Luteolin Mitigates D-Galactose-Induced Brain Ageing in Rats: SIRT1-Mediated Neuroprotection.

Luteolin is an essential natural polyphenol found in a variety of plants. Numerous studies have supported its protective role in neurodegenerative diseases, yet the research for its therapeutic utility in D-galactose (D-gal)-induced brain ageing is still lacking. In this study, the potential neuroprotective impact of luteolin against D-gal-induced brain ageing was explored. Forty rats were randomly divided into four groups: control, luteolin, D-gal, and luteolin-administered D-gal groups. All groups were subjected to behavioural, cholinergic function, and hippocampal mitochondrial respiration assessments. Hippocampal oxidative, neuro-inflammatory, senescence and apoptotic indicators were detected. Gene expressions of SIRT1, BDNF, and RAGE were assessed. Hippocampal histopathological studies, along with GFAP and Ki67 immunoreactivity, were performed. Our results demonstrated that luteolin effectively alleviated D-gal-induced cognitive impairment and reversed cholinergic abnormalities. Furthermore, luteolin administration substantially mitigated hippocampus oxidative stress, mitochondrial dysfunction, neuro-inflammation, and senescence triggered by D-gal. Additionally, luteolin treatment considerably attenuated neuronal apoptosis and upregulated hippocampal SIRT1 mRNA expression. In conclusion, our findings revealed that luteolin administration attenuated D-gal-evoked brain senescence, improving mitochondrial function and enhancing hippocampal neuroregeneration in an ageing rat model through its antioxidant, senolytic, anti-inflammatory, and anti-apoptotic impacts, possibly due to upregulation of SIRT1. Luteolin could be a promising therapeutic modality for brain aging-associated abnormalities.

The association between cannabis use and neuroimaging measures in older adults: findings from the UK biobank.

BACKGROUND: Cannabis use has increased in recent years. However, the long-term implications of cannabis use on brain health remain unknown. We explored the associations of cannabis use with volumetric brain magnetic resonance imaging (MRI) measures in dementia-free older adults. METHODS: This cross-sectional and longitudinal study included dementia-free participants of the UK Biobank aged ≥60 years. Linear regression models were used to evaluate the association of cannabis use and patterns of use with volumetric brain MRI measures. The association between cannabis use and change in brain MRI measures over time was also tested. All models were adjusted for potential confounders. RESULTS: The sample included 19,932 participants (mean age 68 ± 5 years, 48% men), 3,800 (19%) reported lifetime use of cannabis. Cannabis use was associated with smaller total, white, grey and peripheral cortical grey matter volumes (B = -6,690 ± 1,157; P < 0.001, B = -4,396 ± 766; P < 0.001, B = -2,140 ± 690; P = 0.002 and B = -2,451 ± 606; P < 0.001, respectively). Among cannabis users, longer duration of use was associated with smaller total brain, grey and cortical grey matter volumes (B = -7,878 ± 2,396; P = 0.001, B = -5,411 ± 1,430; P < 0.001, B = -5,396 ± 1,254; P < 0.001, respectively), and with increased white matter hyperintensity volume (B = 0.09 ± 0.03; P = 0.008). Additionally, current vs. former users (B = -10,432 ± 4,395; P = 0.020) and frequent versus non-frequent users (B = -2,274 ± 1,125; P = 0.043) had smaller grey and cortical grey matter volumes, respectively. No significant associations were observed between cannabis use and change in brain MRI measures. DISCUSSION: Our findings suggest that cannabis use, particularly longer duration and frequent use, may be related to smaller grey and white matter volumes in older ages, but not to late-life changes in these measures over time.

The association between adherence to the EAT-Lancet diet and cognitive ageing.

