What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus

Small effects of olfactory identification and discrimination on global cognitive and executive performance over 1 year in aging people without a history of age-related cognitive impairment

Olfactory and cognitive performance share neural correlates profoundly affected by physiological aging. However, whether odor identification and discrimination scores predict global cognitive status and executive function in healthy older people with intact cognition is unclear. Therefore, in the present study, we set out to elucidate these links in a convenience sample of 204 independently living, cognitively intact healthy Czech adults aged 77.4 ± 8.7 (61-97 years) over two waves of data collection (one-year interval). We used the Czech versions of the Montreal Cognitive Assessment (MoCA) to evaluate global cognition, and the Prague Stroop Test (PST), Trail Making Test (TMT), and several verbal fluency (VF) tests to assess executive function. As a subsidiary aim, we aimed to examine the contribution of olfactory performance towards achieving a MoCA score above vs. below the published cut-off value. We found that the MoCA scores exhibited moderate associations with both odor identification and discrimination. Furthermore, odor identification significantly predicted PST C and C/D scores. Odor discrimination significantly predicted PST C/D, TMT B/A, and standardized composite VF scores. Our findings demonstrate that olfaction, on the one hand, and global cognition and executive function, on the other, are related even in healthy older people.

Crosstalk between ferroptosis and necroptosis in cerebral ischemia/reperfusion injury and Naotaifang formula exerts neuroprotective effect via HSP90-GCN2-ATF4 pathway

BACKGROUND

Cerebral ischemia/reperfusion injury (CIRI) is a sequence of pathophysiological processes after blood recanalization in the patients with ischemic stroke, and has become the hinder for the rehabilitation. Naotaifang formula (NTF) has exhibited the clinical effectiveness for this disease. However, its action effects and molecular mechanisms against CIRI are not fully elucidated.

PURPOSE

The research was to clarify the crosstalk between ferroptosis and necroptosis in CIRI, and uncover the mechanism underlying the neuroprotection of NTF.

METHODS

This study established MCAO/R rat models with various reperfusion times. Western blot, transmission electron microscope, laser speckle imaging, immunofluorescence, immunohistochemistry and pathological staining were conducted to detect and analyze the obtained results. Subsequently, various NTF doses were used to intervene in MCAO/R rats, and biology experiments, such as western blot, Evans blue, immunofluorescence and immunohistochemistry, were used to analyze the efficacy of NTF doses. The effect of NTF was further clarified through in vitro experiments. Eventually, HT22 cells that suffered OGD/R were subjected to pre-treatment with plasmids overexpressing HSP90, MLKL, and GPX4 to indicate the interaction among ferroptosis and necroptosis.

RESULTS

There was a gradual increase in the Zea Longa score and cerebral infarction volume following CIRI with prolonged reperfusion. Furthermore, the expression of factors associated with pro-ferroptosis and pro-necroptosis was upregulated in the cortex and hippocampus. NTF alleviated ferroptosis and necroptosis in a dose-dependent manner, downregulated HSP90 levels, reduced blood-brain barrier permeability, and thus protected nerve cells from CIRI. The results in vitro research aligned with those of the in vivo research. HSP90 and MLKL overexpression promoted necroptosis and ferroptosis while activating the GCN2-ATF4 pathway. GPX4 overexpression had no effect on necroptosis or the associated signaling pathway. The administration of NTF alone, as well as its combination with the overexpression of HSP90, MLKL, or GPX4 plasmids, decreased the expression levels of factors associated with pro-ferroptosis and pro-necroptosis and reduced the protein levels of the HSP90-GCN2-ATF4 pathway. Moreover, the regulatory effects of the NTF alone group on GSH, ferrous iron, and GCN2 were more significant compared with those of the HSP90 overexpression combination group.

CONCLUSION

Ferroptosis and necroptosis were gradually aggravated following CIRI with prolonged reperfusion. MLKL overexpression may promote ferroptosis and necroptosis, while GPX4 overexpression may have little effect on necroptosis. HSP90 overexpression accelerated both forms of cell death via the HSP90-GCN2-ATF4 pathway. NTF alleviated ferroptosis and necroptosis to attenuate CIRI by regulating the HSP90-GCN2-ATF4 pathway. Our research provided evidence for the potential of drug development by targeting HSP90, MLKL, and GPX4 to protect against ischemic stroke.

Educational Attainment Moderates Task-State Control Network Connectivity Relations to Response Conflict Among Healthy Older Adults

OBJECTIVES

Older adult executive function varies widely due to brain and cognitive aging. Variance in older adult executive function is linked to increased response conflict from cognitive and brain aging. Cognitive reserve (CR) is a theoretical protective mechanism that lessens brain aging's impact on cognition and is associated with greater educational attainment. Recent work in rest-state functional magnetic resonance imaging (fMRI) suggests CR proxies moderate the relationship between functional connectivity (FC) and cognitive performance. Brain network FC in "control networks," including the salience (SN), dorsal attention and frontoparietal networks, are associated with cognitive processes in older adults. CR is hypothesized to maintain cognitive processing in part through changes in how brain networks respond to cognitive demands. However, it is unclear how CR proxies like educational attainment are related to control network FC during performance when cognitive demands are increased relative to rest. Because CR is expressed more in those with higher education, we hypothesized stronger control network FC would relate to better performance, where this relationship would be strongest among the most educated.

METHODS

We collected flanker task data during fMRI to assess the impact of a CR proxy (i.e., educational attainment) on response conflict among older adult subjects (n = 42, age = 65-80).

RESULTS

Linear mixed-effects models showed more educated older adults with greater SN-FC had a smaller flanker effect (i.e., less influence of distractors; p < .001) during task performance.

DISCUSSION

For the first time, we show that educational attainment moderates the relationship between task-state SN-FC and executive function among older adults.

Does resistance training in older adults lead to structural brain changes associated with a lower risk of Alzheimer's dementia? A narrative review

Dementia, particularly Alzheimer's Disease (AD), has links to several modifiable risk factors, especially physical inactivity. When considering the relationship between physcial activity and dementia risk, cognitive benefits are generally attributed to aerobic exercise, with resistance exercise (RE) receiving less attention. This review aims to address this gap by evaluating the impact of RE on brain structures and cognitive deficits associated with AD. Drawing insights from randomized controlled trials (RCTs) utilizing structural neuroimaging, the specific influence of RE on AD-affected brain structures and their correlation with cognitive function are discussed. Preliminary findings suggest that RE induces structural brain changes in older adults that could reduce the risk of AD or mitigate AD progression. Importantly, the impacts of RE appear to follow a dose-response effect, reversing pathological structural changes and improving associated cognitive functions if performed at least twice per week for at least six months, with greatest effects in those already experiencing some element of cognitive decline. While more research is eagerly awaited, this review contributes insights into the potential benefits of RE for cognitive health in the context of AD-related changes in brain structure and function.

The Effects of Computerized Cognitive Training in Older Adults' Cognitive Performance and Biomarkers of Structural Brain Aging

OBJECTIVES

Cognitive training (CT) has been investigated as a means of delaying age-related cognitive decline in older adults. However, its impact on biomarkers of age-related structural brain atrophy has rarely been investigated, leading to a gap in our understanding of the linkage between improvements in cognition and brain plasticity. This study aimed to explore the impact of CT on cognitive performance and brain structure in older adults.

METHODS

One hundred twenty-four cognitively normal older adults recruited from 2 study sites were randomly assigned to either an adaptive CT (n = 60) or a casual game training (active control, AC, n = 64).

RESULTS

After 10 weeks of training, CT participants showed greater improvements in the overall cognitive composite score (Cohen's d = 0.66, p < .01) with nonsignificant benefits after 6 months from the completion of training (Cohen's d = 0.36, p = .094). The CT group showed significant maintenance of the caudate volume as well as significant maintained fractional anisotropy in the left internal capsule and in left superior longitudinal fasciculus compared to the AC group. The AC group displayed an age-related decrease in these metrics of brain structure.

DISCUSSION

Results from this multisite clinical trial demonstrate that the CT intervention improves cognitive performance and helps maintain caudate volume and integrity of white matter regions that are associated with cognitive control, adding to our understanding of the changes in brain structure contributing to changes in cognitive performance from adaptive CT.

CLINICAL TRIAL REGISTRATION

NCT03197454.

