Atrophy, metabolism and cognition in the posterior cortical atrophy spectrum based on Alzheimer's disease cerebrospinal fluid biomarkers

The characteristics of brain atrophy prior to the onset of Alzheimer's disease: a longitudinal study

Objective

We aimed to use the onset time of Alzheimer's disease (AD) as the reference time to longitudinally investigate the atrophic characteristics of brain structures prior to the onset of AD.

Materials and methods

A total of 328 participants from the ADNI database with clear onset of AD and structural imaging data were included in our study. The time before the onset of AD (abbreviated as BAD) was calculated. We investigated the longitudinal brain changes in 97 regions using multivariate linear mixed effects regression models.

Results

The average BAD was -28.15 months, with a range from -156 to 0 months. The 54 brain regions showed significant atrophy prior to the onset of AD, and these regions were mainly distributed in the frontal and temporal lobes. The parietal and occipital lobe exhibited relatively less atrophy than the other brain lobes. Sex, age, and magnetic field strength had greater direct impacts on structural indicators than APOE genotype and education. The analysis of interaction effects revealed that the APOE ε4 mutation carriers exhibited more severe structural changes in specific brain regions as the BAD increased. However, sex, age, and education had minimal regulatory influence on the structural changes associated with BAD.

Conclusion

Longitudinal analysis, with the onset time point of AD as the reference, can accurately describe the features of structural changes preceding the onset of AD and provide a comprehensive understanding of AD development.

Characterizing Differences in Functional Connectivity Between Posterior Cortical Atrophy and Semantic Dementia by Seed-Based Approach

Background

Posterior cortical atrophy (PCA) and semantic dementia (SD) are focal syndromes involving different cerebral regions. This study aimed to demonstrate the existence of abnormal functional connectivity (FC) with an affected network in PCA and SD.

Methods

A total of 10 patients with PCA, 12 patients with SD, and 11 controls were recruited to undergo a detailed clinical history interview and physical examination, neuropsychological assessments, and PET/MRI scan. Seed-based FC analyses were conducted to construct FC in language network, visual network, and salience network. The two-sample t-test was performed to reveal distinct FC patterns in PCA and SD, and we further related the FC difference to cognition. Meanwhile, the uptake value of fluorodeoxyglucose in regions with FC alteration was also extracted for comparison.

Results

We found a global cognitive impairment in patients with PCA and SD. The results of FC analyses showed that patients with PCA present decreased FC in left precentral gyrus to left V1 and increased FC in right inferior frontal gyrus to right V1 in the visual network, right medial frontal gyrus and left fusiform to left anterior temporal lobe and post-superior temporal gyrus in the language network, and left superior temporal gyrus to left anterior insula in the salience network, which were related to cognitive function. Patients with SD had decreased FC from right superior frontal gyrus, right middle frontal gyrus and right superior frontal gyrus to left anterior temporal lobe, or post-superior temporal gyrus in the language network, as well as left superior frontal gyrus to right anterior insula in the salience network, positively relating to cognitive function, but increased FC in the right superior temporal gyrus to left anterior temporal lobe in the language network, and right insula and left anterior cingulum to right anterior insula in the salience network, negatively relating to cognitive function. Most of the regions with FC change in patients with PCA and SD had abnormal metabolism simultaneously.

Conclusion

Abnormal connectivity spread over the cortex involving language and salience networks was common in patients with PCA and SD, whereas FC change involving the visual network was unique to patients with PCA. The FC changes were matched for cognitive deficits.

α-synuclein as an emerging pathophysiological biomarker of Alzheimer's disease

INTRODUCTION

α-syn aggregates represent the pathological hallmark of synucleinopathies as well as a frequent copathology (almost 1/3 of cases) in AD. Recent research indicates a potential role of α-syn species, measured in CSF with conventional analytical techniques, in the differential diagnosis between AD and synucleinopathies (such as DLB). Pioneering studies report the detection of α-syn in blood, however, conclusive investigations are controversial. Ultrasensitive seed amplification techniques, enabling the selective quantification of α-syn seeds, may represent an effective solution to identify the α-syn component in AD and facilitate a biomarker-guided stratification.

