MoCA), and impaired performance on Symbol Digit Modality test (SDMT). Further, we found that PDAβ+ patients had higher CSF total-tau/Aβ1 - 42 (p = 0.001) and phosphorylated-tau/Aβ1 - 42 in (p = 0.002) compared to amyloid-negative PD.

CONCLUSION

These findings suggest that multiple disease processes are associated with PD cognitive impairment and amyloid deposits may be observed already in early stages. However, prevalence of amyloid positivity is in the range of literature age-matched control population. Increased cortical and subcortical amyloid is associated with poor performance in attentive-executive domains while cognitive deficits at MoCA and SDMT may identify amyloid-related dysfunction in early PD.

Case report: a giant arachnoid cyst masking Alzheimer's disease

BACKGROUND

Intracranial arachnoid cysts are usually benign congenital findings of neuroimaging modalities, sometimes however, leading to focal neurological and psychiatric comorbidities. Whether primarily clinically silent cysts may become causally involved in cognitive decline in old age is neither well examined nor understood.

CASE PRESENTATION

A 66-year old caucasian man presenting with a giant left-hemispheric frontotemporal cyst without progression of size, presented with slowly progressive cognitive decline. Neuropsychological assessment revealed an amnestic mild cognitive impairment (MCI) without further neurological or psychiatric symptoms. The patient showed mild medio-temporal lobe atrophy on structural MRI. Diffusion tensor and functional magnetic resonance imaging depicted a rather sustained function of the strongly suppressed left hemisphere. Amyloid-PET imaging was positive for increased amyloid burden and he was homozygous for the APOEε3-gene. A diagnosis of MCI due to Alzheimer's disease was given and a co-morbidity with a silent arachnoid cyst was assumed. To investigate, if a potentially reduced CSF flow due to the giant arachnoid cyst contributed to the early manifestation of AD, we reviewed 15 case series of subjects with frontotemporal arachnoid cysts and cognitive decline. However, no increased manifestation of neurodegenerative disorders was reported.

CONCLUSIONS

With this case report, we illustrate the necessity of a systematic work-up for neurodegenerative disorders in patients with arachnoid cysts and emerging cognitive decline. We finally propose a modus operandi for the stratification and management of patients with arachnoid cysts potentially susceptive for cognitive dysfunction.

The mediating role of hippocampal networks on stress regulation in amnestic mild cognitive impairment

Objectives

To examine the role of the hippocampus in stress regulation in older adults with amnestic mild cognitive impairment (aMCI).

Methods

This study combined resting-state functional MRI, structural MRI, self-reported chronic stress exposure, and an electrocardiography-based acute stress protocol to compare aMCI group (n = 17) to their cognitively healthy counterparts (HC, n = 22).

Results

For the entire sample, there was a positive correlation between chronic stress exposure and acute stress regulation. The aMCI group showed significantly smaller volumes in the right hippocampus than HC. The two groups did not differ in chronic stress exposure or acute stress regulation. In the HC group, the left hippocampal connectivity with inferior parietal lobe was significantly correlated with both the chronic stress and acute stress. In the aMCI group, the left hippocampal connectivity with both the right insula and the left precentral gyrus was significantly correlated to chronic stress exposure and acute stress regulation. Additionally, the left hippocampal connectivity with right insula significantly mediated the relationship between chronic stress exposure and acute stress regulation in aMCI group.

Conclusions

Extra hippocampal networks may be recruited as compensation to attend the maintenance of relatively normal stress regulation in aMCI by alleviating the detrimental effects of chronic stress exposure on acute stress regulation.

Prediction of Conversion From Amnestic Mild Cognitive Impairment to Alzheimer's Disease Based on the Brain Structural Connectome

Background: Early prediction of disease progression in patients with amnestic mild cognitive impairment (aMCI) is important for early diagnosis and intervention of Alzheimer's disease (AD). Previous brain network studies have suggested topological disruptions of the brain connectome in aMCI patients. However, whether brain connectome markers at baseline can predict longitudinal conversion from aMCI to AD remains largely unknown.