An insight into the concept of neuroinflammation and neurodegeneration in Alzheimer's disease: targeting molecular approach Nrf2, NF-κB, and CREB

Alzheimer's disease (AD) is a most prevalent neurologic disorder characterized by cognitive dysfunction, amyloid-β (Aβ) protein accumulation, and excessive neuroinflammation. It affects various life tasks and reduces thinking, memory, capability, reasoning and orientation ability, decision, and language. The major parts responsible for these abnormalities are the cerebral cortex, amygdala, and hippocampus. Excessive inflammatory markers release, and microglial activation affect post-synaptic neurotransmission. Various mechanisms of AD pathogenesis have been explored, but still, there is a need to debate the role of NF-κB, Nrf2, inflammatory markers, CREB signaling, etc. In this review, we have briefly discussed the signaling mechanisms and function of the NF-ĸB signaling pathway, inflammatory mediators, microglia activation, and alteration of autophagy. NF-κB inhibition is a current strategy to counter neuroinflammation and neurodegeneration in the brain of individuals with AD. In clinical trials, numbers of NF-κB modulators are being examined. Recent reports revealed that molecular and cellular pathways initiate complex pathological competencies that cause AD. Moreover, this review will provide extensive knowledge of the cAMP response element binding protein (CREB) and how these nuclear proteins affect neuronal plasticity.

Phytoactive drugs used in the treatment of Alzheimer's disease and dementia

The prevalence of Alzheimer's disease and other forms of dementia is increasing worldwide, and finding effective treatments for these conditions is a major public health challenge. Natural bioactive drugs have been identified as a promising source of potential treatments, due to their ability to target multiple pathways and their low toxicity. This paper reviews the current state of research on natural bioactive drugs used in the treatment of Alzheimer's disease and other dementias. The paper summarizes the findings of studies on various natural compounds, including curcumin, resveratrol, caffeine, genistein, quercetin, GinkoBiloba, Withaniasomnifera, Ginseng Brahmi, Giloy, and huperzine, and their effects on cognitive function, neuroinflammation, and amyloid-beta accumulation. In this review, we discuss the mechanism of action involved in the treatment of Alzheimer's disease. The paper also discusses the challenges associated with developing natural bioactive drugs for dementia treatment, including issues related to bioavailability and standardization. Finally, the paper suggests directions for future research in this area, including the need for more rigorous clinical trials and the development of novel delivery systems to improve the efficacy of natural bioactive drugs. Overall, this review highlights the potential of natural bioactive drugs as a promising avenue for the development of safe and effective treatments for Alzheimer's disease and other dementias.

Predicting changes in brain metabolism and progression from mild cognitive impairment to dementia using multitask Deep Learning models and explainable AI

BACKGROUND

The prediction of Alzheimer's disease (AD) progression from its early stages is a research priority. In this context, the use of Artificial Intelligence (AI) in AD has experienced a notable surge in recent years. However, existing investigations predominantly concentrate on distinguishing clinical phenotypes through cross-sectional approaches. This study aims to investigate the potential of modeling additional dimensions of the disease, such as variations in brain metabolism assessed via [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET), and utilize this information to identify patients with mild cognitive impairment (MCI) who will progress to dementia (pMCI).

METHODS

We analyzed data from 1,617 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had undergone at least one FDG-PET scan. We identified the brain regions with the most significant hypometabolism in AD and used Deep Learning (DL) models to predict future changes in brain metabolism. The best-performing model was then adapted under a multi-task learning framework to identify pMCI individuals. Finally, this model underwent further analysis using eXplainable AI (XAI) techniques.

RESULTS

Our results confirm a strong association between hypometabolism, disease progression, and cognitive decline. Furthermore, we demonstrated that integrating data on changes in brain metabolism during training enhanced the models' ability to detect pMCI individuals (sensitivity=88.4%, specificity=86.9%). Lastly, the application of XAI techniques enabled us to delve into the brain regions with the most significant impact on model predictions, highlighting the importance of the hippocampus, cingulate cortex, and some subcortical structures.

CONCLUSION

This study introduces a novel dimension to predictive modeling in AD, emphasizing the importance of projecting variations in brain metabolism under a multi-task learning paradigm.

Interpretable deep clustering survival machines for Alzheimer's disease subtype discovery

Alzheimer's disease (AD) is a complex neurodegenerative disorder that has impacted millions of people worldwide. The neuroanatomical heterogeneity of AD has made it challenging to fully understand the disease mechanism. Identifying AD subtypes during the prodromal stage and determining their genetic basis would be immensely valuable for drug discovery and subsequent clinical treatment. Previous studies that clustered subgroups typically used unsupervised learning techniques, neglecting the survival information and potentially limiting the insights gained. To address this problem, we propose an interpretable survival analysis method called Deep Clustering Survival Machines (DCSM), which combines both discriminative and generative mechanisms. Similar to mixture models, we assume that the timing information of survival data can be generatively described by a mixture of parametric distributions, referred to as expert distributions. We learn the weights of these expert distributions for individual instances in a discriminative manner by leveraging their features. This allows us to characterize the survival information of each instance through a weighted combination of the learned expert distributions. We demonstrate the superiority of the DCSM method by applying this approach to cluster patients with mild cognitive impairment (MCI) into subgroups with different risks of converting to AD. Conventional clustering measurements for survival analysis along with genetic association studies successfully validate the effectiveness of the proposed method and characterize our clustering findings.

Effects of MicroRNAs and Long Non-coding RNAs on Beneficial Action of Exercise on Cognition in Degenerative Diseases: A Review

Recent research has exposed a growing body of proof underscoring the importance of microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) in maintaining the physical composition of neurons and influencing cognitive functioning in both standard and atypical circumstances. Extensive research has been conducted on the possible application of miRNAs and lncRNAs as biomarkers for various diseases, with a particular focus on brain disorders, as they possess remarkable durability in cell-free surroundings and can endure repeated freezing and thawing processes. It is intriguing to note that miRNAs and lncRNAs have the ability to function through paracrine mechanisms, thereby playing a role in communication between different organs. Recent research has proposed that the improvement of cognitive abilities through physical exercise in mentally healthy individuals is a valuable method for uncovering potential connections between miRNAs, or microRNAs, and lncRNAs, and human cognitive function. The process of cross-correlating data from disease models and patients with existing data will be crucial in identifying essential miRNAs and lncRNAs, which can potentially act as biomarkers or drug targets in the treatment of cognitive disorders. By combining this method with additional research in animal models, we can determine the function of these molecules and their potential impact on therapy. This article discusses the latest research about the primary miRNAs, lncRNAs, and their exosomes that are affected by physical activity in terms of human cognitive function.

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimer's disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

Aging Brain from a Lifespan Perspective

Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.

Association between physical frailty and cortical structure in middle-aged and elderly people: a Mendelian randomization study

Introduction

Physical weakness is associated with cortical structures, but the exact causes remain to be investigated. Therefore, we utilized Mendelian randomization (MR) analysis to uncover the underlying connection between frailty and cortical structures.

Methods

The Genome-Wide Association Study (GWAS) on frailty pooled data from publicly available sources such as the UK Biobank and included five indicators of frailty: weakness, walking speed, weight loss, physical activity, and exhaustion. GWAS data on cerebral cortical structure were obtained from the ENIGMA consortium, and we assessed the causal relationship between hereditary frailty and cortical surface area (SA) or cortical thickness (TH). Inverse variance weighting (IVW) was used as the primary estimate, and heterogeneity and multidimensionality were monitored by MR-PRESSO to detect outliers. Additionally, MR-Egger, Cochran's Q test, and weighted median were employed.

Results

At the aggregate level, there was no causal relationship between frailty and cortical thickness or surface area. At the regional level, frailty was associated with the thickness of the middle temporal lobe, parahippocampus, rostral middle frontal lobe, lower parietal lobe, anterior cingulate gyrus, upper temporal lobe, lateral orbital frontal cortex, pericardial surface area, rostral middle frontal lobe, upper temporal lobe, rostral anterior cingulate gyrus, lower parietal lobe, and upper parietal lobe. These results were nominally significant, and sensitivity analyses did not detect any multidirectionality or heterogeneity, suggesting that the results of our analyses are reliable.

Discussion

The results of our analyses suggest a potential causal relationship between somatic weakness and multiple regions of cortical structure. However, the specific mechanisms of influence remain to be investigated. Preliminary results from our analysis suggest that the effects of physical frailty on cortical structures are influenced by various factors related to frailty exposure. This relationship has been documented, and it is therefore both feasible and meaningful to build on existing research to explore the clinical significance of the relationship.