AREAS COVERED

We performed a PubMed-based review of the latest findings on α-syn-related biomarkers for AD, focusing on bodily fluids. A dissertation on the role of ultrasensitive seed amplification assays, detecting α-syn seeds from different biological samples, was conducted.

EXPERT OPINION

α-syn may contribute to progressive AD neurodegeneration through cross-seeding especially with tau protein. Ultrasensitive seed amplification techniques may support a biomarker-drug co-development pathway and may be a pathophysiological candidate biomarker for the evolving ATX(N) system to classify AD and the spectrum of primary NDDs. This would contribute to a precise approach to AD, aimed at implementing disease-modifying treatments.

Association of Neurofibrillary Tangle Distribution With Age at Onset-Related Clinical Heterogeneity in Alzheimer Disease: An Autopsy Study

BACKGROUND AND OBJECTIVE

Patients with earlier age at onset of sporadic Alzheimer disease (AD) are more likely than those with later onset to present with atypical clinical and cognitive features. We sought to determine whether this age-related clinical and cognitive heterogeneity is mediated by different topographic distributions of tau-aggregate neurofibrillary tangles (NFTs) or by variable amounts of concomitant non-AD neuropathology.

METHODS

The relative distribution of NFT density in hippocampus and midfrontal neocortex was calculated, and α-synuclein, TAR DNA binding protein 43 (TDP-43), and microvascular copathologies were staged, in patients with severe AD and age at onset of 51-60 (n = 40), 61-70 (n = 41), and >70 (n = 40) years. Regression, mediation, and mixed effects models examined relationships of pathologic findings with clinical features and longitudinal cognitive decline.

RESULTS

Patients with later age at onset of AD were less likely to present with nonmemory complaints (odds ratio [OR] 0.46 per decade, 95% confidence interval [CI] 0.22-0.88), psychiatric symptoms (β = -0.66, 95% CI -1.15 to -0.17), and functional impairment (β = -1.25, 95% CI -2.34 to -0.16). TDP-43 (OR 2.00, 95% CI 1.23-3.35) and microvascular copathology (OR 2.02, 95% CI 1.24-3.40) were more common in later onset AD, and α-synuclein copathology was not related to age at onset. NFT density in midfrontal cortex (β = -0.51, 95% CI -0.72 to -0.31) and midfrontal/hippocampal NFT ratio (β = -0.18, 95% CI -0.26 to -0.10) were lower in those with later age at onset. Executive function (β = 0.48, 95% CI 0.09-0.90) and visuospatial cognitive deficits (β = 0.97, 95% CI 0.46-1.46) were less impaired in patients with later age at onset. Mediation analyses showed that the effect of age at onset on severity of executive function deficits was mediated by midfrontal/hippocampal NFT ratio (β = 0.21, 95% CI 0.08-0.38) and not by concomitant non-AD pathologies. Midfrontal/hippocampal NFT ratio also mediated an association between earlier age at onset and faster decline on tests of global cognition, executive function, and visuospatial abilities.

DISCUSSION

Worse executive dysfunction and faster cognitive decline in people with sporadic AD with earlier rather than later age at onset is mediated by greater relative midfrontal neocortical to hippocampal NFT burden and not by concomitant non-AD neuropathology.

