Alzheimer's Disease Progressively Reduces Visual Functional Network Connectivity

Monoclonal antibody therapy for Alzheimer's disease focusing on intracerebral targets

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. Due to the complexity of the disorder and the presence of the blood-brain barrier (BBB), its drug discovery and development are facing enormous challenges, especially after several failures of monoclonal antibody (mAb) trials. Nevertheless, the Food and Drug Administration's approval of the mAb aducanumab has ushered in a new day. As we better understand the disease's pathogenesis and identify novel intracerebral therapeutic targets, antibody-based therapies have advanced over the past few years. The mAb drugs targeting β-amyloid or hyperphosphorylated tau protein are the focus of the current research. Massive neuronal loss and glial cell-mediated inflammation are also the vital pathological hallmarks of AD, signaling a new direction for research on mAb drugs. We have elucidated the mechanisms by which AD-specific mAbs cross the BBB to bind to targets. In order to investigate therapeutic approaches to treat AD, this review focuses on the promising mAbs targeting intracerebral dysfunction and related strategies to cross the BBB.

Altered resting-state functional connectivity and dynamic network properties in cognitive impairment: an independent component and dominant-coactivation pattern analyses study

Introduction

Cognitive impairment (CI) due to Alzheimer's disease (AD) encompasses a decline in cognitive abilities and can significantly impact an individual's quality of life. Early detection and intervention are crucial in managing CI, both in the preclinical and prodromal stages of AD prior to dementia.

Methods

In this preliminary study, we investigated differences in resting-state functional connectivity and dynamic network properties between 23 individual with CI due to AD based on clinical assessment and 15 healthy controls (HC) using Independent Component Analysis (ICA) and Dominant-Coactivation Pattern (d-CAP) analysis. The cognitive status of the two groups was also compared, and correlations between cognitive scores and d-CAP switching probability were examined.

Results

Results showed comparable numbers of d-CAPs in the Default Mode Network (DMN), Executive Control Network (ECN), and Frontoparietal Network (FPN) between HC and CI groups. However, the Visual Network (VN) exhibited fewer d-CAPs in the CI group, suggesting altered dynamic properties of this network for the CI group. Additionally, ICA revealed significant connectivity differences for all networks. Spatial maps and effect size analyses indicated increased coactivation and more synchronized activity within the DMN in HC compared to CI. Furthermore, reduced switching probabilities were observed for the CI group in DMN, VN, and FPN networks, indicating less dynamic and flexible functional interactions.

Discussion

The findings highlight altered connectivity patterns within the DMN, VN, ECN, and FPN, suggesting the involvement of multiple functional networks in CI. Understanding these brain processes may contribute to developing targeted diagnostic and therapeutic strategies for CI due to AD.

Brain Representation of Animal and Non-Animal Images in Patients with Mild Cognitive Impairment and Alzheimer's Disease

Background

In early Alzheimer's disease (AD), high-level visual functions and processing speed are impacted. Few functional magnetic resonance imaging (fMRI) studies have investigated high-level visual deficits in AD, yet none have explored brain activity patterns during rapid animal/non-animal categorization tasks.

Objective

To address this, we utilized the previously known Integrated Cognitive Assessment (ICA) to collect fMRI data and compare healthy controls (HC) to individuals with mild cognitive impairment (MCI) and mild AD.

Methods

The ICA encompasses a rapid visual categorization task that involves distinguishing between animals and non-animals within natural scenes. To comprehensively explore variations in brain activity levels and patterns, we conducted both univariate and multivariate analyses of fMRI data.

Results

The ICA task elicited activation across a range of brain regions, encompassing the temporal, parietal, occipital, and frontal lobes. Univariate analysis, which compared responses to animal versus non-animal stimuli, showed no significant differences in the regions of interest (ROIs) across all groups, with the exception of the left anterior supramarginal gyrus in the HC group. In contrast, multivariate analysis revealed that in both HC and MCI groups, several regions could differentiate between animals and non-animals based on distinct patterns of activity. Notably, such differentiation was absent within the mild AD group.