Inflammation subsequent to mild iron excess differentially alters regional brain iron metabolism, oxidation and neuroinflammation status in mice

Iron dyshomeostasis and neuroinflammation, characteristic features of the aged brain, and exacerbated in neurodegenerative disease, may induce oxidative stress-mediated neurodegeneration. In this study, the effects of potential priming with mild systemic iron injections on subsequent lipopolysaccharide (LPS)-induced inflammation in adult C57Bl/6J mice were examined. After cognitive testing, regional brain tissues were dissected for iron (metal) measurements by total reflection X-ray fluorescence and synchrotron radiation X-Ray fluorescence-based elemental mapping; and iron regulatory, ferroptosis-related, and glia-specific protein analysis, and lipid peroxidation by western blotting. Microglial morphology and astrogliosis were assessed by immunohistochemistry. Iron only treatment enhanced cognitive performance on the novel object location task compared with iron priming and subsequent LPS-induced inflammation. LPS-induced inflammation, with or without iron treatment, attenuated hippocampal heme oxygenase-1 and augmented 4-hydroxynonenal levels. Conversely, in the cortex, elevated ferritin light chain and xCT (light chain of System Xc-) were observed in response to LPS-induced inflammation, without and with iron-priming. Increased microglial branch/process lengths and astrocyte immunoreactivity were also increased by combined iron and LPS in both the hippocampus and cortex. Here, we demonstrate iron priming and subsequent LPS-induced inflammation led to iron dyshomeostasis, compromised antioxidant function, increased lipid peroxidation and altered neuroinflammatory state in a brain region-dependent manner.

Predicting brain age gap with radiomics and automl: A Promising approach for age-Related brain degeneration biomarkers

The Brain Age Gap (BAG), which refers to the difference between chronological age and predicted neuroimaging age, is proposed as a potential biomarker for age-related brain degeneration. However, existing brain age prediction models usually rely on a single marker and can not discover meaningful hidden information in radiographic images. This study focuses on the application of radiomics, an advanced imaging analysis technique, combined with automated machine learning to predict BAG. Our methods achieve a promising result with a mean absolute error of 1.509 using the Alzheimer's Disease Neuroimaging Initiative dataset. Furthermore, we find that the hippocampus and parahippocampal gyrus play a significant role in predicting age with interpretable method called SHapley Additive exPlanations. Additionally, our investigation of age prediction discrepancies between patients with Alzheimer's disease (AD) and those with mild cognitive impairment (MCI) reveals a notable correlation with clinical cognitive assessment scale scores. This suggests that BAG has the potential to serve as a biomarker to support the diagnosis of AD and MCI. Overall, this study presents valuable insights into the application of neuroimaging models in the diagnosis of neurodegenerative diseases.

Obesity during preclinical Alzheimer's disease development exacerbates brain metabolic decline

Alzheimer's disease (AD) is the most common form of dementia. Obesity in middle age increases AD risk and severity, which is alarming given that obesity prevalence peaks at middle age and obesity rates are accelerating worldwide. Midlife, but not late-life obesity increases AD risk, suggesting that this interaction is specific to preclinical AD. AD pathology begins in middle age, with accumulation of amyloid beta (Aβ), hyperphosphorylated tau, metabolic decline, and neuroinflammation occurring decades before cognitive symptoms appear. We used a transcriptomic discovery approach in young adult (6.5 months old) male and female TgF344-AD rats that overexpress mutant human amyloid precursor protein and presenilin-1 and wild-type (WT) controls to determine whether inducing obesity with a high-fat/high-sugar "Western" diet during preclinical AD increases brain metabolic dysfunction in dorsal hippocampus (dHC), a brain region vulnerable to the effects of obesity and early AD. Analyses of dHC gene expression data showed dysregulated mitochondrial and neurotransmission pathways, and up-regulated genes involved in cholesterol synthesis. Western diet amplified the number of genes that were different between AD and WT rats and added pathways involved in noradrenergic signaling, dysregulated inhibition of cholesterol synthesis, and decreased intracellular lipid transporters. Importantly, the Western diet impaired dHC-dependent spatial working memory in AD but not WT rats, confirming that the dietary intervention accelerated cognitive decline. To examine later consequences of early transcriptional dysregulation, we measured dHC monoamine levels in older (13 months old) AD and WT rats of both sexes after long-term chow or Western diet consumption. Norepinephrine (NE) abundance was significantly decreased in AD rats, NE turnover was increased, and the Western diet attenuated the AD-induced increases in turnover. Collectively, these findings indicate obesity during prodromal AD impairs memory, potentiates AD-induced metabolic decline likely leading to an overproduction of cholesterol, and interferes with compensatory increases in NE transmission.

Comparison between morphometry and radiomics: detecting normal brain aging based on grey matter

Objective

Voxel-based morphometry (VBM), surface-based morphometry (SBM), and radiomics are widely used in the field of neuroimage analysis, while it is still unclear that the performance comparison between traditional morphometry and emerging radiomics methods in diagnosing brain aging. In this study, we aimed to develop a VBM-SBM model and a radiomics model for brain aging based on cognitively normal (CN) individuals and compare their performance to explore both methods' strengths, weaknesses, and relationships.

Methods

967 CN participants were included in this study. Subjects were classified into the middle-aged group (n = 302) and the old-aged group (n = 665) according to the age of 66. The data of 360 subjects from the Alzheimer's Disease Neuroimaging Initiative were used for training and internal test of the VBM-SBM and radiomics models, and the data of 607 subjects from the Australian Imaging, Biomarker and Lifestyle, the National Alzheimer's Coordinating Center, and the Parkinson's Progression Markers Initiative databases were used for the external tests. Logistics regression participated in the construction of both models. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were used to evaluate the two model performances. The DeLong test was used to compare the differences in AUCs between models. The Spearman correlation analysis was used to observe the correlations between age, VBM-SBM parameters, and radiomics features.

Results

The AUCs of the VBM-SBM model and radiomics model were 0.697 and 0.778 in the training set (p = 0.018), 0.640 and 0.789 in the internal test set (p = 0.007), 0.736 and 0.737 in the AIBL test set (p = 0.972), 0.746 and 0.838 in the NACC test set (p < 0.001), and 0.701 and 0.830 in the PPMI test set (p = 0.036). Weak correlations were observed between VBM-SBM parameters and radiomics features (p < 0.05).

Conclusion

The radiomics model achieved better performance than the VBM-SBM model. Radiomics provides a good option for researchers who prioritize performance and generalization, whereas VBM-SBM is more suitable for those who emphasize interpretability and clinical practice.

Caudate functional networks influence brain structural changes with aging

Neurogenesis decline with aging may be associated with brain atrophy. Subventricular zone neuron precursor cells possibly modulate striatal neuronal activity via the release of soluble molecules. Neurogenesis decay in the subventricular zone may result in structural alterations of brain regions connected to the caudate, particularly to its medial component. The aim of this study was to investigate how the functional organization of caudate networks relates to structural brain changes with aging. One hundred and fifty-two normal subjects were recruited: 52 young healthy adults (≤35 years old), 42 middle-aged (36 ≤ 60 years old) and 58 elderly subjects (≥60 years old). In young adults, stepwise functional connectivity was used to characterize regions that connect to the medial and lateral caudate at different levels of link-step distances. A statistical comparison between the connectivity of medial and lateral caudate in young subjects was useful to define medial and lateral caudate connected regions. Atrophy of medial and lateral caudate connected regions was estimated in young, middle-aged and elderly subjects using T1-weighted images. Results showed that middle-aged and elderly adults exhibited decreased stepwise functional connectivity at one-link step from the caudate, particularly in the frontal, parietal, temporal and occipital brain regions, compared to young subjects. Elderly individuals showed increased stepwise functional connectivity in frontal, parietal, temporal and occipital lobes compared to both young and middle-aged adults. Additionally, elderly adults displayed decreased stepwise functional connectivity compared to middle-aged subjects in specific parietal and subcortical areas. Moreover, in young adults, the medial caudate showed higher direct connectivity to the basal ganglia (left thalamus), superior, middle and inferior frontal and inferior parietal gyri (medial caudate connected region) relative to the lateral caudate. Considering the opposite contrast, lateral caudate showed stronger connectivity to the basal ganglia (right pallidum), orbitofrontal, rostral anterior cingulate and insula cortices (lateral caudate connected region) compared to medial caudate. In elderly subjects, the medial caudate connected region showed greater atrophy relative to the lateral caudate connected region. Brain regions linked to the medial caudate appear to be more vulnerable to aging than lateral caudate connected areas. The adjacency to the subventricular zone may, at least partially, explain these findings. Stepwise functional connectivity analysis can be useful to evaluate the role of the subventricular zone in network disruptions in age-related neurodegenerative disorders.

Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers

Structural brain changes underly cognitive changes in older age and contribute to inter-individual variability in cognition. Here, we assessed how changes in cortical thickness, surface area, and subcortical volume, are related to cognitive change in cognitively unimpaired older adults using structural magnetic resonance imaging (MRI) data-driven clustering. Specifically, we tested (1) which brain structural changes over time predict cognitive change in older age (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers phosphorylated tau (p-tau) and amyloid-β (Aβ42), and (3) the degree of overlap between clusters derived from different structural features. In total 1899 cognitively healthy older adults (50 - 93 years) were followed up to 16 years with neuropsychological and structural MRI assessments, a subsample of which (n = 612) had CSF p-tau and Aβ42 measurements. We applied Monte-Carlo Reference-based Consensus clustering to identify subgroups of older adults based on structural brain change patterns over time. Four clusters for each brain feature were identified, representing the degree of longitudinal brain decline. Each brain feature provided a unique contribution to brain aging as clusters were largely independent across modalities. Cognitive change and baseline cognition were best predicted by cortical area change, whereas higher levels of p-tau and Aβ42 were associated with changes in subcortical volume. These results provide insights into the link between changes in brain morphology and cognition, which may translate to a better understanding of different aging trajectories.

Longitudinal changes in brain-derived neurotrophic factor (BDNF) but not cytokines contribute to hippocampal recovery in anorexia nervosa above increases in body mass index

BACKGROUND

Physical sequelae of anorexia nervosa (AN) include a marked reduction in whole brain volume and subcortical structures such as the hippocampus. Previous research has indicated aberrant levels of inflammatory markers and growth factors in AN, which in other populations have been shown to influence hippocampal integrity.

METHODS

Here we investigated the influence of concentrations of two pro-inflammatory cytokines (tumor necrosis factor-alpha [TNF-α] and interleukin-6 [IL-6]) and brain-derived neurotrophic factor (BDNF) on the whole hippocampal volume, as well as the volumes of three regions (the hippocampal body, head, and tail) and 18 subfields bilaterally. Investigations occurred both cross-sectionally between acutely underweight adolescent/young adult females with AN (acAN; n = 82) and people recovered from AN (recAN; n = 20), each independently pairwise age-matched with healthy controls (HC), and longitudinally in acAN after partial renourishment (n = 58). Hippocampal subfield volumes were quantified using FreeSurfer. Concentrations of molecular factors were analyzed in linear models with hippocampal (subfield) volumes as the dependent variable.

RESULTS

Cross-sectionally, there was no evidence for an association between IL-6, TNF-α, or BDNF and between-group differences in hippocampal subfield volumes. Longitudinally, increasing concentrations of BDNF were positively associated with longitudinal increases in bilateral global hippocampal volumes after controlling for age, age2, estimated total intracranial volume, and increases in body mass index (BMI).

CONCLUSIONS

These findings suggest that increases in BDNF may contribute to global hippocampal recovery over and above increases in BMI during renourishment. Investigations into treatments targeted toward increasing BDNF in AN may be warranted.

Aberrant morphometric networks in Alzheimer's disease have hemispheric asymmetry and age dependence

Alzheimer's disease (AD) is associated with abnormal accumulations of hyperphosphorylated tau and amyloid-β proteins, resulting in unique patterns of atrophy in the brain. We aimed to elucidate some characteristics of the AD's morphometric networks constructed by associating different morphometric features among brain areas and evaluating their relationship to Mini-Mental State Examination total score and age. Three-dimensional T1-weighted (3DT1) image data scanned by the same 1.5T magnetic resonance imaging (MRI) were obtained from 62 AD patients and 41 healthy controls (HCs) and were analysed by using FreeSurfer. The associations of the extracted six morphometric features between regions were estimated by correlation coefficients. The global and local graph theoretical measures for this network were evaluated. Associations between graph theoretical measures and age, sex and cognition were evaluated by multiple regression analysis in each group. Global measures of integration: global efficiency and mean information centrality were significantly higher in AD patients. Local measures of integration: node global efficiency and information centrality were significantly higher in the entorhinal cortex, fusiform gyrus and posterior cingulate cortex of AD patients but only in the left hemisphere. All global measures were correlated with age in AD patients but not in HCs. The information centrality was associated with age in AD's broad brain regions. Our results showed that altered morphometric networks due to AD are left-hemisphere dominant, suggesting that AD pathogenesis has a left-right asymmetry. Ageing has a unique impact on the morphometric networks in AD patients. The information centrality is a sensitive graph theoretical measure to detect this association.

Effects of current alcohol use on brain volume among older adults in the Gothenburg H70 Birth Cohort study 2014-16

Brain gray- and white matter changes is well described in alcohol-dependent elderly subjects; however, the effect of lower levels of alcohol consumption on the brain is poorly understood. We investigated the impact of different amounts of weekly alcohol consumption on brain structure in a population-based sample of 70-year-olds living in Gothenburg, Sweden. Cross-sectional data from 676 participants from The Gothenburg H70 Birth Cohort Study 2014-16 were included. Current alcohol consumers were divided into seven groups based on self-reported weekly amounts of alcohol consumption in grams (g) (0-50 g/week, used as reference group, 51-100 g/week, 101-150 g/week, 151-200 g/week, 201-250 g/week, 251-300 g/week, and > 300 g/week). Subcortical volumes and cortical thickness were assessed on T1-weighted structural magnetic resonance images using FreeSurfer 5.3, and white matter integrity assessed on diffusion tensor images, using tract-based statistics in FSL. General linear models were carried out to estimate associations between alcohol consumption and gray- and white matter changes in the brain. Self-reported consumption above 250 g/week was associated with thinning in the bilateral superior frontal gyrus, the right precentral gyrus, and the right lateral occipital cortex, in addition to reduced fractional anisotropy (FA) and increased mean diffusivity (MD) diffusively spread in many tracts all over the brain. No changes were found in subcortical gray matter structures. These results suggest that there is a non-linear relationship between alcohol consumption and structural brain changes, in which loss of cortical thickness only occur in non-demented 70-year-olds who consume more than 250 g/week.

A novel neuroimaging signature for ADRD risk stratification in the community

INTRODUCTION

Early risk stratification for clinical dementia could lead to preventive therapies. We identified and validated a magnetic resonance imaging (MRI) signature for Alzheimer's disease (AD) and related dementias (ARDR).

METHODS

An MRI ADRD signature was derived from cortical thickness maps in Framingham Heart Study (FHS) participants with AD dementia and matched controls. The signature was related to the risk of ADRD and cognitive function in FHS. Results were replicated in the University of California Davis Alzheimer's Disease Research Center (UCD-ADRC) cohort.

RESULTS

Participants in the bottom quartile of the signature had more than three times increased risk for ADRD compared to those in the upper three quartiles (P < 0.001). Greater thickness in the signature was related to better general cognition (P < 0.01) and episodic memory (P = 0.01). Results replicated in UCD-ADRC.

DISCUSSION

We identified a robust neuroimaging biomarker for persons at increased risk of ADRD. Other cohorts will further test the validity of this biomarker.

Bidirectional two-sample mendelian randomization analysis identifies causal associations of MRI-based cortical thickness and surface area relation to NAFLD

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) patients have exhibited extra-hepatic neurological changes, but the causes and mechanisms remain unclear. This study investigates the causal effect of NAFLD on cortical structure through bidirectional two-sample Mendelian randomization analysis.

METHODS

Genetic data from 778,614 European individuals across four NAFLD studies were used to determine genetically predicted NAFLD. Abdominal MRI scans from 32,860 UK Biobank participants were utilized to evaluate genetically predicted liver fat and volume. Data from the ENIGMA Consortium, comprising 51,665 patients, were used to evaluate the associations between genetic susceptibility, NAFLD risk, liver fat, liver volume, and alterations in cortical thickness (TH) and surface area (SA). Inverse-variance weighted (IVW) estimation, Cochran Q, and MR-Egger were employed to assess heterogeneity and pleiotropy.

RESULTS

Overall, NAFLD did not significantly affect cortical SA or TH. However, potential associations were noted under global weighting, relating heightened NAFLD risk to reduced parahippocampal SA and decreased cortical TH in the caudal middle frontal, cuneus, lingual, and parstriangularis regions. Liver fat and volume also influenced the cortical structure of certain regions, although no Bonferroni-adjusted p-values reached significance. Two-step MR analysis revealed that liver fat, AST, and LDL levels mediated the impact of NAFLD on cortical structure. Multivariable MR analysis suggested that the impact of NAFLD on the cortical TH of lingual and parstriangularis was independent of BMI, obesity, hyperlipidemia, and diabetes.

CONCLUSION

This study provides evidence that NAFLD causally influences the cortical structure of the brain, suggesting the existence of a liver-brain axis in the development of NAFLD.