The temporal lobe in typical and atypical Alzheimer disease

Alzheimer disease (AD) is defined neuropathologically by abnormal extra-cellular β-amyloid plaques combined with intraneuronal tau aggregation. Patients sharing the same neuropathological features but presenting different clinical manifestations and evolutions have led to the notion of AD spectrum. This spectrum encompasses typical and atypical forms of AD. For all of them, specific parts of the temporal lobes, as well as their structural and functional connections with other brain regions, are affected. In typical amnestic late-onset Alzheimer's disease (>65 years old; LOAD), tau pathology gradually spreads to the brain from the medial temporal lobe (MTL). MTL is an inhomogeneous structure consisting of several subregions densely connected to each other and to other cortical and subcortical brain regions. These regions play a crucial role in the storage of information in episodic memory. In less common early-onset AD (<65 years old; EOAD), a large proportion of patients presents atypical clinical manifestations, in which memory impairment is not inaugural and predominant. Instead, these patients have predominant and/or isolated deficits in language, visuospatial, motor, or executive/behavioral functions. In atypical variants, brain damage is mainly centered on the posterior regions, with relative sparing of the MTL. However, the temporal lobe also appears to be variably and specifically damaged in some subtypes of EOAD. For example, the left superior temporal gyrus is the core of brain damage in the language variant, as well as the ventral regions of the temporal lobe play an important role in the clinic of the visual variant.

Breakdown of specific functional brain networks in clinical variants of Alzheimer's disease

Alzheimer's disease (AD) is characterized by different clinical entities. Although AD phenotypes share a common molecular substrate (i.e., amyloid beta and tau accumulation), several clinicopathological differences exist. Brain functional networks might provide a macro-scale scaffolding to explain this heterogeneity. In this review, we summarize the evidence linking different large-scale functional network abnormalities to distinct AD phenotypes. Specifically, executive deficits in early-onset AD link with the dysfunction of networks that support sustained attention and executive functions. Posterior cortical atrophy relates to the breakdown of visual and dorsal attentional circuits, while the primary progressive aphasia variant of AD may be associated with the dysfunction of the left-lateralized language network. Additionally, network abnormalities might provide in vivo signatures for distinguishing proteinopathies that mimic AD, such as TAR DNA binding protein 43 related pathologies. These network differences vis-a-vis clinical syndromes are more evident in the earliest stage of AD. Finally, we discuss how these findings might pave the way for new tailored interventions targeting the most vulnerable brain circuit at the optimal time window to maximize clinical benefits.

Prediction of the progression from mild cognitive impairment to Alzheimer's disease using a radiomics-integrated model

Objective:

This study aimed to build and validate a radiomics-integrated model with whole-brain magnetic resonance imaging (MRI) to predict the progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD).

Methods:

357 patients with MCI were selected from the ADNI database, which is an open-source database for AD with multicentre cooperation, of which 154 progressed to AD during the 48-month follow-up period. Subjects were divided into a training and test group. For each patient, the baseline T₁WI MR images were automatically segmented into white matter, gray matter and cerebrospinal fluid (CSF), and radiomics features were extracted from each tissue. Based on the data from the training group, a radiomics signature was built using logistic regression after dimensionality reduction. The radiomics signatures, in combination with the apolipoprotein E4 (APOE4) and baseline neuropsychological scales, were used to build an integrated model using machine learning. The receiver operating characteristics (ROC) curve and data of the test group were used to evaluate the diagnostic accuracy and reliability of the model, respectively. In addition, the clinical prognostic efficacy of the model was evaluated based on the time of progression from MCI to AD.

Results:

Stepwise logistic regression analysis showed that the APOE4, clinical dementia rating, AD assessment scale, and radiomics signature were independent predictors of MCI progression to AD. The integrated model was constructed based on independent predictors using machine learning. The ROC curve showed that the accuracy of the model in the training and the test sets was 0.814 and 0.807, with a specificity of 0.671 and 0.738, and a sensitivity of 0.822 and 0.745, respectively. In addition, the model had the most significant diagnostic efficacy in predicting MCI progression to AD within 12 months, with an AUC of 0.814, sensitivity of 0.726, and specificity of 0.798.

