The cerebellum in Alzheimer's disease: evaluating its role in cognitive decline

A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes

Environmental cues influence the highly dynamic morphology of microglia. Strategies to characterize these changes usually involve user-selected morphometric features, which preclude the identification of a spectrum of context-dependent morphological phenotypes. Here we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes and overcomes feature-selection biases and biological variability. We extract spatially heterogeneous and sexually dimorphic morphological phenotypes for seven adult mouse brain regions. This sex-specific phenotype declines with maturation but increases over the disease trajectories in two neurodegeneration mouse models, with females showing a faster morphological shift in affected brain regions. Remarkably, microglia morphologies reflect an adaptation upon repeated exposure to ketamine anesthesia and do not recover to control morphologies. Finally, we demonstrate that both long primary processes and short terminal processes provide distinct insights to morphological phenotypes. MorphOMICs opens a new perspective to characterize microglial morphology.

The functional connectivity and neuropsychology underlying mental planning operations: data from the digital clock drawing test

We examined the construct of mental planning by quantifying digital clock drawing digit placement accuracy in command and copy conditions, and by investigating its underlying neuropsychological correlates and functional connectivity. We hypothesized greater digit misplacement would associate with attention, abstract reasoning, and visuospatial function, as well as functional connectivity from a major source of acetylcholine throughout the brain: the basal nucleus of Meynert (BNM). Participants (n = 201) included non-demented older adults who completed all metrics within 24 h of one another. A participant subset met research criteria for mild cognitive impairment (MCI; n = 28) and was compared to non-MCI participants on digit misplacement accuracy and expected functional connectivity differences. Digit misplacement and a comparison dissociate variable of total completion time were acquired for command and copy conditions. a priori fMRI seeds were the bilateral BNM. Command digit misplacement is negatively associated with semantics, visuospatial, visuoconstructional, and reasoning (p's < 0.01) and negatively associated with connectivity from the BNM to the anterior cingulate cortex (ACC; p = 0.001). Individuals with MCI had more misplacement and less BNM-ACC connectivity (p = 0.007). Total completion time involved posterior and cerebellar associations only. Findings suggest clock drawing digit placement accuracy may be a unique metric of mental planning and provide insight into neurodegenerative disease.

Gray matter volume of cerebellum associated with idiopathic normal pressure hydrocephalus: A cross-sectional analysis

The cause of idiopathic normal pressure hydrocephalus's (iNPH) clinical symptoms remains unclear. The cerebral cortex is the center of the brain and provides a structural basis for complex perception and motor function. This study aimed to explore the relationship between changes in cerebral cortex volume and clinical symptoms in patients with iNPH. This study included 21 iNPH patients and 20 normal aging (NA) controls. Voxel-based morphometry statistical results showed that, compared with NA, the gray matter volumes of patients with iNPH in the bilateral temporal lobe, bilateral hippocampus, bilateral thalamus, bilateral insula, left amygdala, right lenticular nucleus, right putamen, and cerebellum decreased, while the volumes of gray matter in the bilateral paracentral lobules, precuneus, bilateral supplementary motor area, medial side of the left cerebral hemisphere, and median cingulate and paracingulate gyri increased. Correlation analysis among the volumes of white matter and gray matter in the cerebrum and cerebellum and the iNPH grading scale (iNPHGS) revealed that the volume of white matter was negatively correlated with the iNPHGS (P < 0.05), while the gray matter volumes of cerebellar area 6 and area 8 were negatively correlated with the clinical symptoms of iNPH (P < 0.05). The volume of gray matter in the cerebellar vermis was negatively correlated with gait, and the gray matter volume of cerebellar area 6 was negatively correlated with cognition. Our findings suggest that the cerebellum also plays an important role in the pathogenesis of iNPH, potentially highlighting new research avenues for iNPH.

A multi-expert ensemble system for predicting Alzheimer transition using clinical features

Alzheimer’s disease (AD) diagnosis often requires invasive examinations (e.g., liquor analyses), expensive tools (e.g., brain imaging) and highly specialized personnel. The diagnosis commonly is established when the disorder has already caused severe brain damage, and the clinical signs begin to be apparent. Instead, accessible and low-cost approaches for early identification of subjects at high risk for developing AD years before they show overt symptoms are fundamental to provide a critical time window for more effective clinical management, treatment, and care planning. This article proposes an ensemble-based machine learning algorithm for predicting AD development within 9 years from first overt signs and using just five clinical features that are easily detectable with neuropsychological tests. The validation of the system involved both healthy individuals and mild cognitive impairment (MCI) patients drawn from the ADNI open dataset, at variance with previous studies that considered only MCI. The system shows higher levels of balanced accuracy, negative predictive value, and specificity than other similar solutions. These results represent a further important step to build a preventive fast-screening machine-learning-based tool to be used as a part of routine healthcare screenings.

Age-volume associations in cerebellar lobules by sex and reproductive stage

The cerebellum has established associations with motor function and a well-recognized role in cognition. In advanced age, cognitive and motor impairments contribute to reduced quality of life and are more common. Regional cerebellar volume is associated with performance across these domains and sex hormones may influence this volume. Examining sex differences in regional cerebellar volume in conjunction with age, and in the context of reproductive stage stands to improve our understanding of cerebellar aging and pathology. Data from 508 healthy adults (ages 18-88; 47% female) from the Cambridge Centre for Ageing and Neuroscience database were used here. CERES was used to assess lobular volume in T1-weighted images. We examined sex differences in adjusted regional cerebellar volume while controlling for age. A subgroup of participants (n = 370, 50% female) was used to assess group differences in female reproductive stages as compared to age-matched males. Sex differences in adjusted volume were seen across most anterior and posterior cerebellar lobules. Most of these lobules had significant linear relationships with age in males and females. While there were no interactions between sex and reproductive stage groups, exploratory analyses in females alone revealed multiple regional differences by reproductive stage. We found sex differences in volume across much of the cerebellum, linear associations with age, and did not find an interaction for sex and reproductive stage on regional cerebellar volume. Longitudinal investigation into hormonal influences on cerebellar structure and function is warranted as hormonal changes with menopause may impact cerebellar volume over time.

Comprehensive analysis reveals a 5-gene signature and immune cell infiltration in Alzheimer’s disease with qPCR validation

Over 50 million people around the world currently are suffering from Alzheimer’s disease (AD) without any effective therapy. Neuroinflammation plays a pivotal role in AD, which leads us to probe the profile of immune cell infiltration in AD. Here, we analyzed a microarray dataset (GSE44770) containing 115 AD and 115 control samples to determine biomarkers and immune infiltration characteristics of AD by multiple bioinformatics methods. First, we identified 3,840 DEGs (1892 upregulated and 1948 downregulated) by using the limma package and 2,697 hub genes by constructing a weighted gene correlation network, and they had a total of 2,167 intersecting genes. Second, combining the LASSO logistic regression and SVM-RFE, we obtained five biomarkers (DGKG, MAP3K7IP2, NFKBIE, VIP, and PCCB), which may reveal the key pathogenetic features of AD and serve as diagnostic markers assessed by the ROC curve (AUC = 0.9716) and validation of another AD dataset (GSE33000) (AUC = 0.9388). Third, immune cell infiltration analysis revealed that compared with control samples, plasma cells, CD8 T cells, T follicular helper cells, and activated NK cells infiltrated less in AD; Monocytes, M2 macrophages, and neutrophils infiltrated more in AD. Neutrophils and activated NK cells demonstrated the most significant and negative correlation. Then, Spearman correlation analysis between the five biomarkers and immune infiltrating cells revealed that all of them were significantly associated with plasma cells. Finally, mRNA levels of VIP and PCCB were conformed in a murine AD model. In conclusion, DGKG, MAP3K7IP2, NFKBIE, VIP, and PCCB may be used as diagnostic markers of AD, and the disruption of the delicate immune balance may be a key process in the onset and development of AD.

