Alteration of functional connectivity in patients with Alzheimer's disease revealed by resting-state functional magnetic resonance imaging

Regional-based static and dynamic alterations in Alzheimer disease: a longitudinal study

BACKGROUND

 Alzheimer disease (AD) leads to cognitive decline and alters functional connectivity (FC) in key brain regions. Resting-state functional magnetic resonance imaging (rs-fMRI) assesses these changes using static-FC for overall correlation and dynamic-FC for temporal variability.

OBJECTIVE

 In AD, there is altered FC compared to normal conditions. The present study investigates possible region-specific functional abnormalities occurring longitudinally over 1 year. Our aim is to evaluate the potential usefulness of the static and dynamic approaches in identifying biomarkers of AD progression.

METHODS

 The study involved 15 AD and 20 healthy participants from the Alzheimer's Disease Neuroimaging Initiative 2 (ADNI2) database, tracked over 2 visits within 1 year. Using constrained-independent component analysis, we assessed FC changes across 80-regions of interest in AD over the year, examining both static and dynamic conditions.

RESULTS

 The average regional FC decreased in AD compared to healthy subjects at baseline and after 1 year. The dynamic condition identifies similarities with a few additional changes in the FC compared to the static condition. In both analyses, the baseline assessment revealed reduced connectivity between the following regions: right-middle-occipital and left-superior-occipital, left-hippocampus and right-postcentral, left-lingual and left-fusiform, and precuneus and left-thalamus. Additionally, increased connectivity was found between the left-superior-occipital and precuneus regions. In the 1-year AD assessment, increased connectivity was noted between the right-superior-temporal-pole and right-insular, right-hippocampus and left-caudate, right-middle-occipital and right-superior-temporal-pole, and posterior-cingulate-cortex and middle-temporal-pole regions.

CONCLUSION

 Significant changes were observed at baseline in the frontal, occipital, and core basal-ganglia regions, progressing towards the temporal lobe and subcortical regions in the following year. After 1 year, we observed the aforementioned region-specific neurological differences in AD, significantly aiding diagnosis and disease tracking.

Normal-Tension Glaucoma and Potential Clinical Links to Alzheimer's Disease

Glaucoma is a group of optic neuropathies and the world's leading cause of irreversible blindness. Normal-tension glaucoma (NTG) is a subtype of glaucoma that is characterized by a typical pattern of peripheral retinal loss, in which the patient's intraocular pressure (IOP) is considered within the normal range (<21 mmHg). Currently, the only targetable risk factor for glaucoma is lowering IOP, and patients with NTG continue to experience visual field loss after IOP-lowering treatments. This demonstrates the need for a better understanding of the pathogenesis of NTG and underlying mechanisms leading to neurodegeneration. Recent studies have found significant connections between NTG and cerebral manifestations, suggesting NTG as a neurodegenerative disease beyond the eye. Gaining a better understanding of NTG can potentially provide new Alzheimer's Disease diagnostics capabilities. This review identifies the epidemiology, current biomarkers, altered fluid dynamics, and cerebral and ocular manifestations to examine connections and discrepancies between the mechanisms of NTG and Alzheimer's Disease.

Disrupted Dynamic Functional Network Connectivity Among Cognitive Control Networks in the Progression of Alzheimer's Disease

Background: Alzheimer's disease (AD) is the most common age-related dementia that promotes a decline in memory, thinking, and social skills. The initial stages of dementia can be associated with mild symptoms, and symptom progression to a more severe state is heterogeneous across patients. Recent work has demonstrated the potential for functional network mapping to assist in the prediction of symptomatic progression. However, this work has primarily used static functional connectivity (sFC) from resting-state functional magnetic resonance imaging. Recently, dynamic functional connectivity (dFC) has been recognized as a powerful advance in functional connectivity methodology to differentiate brain network dynamics between healthy and diseased populations. Methods: Group independent component analysis was applied to extract 17 components within the cognitive control network (CCN) from 1385 individuals across varying stages of AD symptomology. We estimated dFC among 17 components within the CCN, followed by clustering the dFCs into 3 recurring brain states, and then estimated a hidden Markov model and the occupancy rate for each subject. Then, we investigated the link between CCN dFC features and AD progression. Also, we investigated the link between sFC and AD progression and compared its results with dFC results. Results: Progression of AD symptoms was associated with increases in connectivity within the middle frontal gyrus. Also, the very mild AD (vmAD) showed less connectivity within the inferior parietal lobule (in both sFC and dFC) and between this region and the rest of CCN (in dFC analysis). Also, we found that within-middle frontal gyrus connectivity increases with AD progression in both sFC and dFC results. Finally, comparing with vmAD, we found that the normal brain spends significantly more time in a state with lower within-middle frontal gyrus connectivity and higher connectivity between the hippocampus and the rest of CCN, highlighting the importance of assessing the dynamics of brain connectivity in this disease. Conclusion: Our results suggest that AD progress not only alters the CCN connectivity strength but also changes the temporal properties in this brain network. This suggests the temporal and spatial pattern of CCN as a biomarker that differentiates different stages of AD.