Conclusion:

The integrated model based on whole-brain radiomics can accurately identify and predict the high-risk population of MCI patients who may progress to AD. Radiomics biomarkers are practical in the precursory stage of such disease.

A systematic review of atypical Alzheimer's disease including behavioural and psychological symptoms

Alzheimer's disease (AD) is the commonest cause of dementia, characterized by the clinical presentation of progressive anterograde episodic memory impairment. However, atypical presentation of patients is increasingly recognized. These atypical AD include logopenic aphasia, behavioural variant AD, posterior cortical atrophy, and corticobasal syndrome. These atypical AD are more common in patients with young onset AD before the age of 65 years old. Since medical needs (including the behavioural and psychological symptoms of dementia) of atypical AD patients could be different from typical AD patients, it is important for clinicians to be aware of these atypical forms of AD. In addition, disease modifying treatment may be available in the future. This review aims at providing an update on various important subtypes of atypical AD including behavioural and psychological symptoms.

Update on posterior cortical atrophy

PURPOSE OF REVIEW

Non-amnestic (or atypical) presentations of neurodegenerative dementias are underrecognized and underdiagnosed, including posterior cortical atrophy (PCA) syndrome, which is characterized by prominent visuospatial and visuoperceptual dysfunction at presentation. It is most commonly due to Alzheimer's disease pathology, while Lewy body disease, corticobasal degeneration, and prion disease are neuropathological entities that are less frequently associated with PCA. The diagnosis of PCA is often delayed, to the detriment of the patient, and awareness and understanding of PCA will improve detection, prognostication, and treatment.

RECENT FINDINGS

The natural history of PCA appears to be distinct from typical Alzheimer's disease and significant heterogeneity exists within the PCA syndrome, with the underlying causes of this heterogeneity beginning to be explored. Functional and molecular imaging can assist in better understanding PCA, particularly assessment of network disruptions that contribute to clinical phenotypes. Cerebrospinal fluid biomarkers are useful to detect underlying pathology, but measures of retinal thickness are less promising. There are currently no adequate treatment options for PCA.

SUMMARY

Continued efforts to characterize PCA are needed, and greater awareness and understanding of atypical presentations of neurodegenerative dementias could serve to elucidate pathobiological mechanisms of underlying disease.

Past, Present, and Future of Non-invasive Brain Stimulation Approaches to Treat Cognitive Impairment in Neurodegenerative Diseases: Time for a Comprehensive Critical Review

Low birth rates and increasing life expectancy experienced by developed societies have placed an unprecedented pressure on governments and the health system to deal effectively with the human, social and financial burden associated to aging-related diseases. At present, ∼24 million people worldwide suffer from cognitive neurodegenerative diseases, a prevalence that doubles every five years. Pharmacological therapies and cognitive training/rehabilitation have generated temporary hope and, occasionally, proof of mild relief. Nonetheless, these approaches are yet to demonstrate a meaningful therapeutic impact and changes in prognosis. We here review evidence gathered for nearly a decade on non-invasive brain stimulation (NIBS), a less known therapeutic strategy aiming to limit cognitive decline associated with neurodegenerative conditions. Transcranial Magnetic Stimulation and Transcranial Direct Current Stimulation, two of the most popular NIBS technologies, use electrical fields generated non-invasively in the brain to long-lastingly enhance the excitability/activity of key brain regions contributing to relevant cognitive processes. The current comprehensive critical review presents proof-of-concept evidence and meaningful cognitive outcomes of NIBS in eight of the most prevalent neurodegenerative pathologies affecting cognition: Alzheimer's Disease, Parkinson's Disease, Dementia with Lewy Bodies, Primary Progressive Aphasias (PPA), behavioral variant of Frontotemporal Dementia, Corticobasal Syndrome, Progressive Supranuclear Palsy, and Posterior Cortical Atrophy. We analyzed a total of 70 internationally published studies: 33 focusing on Alzheimer's disease, 19 on PPA and 18 on the remaining neurodegenerative pathologies. The therapeutic benefit and clinical significance of NIBS remains inconclusive, in particular given the lack of a sufficient number of double-blind placebo-controlled randomized clinical trials using multiday stimulation regimes, the heterogeneity of the protocols, and adequate behavioral and neuroimaging response biomarkers, able to show lasting effects and an impact on prognosis. The field remains promising but, to make further progress, research efforts need to take in account the latest evidence of the anatomical and neurophysiological features underlying cognitive deficits in these patient populations. Moreover, as the development of in vivo biomarkers are ongoing, allowing for an early diagnosis of these neuro-cognitive conditions, one could consider a scenario in which NIBS treatment will be personalized and made part of a cognitive rehabilitation program, or useful as a potential adjunct to drug therapies since the earliest stages of suh diseases. Research should also integrate novel knowledge on the mechanisms and constraints guiding the impact of electrical and magnetic fields on cerebral tissues and brain activity, and incorporate the principles of information-based neurostimulation.