Methods: In this study, 52 patients with aMCI and 26 demographically matched healthy controls from a longitudinal cohort were evaluated. During 2 years of follow-up, 26 patients with aMCI were retrospectively classified as aMCI converters and 26 patients remained stable as aMCI non-converters based on whether they were subsequently diagnosed with AD. For each participant, diffusion tensor imaging at baseline and deterministic tractography were used to map the whole-brain white matter structural connectome. Graph theoretical analysis was applied to investigate the convergent and divergent connectivity patterns of structural connectome between aMCI converters and non-converters.

Results: Disrupted topological organization of the brain structural connectome were identified in both aMCI converters and non-converters. More severe disruptions of structural connectivity in aMCI converters compared with non-converters were found, especially in the default-mode network regions and connections. Finally, a support vector machine-based classification demonstrated the good discriminative ability of structural connectivity in differentiating aMCI patients from controls with an accuracy of 98%, and in discriminating converters from non-converters with an accuracy of 81%.

Conclusion: Our study provides potential structural connectome/connectivity-based biomarkers for predicting disease progression in aMCI, which is important for the early diagnosis of AD.

Neuroprotective effects of antioxidants in the management of neurodegenerative disorders: A literature review

It is proven that oxidative stress has a pivotal role in the process of neurodegeneration. The use of antioxidants is an attractive method to prevent the incidence of neurodegenerative diseases. We searched major databases (PubMed, Medline, and Google Scholar) using the keywords of neurodegeneration, oxidative stress, and antioxidant for both review and original studies, which have reported the various beneficial effects of antioxidants. About 70 studies were identified for this review. Among various antioxidants, nine antioxidants with the most applications in research investigations were selected and the major findings concerning their protective effects were reviewed. It is concluded that antioxidants can modify and readjust the oxidative stress in the biological milieu, elicit neuroprotective effects, and positively impact the management of neurodegenerative processes.

Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative

INTRODUCTION

The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late-onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials.

METHODS

We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news-publications/publications/).

RESULTS

(1) Data-driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β-Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a "typical AD" subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies.

DISCUSSION

ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.

The Efficacy of Cognitive Intervention in Mild Cognitive Impairment (MCI): a Meta-Analysis of Outcomes on Neuropsychological Measures

Cognitive training in MCI may stimulate pre-existing neural reserves or recruit neural circuitry as “compensatory scaffolding” prompting neuroplastic reorganization to meet task demands (Reuter-Lorenz & Park, 2014). However, existing systematic reviews and meta-analytic studies exploring the benefits of cognitive interventions in MCI have been mixed. An updated examination regarding the efficacy of cognitive intervention in MCI is needed given improvements in adherence to MCI diagnostic criteria in subject selection, better defined interventions and strategies applied, increased use of neuropsychological measures pre- and post-intervention, as well as identification of moderator variables which may influence treatment. As such, this meta-analytic review was conducted to examine the efficacy of cognitive intervention in individuals diagnosed with mild cognitive impairment (MCI) versus MCI controls based on performance of neuropsychological outcome measures in randomized controlled trials (RCT). RCT studies published from January 1995 to June 2017 were obtained through source databases of MEDLINE-R, PubMed, Healthstar, Global Health, PSYCH-INFO, and Health and Psychological Instruments using search parameters for MCI diagnostic category (mild cognitive impairment, MCI, pre-Alzheimer’s disease, early cognitive decline, early onset Alzheimer’s disease, and preclinical Alzheimer’s disease) and the intervention or training conducted (intervention, training, stimulation, rehabilitation, or treatment). Other inclusion and exclusion criteria included subject selection based on established MCI criteria, RCT design in an outpatient setting, MCI controls (active or passive), and outcomes based on objective neuropsychological measures. From the 1199 abstracts identified, 26 articles met inclusion criteria for the meta-analyses completed across eleven (11) countries; 92.31% of which have been published within the past 7 years. A series of meta-analyses were performed to examine the effects of cognitive intervention by cognitive domain, type of training, and intervention content (cognitive domain targeted). We found significant, moderate effects for multicomponent training (Hedges’ g observed = 0.398; CI [0.164, 0.631]; Z = 3.337; p = 0.001; Q = 55.511; df = 15; p = 0.000; I² = 72.978%; τ² = 0.146) as well as multidomain-focused strategies (Hedges’ g = 0.230; 95% CI [0.108, 0.352]; Z = 3.692; p  < 0.001; Q = 12.713; df = 12; p = 0.390; I² = 5.612; τ² = 0.003). The effects for other interventions explored by cognitive domain, training type, or intervention content were indeterminate due to concerns for heterogeneity, bias, and small cell sizes. In addition, subgroup and meta-regression analyses were conducted with the moderators of MCI category, mode of intervention, training type, intervention content, program duration (total hours), type of control group (active or passive), post-intervention follow-up assessment period, and control for repeat administration. We found significant overall effects for intervention content with memory focused interventions appearing to be more effective than multidomain approaches. There was no evidence of an influence on outcomes for the other covariates examined. Overall, these findings suggest individuals with MCI who received multicomponent training or interventions targeting multiple domains (including lifestyle changes) were apt to display an improvement on outcome measures of cognition post-intervention. As such, multicomponent and multidomain forms of intervention may prompt recruitment of alternate neural processes as well as support primary networks to meet task demands simultaneously. In addition, interventions with memory and multidomain forms of content appear to be particularly helpful, with memory-based approaches possibly being more effective than multidomain methods. Other factors, such as program duration, appear to have less of an influence on intervention outcomes. Given this, although the creation of new primary network paths appears strained in MCI, interventions with memory-based or multidomain forms of content may facilitate partial activation of compensatory scaffolding and neuroplastic reorganization. The positive benefit of memory-based strategies may also reflect transfer effects indicative of compensatory network activation and the multiple-pathways involved in memory processes. Limitations of this review are similar to other meta-analysis in MCI, including a modest number studies, small sample sizes, multiple forms of interventions and types of training applied (some overlapping), and, while greatly improved in our view, a large diversity of instruments used to measure outcome. This is apt to have contributed to the presence of heterogeneity and publication bias precluding a more definitive determination of the outcomes observed.