Subject-specific features of excitation/inhibition profiles in neurodegenerative diseases

Brain pathologies are characterized by microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients' excitation/inhibition profiles on neurodegenerative diseases including Alzheimer's Disease, Frontotemporal Dementia, and Amyotrophic Lateral Sclerosis. In this work, we used The Virtual Brain (TVB) simulation platform to simulate brain dynamics in healthy and neurodegenerative conditions and to extract information about the excitatory/inhibitory balance in single subjects. The brain structural and functional connectomes were extracted from 3T-MRI (Magnetic Resonance Imaging) scans and TVB nodes were represented by a Wong-Wang neural mass model endowing an explicit representation of the excitatory/inhibitory balance. Simulations were performed including both cerebral and cerebellar nodes and their structural connections to explore cerebellar impact on brain dynamics generation. The potential for clinical translation of TVB derived biophysical parameters was assessed by exploring their association with patients' cognitive performance and testing their discriminative power between clinical conditions. Our results showed that TVB biophysical parameters differed between clinical phenotypes, predicting higher global coupling and inhibition in Alzheimer's Disease and stronger N-methyl-D-aspartate (NMDA) receptor-dependent excitation in Amyotrophic Lateral Sclerosis. These physio-pathological parameters allowed us to perform an advanced analysis of patients' conditions. In backward regressions, TVB-derived parameters significantly contributed to explain the variation of neuropsychological scores and, in discriminant analysis, the combination of TVB parameters and neuropsychological scores significantly improved the discriminative power between clinical conditions. Moreover, cluster analysis provided a unique description of the excitatory/inhibitory balance in individual patients. Importantly, the integration of cerebro-cerebellar loops in simulations improved TVB predictive power, i.e., the correlation between experimental and simulated functional connectivity in all pathological conditions supporting the cerebellar role in brain function disrupted by neurodegeneration. Overall, TVB simulations reveal differences in the excitatory/inhibitory balance of individual patients that, combined with cognitive assessment, can promote the personalized diagnosis and therapy of neurodegenerative diseases.

Cerebellum and Emotion in Social Behavior

Accumulating evidence suggests that the cerebellum plays a crucial role not only in the motor and cognitive domains but also in emotions and social behavior. In the present chapter, after a general introduction on the significance of the emotional components of social behavior, we describe recent efforts to understand the contributions of the cerebellum in social cognition focusing on the emotional and affective aspects. Specifically, starting from the description of the cerebello-cortical networks subtending the social-affective domains, we illustrate the most recent findings on the social cerebellum and the possible functional mechanisms by which the cerebellum modulate social-affective behavior. Finally, we discuss the possible consequences of cerebellar dysfunction in the social-affective domain, focusing on those neurological and psychopathological conditions in which emotional and social behavior difficulties have been described as being associated with cerebellar structural or functional alterations.

Multiple Cognitive and Behavioral Factors Link Association Between Brain Structure and Functional Impairment of Daily Instrumental Activities in Older Adults

OBJECTIVE

Functional impairment in daily activity is a cornerstone in distinguishing the clinical progression of dementia. Multiple indicators based on neuroimaging and neuropsychological instruments are used to assess the levels of impairment and disease severity; however, it remains unclear how multivariate patterns of predictors uniquely predict the functional ability and how the relative importance of various predictors differs.

METHOD

In this study, 881 older adults with subjective cognitive complaints, mild cognitive impairment (MCI), and dementia with Alzheimer's type completed brain structural magnetic resonance imaging (MRI), neuropsychological assessment, and a survey of instrumental activities of daily living (IADL). We utilized the partial least square (PLS) method to identify latent components that are predictive of IADL.

RESULTS

The result showed distinct brain components (gray matter density of cerebellar, medial temporal, subcortical, limbic, and default network regions) and cognitive-behavioral components (general cognitive abilities, processing speed, and executive function, episodic memory, and neuropsychiatric symptoms) were predictive of IADL. Subsequent path analysis showed that the effect of brain structural components on IADL was largely mediated by cognitive and behavioral components. When comparing hierarchical regression models, the brain structural measures minimally added the explanatory power of cognitive and behavioral measures on IADL.

CONCLUSION

Our finding suggests that cerebellar structure and orbitofrontal cortex, alongside with medial temporal lobe, play an important role in the maintenance of functional status in older adults with or without dementia. Moreover, the significance of brain structural volume affects real-life functional activities via disruptions in multiple cognitive and behavioral functions.

Brain integrity is altered by hepatic APOE ε4 in humanized-liver mice

Liver-generated plasma apolipoprotein E (apoE) does not enter the brain but nonetheless correlates with Alzheimer's disease (AD) risk and AD biomarker levels. Carriers of APOEε4, the strongest genetic AD risk factor, exhibit lower plasma apoE and altered brain integrity already at mid-life versus non-APOEε4 carriers. Whether altered plasma liver-derived apoE or specifically an APOEε4 liver phenotype promotes neurodegeneration is unknown. Here we investigated the brains of Fah-/-, Rag2-/-, Il2rg-/- mice on the Non-Obese Diabetic (NOD) background (FRGN) with humanized-livers of an AD risk-associated APOE ε4/ε4 versus an APOE ε2/ε3 genotype. Reduced endogenous mouse apoE levels in the brains of APOE ε4/ε4 liver mice were accompanied by various changes in markers of synaptic integrity, neuroinflammation and insulin signaling. Plasma apoE4 levels were associated with unfavorable changes in several of the assessed markers. These results propose a previously unexplored role of the liver in the APOEε4-associated risk of neurodegenerative disease.

Aging the brain: multi-region methylation principal component based clock in the context of Alzheimer's disease

Alzheimer's disease (AD) risk increases exponentially with age and is associated with multiple molecular hallmarks of aging, one of which is epigenetic alterations. Epigenetic age predictors based on 5' cytosine methylation (DNAm), or epigenetic clocks, have previously suggested that epigenetic age acceleration may occur in AD brain tissue. Epigenetic clocks are promising tools for the quantification of biological aging, yet we hypothesize that investigation of brain aging in AD will be assisted by the development of brain-specific epigenetic clocks. Therefore, we generated a novel age predictor termed PCBrainAge that was trained solely in cortical samples. This predictor utilizes a combination of principal components analysis and regularized regression, which reduces technical noise and greatly improves test-retest reliability. To characterize the scope of PCBrainAge's utility, we generated DNAm data from multiple brain regions in a sample from the Religious Orders Study and Rush Memory and Aging Project. PCBrainAge captures meaningful heterogeneity of aging: Its acceleration demonstrates stronger associations with clinical AD dementia, pathologic AD, and APOE ε4 carrier status compared to extant epigenetic age predictors. It further does so across multiple cortical and subcortical regions. Overall, PCBrainAge's increased reliability and specificity makes it a particularly promising tool for investigating heterogeneity in brain aging, as well as epigenetic alterations underlying AD risk and resilience.

The fractional amplitude of low-frequency fluctuations signals related to amyloid uptake in high-risk populations—A pilot fMRI study

Background

Patients with type 2 diabetes mellitus (T2DM) and subjective cognitive decline (SCD) have a higher risk to develop Alzheimer's Disease (AD). Resting-state-functional magnetic resonance imaging (rs-fMRI) was used to document neurological involvement in the two groups from the aspect of brain dysfunction. Accumulation of amyloid-β (Aβ) starts decades ago before the onset of clinical symptoms and may already have been associated with brain function in high-risk populations. However, this study aims to compare the patterns of fractional amplitude of low-frequency fluctuations (fALFF) maps between cognitively normal high-risk groups (SCD and T2DM) and healthy elderly and evaluate the association between regional amyloid deposition and local fALFF signals in certain cortical regions.

Materials and methods

A total of 18 T2DM, 11 SCD, and 18 healthy elderlies were included in this study. The differences in the fALFF maps were compared between HC and high-risk groups. Regional amyloid deposition and local fALFF signals were obtained and further correlated in two high-risk groups.

Results

Compared to HC, the altered fALFF signals of regions were shown in SCD such as the left posterior cerebellum, left putamen, and cingulate gyrus. The T2DM group illustrated altered neural activity in the superior temporal gyrus, supplementary motor area, and precentral gyrus. The correlation between fALFF signals and amyloid deposition was negative in the left anterior cingulate cortex for both groups. In the T2DM group, a positive correlation was shown in the right occipital lobe and left mesial temporal lobe.

Conclusion

The altered fALFF signals were demonstrated in high-risk groups compared to HC. Very early amyloid deposition in SCD and T2DM groups was observed to affect the neural activity mainly involved in the default mode network (DMN).