Parieto-occipital sulcus widening differentiates posterior cortical atrophy from typical Alzheimer disease

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Parieto-occipital sulcus visual rating scale can distinguish PCA from typical AD.

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Visual rating scales have been validated using VBM and Brainvisa Morphologist.

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Visual rating score reflects sulcal widening rather than grey matter reduction.

Objectives

Posterior Cortical Atrophy (PCA) is an atypical presentation of Alzheimer disease (AD) characterized by atrophy of posterior brain regions. This pattern of atrophy is usually evaluated with Koedam visual rating scale, a score developed to enable visual assessment of parietal atrophy on magnetic resonance imaging (MRI). However, Koedam scale is complex to assess and its utility in the differential diagnosis between PCA and typical AD has not been demonstrated yet. The aim of this study is therefore to spot a simple and reliable MRI element able to differentiate between PCA and typical AD using visual rating scales.

Methods

15 patients who presented with progressive complex visual disorders and predominant occipitoparietal hypometabolism on PET-FDG were selected from our centre and compared with 30 typical AD patients and 15 healthy subjects. We used previously validated visual rating scales including Koedam scale, which we divided into three major components: posterior cingulate, precuneus and parieto-occipital. Subsequently we validated the results using the automated software Brainvisa Morphologist and Voxel Based Morphometry (VBM).

Results

Patients with PCA, compared to typical AD, showed higher widening of the parieto-occipital sulcus, assessed both with visual rating scales and Brainvisa. In the corresponding areas, the VBM analysis showed an inverse correlation between the results obtained from the visual evaluation scales with the volume of the grey matter and a direct correlation between the same results with the cerebrospinal fluid volume.

Conclusions

A visually based rating scale for parieto-occipital sulcus can distinguish Posterior Cortical Atrophy from typical Alzheimer disease.

Latent atrophy factors related to phenotypical variants of posterior cortical atrophy

OBJECTIVE

To determine whether atrophy relates to phenotypical variants of posterior cortical atrophy (PCA) recently proposed in clinical criteria (i.e., dorsal, ventral, dominant-parietal, and caudal) we assessed associations between latent atrophy factors and cognition.

METHODS

We employed a data-driven Bayesian modeling framework based on latent Dirichlet allocation to identify latent atrophy factors in a multicenter cohort of 119 individuals with PCA (age 64 ± 7 years, 38% male, Mini-Mental State Examination 21 ± 5, 71% β-amyloid positive, 29% β-amyloid status unknown). The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, MRI scanner field strength, and whole-brain gray matter volume) and provides voxelwise probabilistic maps for a predetermined number of atrophy factors, allowing every individual to express each factor to a degree without a priori classification. Individual factor expressions were correlated to 4 PCA-specific cognitive domains (object perception, space perception, nonvisual/parietal functions, and primary visual processing) using general linear models.

