Ageing Research Reviews最新文献

The human brain stands as an intricate organ, embodying a nexus of structure, function, development, and diversity. This review delves into the multifaceted landscape of the brain, spanning its anatomical intricacies, diverse functional capacities, dynamic developmental trajectories, and inherent variability across individuals. The dynamic process of brain development, from early embryonic stages to adulthood, highlights the nuanced changes that occur throughout the lifespan. The brain, a remarkably complex organ, is composed of various anatomical regions, each contributing uniquely to its overall functionality. Through an exploration of neuroanatomy, neurophysiology, and electrophysiology, this review elucidates how different brain structures interact to support a wide array of cognitive processes, sensory perception, motor control, and emotional regulation. Moreover, it addresses the impact of age, sex, and ethnic background on brain structure and function, and gender differences profoundly influence the onset, progression, and manifestation of brain disorders shaped by genetic, hormonal, environmental, and social factors. Delving into the complexities of the human brain, it investigates how variations in anatomical configuration correspond to diverse functional capacities across individuals. Furthermore, it examines the impact of neurodegenerative diseases on the structural and functional integrity of the brain. Specifically, our article explores the pathological processes underlying neurodegenerative diseases, such as Alzheimer's, Parkinson's, and Huntington's diseases, shedding light on the structural alterations and functional impairments that accompany these conditions. We will also explore the current research trends in neurodegenerative diseases and identify the existing gaps in the literature. Overall, this article deepens our understanding of the fundamental principles governing brain structure and function and paves the way for a deeper understanding of individual differences and tailored approaches in neuroscience and clinical practice—additionally, a comprehensive understanding of structural and functional changes that manifest in neurodegenerative diseases.

We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.

Introduction

Emerging and advanced technologies in the field of Artificial Intelligence (AI) represent promising methods to predict and diagnose neurodegenerative diseases, such as dementia. By using multimodal approaches, Machine Learning (ML) seems to provide a better understanding of the pathological mechanisms underlying the onset of dementia. The purpose of this review was to discuss the current ML application in the field of neuropsychology and electrophysiology, exploring its results in both prediction and diagnosis for different forms of dementia, such as Alzheimer’s disease (AD), Vascular Dementia (VaD), Dementia with Lewy bodies (DLB), and Frontotemporal Dementia (FTD).

Methods

Main ML-based papers focusing on neuropsychological assessments and electroencephalogram (EEG) studies were analyzed for each type of dementia.

Results

An accuracy ranging between 70 % and 90 % or even more was observed in all neurophysiological and electrophysiological results trained by ML. Among all forms of dementia, the most significant findings were observed for AD. Relevant results were mostly related to diagnosis rather than prediction, because of the lack of longitudinal studies with appropriate follow-up duration. However, it remains unclear which ML algorithm performs better in diagnosing or predicting dementia.

Conclusions

Neuropsychological and electrophysiological measurements, together with ML analysis, may be considered as reliable instruments for early detection of dementia.

Alzheimer's disease (AD) and Diabetes mellitus (DM) exhibit comparable pathophysiological pathways. Genetic abnormalities in APP, PS-1, and PS-2 are linked to AD, with diagnostic aid from CSF and blood biomarkers. Insulin dysfunction, termed "type 3 diabetes mellitus" in AD, involves altered insulin signalling and neuronal shrinkage. Insulin influences beta-amyloid metabolism, exacerbating neurotoxicity in AD and amyloid production in DM. Both disorders display impaired glucose transporter expression, hastening cognitive decline. Mitochondrial dysfunction and Toll-like receptor 4-mediated inflammation worsen neurodegeneration in both diseases. ApoE4 raises disease risk, especially when coupled with dyslipidemia common in DM. Targeting shared pathways like insulin-degrading enzyme activation and HSP60 holds promise for therapeutic intervention. Recognizing these interconnected mechanisms underscores the imperative for developing tailored treatments addressing the overlapping pathophysiology of AD and DM, offering potential avenues for more effective management of both conditions.

Alzheimer's disease (AD) is a fatal neurodegenerative disease in which senile plaques and neurofibrillary tangles are crucially involved in its physiological and pathophysiological processes. Growing animal and clinical studies have suggested that AD is also comorbid with some metabolic diseases, including type 2 diabetes mellitus (T2DM), and therefore, it is often considered brain diabetes. AD and T2DM share multiple molecular and biochemical mechanisms, including impaired insulin signaling, oxidative stress, gut microbiota dysbiosis, and mitochondrial dysfunction. In this review article, we mainly introduce oxidative stress and mitochondrial dysfunction and explain their role and the underlying molecular mechanism in T2DM and AD pathogenesis; then, according to the current literature, we comprehensively evaluate the possibility of regulating oxidative homeostasis and mitochondrial function as therapeutics against AD. Furthermore, considering dietary polyphenols' antioxidative and antidiabetic properties, the strategies for applying them as potential therapeutical interventions in patients with AD symptoms are assessed.