Functional neuroplasticity of facilitation and interference effects on inhibitory control following 3-month physical exercise in aging

Preservation of executive function, like inhibition, closely links to the quality of life in senior adults. Although neuroimaging literature has shown enhanced inhibitory function followed by aerobic exercise, current evidence implies inconsistent neuroplasticity patterns along different time durations of exercise. Hence, we conducted a 12-week exercise intervention on 12 young and 14 senior volunteers and repeatedly measured the inhibitory functionality of distinct aspects (facilitation and interference effects) using the numerical Stroop task and functional Magnetic Resonance Imaging. Results showcased improved accuracy and reduced reaction times (RT) after 12-week exercise, attributed to frontoparietal and default mode network effects. In young adults, the first phase (0 to six weeks) exercise increased the activation of the right superior medial frontal gyrus, associated with reduced RT in interference, but in the second intervention phase (six to twelve weeks), the decreased activation of the left superior medial frontal gyrus positively correlated with reduced RT in facilitation. In senior adults, the first six-week intervention led to reduced activations of the inferior frontal gyrus, inferior parietal gyrus, and default mode network regions, associated with the reduced RT in interference. Still, in the second intervention phase, only the visual area exhibited increased activity, associated with reduced RT in interference. Except for the distinctive brain plasticity between the two phases of exercise intervention, the between-group comparison also presented that the old group gained more cognitive benefits within the first six weeks of exercise intervention; however, the cognitive improvements in the young group occurred after six weeks of intervention. Limited by the sample size, these preliminary findings corroborated the benefits of aerobic exercise on the inhibitory functions, implying an age × exercise interaction on the brain plasticity for both facilitation and interference.

Cortical structure and the risk of amyotrophic lateral sclerosis: A bidirectional Mendelian randomization study

BACKGROUND

Current observational studies indicate progressive brain atrophy is closely associated with the clinical feature of amyotrophic lateral sclerosis. However, it is unclear whether the changes in cortical structure are the cause or result of ALS. Our study aimed to investigate the causal relationship between cortical structure and ALS risk using a bidirectional two-sample MR study.

METHODS

We collected publicly available genome-wide association studies' summary statistics for cortical structure from UK Biobank and ENIGMA consortium (n = 33,992) and ALS from the Project MinE (n = 138,086). We used the inverse variance weighted method (IVW) as primary analysis in order to evaluate the causal effects. In addition, the weighted median and MR Egger methods were performed to ensure the robustness and reliability of the IVW results.

RESULTS

We found the decreased surface of the paracentral lobule and thickness of the frontal pole and middle temporal lobe were suggestively associated with an increased risk of ALS as well as the increased surface of medial orbitofrontal and middle temporal lobe. In another aspect, the causalities between the susceptibility to ALS and the volume of the transverse temporal gyrus and superior temporal gyrus were negative. Besides, the susceptibility to ALS might also contribute to an increased thickness of the postcentral gyrus and superior parietal gyrus.

CONCLUSION

In this two-sample MR analysis, we observed that multiple cortical brain regions are associated with a higher ALS risk. Further research into the underlying mechanisms is required to back up our findings.

Vulnerability of the Hippocampus to Insults: Links to Blood-Brain Barrier Dysfunction

The hippocampus is a critical brain substrate for learning and memory; events that harm the hippocampus can seriously impair mental and behavioral functioning. Hippocampal pathophysiologies have been identified as potential causes and effects of a remarkably diverse array of medical diseases, psychological disorders, and environmental sources of damage. It may be that the hippocampus is more vulnerable than other brain areas to insults that are related to these conditions. One purpose of this review is to assess the vulnerability of the hippocampus to the most prevalent types of insults in multiple biomedical domains (i.e., neuroactive pathogens, neurotoxins, neurological conditions, trauma, aging, neurodegenerative disease, acquired brain injury, mental health conditions, endocrine disorders, developmental disabilities, nutrition) and to evaluate whether these insults affect the hippocampus first and more prominently compared to other brain loci. A second purpose is to consider the role of hippocampal blood-brain barrier (BBB) breakdown in either causing or worsening the harmful effects of each insult. Recent research suggests that the hippocampal BBB is more fragile compared to other brain areas and may also be more prone to the disruption of the transport mechanisms that act to maintain the internal milieu. Moreover, a compromised BBB could be a factor that is common to many different types of insults. Our analysis indicates that the hippocampus is more vulnerable to insults compared to other parts of the brain, and that developing interventions that protect the hippocampal BBB may help to prevent or ameliorate the harmful effects of many insults on memory and cognition.

Systolic blood pressure is associated with abnormal alterations in brain cortical structure: Evidence from a Mendelian randomization study

BACKGROUND

Hypertension has been recognized as a significant risk factor for cerebrovascular diseases and cognitive decline. However, the specific impact of hypertension, systolic/diastolic blood pressure, pulse pressure (PP) and mean arterial pressure (MAP) on brain cortical structure remains unclear. Mendelian randomization (MR) provides a robust approach to investigate the causal relationship between blood pressure components and brain cortical changes.

METHODS

In this MR study, data from large-scale genome-wide association studies for blood pressure components and neuroimaging were utilized to conduct our analyses. We leveraged genetic variants associated specifically with hypertension (122,620 cases and 332,683 controls), systolic (469,767 individuals), diastolic (490,469 individuals) blood pressure, PP (810,865 individuals) and MAP (over 1 million individuals) to evaluate their effects on brain cortex surficial area (51,665 individuals) and cortex thickness (51,665 individuals).

RESULTS

Our findings revealed a significant correlation between systolic blood pressure and abnormal reduction in brain cortex surficial area (β=-1330.69, 95% confident interval [CI]: -2655.35 to -6.02, p = 0.0489); however, no significant relationship was found between systolic blood pressure and brain cortex thickness (β=-0.0078, 95% CI: -0.0178 to 0.0022, p = 0.1287). Additionally, no significant associations were observed between hypertension (β=-200.05, p = 0.6884; β=-0.0051, p = 0.1179, respectively), diastolic blood pressure (β=-460.63, p = 0.5160; β=0.0047, p = 0.2448, respectively), PP (β=1041.84, p = 0.3725; β=-0.0112, p = 0.2212, respectively), MAP (β=-18.84, p = 0.8841; β=0.0002, p = 0.7654, respectively) and both brain cortex surficial area and brain cortex thickness.

CONCLUSION

Our MR study provides evidence supporting the hypothesis that systolic blood pressure, rather than diastolic blood pressure, PP or MAP, is associated with abnormal changes in brain cortical structure.

Cognitive Dysfunction and Exercise: From Epigenetic to Genetic Molecular Mechanisms

Maintaining good health is crucial, and exercise plays a vital role in achieving this goal. It offers a range of positive benefits for cognitive function, regardless of age. However, as our population ages and life expectancy increases, cognitive impairment has become a prevalent issue, often coexisting with age-related neurodegenerative conditions. This can result in devastating consequences such as memory loss, difficulty speaking, and confusion, greatly hindering one's ability to lead an ordinary life. In addition, the decrease in mental capacity has a significant effect on an individual's physical and emotional well-being, greatly reducing their overall level of contentment and causing a significant financial burden for communities. While most current approaches aim to slow the decline of cognition, exercise offers a non-pharmacological, safe, and accessible solution. Its effects on cognition are intricate and involve changes in the brain's neural plasticity, mitochondrial stability, and energy metabolism. Moreover, exercise triggers the release of cytokines, playing a significant role in the body-brain connection and its impact on cognition. Additionally, exercise can influence gene expression through epigenetic mechanisms, leading to lasting improvements in brain function and behavior. Herein, we summarized various genetic and epigenetic mechanisms that can be modulated by exercise in cognitive dysfunction.

Neuronal microstructural changes in the human brain are associated with neurocognitive aging

Gray matter (GM) alterations play a role in aging-related disorders like Alzheimer's disease and related dementias, yet MRI studies mainly focus on macroscopic changes. Although reliable indicators of atrophy, morphological metrics like cortical thickness lack the sensitivity to detect early changes preceding visible atrophy. Our study aimed at exploring the potential of diffusion MRI in unveiling sensitive markers of cortical and subcortical age-related microstructural changes and assessing their associations with cognitive and behavioral deficits. We leveraged the Human Connectome Project-Aging cohort that included 707 unimpaired participants (394 female; median age = 58, range = 36-90 years) and applied the powerful mean apparent diffusion propagator model to measure microstructural parameters, along with comprehensive behavioral and cognitive test scores. Both macro- and microstructural GM characteristics were strongly associated with age, with widespread significant microstructural correlations reflective of cellular morphological changes, reduced cellular density, increased extracellular volume, and increased membrane permeability. Importantly, when correlating MRI and cognitive test scores, our findings revealed no link between macrostructural volumetric changes and neurobehavioral performance. However, we found that cellular and extracellular alterations in cortical and subcortical GM regions were associated with neurobehavioral performance. Based on these findings, it is hypothesized that increased microstructural heterogeneity and decreased neurite orientation dispersion precede macrostructural changes, and that they play an important role in subsequent cognitive decline. These alterations are suggested to be early markers of neurocognitive performance that may distinctly aid in identifying the mechanisms underlying phenotypic aging and subsequent age-related functional decline.

Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach

Background

The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points.

Objective

To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach.

Methods

We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline.

Results

We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G > T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neurons and plays a role in controlling cell growth and differentiation. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways.

Conclusions

Our deep learning model effectively extracted relevant neuroimaging features and predicted individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene.

Impact of Concurrent Visual and Hearing Impairment on Incident Alzheimer's Disease: The LIFE Study

Background

The prevalence of Alzheimer's disease (AD) is increasing in Japan due to population aging. The association between sensory impairment and incident AD remains unclear.

Objective

This study aimed to investigate the impact of sensory impairment on incident AD.

Methods

We analyzed residents of five municipalities participating in the Longevity Improvement & Fair Evidence (LIFE) Study. The participants comprised individuals who had newly applied for long-term care needs certification between 2017 and 2022 and had no cognitive impairment upon application or AD diagnosis within the preceding six months. Participants were classified according to sensory impairment status: visual impairment (VI), hearing impairment (HI), neither sensory impairment (NSI), and dual sensory impairment (DSI). The month succeeding the certification application was set as the index month, and the interval from that month until AD onset was assessed. Multivariable Cox proportional hazards analysis was performed to calculate the risk of AD onset according to sensory impairment status while adjusting for sex, age, dependence level, self-reliance level, and comorbidities.

Results

Among 14,186 participants, we identified 1,194 (8.4%) who developed AD over a median follow-up period of 22.6 months. VI and HI only were not associated with incident AD. However, DSI conferred a significantly higher risk (HR: 1.6, CI: 1.1-2.2, p = 0.008) of AD onset than NSI.

Conclusions

Individuals with concurrent DSI have a higher risk of developing AD than those with single or NSI. Preventing and treating sensory impairment may not only improve functional outcomes, but could also help to reduce the future risk of AD.

Multivariate investigation of aging in mouse models expressing the Alzheimer's protective APOE2 allele: integrating cognitive metrics, brain imaging, and blood transcriptomics

APOE allelic variation is critical in brain aging and Alzheimer's disease (AD). The APOE2 allele associated with cognitive resilience and neuroprotection against AD remains understudied. We employed a multipronged approach to characterize the transition from middle to old age in mice with APOE2 allele, using behavioral assessments, image-derived morphometry and diffusion metrics, structural connectomics, and blood transcriptomics. We used sparse multiple canonical correlation analyses (SMCCA) for integrative modeling, and graph neural network predictions. Our results revealed brain sub-networks associated with biological traits, cognitive markers, and gene expression. The cingulate cortex emerged as a critical region, demonstrating age-associated atrophy and diffusion changes, with higher fractional anisotropy in males and middle-aged subjects. Somatosensory and olfactory regions were consistently highlighted, indicating age-related atrophy and sex differences. The hippocampus exhibited significant volumetric changes with age, with differences between males and females in CA3 and CA1 regions. SMCCA underscored changes in the cingulate cortex, somatosensory cortex, olfactory regions, and hippocampus in relation to cognition and blood-based gene expression. Our integrative modeling in aging APOE2 carriers revealed a central role for changes in gene pathways involved in localization and the negative regulation of cellular processes. Our results support an important role of the immune system and response to stress. This integrative approach offers novel insights into the complex interplay among brain connectivity, aging, and sex. Our study provides a foundation for understanding the impact of APOE2 allele on brain aging, the potential for detecting associated changes in blood markers, and revealing novel therapeutic intervention targets.

Precision Brain Morphometry Using Cluster Scanning

Measurement error limits the statistical power to detect group differences and longitudinal change in structural MRI morphometric measures (e.g., hippocampal volume, prefrontal thickness). Recent advances in scan acceleration enable extremely fast T1-weighted scans (~1 minute) to achieve morphometric errors that are close to the errors in longer traditional scans. As acceleration allows multiple scans to be acquired in rapid succession, it becomes possible to pool estimates to increase measurement precision, a strategy known as "cluster scanning." Here we explored brain morphometry using cluster scanning in a test-retest study of 40 individuals (12 younger adults, 18 cognitively unimpaired older adults, and 10 adults diagnosed with mild cognitive impairment or Alzheimer's Dementia). Morphometric errors from a single compressed sensing (CS) 1.0mm scan with 6x acceleration (CSx6) were, on average, 12% larger than a traditional scan using the Alzheimer's Disease Neuroimaging Initiative (ADNI) protocol. Pooled estimates from four clustered CSx6 acquisitions led to errors that were 34% smaller than ADNI despite having a shorter total acquisition time. Given a fixed amount of time, a gain in measurement precision can thus be achieved by acquiring multiple rapid scans instead of a single traditional scan. Errors were further reduced when estimates were pooled from eight CSx6 scans (51% smaller than ADNI). Neither pooling across a break nor pooling across multiple scan resolutions boosted this benefit. We discuss the potential of cluster scanning to improve morphometric precision, boost statistical power, and produce more sensitive disease progression biomarkers.

Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer's disease

Alzheimer's disease (AD) remains one of the most extensively researched neurodegenerative disorders due to its widespread prevalence and complex risk factors. Age is a crucial risk factor for AD, which can be estimated by the disparity between physiological age and estimated brain age. To model AD risk more effectively, integrating biological, genetic, and cognitive markers is essential. Here, we utilized mouse models expressing the major APOE human alleles and human nitric oxide synthase 2 to replicate genetic risk for AD and a humanized innate immune response. We estimated brain age employing a multivariate dataset that includes brain connectomes, APOE genotype, subject traits such as age and sex, and behavioral data. Our methodology used Feature Attention Graph Neural Networks (FAGNN) for integrating different data types. Behavioral data were processed with a 2D Convolutional Neural Network (CNN), subject traits with a 1D CNN, brain connectomes through a Graph Neural Network using quadrant attention module. The model yielded a mean absolute error for age prediction of 31.85 days, with a root mean squared error of 41.84 days, outperforming other, reduced models. In addition, FAGNN identified key brain connections involved in the aging process. The highest weights were assigned to the connections between cingulum and corpus callosum, striatum, hippocampus, thalamus, hypothalamus, cerebellum, and piriform cortex. Our study demonstrates the feasibility of predicting brain age in models of aging and genetic risk for AD. To verify the validity of our findings, we compared Fractional Anisotropy (FA) along the tracts of regions with the highest connectivity, the Return-to-Origin Probability (RTOP), Return-to-Plane Probability (RTPP), and Return-to-Axis Probability (RTAP), which showed significant differences between young, middle-aged, and old age groups. Younger mice exhibited higher FA, RTOP, RTAP, and RTPP compared to older groups in the selected connections, suggesting that degradation of white matter tracts plays a critical role in aging and for FAGNN's selections. Our analysis suggests a potential neuroprotective role of APOE2, relative to APOE3 and APOE4, where APOE2 appears to mitigate age-related changes. Our findings highlighted a complex interplay of genetics and brain aging in the context of AD risk modeling.

Multi-domain cognition dysfunction accompanies frontoparietal and temporal amyloid accumulation in the elderly

It is helpful to understand the pathology of Alzheimer's disease by exploring the relationship between amyloid-β accumulation and cognition. The study explored the relationship between regional amyloid-β accumulation and multiple cognitions and study their application value in the Alzheimer's disease diagnosis. 135 participants completed 18F-florbetapir Positron Emission Tomography (PET), structural MRI, and a cognitive battery. Partial correlation was used to examine the relationship between global and regional amyloid-β accumulation and cognitions. Then, a support vector machine was applied to determine whether cognition-related accumulation regions can adequately distinguish the cognitively normal controls (76 participants) and mild cognitive impairment (30 participants) groups or mild cognitive impairment and Alzheimer's disease (29 participants) groups. The result showed that amyloid-β accumulation regions were mainly located in the frontoparietal cortex, calcarine fissure, and surrounding cortex and temporal pole regions. Episodic memory-related regions included the frontoparietal cortices; executive function-related regions included the frontoparietal, temporal, and occipital cortices; and processing speed-related regions included the frontal and occipital cortices. Support vector machine analysis showed that only episodic memory-related amyloid-β accumulation regions had better classification performance during the progression of Alzheimer's disease. Assessing regional changes in amyloid, particularly in frontoparietal regions, can aid in the early detection of amyloid-related decline in cognitive function.