RESULTS

The model revealed 4 distinct yet partially overlapping atrophy factors: right-dorsal, right-ventral, left-ventral, and limbic. We found that object perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space perception was associated with atrophy that predominantly represents the right-dorsal and right-ventral factors. However, individual participant profiles revealed that the large majority expressed multiple atrophy factors and had mixed clinical profiles with impairments across multiple domains, rather than displaying a discrete clinical-radiologic phenotype.

CONCLUSION

Our results indicate that specific brain behavior networks are vulnerable in PCA, but most individuals display a constellation of affected brain regions and symptoms, indicating that classification into 4 mutually exclusive variants is unlikely to be clinically useful.

Global Brain Involvement in Posterior Cortical Atrophy: Multimodal MR Imaging Investigation

Posterior cortical atrophy (PCA), considered a visual variant of Alzheimer's disease, has similar pathological characteristics yet shows a selective visual manifestation with relative preservation of other cortical areas, at least at early stages of disease. Using a gamut of imaging methods, we aim to evaluate the global aspect of this relatively local disease and describe the interplay of the involvement of the different brain components. Ten PCA patients and 14 age-matched controls underwent MRI scans. Cortical thickness was examined to identify areas of cortical thinning. Hippocampal volume was assessed using voxel-based morphometry. The integrity of 20 fiber tracts was assessed by Diffusion Tensor Imaging. Regions of difference in global functional connectivity were identified by resting-state fMRI, using multi-variant pattern analysis. Correlations were examined to evaluate the connection between grey matter atrophy, the network changes and the disease load. The patients presented bilateral cortical thinning, primarily in their brains' posterior segments. Impaired segments of white matter integrity were evident only within three fiber tracts in the left hemisphere. Four areas were identified as different in their global connectivity pattern. The visual network-related areas showed reduced connectivity and was correlated to atrophy. Right Broadman area 39 showed in addition increased connectivity to the frontal areas. Global structural and functional imaging pointed to the highly localized nature of PCA. Functional connectivity followed grey matter atrophy in visual regions. White matter involvement seemed less prominent, however damage is directly related to presence of disease and not mediated only by grey matter damage.

Abnormal dynamic functional connectivity in Alzheimer's disease

Aims

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Previous studies have demonstrated abnormalities in functional connectivity (FC) of AD under the assumption that FC is stationary during scanning. However, studies on the FC dynamics of AD, which may provide more insightful perspectives in understanding the neural mechanisms of AD, remain largely unknown.

Methods

Combining the sliding‐window approach and the k‐means algorithm, we identified three reoccurring dynamic FC states from resting‐state fMRI data of 26 AD and 26 healthy controls. The between‐group differences both in FC states and in regional temporal variability were calculated, followed by a correlation analysis of these differences with cognitive performances of AD patients.

Results

We identified three reoccurring FC states and found abnormal FC mainly in the frontal and temporal cortices. The temporal properties of FC states were changed in AD as characterized by decreased dwell time in State I and increased dwell time in State II. Besides, we found decreased regional temporal variability mainly in the somatomotor, temporal and parietal regions. Disrupted dynamic FC was significantly correlated with cognitive performances of AD patients.

Conclusion

Our findings suggest abnormal dynamic FC in AD patients, which provides novel insights for understanding the pathophysiological mechanisms of AD.

Detecting Abnormal Brain Regions in Schizophrenia Using Structural MRI via Machine Learning