Hippocampus-based static functional connectivity mapping within white matter in mild cognitive impairment

Mild cognitive impairment (MCI) is clinically characterized by memory loss and cognitive impairment closely associated with the hippocampal atrophy. Accumulating studies have confirmed the presence of neural signal changes within white matter (WM) in resting-state functional magnetic resonance imaging (fMRI). However, it remains unclear how abnormal hippocampus activity affects the WM regions in MCI. The current study employs 43 MCI, 71 very MCI (VMCI) and 87 age-, gender-, and education-matched healthy controls (HCs) from the public OASIS-3 dataset. Using the left and right hippocampus as seed points, we obtained the whole-brain functional connectivity (FC) maps for each subject. We then perform one-way ANOVA analysis to investigate the abnormal FC regions among HCs, VMCI, and MCI. We further performed probabilistic tracking to estimate whether the abnormal FC correspond to structural connectivity disruptions. Compared to HCs, MCI and VMCI groups exhibited reduced FC in the right middle temporal gyrus within gray matter, and right temporal pole, right inferior frontal gyrus within white matter. Specific dysconnectivity is shown in the cerebellum Crus II, left inferior temporal gyrus within gray matter, and right frontal gyrus within white matter. In addition, the fiber bundles connecting the left hippocampus and right temporal pole within white matter show abnormally increased mean diffusivity in MCI. The current study proposes a new functional imaging direction for exploring the mechanism of memory decline and pathophysiological mechanisms in different stages of Alzheimer's disease.

Cognitive decline is associated with frequency-specific resting state functional changes in normal aging

Resting state low-frequency brain activity may aid in our understanding of the mechanisms of aging-related cognitive decline. Our purpose was to explore the characteristics of the amplitude of low-frequency fluctuations (ALFF) in different frequency bands of fMRI to better understand cognitive aging. Thirty-seven cognitively normal older individuals underwent a battery of neuropsychological tests and MRI scans at baseline and four years later. ALFF from five different frequency bands (typical band, slow-5, slow-4, slow-3, and slow-2) were calculated and analyzed. A two-way ANOVA was used to explore the interaction effects in voxel-wise whole brain ALFF of the time and frequency bands. Paired-sample t-test was used to explore within-group changes over four years. Partial correlation analysis was performed to assess associations between the altered ALFF and cognitive function. Significant interaction effects of time × frequency were distributed over inferior frontal gyrus, superior frontal gyrus, right rolandic operculum, left thalamus, and right putamen. Significant ALFF reductions in all five frequency bands were mainly found in the right hemisphere and the posterior cerebellum; whereas localization of the significantly increased ALFF were mainly found in the cerebellum at typical band, slow-5 and slow-4 bands, and left hemisphere and the cerebellum at slow-3, slow-2 bands. In addition, ALFF changes showed frequency-specific correlations with changes in cognition. These results suggest that changes of local brain activity in cognitively normal aging should be investigated in multiple frequency bands. The association between ALFF changes and cognitive function can potentially aid better understanding of the mechanisms underlying normal cognitive aging.

Genome-wide association study of cerebellar volume provides insights into heritable mechanisms underlying brain development and mental health

Cerebellar volume is highly heritable and associated with neurodevelopmental and neurodegenerative disorders. Understanding the genetic architecture of cerebellar volume may improve our insight into these disorders. This study aims to investigate the convergence of cerebellar volume genetic associations in close detail. A genome-wide associations study for cerebellar volume was performed in a discovery sample of 27,486 individuals from UK Biobank, resulting in 30 genome-wide significant loci and a SNP heritability of 39.82%. We pinpoint the likely causal variants and those that have effects on amino acid sequence or cerebellar gene-expression. Additionally, 85 genome-wide significant genes were detected and tested for convergence onto biological pathways, cerebellar cell types, human evolutionary genes or developmental stages. Local genetic correlations between cerebellar volume and neurodevelopmental and neurodegenerative disorders reveal shared loci with Parkinson's disease, Alzheimer's disease and schizophrenia. These results provide insights into the heritable mechanisms that contribute to developing a brain structure important for cognitive functioning and mental health.

Identification and validation of Alzheimer's disease-related metabolic brain pattern in biomarker confirmed Alzheimer's dementia patients

Metabolic brain biomarkers have been incorporated in various diagnostic guidelines of neurodegenerative diseases, recently. To improve their diagnostic accuracy a biologically and clinically homogeneous sample is needed for their identification. Alzheimer's disease-related pattern (ADRP) has been identified previously in cohorts of clinically diagnosed patients with dementia due to Alzheimer's disease (AD), meaning that its diagnostic accuracy might have been reduced due to common clinical misdiagnosis. In our study, we aimed to identify ADRP in a cohort of AD patients with CSF confirmed diagnosis, validate it in large out-of-sample cohorts and explore its relationship with patients' clinical status. For identification we analyzed 2-[18F]FDG PET brain scans of 20 AD patients and 20 normal controls (NCs). For validation, 2-[18F]FDG PET scans from 261 individuals with AD, behavioral variant of frontotemporal dementia, mild cognitive impairment and NC were analyzed. We identified an ADRP that is characterized by relatively reduced metabolic activity in temporoparietal cortices, posterior cingulate and precuneus which co-varied with relatively increased metabolic activity in the cerebellum. ADRP expression significantly differentiated AD from NC (AUC = 0.95) and other dementia types (AUC = 0.76-0.85) and its expression correlated with clinical measures of global cognition and neuropsychological indices in all cohorts.

The Role of Brain-Derived Neurotrophic Factor Signaling in Central Nervous System Disease Pathogenesis

Recent studies have found abnormal levels of brain-derived neurotrophic factor (BDNF) in a variety of central nervous system (CNS) diseases (e.g., stroke, depression, anxiety, Alzheimer's disease, and Parkinson's disease). This suggests that BDNF may be involved in the pathogenesis of these diseases. Moreover, regulating BDNF signaling may represent a potential treatment for such diseases. With reference to recent research papers in related fields, this article reviews the production and regulation of BDNF in CNS and the role of BDNF signaling disorders in these diseases. A brief introduction of the clinical application status of BDNF is also provided.

Neural Mechanisms of Motor Dysfunction in Mild Cognitive Impairment and Alzheimer’s Disease: A Systematic Review

Background:

Despite the prevalence of motor symptoms in mild cognitive impairment (MCI) and Alzheimer’s disease (AD), their underlying neural mechanisms have not been thoroughly studied.

Objective:

This review summarizes the neural underpinnings of motor deficits in MCI and AD.

Methods:

We searched PubMed up until August of 2021 and identified 37 articles on neuroimaging of motor function in MCI and AD. Study bias was evaluated based on sample size, availability of control samples, and definition of the study population in terms of diagnosis.

Results:

The majority of studies investigated gait, showing that slower gait was associated with smaller hippocampal volume and prefrontal deactivation. Less prefrontal activation was also observed during cognitive-motor dual tasking, while more activation in cerebellar, cingulate, cuneal, somatosensory, and fusiform brain regions was observed when performing a hand squeezing task. Excessive subcortical white matter lesions in AD were associated with more signs of parkinsonism, poorer performance during a cognitive and motor dual task, and poorer functional mobility. Gait and cognitive dual-tasking was furthermore associated with cortical thickness of temporal lobe regions. Most non-gait motor measures were only reported in one study in relation to neural measures.

Conclusion:

Cross-sectional designs, lack of control groups, mixing amnestic- and non-amnestic MCI, disregard of sex differences, and small sample sizes limited the interpretation of several studies, which needs to be addressed in future research to progress the field.