Conclusions

Our study highlights the ICA task's potential as a valuable cognitive assessment tool designed for MCI and AD. Additionally, our use of fMRI pattern analysis provides valuable insights into the complex changes in brain function associated with AD. This approach holds promise for enhancing our understanding of the disease's progression.

Reproducible Abnormalities and Diagnostic Generalizability of White Matter in Alzheimer's Disease

Alzheimer's disease (AD) is associated with the impairment of white matter (WM) tracts. The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets [321 patients with AD, 265 patients with mild cognitive impairment (MCI), 279 normal controls (NC)], a unified pipeline, and independent site cross-validation. Automated fiber quantification was used to extract diffusion profiles along tracts. Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC. Machine learning models using tract-based features showed good generalizability among independent site cross-validation. The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups. We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.

An atlas of trait associations with resting-state and task-evoked human brain functional organizations in the UK Biobank

Functional magnetic resonance imaging (fMRI) has been widely used to identify brain regions linked to critical functions, such as language and vision, and to detect tumors, strokes, brain injuries, and diseases. It is now known that large sample sizes are necessary for fMRI studies to detect small effect sizes and produce reproducible results. Here we report a systematic association analysis of 647 traits with imaging features extracted from resting-state and task-evoked fMRI data of more than 40,000 UK Biobank participants. We used a parcellation-based approach to generate 64,620 functional connectivity measures to reveal fine-grained details about cerebral cortex functional organizations. The difference between functional organizations at rest and during task was examined, and we have prioritized important brain regions and networks associated with a variety of human traits and clinical outcomes. For example, depression was most strongly associated with decreased connectivity in the somatomotor network. We have made our results publicly available and developed a browser framework to facilitate the exploration of brain function-trait association results (http://fmriatlas.org/).

Endotype Characterization Reveals Mechanistic Differences Across Brain Regions in Sporadic Alzheimer's Disease

Background

While Alzheimer's disease (AD) pathology is associated with altered brain structure, it is not clear whether gene expression changes mirror the onset and evolution of pathology in distinct brain regions. Deciphering the mechanisms which cause the differential manifestation of the disease across different regions has the potential to help early diagnosis.

Objective

We aimed to identify common and unique endotypes and their regulation in tangle-free neurons in sporadic AD (SAD) across six brain regions: entorhinal cortex (EC), hippocampus (HC), medial temporal gyrus (MTG), posterior cingulate (PC), superior frontal gyrus (SFG), and visual cortex (VCX).

Methods

To decipher the states of tangle-free neurons across different brain regions in human subjects afflicted with AD, we performed analysis of the neural transcriptome. We explored changes in differential gene expression, functional and transcription factor target enrichment, and co-expression gene module detection analysis to discern disease-state transcriptomic variances and characterize endotypes. Additionally, we compared our results to tangled AD neuron microarray-based study and the Allen Brain Atlas.

Results

We identified impaired neuron function in EC, MTG, PC, and VCX resulting from REST activation and reversal of mature neurons to a precursor-like state in EC, MTG, and SFG linked to SOX2 activation. Additionally, decreased neuron function and increased dedifferentiation were linked to the activation of SUZ12. Energetic deficit connected to NRF1 inactivation was found in HC, PC, and VCX.

Conclusions

Our findings suggest that SAD manifestation varies in scale and severity in different brain regions. We identify endotypes, such as energetic shortfalls, impaired neuronal function, and dedifferentiation.

Sensory processing deficits and related cortical pathological changes in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder primarily affecting cognitive functions. However, sensory deficits in AD start to draw attention due to their high prevalence and early onsets which suggest that they could potentially serve as diagnostic biomarkers and even contribute to the disease progression. This literature review examines the sensory deficits and cortical pathological changes observed in visual, auditory, olfactory, and somatosensory systems in AD patients, as well as in various AD animal models. Sensory deficits may emerge at the early stages of AD, or even precede the cognitive decline, which is accompanied by cortical pathological changes including amyloid-beta deposition, tauopathy, gliosis, and alterations in neuronal excitability, synaptic inputs, and functional plasticity. Notably, these changes are more pronounced in sensory association areas and superficial cortical layers, which may explain the relative preservation of basic sensory functions but early display of deficits of higher sensory functions. We propose that sensory impairment and the progression of AD may establish a cyclical relationship that mutually perpetuates each condition. This review highlights the significance of sensory deficits with or without cortical pathological changes in AD and emphasizes the need for further research to develop reliable early detection and intervention through sensory systems.