Matrix metalloproteinases are associated with brain atrophy in cognitively unimpaired individuals

Matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) have been linked to age-related neurodegeneration and Alzheimer's disease (AD), but their role in normal aging is poorly understood. We used linear mixed models to determine if baseline or rate of yearly change in cerebrospinal fluid (CSF) levels of MMP-2; MMP-3; MMP-10; TIMP-123 (composite of TIMP-1, TIMP-2, and TIMP-3); or TIMP-4 predicted changes in bilateral entorhinal cortex thickness, hippocampal volume, or lateral ventricle volume in cognitively unimpaired individuals. We also assessed effects on the CSF AD biomarkers amyloid-β42 and phosphorylated tau181. Low baseline levels of MMP-3 predicted larger ventricle volumes and more entorhinal cortex thinning. Increased CSF MMP-2 levels over time predicted more entorhinal thinning, hippocampal atrophy, and ventricular expansion, while increased TIMP-123 over time predicted ventricular expansion. No MMP/TIMPs predicted changes in CSF AD biomarkers. Notably, we show for the first time that longitudinal increases in MMP-2 and TIMP-123 levels may predict age-associated brain atrophy. In conclusion, MMPs and TIMPs may play a role in brain atrophy in cognitively unimpaired aging.

No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy

Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration-which is shorter than current recommendations.

Characterising the covariance pattern between lifestyle factors and structural brain measures: a multivariable replication study of two independent ageing cohorts

Modifiable lifestyle factors have been shown to promote healthy brain ageing. However, studies have typically focused on a single factor at a time. Given that lifestyle factors do not occur in isolation, multivariable analyses provide a more realistic model of the lifestyle-brain relationship. Here, canonical correlation analyses (CCA) examined the relationship between nine lifestyle factors and seven MRI-derived indices of brain structure. The resulting covariance pattern was further explored with Bayesian regressions. CCA analyses were first conducted on a Danish cohort of older adults (n = 251) and then replicated in a British cohort (n = 668). In both cohorts, the latent factors of lifestyle and brain structure were positively correlated (UK: r = .37, p < 0.001; Denmark: r = .27, p < 0.001). In the cross-validation study, the correlation between lifestyle-brain latent factors was r = .10, p = 0.008. However, the pattern of associations differed between datasets. These findings suggest that baseline characterisation and tailoring towards the study sample may be beneficial for achieving targeted lifestyle interventions.

Synergistic neuroprotection by phytocompounds of Bacopa monnieri in scopolamine-induced Alzheimer's disease mice model

BACKGROUND

Millions of people around the globe are affected by Alzheimer's disease (AD). This crippling condition has no treatment despite intensive studies. Some phytocompounds have been shown to protect against Alzheimer's in recent studies.

METHODS

Thus, this work aimed to examine Bacopa monnieri phytocompounds' synergistic effects on neurodegeneration, antioxidant activity, and cognition in the scopolamine-induced AD mice model. The toxicity study of two phytocompounds: quercetin and bacopaside X revealed an LD50 of more than 2000 mg/kg since no deaths occurred.

RESULTS

The neuroprotection experiment consists of 6 groups i.e., control (saline), scopolamine (1 mg/kg), donepezil (5 mg/kg), Q (25 mg/kg), BX (20 mg/kg), and Q + BX (25 mg/kg + 20 mg/kg). Visual behavioral assessment using the Morris water maze showed that animals in the diseased model group (scopolamine) moved more slowly toward the platform and exhibited greater thigmotaxis behavior than the treatment and control groups. Likewise, the concentration of biochemical NO, GSH, and MDA improved in treatment groups concerning the diseased group. mRNA levels of different marker genes including ChAT, IL-1α, IL-1 β, TNF α, tau, and β secretase (BACE1) improved in treatment groups with respect to the disease group.

CONCLUSION

Both bacopaside X and quercetin synergistically have shown promising results in neuroprotection. Therefore, it is suggested that Q and BX may work synergistically due to their antioxidant and neuroprotective property.

Timing of lifespan influences on brain and cognition

Modifiable risk and protective factors for boosting brain and cognitive development and preventing neurodegeneration and cognitive decline are embraced in neuroimaging studies. We call for sobriety regarding the timing and quantity of such influences on brain and cognition. Individual differences in the level of brain and cognition, many of which present already at birth and early in development, appear stable, larger, and more pervasive than differences in change across the lifespan. Incorporating early-life factors, including genetics, and investigating both level and change will reduce the risk of ascribing undue importance and causality to proximate factors in adulthood and older age. This has implications for both mechanistic understanding and prevention.

Cognitive-exercise dual-task intervention ameliorates cognitive decline in natural aging rats via inhibiting the promotion of LncRNA NEAT1/miR-124-3p on caveolin-1-PI3K/Akt/GSK3β Pathway

Aging-related cognitive impairment (ARCI) is rapidly becoming a healthcare priority. However, there is currently no excellent cure for it. Cognitive-exercise dual-task intervention (CEDI) is a promising method to improve ARCI, while the underlying mechanisms remain unclear. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are involved in the onset, development, and rehabilitation of ARCI. This study aimed to investigate the effects of CEDI and the role of regulation of the lncRNA NEAT1/miR-124-3p on the caveolin-1-PI3K/Akt/GSK3β pathway in CEDI improving cognitive function. Forty 18-month-old natural aging rats were randomly assigned to four groups: exercise training group, cognitive training group, CEDI group, and aging control group, and underwent 12 weeks of intervention. A novel object recognition test was performed to determine the cognitive function, and the hippocampus was separated three days after the behavioral tests for further molecular detection. In an in vitro study, the mouse hippocampal neuronal cell line HT22 was cultured. MiR-124-3p and lncRNA NEAT1 were over-expressed or down-expressed, respectively. The expressions of related proteins, lncRNA, and miRNA were examined by WB and/or qRT-PCR. The results showed that compared with the aging control group, the CEDI group had a higher discrimination index, and significantly decreased the expressions of lncRNA NEAT1, and the protein expressions of caveolin-1 and p-GSK3β, while significantly increased the expressions of miR-124-3p, and the protein expressions of p-PI3K and p-Akt. Inhibition of the lncRNA NEAT1 could significantly increase the protein expressions of p-PI3K and p-Akt in HT22 cells. Upregulation of miR-124-3p decreased the protein expressions of caveolin-1 and p-GSK3β, and increased the protein expressions of p-PI3K and p-Akt significantly. Inhibition of miR-124-3p had the opposite effects. Our study demonstrated that CEDI improved cognitive function in aging rats better than a single intervention. The mechanisms of cognitive improvement could be related to the regulation of the lncRNA NEAT1/miR-124-3p on the caveolin-1-PI3K/Akt/GSK3β pathway.

Rolipram Ameliorates Memory Deficits and Depression-Like Behavior in APP/PS1/tau Triple Transgenic Mice: Involvement of Neuroinflammation and Apoptosis via cAMP Signaling

BACKGROUND

Alzheimer disease (AD) and depression often cooccur, and inhibition of phosphodiesterase-4 (PDE4) has been shown to ameliorate neurodegenerative illness. Therefore, we explored whether PDE4 inhibitor rolipram might also improve the symptoms of comorbid AD and depression.

METHODS

APP/PS1/tau mice (10 months old) were treated with or without daily i.p. injections of rolipram for 10 days. The animal groups were compared in behavioral tests related to learning, memory, anxiety, and depression. Neurochemical measures were conducted to explore the underlying mechanism of rolipram.

RESULTS

Rolipram attenuated cognitive decline as well as anxiety- and depression-like behaviors. These benefits were attributed at least partly to the downregulation of amyloid-β, Amyloid precursor protein (APP), and Presenilin 1 (PS1); lower tau phosphorylation; greater neuronal survival; and normalized glial cell function following rolipram treatment. In addition, rolipram upregulated B-cell lymphoma-2 (Bcl-2) and downregulated Bcl-2-associated X protein (Bax) to reduce apoptosis; it also downregulated interleukin-1β, interleukin-6, and tumor necrosis factor-α to restrain neuroinflammation. Furthermore, rolipram increased cAMP, PKA, 26S proteasome, EPAC2, and phosphorylation of ERK1/2 while decreasing EPAC1.

CONCLUSIONS

Rolipram may mitigate cognitive deficits and depression-like behavior by reducing amyloid-β pathology, tau phosphorylation, neuroinflammation, and apoptosis. These effects may be mediated by stimulating cAMP/PKA/26S and cAMP/exchange protein directly activated by cAMP (EPAC)/ERK signaling pathways. This study suggests that PDE4 inhibitor rolipram can be an effective target for treatment of comorbid AD and depression.

Disentangling accelerated cognitive decline from the normal aging process and unraveling its genetic components: A neuroimaging-based deep learning approach

Background

The progressive cognitive decline that is an integral component of AD unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and Alzheimer's disease between different chronological points.

Methods

We developed a deep-learning framework based on dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline.