Automated brain volumetric program measuring regional brain atrophy in diagnosis of mild cognitive impairment and Alzheimer's disease dementia

A quantitative analysis of brain volume can assist in the diagnosis of Alzheimer's disease (AD) which is ususally accompanied by brain atrophy. With an automated analysis program Quick Brain Volumetry (QBraVo) developed for volumetric measurements, we measured regional volumes and ratios to evaluate their performance in discriminating AD dementia (ADD) and mild cognitive impairment (MCI) patients from normal controls (NC). Validation of QBraVo was based on intra-rater and inter-rater reliability with a manual measurement. The regional volumes and ratios to total intracranial volume (TIV) and to total brain volume (TBV) or total cerebrospinal fluid volume (TCV) were compared among subjects. The regional volume to total cerebellar volume ratio named Standardized Atrophy Volume Ratio (SAVR) was calculated to compare brain atrophy. Diagnostic performances to distinguish among NC, MCI, and ADD were compared between MMSE, SAVR, and the predictive model. In total, 56 NCs, 44 MCI, and 45 ADD patients were enrolled. The average run time of QBraVo was 5 min 36 seconds. Intra-rater reliability was 0.999. Inter-rater reliability was high for TBV, TCV, and TIV (R = 0.97, 0.89 and 0.93, respectively). The medial temporal SAVR showed the highest performance for discriminating ADD from NC (AUC = 0.808, diagnostic accuracy = 80.2%). The predictive model using both MMSE and medial temporal SAVR improved the diagnostic performance for MCI in NC (AUC = 0.844, diagnostic accuracy = 79%). Our results demonstrated QBraVo is a fast and accurate method to measure brain volume. The regional volume calculated as SAVR could help to diagnose ADD and MCI and increase diagnostic accuracy for MCI.

Metabolic brain pattern in dementia with Lewy bodies: Relationship to Alzheimer's disease topography

PURPOSE

Dementia with Lewy bodies (DLB) is the second most common neurodegenerative dementia, that shares clinical and metabolic similarities with both Alzheimer's and Parkinson's disease. In this study we aimed to identify a DLB-related pattern (DLBRP), study its relationship with other metabolic brain patterns and explore its diagnostic and prognostic value.

METHODS

A cohort of 79 participants with DLB, 63 with dementia due to Alzheimer's disease (AD) and 41 normal controls (NCs) and their 2-[¹⁸F]FDG PET scans were analysed for identification and validation of DLBRP. Voxel-wise correlation and multiple linear regression were used to study the relation between DLBRP and Alzheimer's disease-related pattern (ADRP), Parkinson's disease-related pattern (PDRP) and PD-related cognitive pattern (PDCP). Diagnostic and prognostic value of DLBRP and of modified DLBRP after accounting for ADRP overlap (DLBRP ⊥ ADRP), were explored.

RESULTS

The newly identified DLBRP shared topographic similarities with ADRP (R² = 24%) and PDRP (R² = 37%), but not with PDCP. We could accurately discriminate between DLB and NC (AUC = 0.99) based on DLBRP expression, and between DLB and AD (AUC = 0.87) based on DLBRP ⊥ ADRP expression. DLBRP expression correlated with cognitive impairment, but the correlation was lost after accounting for ADRP overlap. DLBRP and DLBRP ⊥ ADRP correlated with patients' survival time.

CONCLUSION

DLBRP has proven to be a specific metabolic brain biomarker of DLB, sharing similarities with ADRP and PDRP, but not PDCP. We observed a similar metabolic mechanism underlying cognitive impairment in DLB and AD. DLB-specific metabolic changes were more detrimental for overall survival.

Multimodal data integration via mediation analysis with high-dimensional exposures and mediators

Motivated by an imaging proteomics study for Alzheimer's disease (AD), in this article, we propose a mediation analysis approach with high-dimensional exposures and high-dimensional mediators to integrate data collected from multiple platforms. The proposed method combines principal component analysis with penalized least squares estimation for a set of linear structural equation models. The former reduces the dimensionality and produces uncorrelated linear combinations of the exposure variables, whereas the latter achieves simultaneous path selection and effect estimation while allowing the mediators to be correlated. Applying the method to the AD data identifies numerous interesting protein peptides, brain regions, and protein-structure-memory paths, which are in accordance with and also supplement existing findings of AD research. Additional simulations further demonstrate the effective empirical performance of the method.

Don't forget the little brain: A framework for incorporating the cerebellum into the understanding of cognitive aging

With the rapidly growing population of older adults, an improved understanding of brain and cognitive aging is critical, given the impacts on health, independence, and quality of life. To this point, we have a well-developed literature on the cortical contributions to cognition in advanced age. However, while this work has been foundational for our understanding of brain and behavior in older adults, subcortical contributions, particularly those from the cerebellum, have not been integrated into these models and frameworks. Incorporating the cerebellum into models of cognitive aging is an important step for moving the field forward. There has also been recent interest in this structure in Alzheimer's dementia, indicating that such work may be beneficial to our understanding of neurodegenerative disease. Here, I provide an updated overview of the cerebellum in advanced age and propose that it serves as a critical source of scaffolding or reserve for cortical function. Age-related impacts on cerebellar function further impact cortical processing, perhaps resulting in many of the activation patterns commonly seen in aging.

The role of H3K9 acetylation and gene expression in different brain regions of Alzheimer's disease patients

Aims: To evaluate H3K9 acetylation and gene expression profiles in three brain regions of Alzheimer's disease (AD) patients and elderly controls, and to identify AD region-specific abnormalities. Methods: Brain samples of auditory cortex, hippocampus and cerebellum from AD patients and controls underwent chromatin immunoprecipitation sequencing, RNA sequencing and network analyses. Results: We found a hyperacetylation of AD cerebellum and a slight hypoacetylation of AD hippocampus. The transcriptome revealed differentially expressed genes in the hippocampus and auditory cortex. Network analysis revealed Rho GTPase-mediated mechanisms. Conclusions: These findings suggest that some crucial mechanisms, such as Rho GTPase activity and cytoskeletal organization, are differentially dysregulated in brain regions of AD patients at the epigenetic and transcriptomic levels, and might contribute toward future research on AD pathogenesis.

Association Between Mild Neurocognitive Disorder Due to Alzheimer's Disease and Possible Attention-deficit/Hyperactivity Disorder: A Case Report

Recent literature concerning attention-deficit/hyperactivity disorder (ADHD) underlines the persistence of this neurodevelopmental illness in older patients. Comorbidity with a neurodegenerative disease is thus possible. However, few studies have investigated this topic. To our knowledge, this is the first case report of such a possible association, which raises important questions about clinical presentation, symptoms, diagnosis, and treatment. A 72-year-old man, without any psychiatric history, presented with depression, subjective memory loss, and attention deficit and anxious symptoms, and was diagnosed with mild neurocognitive disorder due to Alzheimer's disease. However, the patient's attentional symptoms appeared to have been present since childhood. A formalized diagnostic interview assessing for ADHD did not allow for a clear diagnosis, possibly due to recall bias. The patient's anxiety symptoms also did not respond well to cognitive behavioral therapy coupled with different antidepressants. We hypothesized the presence of ADHD, with the symptoms balanced until now by the patient's high cognitive capacities, and we postulated that the onset of a neurogenerative process may have disrupted this balance. In this case report, we discuss symptom dimensionality, the interplay between neurodegenerative and neurodevelopmental diseases, and various treatment options. Attentional deficits and anxiety symptoms are frequent in mild neurocognitive disorders due to neurodegenerative illnesses. It is important to explore the time of onset of such symptoms since neurodegenerative processes can worsen neurodevelopmental conditions. Moreover, identification of a pre-existing neurodevelopmental condition can lead to alternative care and treatment options. In addition, the unexplained worsening of ADHD symptoms should prompt clinicians to assess for a neurodegenerative process.

Feature aggregation graph convolutional network based on imaging genetic data for diagnosis and pathogeny identification of Alzheimer's disease

The roles of brain regions activities and gene expressions in the development of Alzheimer's disease (AD) remain unclear. Existing imaging genetic studies usually has the problem of inefficiency and inadequate fusion of data. This study proposes a novel deep learning method to efficiently capture the development pattern of AD. First, we model the interaction between brain regions and genes as node-to-node feature aggregation in a brain region-gene network. Second, we propose a feature aggregation graph convolutional network (FAGCN) to transmit and update the node feature. Compared with the trivial graph convolutional procedure, we replace the input from the adjacency matrix with a weight matrix based on correlation analysis and consider common neighbor similarity to discover broader associations of nodes. Finally, we use a full-gradient saliency graph mechanism to score and extract the pathogenetic brain regions and risk genes. According to the results, FAGCN achieved the best performance among both traditional and cutting-edge methods and extracted AD-related brain regions and genes, providing theoretical and methodological support for the research of related diseases.