Classification of Alzheimer's Disease Using Maximal Information Coefficient-Based Functional Connectivity with an Extreme Learning Machine

Alzheimer's disease (AD) is a progressive chronic illness that leads to cognitive decline and dementia. Neuroimaging technologies, such as functional magnetic resonance imaging (fMRI), and deep learning approaches offer promising avenues for AD classification. In this study, we investigate the use of fMRI-based functional connectivity (FC) measures, including the Pearson correlation coefficient (PCC), maximal information coefficient (MIC), and extended maximal information coefficient (eMIC), combined with extreme learning machines (ELM) for AD classification. Our findings demonstrate that employing non-linear techniques, such as MIC and eMIC, as features for classification yields accurate results. Specifically, eMIC-based features achieve a high accuracy of 94% for classifying cognitively normal (CN) and mild cognitive impairment (MCI) individuals, outperforming PCC (81%) and MIC (85%). For MCI and AD classification, MIC achieves higher accuracy (81%) compared to PCC (58%) and eMIC (78%). In CN and AD classification, eMIC exhibits the best accuracy of 95% compared to MIC (90%) and PCC (87%). These results underscore the effectiveness of fMRI-based features derived from non-linear techniques in accurately differentiating AD and MCI individuals from CN individuals, emphasizing the potential of neuroimaging and machine learning methods for improving AD diagnosis and classification.

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.

Transcranial alternating current stimulation combined with sound stimulation improves cognitive function in patients with Alzheimer's disease: Study protocol for a randomized controlled trial

Background

The number of patients with Alzheimer's disease (AD) worldwide is increasing yearly, but the existing treatment methods have poor efficacy. Transcranial alternating current stimulation (tACS) is a new treatment for AD, but the offline effect of tACS is insufficient. To prolong the offline effect, we designed to combine tACS with sound stimulation to maintain the long-term post-effect.

Materials and methods

To explore the safety and effectiveness of tACS combined with sound stimulation and its impact on the cognition of AD patients. This trial will recruit 87 patients with mild to moderate AD. All patients were randomly divided into three groups. The change in Alzheimer's Disease Assessment Scale-Cognitive (ADAS-Cog) scores from the day before treatment to the end of treatment and 3 months after treatment was used as the main evaluation index. We will also explore the changes in the brain structural network, functional network, and metabolic network of AD patients in each group after treatment.

Discussion

We hope to conclude that tACS combined with sound stimulation is safe and tolerable in 87 patients with mild to moderate AD under three standardized treatment regimens. Compared with tACS alone or sound alone, the combination group had a significant long-term effect on cognitive improvement. To screen out a better treatment plan for AD patients. tACS combined with sound stimulation is a previously unexplored, non-invasive joint intervention to improve patients' cognitive status. This study may also identify the potential mechanism of tACS combined with sound stimulation in treating mild to moderate AD patients.

Clinical Trial Registration

Clinicaltrials.gov, NCT05251649. Registered on February 22, 2022.

Unravelling the relationship between amyloid accumulation and brain network function in normal aging and very mild cognitive decline: a longitudinal analysis

Pathological changes in the brain begin accumulating decades before the appearance of cognitive symptoms in Alzheimer's disease. The deposition of amyloid beta proteins and other neurotoxic changes occur, leading to disruption in functional connections between brain networks. Discrete characterization of the changes that take place in preclinical Alzheimer's disease has the potential to help treatment development by targeting the neuropathological mechanisms to prevent cognitive decline and dementia from occurring entirely. Previous research has focused on the cross-sectional differences in the brains of patients with mild cognitive impairment or Alzheimer's disease and healthy controls or has concentrated on the stages immediately preceding cognitive symptoms. The present study emphasizes the early preclinical phases of neurodegeneration. We use a longitudinal approach to examine the brain changes that take place during the early stages of cognitive decline in the Open Access Series of Imaging Studies-3 data set. Among 1098 participants, 274 passed the inclusion criteria (i.e. had at least two cognitive assessments and two amyloid scans). Over 90% of participants were healthy at baseline. Over 8-10 years, some participants progressed to very mild cognitive impairment (n = 48), while others stayed healthy (n = 226). Participants with cognitive decline show faster amyloid accumulation in the lateral temporal, motor and parts of the lateral prefrontal cortex. These changes in amyloid levels were linked to longitudinal increases in the functional connectivity of select networks, including default mode, frontoparietal and motor components. Our findings advance the understanding of amyloid staging and the corresponding changes in functional organization of large-scale brain networks during the progression of early preclinical Alzheimer's disease.