Results

We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G>T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neuron and plays a role in controlling cell growth and differentiation. In addition, MUC7 and PROL1/OPRPNon chromosome 4 were significant at the gene level. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Furthermore, we found that the cognitive decline slope GWAS was positively correlated with previous AD GWAS.

Conclusion

Our deep learning model was demonstrated effective on extracting relevant neuroimaging features and predicting individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene. Our approach has the potential to disentangle accelerated cognitive decline from the normal aging process and to determine its related genetic factors, leveraging opportunities for early intervention.

Polysaccharides from sea buckthorn (Hippophae rhamnoides L.) berries ameliorate cognitive dysfunction in AD mice induced by a combination of d-gal and AlCl3 by suppressing oxidative stress and inflammation reaction

BACKGROUND

The therapeutic properties of Hippophae rhamnoides L. were known in Ancient Greece and in Tibetan and Mongolian medicine, which commonly used it for the treatment of heart ailments, rheumatism, and brain disorders. Modern studies have indicated that Hippophae rhamnoides L. polysaccharide (HRP) can improve cognitive impairment in mice with Alzheimer's disease (AD) but the specific mechanisms of the protective effect of HRP have not been elucidated fully.

RESULTS

Our results showed that Hippophae rhamnoides L. polysaccharide I (HRPI) improved pathological behaviors related to memory and cognition, and reduced 1 Beta-amyloid (Aβ) peptide deposition and neuronal cell necrosis. Pretreatment with Hippophae rhamnoides L. polysaccharide I (HRPI) also decreased the level of Toll-like receptor 4 (TLR4) and Myeloid differentiation factor 88 (MyD88), and reduced the release of inflammatory factors Tumor necrosis factor alpha (TNFα) and interleukin 6 (IL-6) in the brains of mice with AD. Treatment with HRPI also suppressed the expression level of Recombinant Kelch Like ECH Associated Protein 1 (KEAP1), and increased the levels of Nuclear factor erythroid 2-Related Factor 2 (Nrf2), antioxidant enzymes Superoxide dismutase (SOD) and Glutathione peroxidase (GSH-Px) in the brains of AD mice.

CONCLUSIONS

On the whole, these findings revealed that HRPI could improve the learning and memory ability and attenuate pathologic impairment in AD mice, and the underlying mechanisms may involve mediating oxidative stress and inflammation, possibly through the regulation of the Keap1/Nrf2 and TLR4/MyD88 signaling pathways. © 2023 Society of Chemical Industry.

Neuroimaging-Derived Predicted Brain Age and Alcohol Use Among Community-Dwelling Older Adults

OBJECTIVES

Observational studies have suggested that moderate alcohol use is associated with reduced risk of dementia. However, the nature of this association is not understood. We investigated whether light to moderate alcohol use may be associated with slower brain aging, among a cohort of older community-dwelling adults using a biomarker of brain age based on structural neuroimaging measures.

DESIGN

Cross-sectional observational study.

PARTICIPANTS

Well-characterized members of a longitudinal cohort study who underwent neuroimaging. We categorized the 163 participants (mean age 76.7 ± 7.7, 60% women) into current nondrinkers, light drinkers (1-7 drinks/week) moderate drinkers (>7-14 drinks/week), or heavier drinkers (>14 drinks/week).

MEASUREMENTS

We calculated brain-predicted age using structural MRIs processed with the BrainAgeR program, and calculated the difference between brain-predicted age and chronological age (brain-predicted age difference, or brain-PAD). We used analysis of variance to determine if brain-PAD differed across alcohol groups, controlling for potential confounders.

RESULTS

Brain-PAD differed across alcohol groups (F[3, 150] = 4.02; p = 0.009) with heavier drinkers showing older brain-PAD than light drinkers (by about 6 years). Brain-PAD did not differ across light, moderate, and nondrinkers. Similar results were obtained after adjusting for potentially mediating health-related measures, and after excluding individuals with a history of heavier drinking.

DISCUSSION

Among this sample of healthy older adults, consumption of more than 14 drinks/week was associated with a biomarker of advanced brain aging. Light and moderate drinking was not associated with slower brain aging relative to non-drinking.

Neurofilaments - Small proteins of physiological significance and predictive power for future neurodegeneration and cognitive decline across the life span

Neurofilaments (NFs) are not only important for axonal integrity and nerve conduction in large myelinated axons but they are also thought to be crucial for receptor and synaptic functioning. Therefore, NFs may play a critical role in cognitive functions, as cognitive processes are known to depend on synaptic integrity and are modulated by dopaminergic signaling. Here, we present a theory-driven interdisciplinary approach that NFs may link inflammation, neurodegeneration, and cognitive functions. We base our hypothesis on a wealth of evidence suggesting a causal link between inflammation and neurodegeneration and between these two and cognitive decline (see Fig. 1), also taking dopaminergic signaling into account. We conclude that NFs may not only serve as biomarkers for inflammatory, neurodegenerative, and cognitive processes but also represent a potential mechanical hinge between them, moreover, they may even have predictive power regarding future cognitive decline. In addition, we advocate the use of both NFs and MRI parameters, as their synthesis offers the opportunity to individualize medical treatment by providing a comprehensive view of underlying disease activity in neurological diseases. Since our society will become significantly older in the upcoming years and decades, maintaining cognitive functions and healthy aging will play an important role. Thanks to technological advances in recent decades, NFs could serve as a rapid, noninvasive, and relatively inexpensive early warning system to identify individuals at increased risk for cognitive decline and could facilitate the management of cognitive dysfunctions across the lifespan.

Executive function and episodic memory composite scores in older adults: relations with sex, mood, and subjective sleep quality

Executive function and episodic memory processes are particularly vulnerable to aging. We sought to learn the degree to which sex, mood, and subjective sleep quality might be related to executive function and episodic memory composite scores in community-dwelling older adults. We replicated Glisky and colleagues' two-factor (i.e., executive function [N=263] versus episodic memory [N=151]) structure, and found that it did not significantly differ between males and females. Moderation analyses revealed no interactions between sex, mood, and sleep in predicting either composite score. However, females significantly outperformed males on the episodic memory composite, and on all the individual tests comprising it. Ours is the first study to look at sex differences in this battery's factor structure and its potential relations with mood and sleep. Future longitudinal studies in both healthy and clinical populations will help us further probe the possible influence of these variables on executive function and episodic memory in aging.

Investigating the effects of the aging brain on real tool use performance-an fMRI study

Introduction

Healthy aging affects several domains of cognitive and motor performance and is further associated with multiple structural and functional neural reorganization patterns. However, gap of knowledge exists, referring to the impact of these age-related alterations on the neural basis of tool use-an important, complex action involved in everyday life throughout the entire lifespan. The current fMRI study aims to investigate age-related changes of neural correlates involved in planning and executing a complex object manipulation task, further providing a better understanding of impaired tool use performance in apraxia patients.

Methods

A balanced number of sixteen older and younger healthy adults repeatedly manipulated everyday tools in an event-related Go-No-Go fMRI paradigm.

Results

Our data indicates that the left-lateralized network, including widely distributed frontal, temporal, parietal and occipital regions, involved in tool use performance is not subjected to age-related functional reorganization processes. However, age-related changes regarding the applied strategical procedure can be detected, indicating stronger investment into the planning, preparatory phase of such an action in older participants.

Age-, sex-, and pathology-related variability in brain structure and cognition

This work aimed to investigate potential pathways linking age and imaging measures to early age- and pathology-related changes in cognition. We used [18F]-Flutemetamol (amyloid) and [18F]-Flortaucipir (tau) positron emission tomography (PET), structural MRI, and neuropsychological assessment from 232 elderly individuals aged 50-89 years (46.1% women, 23% APOE-ε4 carrier, 23.3% MCI). Tau-PET was available for a subsample of 93 individuals. Structural equation models were used to evaluate cross-sectional pathways between age, amyloid and tau burden, grey matter thickness and volumes, white matter hyperintensity volume, lateral ventricle volume, and cognition. Our results show that age is associated with worse outcomes in most of the measures examined and had similar negative effects on episodic memory and executive functions. While increased lateral ventricle volume was consistently associated with executive function dysfunction, participants with mild cognitive impairment drove associations between structural measures and episodic memory. Both age and amyloid-PET could be associated with medial temporal lobe tau, depending on whether we used a continuous or a dichotomous amyloid variable. Tau burden in entorhinal cortex was related to worse episodic memory in individuals with increased amyloid burden (Centiloid >12) independently of medial temporal lobe atrophy. Testing models for sex differences revealed that amyloid burden was more strongly associated with regional atrophy in women compared with men. These associations were likely mediated by higher tau burden in women. These results indicate that influences of pathological pathways on cognition and sex-specific vulnerabilities are dissociable already in early stages of neuropathology and cognitive impairment.