Cerebellum-Cortical Interaction in Spatial Navigation and Its Alteration in Dementias

The cerebellum has a homogeneous structure and performs different computational functions such as modulation/coordination of the communication between cerebral regions, and regulation/integration of sensory information. Albeit cerebellar activity is generally associated with motor functions, several recent studies link it to various cognitive functions, including spatial navigation. In addition, cerebellar activity plays a modulatory role in different cognitive domains and brain processes. Depending on the network involved, cerebellar damage results in specific functional alterations, even when no function loss might be detected. In the present review, we discuss evidence of brainstem degeneration and of a substantial reduction of neurons in nuclei connected to the inferior olivary nucleus in the early stages of Alzheimer’s disease. Based on the rich patterns of afferences from the inferior olive nucleus to the cerebellum, we argue that the subtle alterations in spatial navigation described in the early stages of dementia stem from alterations of the neuromodulatory functions of the cerebellum.

Exploring the dual character of metformin in Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disease, which results in dementia typically in the elderly. The disease is mainly characterized by the deposition of amyloid beta (Aβ) plaques and neurofibrillary tangles (NFTs) in the brain. However, only few drugs are available for AD because of its unknown pathological mechanism which limits the development of new drugs. Therefore, it is urgent to identify potential therapeutic strategies for AD. Moreover, research have showed that there is a significant association between Type 2 diabetes mellites (T2DM) and AD, suggesting that the two diseases may share common pathophysiological mechanisms. Such mechanisms include impaired insulin signaling, altered glucose metabolism, inflammation, oxidative stress, and premature aging, which strongly affect cognitive function and increased risk of dementia. Consequently, as a widely used drug for T2DM, metformin also has therapeutic potential for AD in vivo. It has been confirmed that metformin is beneficial on the brain of AD animal models. The mechanisms underlying the effects of metformin in Alzheimer's disease are complex and multifaceted. Metformin may work through mechanisms involving homeostasis of glucose metabolism, decrease of amyloid plaque deposition, normalization of tau protein phosphorylation and enhancement of autophagy. However, in clinical trials, metformin had little effects on patients with mild cognitive impairment or mild AD. Pathological effects and negative clinical results of metformin on AD make the current topic quite controversial. By reviewing the latest progress of related research, this paper summarizes the possible role of metformin in AD. The purpose of this study is not only to determine the potential treatment of AD, but also other related neurodegenerative diseases.

Gene Expression Analysis of the Endocannabinoid System in Presymptomatic APP/PS1 Mice

Alzheimer’s disease (AD) is the most common type of dementia and neurodegeneration. The actual cause of AD progression is still unknown and no curative treatment is available. Recently, findings in human samples and animal models pointed to the endocannabinoid system (ECS) as a promising therapeutic approach against AD. However, the specific mechanisms by which cannabinoid drugs induce potential beneficial effects are still undefined. For this reason, it is required a full characterization of the ECS at different time points of AD progression considering important factors such as sex or the analysis of different brain regions to improve future cannabinoid-dependent therapies in AD. Thus, the main aim of the present study is to expand our knowledge of the status of the ECS in a presymptomatic period (3 months of age) using the AD mouse model APP/PS1 mice. First, we evaluated different behavioral domains including anxiety, cognitive functions, and social interactions in male and female APP/PS1 mice at 4 months of age. Although a mild working memory impairment was observed in male APP/PS1 mice, in most of the behaviors assessed we found no differences between genotypes. At 3 months of age, we performed a characterization of the ECS in different brain regions of the APP/PS1 mice considering the sex variable. We assessed the expression of the ECS components by quantitative Real-Time Polymerase Chain Reaction in the hippocampus, prefrontal cortex, hypothalamus, olfactory bulb, and cerebellum. Interestingly, gene expression levels of the type-1 and type-2 cannabinoid receptors and the anabolic and catabolic enzymes, differed depending on the brain region and the sex analyzed. For example, CB1R expression levels decreased in both hippocampus and prefrontal cortex of male APP/PS1 mice but increased in female mice. In contrast, CB2R expression was decreased in females, whereas males tended to have higher levels. Overall, our data indicated that the ECS is already altered in APP/PS1 mice at the presymptomatic stage, suggesting that it could be an early event contributing to the pathophysiology of AD or being a potential predictive biomarker.

The Potential Crosstalk Between the Brain and Visceral Adipose Tissue in Alzheimer's Development

The bidirectional communication between the brain and peripheral organs have been widely documented, but the impact of visceral adipose tissue (VAT) dysfunction and its relation to structural and functional brain changes have yet to be fully elucidated. This review initially examines the clinical evidence supporting associations between the brain and VAT before visiting the roles of the autonomic nervous system, fat and glucose metabolism, neuroinflammation, and metabolites. Finally, the possible effects and potential mechanisms of the brain-VAT axis on the pathogenesis of Alzheimer's disease are discussed, providing new insights regarding future prevention and therapeutic strategies.

Subcortical and Cerebellar Neural Correlates of Prodromal Alzheimer’s Disease with Prolonged Sleep Latency

Background: Despite the important associations among sleep, Alzheimer’s disease (AD), subcortical structures, and the cerebellum, structural and functional magnetic resonance imaging (MRI) with regard to these regions and sleep on patients in AD trajectory are scarce. Objective: This study aimed to evaluate the influence of prolonged sleep latency on the structural and functional alterations in the subcortical and cerebellar neural correlates in amyloid-β positive amnestic mild cognitive impairment patients (Aβ+aMCI). Methods: A total of 60 patients with aMCI who were identified as amyloid positive ([18F] flutemetamol+) were recruited in the study, 24 patients with normal sleep latency (aMCI-n) and 36 patients prolonged sleep latency (aMCI-p). Cortical thickness and volumes between the two groups were compared. Volumetric analyses were implemented on the brainstem, thalamus, and hippocampus. Subcortical and cerebellar resting state functional connectivity (FC) differences were measured between the both groups through seed-to-voxel analysis. Additionally, group x Aβ interactive effects on FC values were tested with a general linear model. Result: There was a significantly decreased brainstem volume in aMCI-p subjects. We observed a significant reduction of the locus coeruleus (LC) FC with frontal, temporal, insular cortices, hippocampus, and left thalamic FC with occipital cortex. Moreover, the LC FC with occipital cortex and left hippocampal FC with frontal cortex were increased in aMCI-p subjects. In addition, there was a statistically significant group by regional standardized uptake value ratio interactions discovered in cerebro-cerebellar networks. Conclusion: The aforementioned findings suggest that prolonged sleep latency may be a detrimental factor in compromising structural and functional correlates of subcortical structures and the cerebellum, which may accelerate AD pathophysiology.

Cerebellar Coordination of Neuronal Communication in Cerebral Cortex

Cognitive processes involve precisely coordinated neuronal communications between multiple cerebral cortical structures in a task specific manner. Rich new evidence now implicates the cerebellum in cognitive functions. There is general agreement that cerebellar cognitive function involves interactions between the cerebellum and cerebral cortical association areas. Traditional views assume reciprocal interactions between one cerebellar and one cerebral cortical site, via closed-loop connections. We offer evidence supporting a new perspective that assigns the cerebellum the role of a coordinator of communication. We propose that the cerebellum participates in cognitive function by modulating the coherence of neuronal oscillations to optimize communications between multiple cortical structures in a task specific manner.

Tibolone Improves Memory and Decreases the Content of Amyloid-β Peptides and Tau Protein in the Hippocampus of a Murine Model of Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) affects women more than men and consequently has been associated with menopause. Tibolone (TIB) has been used as a hormone replacement therapy to alleviate climacteric symptoms. Neuroprotective effects of TIB have also been reported in some animal models.

OBJECTIVE

This study aimed to assess the effect of TIB on memory and Aβ peptides and tau protein content in the hippocampus and cerebellum of transgenic 3xTgAD ovariectomized mice.