Urolithin A (UA) is a gut metabolite derived from ellagic acid. This systematic review assesses the potential geroprotective effect of UA in humans. In five studies including 250 healthy individuals, UA (10–1000 mg/day) for a duration ranging from 28 days to 4 months, showed a dose-dependent anti-inflammatory effect and upregulated some mitochondrial genes, markers of autophagy, and fatty acid oxidation. It did not affect mitochondrial maximal adenosine triphosphate production, biogenesis, dynamics, or gut microbiota composition. UA increased muscle strength and endurance, however, had no effect on anthropometrics, cardiovascular outcomes, and physical function. Unrelated adverse events were mild or moderate. Further research across more physiological systems and longer intervention periods is required.

As we age, maintaining good oral health becomes increasingly crucial for performing daily tasks. Age-related physiological decline can disrupt various biological systems, causing a significant challenge for geriatric dentistry. A systematic review of the literature using six different electronic databases was conducted to investigate the relationship between oral health indicators and bone mineral density disorders in older adults. The study is registered as a priori protocol on PROSPERO (CRD42023403340). A minimum age of 60 years was the main inclusion criterion for all original research articles. Two independent researchers assessed the eligibility of 19,362 records against the inclusion criteria and found 12 articles fitting the eligibility requirements. Five different indicators of poor oral health [number of teeth, periodontal disease, general oral health (dental caries prevalence and dental treatment needs), masticatory function, and occlusal force)] were found related to three outcomes linked to bone mineral density disorders (osteoporosis, fractures, and decreased bone mineral density), regardless of the adopted assessment tools. The number of teeth was negatively associated with fractures and a decreased bone mineral density, while periodontal disease was positively associated with osteoporosis and a decreased bone mineral density. Masticatory function was associated only with osteoporosis, while general oral health was associated only with fractures and occlusal force only with bone mineral density. The oral health indicator most frequently associated with outcomes linked to bone mineral density disorders was the number of teeth. The present findings could help to assess the contribution of each oral health indicator to the development of bone mineral density disorders in older age.

Recently, the incidence of heat-related illnesses has exhibited a steadily upward trend, which is closely associated with several environmental factors such as climate change and air pollution. The progression of heat-related illnesses is a continuous process and can progress to the terminal period when it transforms into heat stroke, the most severe form. Heat stroke is markedly by a core body temperature above 40°C and central nervous system dysfunction. Current knowledge suggests that the pathogenesis of heat stroke is complex and varied, including inflammatory response, oxidative stress, cell death, and coagulation dysfunction. This review consolidated recent research progress on the pathophysiology and pathogenesis of heat stroke, with a focus on the related molecular mechanisms. In addition, we reviewed common strategies and sorted out the drugs in various preclinical stages for heat stroke, aiming to offer a comprehensive research roadmap for more in-depth researches into the mechanisms of heat stroke and the reduction in the mortality of heat stroke in the future.

Alzheimer's Disease (AD) is a challenging neurodegenerative condition, with overwhelming implications for affected individuals and healthcare systems worldwide. Animal models have played a crucial role in studying AD pathogenesis and testing therapeutic interventions. Remarkably, studies on the genetic factors affecting AD risk, such as APOE and TREM2, have provided valuable insights into disease mechanisms. Early diagnosis has emerged as a crucial factor in effective AD management, as demonstrated by clinical studies emphasizing the benefits of initiating treatment at early stages. Novel diagnostic technologies, including RNA sequencing of microglia, offer promising avenues for early detection and monitoring of AD progression. Therapeutic strategies remain to evolve, with a focus on targeting amyloid beta (Aβ) and tau pathology. Advances in animal models, such as APP-KI mice, and the advancement of anti-Aβ drugs signify progress towards more effective treatments. Therapeutically, the focus has shifted towards intricate approaches targeting multiple pathological pathways simultaneously. Strategies aimed at reducing Aβ plaque accumulation, inhibiting tau hyperphosphorylation, and modulating neuroinflammation are actively being explored, both in preclinical models and clinical trials. While challenges continue in developing validated animal models and translating preclinical findings to clinical success, the continuing efforts in understanding AD at molecular, cellular, and clinical levels offer hope for improved management and eventual prevention of this devastating disease.

Alzheimer's disease (AD) is a leading cause of cognitive impairment worldwide. Overweight and obesity are strongly associated with comorbidities, such as hypertension, diabetes, and insulin resistance (IR), which contribute substantially to the development of AD and subsequent morbidity and mortality. Adipose tissue (AT) is a highly dynamic organ composed of a diverse array of cell types, which can be classified based on their anatomic localization or cellular composition. The expansion and remodeling of AT in the context of obesity involves immunometabolic and functional shifts steered by the intertwined actions of multiple immune cells and cytokine signaling within AT, which contribute to the development of metabolic disorders, IR, and systemic markers of chronic low-grade inflammation. Chronic low-grade inflammation, a prolonged, low-dose stimulation by specific immunogens that can progress from localized sites and affect multiple organs throughout the body, leads to neurodystrophy, increased apoptosis, and disruption of homeostasis, manifesting as brain atrophy and AD-related pathology. In this review, we sought to elucidate the mechanisms by which AT contributes to the onset and progression of AD in obesity through the mediation of chronic low-grade inflammation, particularly focusing on the roles of adipokines and AT-resident immune cells.