Network synchronization deficits caused by dementia and Alzheimer's disease serve as topographical biomarkers: a pilot study

Mild cognitive impairment (MCI) is known as an early stage of cognitive decline. Amnestic MCI (aMCI) is considered as the preliminary stage of dementia which may progress to Alzheimer’s disease (AD). While some aMCI patients may stay in this condition for years, others might develop dementia associated with AD. Early detection of MCI allows for potential treatments to prevent or decelerate the process of developing dementia. Standard methods of diagnosing MCI and AD employ structural (imaging), behavioral (cognitive tests), and genetic or molecular (blood or CSF tests) techniques. Our study proposes network-level neural synchronization parameters as topographical markers for diagnosing aMCI and AD. We conducted a pilot study based on EEG data recorded during an olfactory task from a group of elderly participants consisting of healthy individuals and patients of aMCI and AD to assess the value of different indicators of network-level phase and amplitude synchronization in differentiating the three groups. Significant differences were observed in the percent phase locking value, theta-gamma phase-amplitude coupling, and amplitude coherence between the groups, and classifiers were developed to differentiate the three groups based on these parameters. The observed differences in these indicators of network-level functionality of the brain can help explain the underlying processes involved in aMCI and AD.

Combined functional and structural imaging of brain white matter reveals stage-dependent impairment in multiple system atrophy of cerebellar type

Advances in fMRI of brain white matter (WM) have established the feasibility of understanding how functional signals of WM evolve with brain diseases. By combining functional signals with structural features of WM, the current study characterizes functional and structural impairments of WM in cerebelar type multiple system atrophy, with the goal to derive new mechanistic insights into the pathological progression of this disease. Our analysis of 30 well-diagnosed patients revealed pronounced decreases in functional connectivity in WM bundles of the cerebellum and brainstem, and concomitant local structural alterations that depended on the disease stage. The novel findings implicate a critical time point in the pathological evolution of the disease, which could guide optimal therapeutic interventions. Furthermore, fMRI signals of impaired WM bundles exhibited superior sensitivity in differentiating initial disease development, which demonstrates great potential of using these signals to inform disease management.

Functional Connectivity Hypointensity of Middle Cingulate Gyrus and Thalamus in Age-Related Macular Degeneration Patients: A Resting-State Functional Magnetic Resonance Imaging Study

Objective

Age-related macular degeneration (AMD) causes visual damage and blindness globally. The purpose of this study was to investigate changes in functional connectivity (FC) in AMD patients using resting-state functional magnetic resonance imaging (rs-fMRI).

Subjects and Methods

A total of 23 patients (12 male, 11 female) with AMD were enrolled to the AMD patients group (AMDs), and 17 healthy age-, sex-, and education-matched controls (9 male, 8 female) to the healthy controls group (HCs). All participants underwent rs-fMRI and mean FC values were compared between the two groups.

Results

Significantly higher FC values were found in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), inferior parietal lobule (IPL), rectal gyrus (RTG), and superior parietal lobule (SPL) in AMDs compared with HCs. Conversely, FC values in the cerebellum posterior lobe (CPL), middle cingulate gyrus (MCG), medulla (MDL), cerebellum anterior lobe (CAL), and thalamus (TLM) were significantly lower in AMDs than in HCs.

Conclusion

This study demonstrated FC abnormalities in many specific cerebral regions in AMD patients, and may provide new insights for exploration of potential pathophysiological mechanism of AMD-induced functional cerebral changes.