METHODS

Three-month-old female mice were ovariectomized. Ten days after surgery, animals were divided into four groups: wild-type (WT)+vehicle; WT+TIB (1 mg/kg); 3xTgAD+vehicle; and 3xTgAD+TIB (1 mg/kg). TIB was administered for three months, and memory was evaluated using the object-in-context recognition task. Subsequently, animals were decapitated, and the hippocampus and cerebellum were dissected. Using commercial ELISA kits, these brain structures were homogenized in a PBS buffer for quantifying Aβ40 and Aβ42 and phosphorylated and total tau.ResultsA long-term memory deficit was observed in the 3xTgAD+vehicle group. In contrast, TIB treatment improved long-term memory in the 3xTgAD+TIB group than those treated with vehicle (p < 0.05). Furthermore, TIB treatment decreased Aβ and tau content in the hippocampus of 3xTgAD mice compared to vehicle-treated groups (p < 0.05). No significant changes were observed in the cerebellum.

CONCLUSION

Chronic treatment with TIB showed neuroprotective effects and delayed AD neuropathology in the 3xTgAD mice. Our results support hormone replacement therapy with TIB in menopausal women for neuroprotection.

Planning in amnestic mild cognitive impairment: an fMRI study

INTRODUCTION

The memory impairment that is characteristic of amnestic mild cognitive impairment (aMCI) is often accompanied by difficulties in executive functioning, including planning. Though planning deficits in aMCI are well documented, their neural correlates are largely unknown, and have not yet been investigated with functional magnetic resonance imaging (fMRI).

OBJECTIVES

The aim of this study was to: (1) identify differences in brain activity and connectivity during planning in people with aMCI and cognitively healthy older adults, and (2) find whether planning-related activity and connectivity are associated with cognitive performance and symptoms of apathy.

METHODS

Twenty-five people with aMCI and 15 cognitively healthy older adults performed a visuospatial planning task (Tower of London; ToL) during fMRI. Task-related brain activation, spatial maps of task-related independent components, and seed-to-voxel functional connectivity were compared between the two groups and regressed against measures of executive functions (Trail Making Test difference score, TMT B-A; Digit Symbol Substitution Test, DSST), delayed recall (Rey Auditory Verbal Learning Test), and apathy (Apathy Evaluation Scale).

RESULTS

People with aMCI scored lower on task-switching (TMT B-A), working memory (DSST), and planning (ToL). During planning, people with aMCI had less activation in the bilateral anterior calcarine sulcus/cuneus, the bilateral temporal cortices, the left precentral gyrus, the thalamus, and the right cerebellum. Across all participants, higher planning-related activity in the supplementary motor area, the retrosplenial cortex and surrounding areas, and the right temporal cortex was related to better delayed recall. There were no between-group differences in functional connectivity, nor were there any associations between connectivity and cognition. We also did not find any associations between brain activity or connectivity and apathy.

CONCLUSION

Impaired planning in people with aMCI appears to be accompanied by lower activation in a diffuse cortico-thalamic network. Across all participants, higher planning-related activity in parieto-occipital, temporal, and frontal areas was related to better memory performance. The results point to the relevance of planning deficits for understanding aMCI and extend its clinical and neurobiological signature.

Low-intensity treadmill exercise protects cognitive impairment by enhancing cerebellar mitochondrial calcium retention capacity in a rat model of chronic cerebral hypoperfusion

Chronic cerebral hypoperfusion (CCH) is caused by reduced blood flow to the brain representing gradually cognitive impairment. CCH induces mitochondrial dysfunction and neuronal cell death in the brain. Exercise is known to have a neuroprotective effect on brain damage and cognitive dysfunction. This study aimed to clarify the neuroprotective effect of low-intensity treadmill exercise (LITE) by enhancing cerebellar mitochondrial calcium retention capacity in an animal model of CCH. Wistar rats were divided into the sham group, the bilateral common carotid arteries occlusion (BCCAO) group, and the BCCAO and treadmill exercise (BCCAO+Ex) group. BCCAO+Ex group engaged the LITE on a treadmill for 30 min once a day for 8 weeks before the BCCAO surgery to investigate the protective effect of LITE on cognitive impairment. CCH induced by BCCAO resulted in mitochondrial dysfunction in the cerebellum, including impaired calcium homeostasis. CCH also decreased cerebellar Purkinje cells including of calbindin D28k and parvalbumin, resulting in cognitive impairment. The impairment of mitochondrial function, loss of cerebellar Purkinje cells, and cognitive dysfunction ameliorated by exercise. The present study showed that LITE hindered the deficit of spatial working memory and loss of Purkinje cell in the cerebellum induced by CCH. We confirmed that the protective effect of LITE on Purkinje cell by enhanced the mitochondrial calcium retention capacity. We suggest that LITE may protect against cognitive impairment, and further studies are needed to develop the intervention for patients who suffered from CCH.

Vector Auto-Regressive Deep Neural Network: A Data-Driven Deep Learning-Based Directed Functional Connectivity Estimation Toolbox

An important goal in neuroscience is to elucidate the causal relationships between the brain's different regions. This can help reveal the brain's functional circuitry and diagnose lesions. Currently there are a lack of approaches to functional connectome estimation that leverage the state-of-the-art in deep learning architectures and training methodologies. Therefore, we propose a new framework based on a vector auto-regressive deep neural network (VARDNN) architecture. Our approach consists of a set of nodes, each with a deep neural network structure. These nodes can be mapped to any spatial sub-division based on the data to be analyzed, such as anatomical brain regions from which representative neural signals can be obtained. VARDNN learns to reproduce experimental time series data using modern deep learning training techniques. Based on this, we developed two novel directed functional connectivity (dFC) measures, namely VARDNN-DI and VARDNN-GC. We evaluated our measures against a number of existing functional connectome estimation measures, such as partial correlation and multivariate Granger causality combined with large dimensionality counter-measure techniques. Our measures outperformed them across various types of ground truth data, especially as the number of nodes increased. We applied VARDNN to fMRI data to compare the dFC between 41 healthy control vs. 32 Alzheimer's disease subjects. Our VARDNN-DI measure detected lesioned regions consistent with previous studies and separated the two groups well in a subject-wise evaluation framework. Summarily, the VARDNN framework has powerful capabilities for whole brain dFC estimation. We have implemented VARDNN as an open-source toolbox that can be freely downloaded for researchers who wish to carry out functional connectome analysis on their own data.

Inflamma-MicroRNAs in Alzheimer's Disease: From Disease Pathogenesis to Therapeutic Potentials

Alzheimer’s disease (AD) is the most common cause of senile dementia. Although AD research has made important breakthroughs, the pathogenesis of this disease remains unclear, and specific AD diagnostic biomarkers and therapeutic strategies are still lacking. Recent studies have demonstrated that neuroinflammation is involved in AD pathogenesis and is closely related to other health effects. MicroRNAs (miRNAs) are a class of endogenous short sequence non-coding RNAs that indirectly inhibit translation or directly degrade messenger RNA (mRNA) by specifically binding to its 3′ untranslated region (UTR). Several broadly expressed miRNAs including miR-21, miR-146a, and miR-155, have now been shown to regulate microglia/astrocytes activation. Other miRNAs, including miR-126 and miR-132, show a progressive link to the neuroinflammatory signaling. Therefore, further studies on these inflamma-miRNAs may shed light on the pathological mechanisms of AD. The differential expression of inflamma-miRNAs (such as miR-29a, miR-125b, and miR-126-5p) in the peripheral circulation may respond to AD progression, similar to inflammation, and therefore may become potential diagnostic biomarkers for AD. Moreover, inflamma-miRNAs could also be promising therapeutic targets for AD treatment. This review provides insights into the role of inflamma-miRNAs in AD, as well as an overview of general inflamma-miRNA biology, their implications in pathophysiology, and their potential roles as biomarkers and therapeutic targets.

Evidence for a pervasive autobiographical memory impairment in Logopenic Progressive Aphasia

Although characterized primarily as a language disorder, mounting evidence indicates episodic amnesia in Logopenic Progressive Aphasia (LPA). Whether such memory disturbances extend to information encoded pre-disease onset remains unclear. To address this question, we examined autobiographical memory in 10 LPA patients, contrasted with 18 typical amnestic Alzheimer's disease and 16 healthy Control participants. A validated assessment, the Autobiographical Interview, was employed to explore autobiographical memory performance across the lifespan under free and probed recall conditions. Relative to Controls, LPA patients showed global impairments across all time periods for free recall, scoring at the same level as disease-matched cases of Alzheimer's disease. Importantly, these retrieval deficits persisted in LPA, even when structured probing was provided, and could not be explained by overall level of language disruption or amount of information generated during autobiographical narration. Autobiographical memory impairments in LPA related to gray matter intensity decrease in predominantly posterior parietal brain regions implicated in memory retrieval. Together, our results suggest that episodic memory disturbances may be an under-appreciated clinical feature of LPA.