Utilizing neuroimaging and machine learning (ML) to differentiate schizophrenia (SZ) patients from normal controls (NCs) and for detecting abnormal brain regions in schizophrenia has several benefits and can provide a reference for the clinical diagnosis of schizophrenia. In this study, structural magnetic resonance images (sMRIs) from SZ patients and NCs were used for discriminative analysis. This study proposed an ML framework based on coarse-to-fine feature selection. The proposed framework used two-sample t-tests to extract the differences between groups first, then further eliminated the nonrelevant and redundant features with recursive feature elimination (RFE), and finally utilized the support vector machine (SVM) to learn the decision models with selected gray matter (GM) and white matter (WM) features. Previous studies have tended to report differences at the group level instead of at the individual level and cannot be widely applied. The method proposed in this study extends the diagnosis to the individual level and has a higher recognition rate than previous methods. The experimental results of this study demonstrate that the proposed framework distinguishes SZ patients from NCs, with the highest classification accuracy reaching over 85%. The identified biomarkers are also consistent with previous literature findings. As a universal method, the proposed framework can be extended to diagnose other diseases.

The Long-Term Effects of Acupuncture on Hippocampal Functional Connectivity in aMCI with Hippocampal Atrophy: A Randomized Longitudinal fMRI Study

Background. Acupuncture has been used to treat amnestic mild cognitive impairment (aMCI) for many years in China. However, the long-term effects of continuous acupuncture treatment remained unclear. Objective. We aimed to explore the long-term effects of continuous acupuncture treatment on hippocampal functional connectivity (FC) in aMCI. Methods. Fifty healthy control (HC) participants and 28 aMCI patients were recruited for resting-state functional magnetic resonance imaging (fMRI) at baseline. The 28 aMCI patients were then divided into the aMCI acupuncture group, which received acupuncture treatment for 6 months, and the aMCI control group, which received no intervention. All aMCI patients completed the second resting-state fMRI scanning after 6 months of acupuncture treatment. Analysis based on the region of interest and two-way analysis of covariance were both used to explore the long-term effects of acupuncture on cognition change and hippocampal FC in aMCI. Results. Compared to HC, aMCI showed decreased right hippocampal FC with the right inferior/middle temporal gyrus (ITG/MTG), left amygdala, and the right fusiform and increased FC with bilateral caudates at baseline. After acupuncture treatment, the right hippocampal FC with right ITG/MTG enhanced significantly in the aMCI acupuncture group, but continued to decrease in the aMCI control group. Whole brain FC analysis showed enhanced right hippocampal FC with the right ITG and the left MTG in the aMCI acupuncture group relative to the aMCI control group. Furthermore, FC strength of the right hippocampus with right ITG at baseline was negatively correlated with the changes in memory scores of aMCI acupuncture patients. Conclusion. Acupuncture treatment could alleviate the progression of cognitive decline and could enhance hippocampal FC with ITG and MTG in aMCI that may be associated with resilience to resistant against neurodegeneration. The findings provided a better understanding of the long-term effects of acupuncture treatment and confirmed the therapeutic role of acupuncture in aMCI.

Functional brain connectome in posterior cortical atrophy

This study investigated the functional brain connectome architecture in patients with Posterior Cortical Atrophy (PCA). Eighteen PCA patients and 29 age- and sex- matched healthy controls were consecutively recruited in a specialized referral center. Participants underwent neurologic examination, cerebrospinal fluid (CSF) examination for Alzheimer's disease (AD) biomarkers, cognitive assessment, and brain MRI. For a smaller subset of participants, FDG-PET examination was available. We assessed topological brain network properties and regional functional connectivity as well as intra- and inter-hemispheric connectivity, using graph analysis and connectomics. Supplementary analyses were performed to explore the association between the CSF AD profile and the connectome status, and taking into account hypometabolic, atrophic, and spared regions (nodes). PCA patients showed diffuse functional connectome alterations at both global and regional level, as well as a connectivity breakdown between the posterior brain nodes. They had a widespread loss of both intra- and inter-hemispheric connections, exceeding the structural damage, and including the frontal connections. In PCA, connectome alterations were identified in all the brain nodes irrespectively of their structural and metabolic classification and were associated with a connectivity breakdown between damaged and spared areas. Taken together, these findings suggest the potentially high sensitivity of graph-analysis and connectomic in capturing the progression and maybe early signs of neurodegeneration in PCA patients.