Cortical thickness is associated with altered autonomic function in cognitively impaired and non-impaired older adults

KEY POINTS

The parasympathetic nervous system (PNS) is critical for adaptation to environment demands. Alzheimer's disease (AD), via frontal compensatory processes, may affect PNS regulation, thereby compromising older adults' capacity for adaptation, and increasing morbidity and mortality risk. Here we found that AD-associated neurodegeneration accompanied an overactive anterior cingulate cortex, which in turn resulted in a high level of PNS activity at rest, as well as strong PNS activity withdrawal in response to the mental effort. This discovery provides the first line of evidence to suggest that AD-associated neurodegeneration links to altered PNS regulation during mental effort in older adults, and that the compensatory processes accompanying frontal hyperactivation appear to be responsible for these alterations.

ABSTRACT

The parasympathetic nervous system (PNS) is critical for adaptation to environment demands. PNS can reflect an individual's regulatory capacity of frontal brain regions and has been linked to cognitive capacity. Yet, the relationship of PNS function to cognitive decline and abnormal frontal function that characterize preclinical progression toward Alzheimer's disease (AD) is unclear. Here, we aimed to elucidate the relationship between PNS function and AD-associated neurodegeneration by testing two competing hypotheses involving frontal regions' activity (neurodegeneration vs. compensation). In 38 older human adults with amnestic mild cognitive impairment (aMCI) or normative cognition, we measured AD-associated neurodegeneration (AD signature cortical thickness; ADSCT), resting-state functional magnetic resonance imaging of frontal regions' spontaneous activation, and an electrocardiography measure of PNS (high frequency heart rate variability; HF-HRV). HF-HRV was assessed at rest and during a cognitive task protocol designed to capture HF-HRV reactivity. Higher HF-HRV at rest was significantly related to both more severe AD-associated neurodegeneration (lower ADSCT scores) and worse cognitive ability. Cognitive impairments were also related to greater suppression of HF-HRV reactivity. High activities of the anterior cingulate cortex significantly mediated relationships between ADSCT and both HF-HRV at rest and HF-HRV reactivity. Notably, these relationships were not affected by the clinical phenotype. We show that AD-associated neurodegeneration is associated with altered PNS regulation and that compensatory processes linked to frontal overactivation might be responsible for those alterations. This finding provides the first line of evidence in a new framework for understanding how early-stage AD-associated neurodegeneration affects autonomic regulation.