Altered functional connectivity of the locus coeruleus in Alzheimer's disease patients with depression symptoms

Studies have shown that functional abnormalities in the locus coeruleus (LC) are strongly associated with depressive symptoms, but the pattern of LC functional connectivity in Alzheimer's disease patients with depressive symptoms (D-AD) remains unclear. The current study aimed to investigate the characteristics of LC functional connectivity (FC) in D-AD using resting-state functional magnetic resonance imaging (rsfMRI). We obtained rsfMRI data in 24 D-AD patients (aged 66-76 years), 14 non-depressive AD patients (nD-AD) (aged 69-79 years) and 20 normal controls (aged 67-74 years) using a 3 T scanner. We used the FC approach to investigate abnormalities in the LC brain network of D-AD patients. One-way ANCOVA and post-hoc two-sample t-tests were performed to compare the strength of functional connectivity from the LC among the three groups. Our results showed that, compared with normal controls, D-AD showed decreased left LC FC with the right caudate and left fusiform gyrus, whereas nD-AD showed decreased left LC FC with the right caudate, right middle frontal gyrus and left fusiform gyrus. Compared to nD-AD, D-AD showed increased left LC FC with right superior frontal gyrus and right precentral gyrus. These findings contribute to our understanding of the neural mechanisms of D-AD.

Immunotherapy with Cleavage-Specific 12A12mAb Reduces the Tau Cleavage in Visual Cortex and Improves Visuo-Spatial Recognition Memory in Tg2576 AD Mouse Model

Tau-targeted immunotherapy is a promising approach for treatment of Alzheimer's disease (AD). Beyond cognitive decline, AD features visual deficits consistent with the manifestation of Amyloid β-protein (Aβ) plaques and neurofibrillary tangles (NFT) in the eyes and higher visual centers, both in animal models and affected subjects. We reported that 12A12-a monoclonal cleavage-specific antibody (mAb) which in vivo neutralizes the neurotoxic, N-terminal 20-22 kDa tau fragment(s)-significantly reduces the retinal accumulation in Tg(HuAPP695Swe)2576 mice of both tau and APP/Aβ pathologies correlated with local inflammation and synaptic deterioration. Here, we report the occurrence of N-terminal tau cleavage in the primary visual cortex (V1 area) and the beneficial effect of 12A12mAb treatment on phenotype-associated visuo-spatial deficits in this AD animal model. We found out that non-invasive administration of 12 A12mAb markedly reduced the pathological accumulation of both truncated tau and Aβ in the V1 area, correlated to significant improvement in visual recognition memory performance along with local increase in two direct readouts of cortical synaptic plasticity, including the dendritic spine density and the expression level of activity-regulated cytoskeleton protein Arc/Arg3.1. Translation of these findings to clinical therapeutic interventions could offer an innovative tau-directed opportunity to delay or halt the visual impairments occurring during AD progression.

Inherent regional brain activity changes in male obstructive sleep apnea with mild cognitive impairment: A resting-state magnetic resonance study

Obstructive sleep apnea (OSA) is the most common sleep disorder worldwide. Previous studies have shown that OSA patients are often accompanied by cognitive function loss, and the underlying neurophysiological mechanism is still unclear. This study aimed to determine whether there are differences in regional homogeneity (Reho) and functional connectivity (FC) across the brain between OSA patients with MCI (OSA-MCI) and those without MCI (OSA-nMCI) and whether such differences can be used to distinguish the two groups. Resting state magnetic resonance data were collected from 48 OSA-MCI patients and 47 OSA-nMCI patients. The brain regions with significant differences in Reho and FC between the two groups were identified, and the Reho and FC features were combined with machine learning methods for classification. Compared with OSA-nMCI patients, OSA-MCI patients showed significantly lower Reho in bilateral lingual gyrus and left superior temporal gyrus. OSA-MCI patients also showed significantly lower FC between the bilateral lingual gyrus and bilateral cuneus, left superior temporal gyrus and left middle temporal gyrus, middle frontal gyrus, and bilateral posterior cingulate/calcarine/cerebellar anterior lobe. Based on Reho and FC features, logistic regression classification accuracy was 0.87; sensitivity, 0.70; specificity, 0.89; and area under the curve, 0.85. Correlation analysis showed that MoCA scale score in OSA patients was significant positive correlation sleep efficiency and negatively correlation with neck circumference. In conclusion, our results showed that the OSA-MCI group showed decreased Reho and FC in specific brain regions compared with the OSA-nMCI group, which may help to understand the underlying neuroimaging mechanism of OSA leading to cognitive dysfunction and may serve as a potential biomarker to distinguish whether OSA is accompanied by cognitive impairment.