Synthesis of New 3-Arylcoumarins Bearing N-Benzyl Triazole Moiety: Dual Lipoxygenase and Butyrylcholinesterase Inhibitors With Anti-Amyloid Aggregation and Neuroprotective Properties Against Alzheimer’s Disease

A novel series of coumarin derivatives linked to the N-benzyl triazole group were synthesized and evaluated against 15-lipoxygenase (15-LOX), and acetyl- and butyrylcholinesterase (AChE and BuChE) to find the most potent derivative against Alzheimer’s disease (AD). Most of the compounds showed weak to moderate activity against ChEs. Among the most active BuChE and 15-LOX inhibitors, 8l and 8n exhibited an excellent neuroprotective effect, higher than the standard drug (quercetin) on the PC12 cell model injured by H2O2 and significantly reduced aggregation of amyloid Aβ1-42, with potencies of 1.44 and 1.79 times higher than donepezil, respectively. Compound 8l also showed more activity than butylated hydroxytoluene (BHT) as the reference antioxidant agent in reducing the levels of H2O2 activated by amyloid β in BV2 microglial cells. Kinetic and ligand–enzyme docking studies were also performed for better understanding of the mode of interaction between the best BuChE inhibitor and the enzyme. Considering the acceptable BuChE and 15-LOX inhibition activities as well as significant neuroprotection, and anti-amyloid aggregation activities, 8l and 8n could be considered as potential MTDLs for further modification and studies against AD.

Acupuncture enhances brain function in patients with mild cognitive impairment: evidence from a functional-near infrared spectroscopy study

Mild cognitive impairment (MCI) is a precursor to Alzheimer’s disease. It is imperative to develop a proper treatment for this neurological disease in the aging society. This observational study investigated the effects of acupuncture therapy on MCI patients. Eleven healthy individuals and eleven MCI patients were recruited for this study. Oxy- and deoxy-hemoglobin signals in the prefrontal cortex during working-memory tasks were monitored using functional near-infrared spectroscopy. Before acupuncture treatment, working-memory experiments were conducted for healthy control (HC) and MCI groups (MCI-0), followed by 24 sessions of acupuncture for the MCI group. The acupuncture sessions were initially carried out for 6 weeks (two sessions per week), after which experiments were performed again on the MCI group (MCI-1). This was followed by another set of acupuncture sessions that also lasted for 6 weeks, after which the experiments were repeated on the MCI group (MCI-2). Statistical analyses of the signals and classifications based on activation maps as well as temporal features were performed. The highest classification accuracies obtained using binary connectivity maps were 85.7% HC vs. MCI-0, 69.5% HC vs. MCI-1, and 61.69% HC vs. MCI-2. The classification accuracies using the temporal features mean from 5 seconds to 28 seconds and maximum (i.e, max(5:28 seconds)) values were 60.6% HC vs. MCI-0, 56.9% HC vs. MCI-1, and 56.4% HC vs. MCI-2. The results reveal that there was a change in the temporal characteristics of the hemodynamic response of MCI patients due to acupuncture. This was reflected by a reduction in the classification accuracy after the therapy, indicating that the patients’ brain responses improved and became comparable to those of healthy subjects. A similar trend was reflected in the classification using the image feature. These results indicate that acupuncture can be used for the treatment of MCI patients.

Multiparametric magnetic resonance imaging and positron emission tomography findings in neurodegenerative diseases: Current status and future directions

Neurodegenerative diseases (NDDs) are characterized by progressive neuronal loss, leading to dementia and movement disorders. NDDs broadly include Alzheimer's disease, frontotemporal lobar degeneration, parkinsonian syndromes, and prion diseases. There is an ever-increasing prevalence of mild cognitive impairment and dementia, with an accompanying immense economic impact, prompting efforts aimed at early identification and effective interventions. Neuroimaging is an essential tool for the early diagnosis of NDDs in both clinical and research settings. Structural, functional, and metabolic imaging modalities, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are widely available. They show encouraging results for diagnosis, monitoring, and treatment response evaluation. The current review focuses on the complementary role of various imaging modalities in relation to NDDs, the qualitative and quantitative utility of newer MRI techniques, novel radiopharmaceuticals, and integrated PET/MRI in the setting of NDDs.

Neuroimaging mechanisms of high-frequency repetitive transcranial magnetic stimulation for treatment of amnestic mild cognitive impairment: a double-blind randomized sham-controlled trial