Reported Hearing Loss in Alzheimer's Disease Is Associated With Loss of Brainstem and Cerebellar Volume

Multiple epidemiological studies have revealed an association between presbycusis and Alzheimer’s Disease (AD). Unfortunately, the neurobiological underpinnings of this relationship are not clear. It is possible that the two disorders share a common, as yet unidentified, risk factor, or that hearing loss may independently accelerate AD pathology. Here, we examined the relationship between reported hearing loss and brain volumes in normal, mild cognitive impairment (MCI) and AD subjects using a publicly available database. We found that among subjects with AD, individuals that reported hearing loss had smaller brainstem and cerebellar volumes in both hemispheres than individuals without hearing loss. In addition, we found that these brain volumes diminish in size more rapidly among normal subjects with reported hearing loss and that there was a significant interaction between cognitive diagnosis and the relationship between reported hearing loss and these brain volumes. These data suggest that hearing loss is linked to brainstem and cerebellar pathology, but only in the context of the pathological state of AD. We hypothesize that the presence of AD-related pathology in both the brainstem and cerebellum creates vulnerabilities in these brain regions to auditory deafferentation-related atrophy. These data have implications for our understanding of the potential neural substrates for interactions between hearing loss and AD.

Cerebellar Dentate Connectivity across Adulthood: A Large-Scale Resting State Functional Connectivity Investigation

Cerebellar contributions to behavior in advanced age are of interest and importance, given its role in motor and cognitive performance. There are differences and declines in cerebellar structure in advanced age and cerebellar resting state connectivity is lower. However, the work on this area to date has focused on the cerebellar cortex. The deep cerebellar nuclei provide the primary cerebellar inputs and outputs to the cortex, as well as the spinal and vestibular systems. Dentate networks can be dissociated such that the dorsal region is associated with the motor cortex, whereas the ventral aspect is associated with the prefrontal cortex. However, whether dentato-thalamo-cortical networks differ across adulthood remains unknown. Here, using a large adult sample (n = 590) from the Cambridge Center for Ageing and Neuroscience, we investigated dentate connectivity across adulthood. We replicated past work showing dissociable resting state networks in the dorsal and ventral aspects of the dentate. In both seeds, we demonstrated that connectivity is lower with advanced age, indicating that connectivity differences extend beyond the cerebellar cortex. Finally, we demonstrated sex differences in dentate connectivity. This expands our understanding of cerebellar circuitry in advanced age and underscores the potential importance of this structure in age-related performance differences.

Decoding perineuronal net glycan sulfation patterns in the Alzheimer's disease brain

The extracellular matrix (ECM) of the brain comprises unique glycan "sulfation codes" that influence neurological function. Perineuronal nets (PNNs) are chondroitin sulfate-glycosaminoglycan (CS-GAG) containing matrices that enmesh neural networks involved in memory and cognition, and loss of PNN matrices is reported in patients with neurocognitive and neuropsychiatric disorders including Alzheimer's disease (AD). Using liquid chromatography tandem mass spectrometry (LC-MS/MS), we show that patients with a clinical diagnosis of AD-related dementia undergo a re-coding of their PNN-associated CS-GAGs that correlates to Braak stage progression, hyperphosphorylated tau (p-tau) accumulation, and cognitive impairment. As these CS-GAG sulfation changes are detectable prior to the regional onset of classical AD pathology, they may contribute to the initiation and/or progression of the underlying degenerative processes and implicate the brain matrix sulfation code as a key player in the development of AD clinicopathology.

Novel insights into the relationship between cerebellum and dementia: A narrative review as a toolkit for clinicians

The role of the cerebellum in neurodegenerative disorders that target cognitive functions has been a subject of increasing interest over the past years. However, a review focused on making clinicians more aware of the role of the cerebellum in dementia is still missing. This narrative review explores the possible factors explaining the involvement of the cerebellum in different kinds of dementia by providing more insights on how this structure can be relevant in clinical practice. It emerged that, despite overlapping in specific areas, structural cerebellar alterations in dementia show a certain degree of disease-specificity. Furthermore, the relevance of cerebellar changes in dementia is corroborated by correlations observed between their topography and cognitive symptomatology, as well as by its previously ignored involvement of the cerebellum in early stages of dementia. Despite needing further investigations, these findings could become a useful diagnostic aid for clinicians that should not be overlooked, in particular for those individuals who do not show distinct and manifest brain or neuropsychological alterations, but that still make clinicians suspect the presence of a neurocognitive disease.

Cerebellar Cortex and Cerebellar White Matter Volume in Normal Cognition, Mild Cognitive Impairment, and Dementia

The cerebellum is commonly viewed as a structure that is primarily responsible for the coordination of voluntary movement, gait, posture, and speech. Recent research has shown evidence that the cerebellum is also responsible for cognition. We analyzed 28 participants divided into three groups (9 with normal cognition, 9 with mild cognitive impairment, and 10 with moderate/severe cognitive impairment) based on the Montreal Cognitive Assessment. We analyzed the cerebellar cortex and white matter volume and assessed differences between groups. Participants with normal cognition had higher average values in total cerebellar volume, cerebellar white matter volume, and cerebellar cortex volume in both hemispheres, but by performing the Kruskal–Wallis test, we did not find these values to be statistically significant.

White Matter Integrity Underlies the Physical-Cognitive Correlations in Subjective Cognitive Decline

Objective: Although previous studies postulated that physical and cognitive decline codeveloped in preclinical dementia, the interconnected relationship among subjective cognitive complaints (SCCs), objective cognitive performance, and physical activity remained hazy. We investigated the mediating roles of physical activity between subjective and objective cognition. Diffusion tensor imaging (DTI) was utilized to test our hypothesis that brain white matter microstructural changes underlie the physical-cognitive decline in subjective cognitive decline (SCD).

Methods: We enrolled cognitively normal older adults aged > 50 years in the Community Medicine Research Center of Keelung Chang Gung Memorial Hospital during 2017–2020. Regression models analyzed mediation effects of physical activity between subjective and objective cognition. The self-reported AD8 questionnaire assessed SCCs. The SCD group, defined by AD8 score ≥ 2, further underwent diffusion MRI scans. Those who agreed to record actigraphy also wore the SOMNOwatch™ for 72 h. Spearman's correlation coefficients evaluated the associations of diffusion indices with physical activity and cognitive performance.

Results: In 95 cognitively normal older adults, the AD8 score and the Montreal Cognitive Assessment (MoCA) score were mediated partially by the metabolic equivalent of the International Physical Activity Questionnaire-Short Form (IPAQ-SF MET) and fully by the sarcopenia score SARC-F. That is, the relation between SCCs and poorer cognitive performance was mediated by physical inactivity. The DTI analysis of 31 SCD participants found that the MoCA score correlated with mean diffusivity at bilateral inferior cerebellar peduncles and the pyramids segment of right corticospinal tract [p < 0.05, false discovery rate (FDR) corrected]. The IPAQ-SF MET was associated with fractional anisotropy (FA) at the right posterior corona radiata (PCR) (p < 0.05, FDR corrected). In 15 SCD participants who completed actigraphy recording, the patterns of physical activity in terms of intradaily variability and interdaily stability highly correlated with FA of bilateral PCR and left superior corona radiata (p < 0.05, FDR corrected).

Conclusions: This study addressed the role of physical activity in preclinical dementia. Physical inactivity mediated the relation between higher SCCs and poorer cognitive performance. The degeneration of specific white matter tracts underlay the co-development process of physical-cognitive decline in SCD.