Quantitative Assessment of Resting-State Functional Connectivity MRI to Differentiate Amnestic Mild Cognitive Impairment, Late-Onset Alzheimer's Disease From Normal Subjects

BACKGROUND

Alzheimer disease (AD) is a neurological disorder with brain network dysfunction. Investigation of the brain network functional connectivity (FC) alterations using resting-state functional MRI (rs-fMRI) can provide valuable information about the brain network pattern in early AD diagnosis.

PURPOSE

To quantitatively assess FC patterns of resting-state brain networks and graph theory metrics (GTMs) to identify potential features for differentiation of amnestic mild cognitive impairment (aMCI) and late-onset AD from normal.

STUDY TYPE

Prospective.

SUBJECTS

A total of 14 normal, 16 aMCI, and 13 late-onset AD.

FIELD STRENGTH/SEQUENCE

A 3.0 T; rs-fMRI: single-shot 2D-EPI and T1-weighted structure: MPRAGE.

ASSESSMENT

By applying bivariate correlation coefficient and Fisher transformation on the time series of predefined ROIs' pairs, correlation coefficient matrixes and ROI-to-ROI connectivity (RRC) were extracted. By thresholding the RRC matrix (with a threshold of 0.15), a graph adjacency matrix was created to compute GTMs.

STATISTICAL TESTS

Region of interest (ROI)-based analysis: parametric multivariable statistical analysis (PMSA) with a false discovery rate using (FDR)-corrected P < 0.05 cluster-level threshold together with posthoc uncorrected P < 0.05 connection-level threshold. Graph-theory analysis (GTA): P-FDR-corrected < 0.05. One-way ANOVA and Chi-square tests were used to compare clinical characteristics.

RESULTS

PMSA differentiated AD from normal, with a significant decrease in FC of default mode, salience, dorsal attention, frontoparietal, language, visual, and cerebellar networks. Furthermore, significant increase in overall FC of visual and language networks was observed in aMCI compared to normal. GTA revealed a significant decrease in global-efficiency (28.05 < 45), local-efficiency (22.98 < 24.05), and betweenness-centrality (14.60 < 17.39) for AD against normal. Moreover, a significant increase in local-efficiency (33.46 > 24.05) and clustering-coefficient (25 > 20.18) were found in aMCI compared to normal.

DATA CONCLUSION

This study demonstrated resting-state FC potential as an indicator to differentiate AD, aMCI, and normal. GTA revealed brain integration and breakdown by providing concise and comprehensible statistics.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

The Functional Network of the Visual Cortex Is Altered in Migraine

Migraine is a common neurological disorder characterized by recurrent episodes of headache, frequently accompanied by various reversible neurological disturbances. Some migraine patients experience visually triggered migraine headache, and most attacks of migraine with aura are associated with the disturbance of vision and photophobia, suggesting an abnormal neural activity in the visual cortex. Numerous studies have shown a large cortical hemodynamic response to visual stimulation and an altered intrinsic visual functional connectivity network in patients with migraine. In this interictal study, we applied a novel data-driven method with fMRI to identify the functional network in the visual cortex evoked by visual stimulation and investigated the effect of migraine on this network. We found that the distribution of the functional network along both the ventral and dorsal visual pathways differed between migraine patients and non-headache healthy control participants, providing evidence that the functional network was altered in migraine between headaches. The functional network was bilateral in the control participants but substantially lateralized in the migraine patients. The results also indicated different effects of colored lenses on the functional network for both participant groups.