Individuals with amnestic mild cognitive impairment (aMCI) have a high risk of developing Alzheimer’s disease. Although repetitive transcranial magnetic stimulation (rTMS) is considered a potentially effective treatment for cognitive impairment in patients with aMCI, the neuroimaging mechanisms are poorly understood. Therefore, we performed a double-blind randomized sham-controlled trial in which rTMS was applied to the left dorsolateral prefrontal cortex of aMCI patients recruited from a community near the Third Hospital Affiliated to Sun Yat-sen University, China. Twenty-four patients with aMCI were randomly assigned to receive true rTMS (treatment group, n = 12, 6 men and 6 women; age 65.08 ± 4.89 years) or sham stimulation (sham group, n = 12, 5 men and 7 women; age 64.67 ± 4.77 years). rTMS parameters included a stimulation frequency of 10 Hz, stimulation duration of 2 seconds, stimulation interval of 8 seconds, 20 repetitions at 80% of the motor threshold, and 400 pulses per session. rTMS/sham stimulation was performed five times per week over a period of 4 consecutive weeks. Our results showed that compared with baseline, Montreal Cognitive Assessment scores were significantly increased and the value of the amplitude of low-frequency fluctuation (ALFF) was significantly increased at the end of treatment and 1 month after treatment. Compared with the sham group, the ALFF values in the right inferior frontal gyrus, triangular part of the inferior frontal gyrus, right precuneus, left angular gyrus, and right supramarginal gyrus were significantly increased, and the ALFF values in the right superior frontal gyrus were significantly decreased in the treatment group. These findings suggest that high-frequency rTMS can effectively improve cognitive function in aMCI patients and alter spontaneous brain activity in cognitive-related brain areas. This study was approved by the Ethics Committee of Shenzhen Baoan Hospital of Southern Medical University, China (approval No. BYL20190901) on September 3, 2019, and registered in the Chinese Clinical Trials Registry (registration No. ChiCTR1900028180) on December 14, 2019.

Aberrant frontostriatal connectivity in Alzheimer's disease with positive palmomental reflex

BACKGROUND AND PURPOSE

Primitive reflexes may reoccur in various neurodegenerative diseases. However, little is known about their structural and functional correlates in the human brain. Notably, the neural mechanisms underlying a positive palmomental reflex (PMR) are poorly understood. As recent studies link Alzheimer's disease (AD)-related primitive reflexes to a dysfunction of the corticostriatal motor circuit (CMC), we conducted the present study to investigate functional and structural correlates of a positive PMR. We hypothesized an involvement of frontostriatal structures and an impairment of the CMC.

METHODS

Using whole-brain resting-state functional connectivity (FC), hypothesis and FC result-based probabilistic tractography, and voxel-based morphometry analyses, we compared two groups of AD patients with either positive (n = 12) or negative PMR (n = 12).

RESULTS

No significant differences in grey matter volume or structural connectivity (SC) could be observed between the PMR-positive and PMR-negative groups. In contrast, the PMR-positive group showed a decreased seed-to-voxel FC between the bilateral supplementary motor area and parts of the right-hemispherical caudate nucleus and thalamus and a decreased region of interest (ROI)-to-ROI FC between the left putamen and the left superior frontal gyrus.

CONCLUSION

Data suggest that dysfunction of the CMC reflected by decreased FC underlies a positive PMR in patients with AD. The lack of significant grey matter or SC differences might reflect that changes in FC appear before changes in SC in the structures of the CMC and brain atrophy.

AT2R's (Angiotensin II Type 2 Receptor's) Role in Cognitive and Cerebrovascular Deficits in a Mouse Model of Alzheimer Disease

Antihypertensive medications targeting the renin-angiotensin system have lowered the incidence and progression of Alzheimer disease. Understanding how these medications function could lead to novel therapeutic strategies. AT4Rs (angiotensin IV receptors) have been associated with angiotensin receptor blockers' cognitive, cerebrovascular, and neuroinflammatory rescue in Alzheimer disease models. Yet, whether AT4Rs act alone or with AT2Rs remains unknown. Here, we investigated whether AT2Rs contribute to losartan's benefits and whether chronic AT2R activation could mimic angiotensin receptor blocker benefits in transgenic mice overexpressing familial Alzheimer disease mutations of the human APP (amyloid precursor protein). Losartan-treated mice (10 mg/kg per day, drinking water, 7 months) received intracerebroventricular (1 month) administration of vehicle or AT2R antagonist PD123319 (1.6 nmol/day). PD123319 countered losartan's benefits on spatial learning and memory, neurovascular coupling, and hampered those on oxidative stress and nitric oxide bioavailability. PD123319 did not oppose losartan's benefits on short-term memory and vasodilatory function and had no benefit on neuroinflammation or Aβ (amyloid β) pathology. Mice receiving either vehicle or selective AT2R agonist compound 21 (intracerebroventricular: 1 nmol/day, 1 month or drinking water: 10 mg/kg per day, 7 months), showed no improvement in memory, vasodilatory function, or nitric oxide bioavailability. Compound 21 treatment normalized neurovascular coupling, reduced astrogliosis independent of persisting microgliosis, and exacerbated oxidative stress in APP mice. Compound 21 reduced dense core Aβ plaques, but not diffuse plaques or Aβ species. Our findings suggest that targeting AT2Rs is not an ideal strategy for restoring Aβ-related cognitive and cerebrovascular deficits.