Functional Territories of Human Dentate Nucleus

Anatomical connections link the cerebellar cortex with multiple sensory, motor, association, and paralimbic cerebral areas. The majority of fibers that exit cerebellar cortex synapse in dentate nuclei (DN) before reaching extracerebellar structures such as cerebral cortex, but the functional neuroanatomy of human DN remains largely unmapped. Neuroimaging research has redefined broad categories of functional division in the human brain showing that primary processing, attentional (task positive) processing, and default-mode (task negative) processing are three central poles of neural macroscale functional organization. This broad spectrum of human neural processing categories is represented not only in the cerebral cortex, but also in the thalamus, striatum, and cerebellar cortex. Whether functional organization in DN obeys a similar set of macroscale divisions, and whether DN are yet another compartment of representation of a broad spectrum of human neural processing categories, remains unknown. Here, we show for the first time that human DN are optimally divided into three functional territories as indexed by high spatio-temporal resolution resting-state MRI in 77 healthy humans, and that these three distinct territories contribute uniquely to default-mode, salience-motor, and visual cerebral cortical networks. Our findings provide a systems neuroscience substrate for cerebellar output to influence multiple broad categories of neural control.

Cerebellar White Matter Disruption in Alzheimer's Disease Patients: A Diffusion Tensor Imaging Study

The cognitive role of the cerebellum has recently gained much attention, and its pivotal role in Alzheimer's disease (AD) has now been widely recognized. Diffusion tensor imaging (DTI) has been used to evaluate the disruption of the microstructural milieu in AD, and though several white matter (WM) tracts such as corpus callosum, inferior and superior longitudinal fasciculus, cingulum, fornix, and uncinate fasciculus have been evaluated in AD, data on cerebellar WM tracts are currently lacking. We performed a tractography-based DTI reconstruction of the middle cerebellar peduncle (MCP), and the left and right superior cerebellar peduncles separately (SCPL and SCPR) and addressed the differences in fractional anisotropy (FA), axial diffusivity (Dax), radial diffusivity (RD), and mean diffusivity (MD) in the three tracts between 50 patients with AD and 25 healthy subjects. We found that AD patients showed a lower FA and a higher RD compared to healthy subjects in MCP, SCPL, and SCPR. Moreover, higher MD was found in SCPR and SCPL and higher Dax in SCPL. This result is important as it challenges the traditional view that WM bundles in the cerebellum are unaffected in AD and might identify new targets for therapeutic interventions.

Role of the cerebellum in the phenotype of neurodegenerative diseases: Mitigate or exacerbate?

Degenerative diseases alter brain activity and functional connectivity. In this issue of the Neuroscience Letters, Yin and others (2021) [6] present data showing increased activity in lobules VIII and IX of the cerebellar vermis in Parkinson's patients with visuospatial disorders. The study refines the fMRI mapping of the cerebellum, but the functional interpretation of the findings remains complex. The architecture and connectivity of the cerebellum set it apart from the rest of the brain and should be considered when interpreting the functional connectivity data. In degenerative diseases, the cerebellum suffers from the same pathology as the cerebral cortex; hence, it is unlikely that changes in the cerebellum could ameliorate clinical symptoms in degenerative diseases. Clinical, surgical data indicate that the primary function of the cerebellum is motor, not cognition or affective. The cerebellar anatomy buttresses these observations. The cerebellum receives direct motor-related inputs but no direct information from the sensory system. Hence, it likely contributes to the behavioral components of emotions and cognition.

PET evidence of preclinical cerebellar amyloid plaque deposition in autosomal dominant Alzheimer's disease-causing Presenilin-1 E280A mutation carriers

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PET evidence of cerebellar Aβ deposition in unimpaired (CU) PSEN1 E280A kindred.

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Cerebellar Aβ PET SUVR began to distinguish CU carriers from non-carriers at age 34.

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Cortical and cerebellar Aβ PET SUVR are positively associated in CU carriers.

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Cerebellar florbetapir SUVR correlated with lower composite score in CU carriers.

Background

In contrast to sporadic Alzheimer’s disease, autosomal dominant Alzheimer’s disease (ADAD) is associated with greater neuropathological evidence of cerebellar amyloid plaque (Aβ) deposition. In this study, we used positron emission tomography (PET) measurements of fibrillar Aβ burden to characterize the presence and age at onset of cerebellar Aβ deposition in cognitively unimpaired (CU) Presenilin-1 (PSEN1) E280A mutation carriers from the world’s largest extended family with ADAD.

Methods

¹⁸F florbetapir and ¹¹C Pittsburgh compound B (PiB) PET data from two independent studies – API ADAD Colombia Trial (NCT01998841) and Colombia-Boston (COLBOS) longitudinal biomarker study were included. The tracers were selected independently by the respective sponsors prior to the start of each study and used exclusively throughout. Template-based cerebellar Aβ-SUVR (standard-uptake value ratios) using a known-to-be-spared pons reference region (cerebellar SUVR_pons), to a) compare 28–56-year-old CU carriers and non-carriers; b) estimate the age at which cerebellar SUVR_pons began to differ significantly in carrier and non-carrier groups; and c) characterize in carriers associations with age, cortical SUVR_pons, delayed recall memory, and API ADAD composite score.

Results

Florbetapir and PiB cerebellar SUVR_pons were significantly higher in carriers than non-carriers (p < 0.0001). Cerebellar SUVR_pons began to distinguish carriers from non-carriers at age 34, 10 years before the carriers’ estimated age at mild cognitive impairment onset. Florbetapir and PiB cerebellar SUVR_pons in carriers were positively correlated with age (r = 0.44 & 0.69, p < 0.001), cortical SUVR_pons (r = 0.55 & 0.69, p < 0.001), and negatively correlated with delayed recall memory (r = −0.21 & −0.50, p < 0.05, unadjusted for cortical SUVR_pons) and API ADAD composite (r = −0.25, p < 0.01, unadjusted for cortical SUVR_pons in florbetapir API ADAD cohort).

Conclusion

This PET study provides evidence of cerebellar Aβ plaque deposition in CU carriers starting about a decade before the clinical onset of ADAD. Additional studies are needed to clarify the impact of using a cerebellar versus pons reference region on the power to detect and track ADAD changes, even in preclinical stages of this disorder.

Distinct genetic regions are associated with differential population susceptibility to chemical exposures

Interactions between environmental factors and genetics underlie the majority of chronic human diseases. Chemical exposures are likely an underestimated contributor, yet gene-environment (GxE) interaction studies rarely assess their modifying effects. Here, we describe a novel method to profile the human genome and identify regions associated with differential population susceptibility to chemical exposures. Single nucleotide polymorphisms (SNPs) implicated in enriched chemical-disease intersections were identified and validated for three chemical classes with expected GxE interaction potential (neuroactive, hepatoactive, and cardioactive compounds). The same approach was then used to characterize consumer product classes with unknown risk for GxE interactions (washing products, cosmetics, and adhesives). Additionally, high-risk variant sets that may confer differential population susceptibility were identified for these consumer product groups through frequent itemset mining and pathway analysis. A dataset of 2454 consumer product chemical-disease linkages, with risk values, SNPs, and pathways for each association was developed, describing the interplay between environmental factors and genetics in human disease progression. We found that genetic hotspots implicated in GxE interactions differ across chemical classes (e.g., washing products had high-risk SNPs implicated in nervous system disease) and illustrate how this approach can discover new associations (e.g., washing product n-butoxyethanol implicated SNPs in the PI3K-Akt signaling pathway for Alzheimer's disease). Hence, our approach can predict high-risk genetic regions for differential population susceptibility to chemical exposures and characterize chemical modifying factors in specific diseases. These methods show promise for describing how chemical exposures can lead to varied health outcomes in a population and for incorporating inter-individual variability into chemical risk assessment.

Interaction Between Cerebellum and Cerebral Cortex, Evidence from Dynamic Causal Modeling

The interaction of the cerebellum with cerebral cortical dynamics is still poorly understood. In this paper, dynamical causal modeling is used to examine the interaction between cerebellum and cerebral cortex as indexed by MRI resting-state functional connectivity in three large-scale networks on healthy young adults (N = 200; Human Connectome Project dataset). These networks correspond roughly to default mode, task positive, and motor as determined by prior cerebellar functional gradient analyses. We find uniform interactions within all considered networks from cerebellum to cerebral cortex, providing support for the notion of a universal cerebellar transform. Our results provide a foundation for future analyses to quantify and further investigate whether this is a property that is unique to the interactions from cerebellum to cerebral cortex.