BACKGROUND: The EAT-Lancet commission has proposed a dietary pattern that is both sustainable and healthy. However, the impact of this diet on cognition in older adults remains unexplored. Therefore, we examined the association between adherence to the EAT-Lancet diet and cognitive ageing. METHODS: We used data from a previous intervention study involving cognitively healthy community-dwelling adults aged ≥65 years. Adherence to the EAT-Lancet diet was calculated using a recently published index and a 190-item food frequency questionnaire. Global and domain-specific cognitive functioning were assessed at baseline and after 2 years using a neuropsychological test battery. Multivariate-adjusted linear regression was conducted to examine associations between EAT-Lancet diet adherence and cognitive functioning (n = 630) and 2-year change (n = 302). RESULTS: Greater adherence to the EAT-Lancet diet was associated with better global cognitive functioning (ß per SD = 3.7 points [95% CI]: 0.04 [0.00, 0.08]) and slower rate of decline (ß per SD [95% CI]: 0.05 [0.02, 0.08]). With respect to domain-specific functioning, beneficial associations were observed cross-sectionally for executive functioning (P < 0.01), and longitudinally for change in executive functioning (P < 0.01) and attention and working memory (P < 0.01). The degree of adherence to the EAT-Lancet was not associated with (changes in) information processing speed or episodic memory. CONCLUSION: We demonstrated that greater adherence to the EAT-Lancet diet is associated with better global cognitive functioning and slower cognitive decline among cognitively healthy older adults. Further research is needed to confirm these findings and assess the potential benefits of the EAT-Lancet diet for the ageing population in a broader context.

Pattern of heterogeneity in normal brain ageing: screening for mild cognitive impairment and its risk of progression with a radiomics model.

PURPOSE: This study aimed to develop a normal brain ageing model based on magnetic resonance imaging and radiomics, therefore identifying radscore, an imaging indicator representing white matter heterogeneity and exploring the significance of radscore in detecting people's cognitive changes. METHODS: Three hundred sixty cognitively normal (CN) subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and 105 CN subjects from the Parkinson's Progression Markers Initiative database were used to develop the model. In ADNI, 230 mild cognitive impairment (MCI) subjects were matched with 230 CN old-aged subjects to evaluate their heterogeneity difference. One hundred four MCI subjects with 48 months of follow-up were divided into low and high heterogeneity groups. Kaplan-Meier survival curve analysis was used to observe the importance of heterogeneity results for predicting MCI progression. RESULTS: The area under the receiver operating characteristic curve of the model in the training, internal test and external test sets was 0.7503, 0.7512 and 0.7514, respectively. There was a significantly positive correlation between age and radscore of CN subjects (r = 0.501; P < .001). The radscore of MCI subjects was significantly higher than that of matched CN subjects (P < .001). The median radscore ratios of MCI to CN from four age groups (66-70y, 71-75y, 76-80y and 81-85y) were 1.611, 1.760, 1.340 and 1.266, respectively. The probability to progression of low and high heterogeneity groups had a significant difference (P = .002). CONCLUSION: When radscore is significantly higher than that of normal ageing, it is necessary to alert the possibility of cognitive impairment and deterioration.

Normative models for neuroimaging markers: Impact of model selection, sample size and evaluation criteria.

Modelling population reference curves or normative modelling is increasingly used with the advent of large neuroimaging studies. In this paper we assess the performance of fitting methods from the perspective of clinical applications and investigate the influence of the sample size. Further, we evaluate linear and non-linear models for percentile curve estimation and highlight how the bias-variance trade-off manifests in typical neuroimaging data. We created plausible ground truth distributions of hippocampal volumes in the age range of 45 to 80 years, as an example application. Based on these distributions we repeatedly simulated samples for sizes between 50 and 50,000 data points, and for each simulated sample we fitted a range of normative models. We compared the fitted models and their variability across repetitions to the ground truth, with specific focus on the outer percentiles (1st, 5th, 10th) as these are the most clinically relevant. Our results quantify the expected decreasing trend in variance of the volume estimates with increasing sample size. However, bias in the volume estimates only decreases a modest amount, without much improvement at large sample sizes. The uncertainty of model performance is substantial for what would often be considered large samples in a neuroimaging context and rises dramatically at the ends of the age range, where fewer data points exist. Flexible models perform better across sample sizes, especially for non-linear ground truth. Surprisingly large samples of several thousand data points are needed to accurately capture outlying percentiles across the age range for applications in research and clinical settings. Performance evaluation methods should assess both bias and variance. Furthermore, caution is needed when attempting to go near the ends of the age range captured by the source data set and, as is a well known general principle, extrapolation beyond the age range should always be avoided. To help with such evaluations of normative models we have made our code available to guide researchers developing or utilising normative models.

The benefits of grape seed extract in neurological disorders and brain aging.

Common neurological disorders, including neurodegenerative diseases, stroke, epilepsy, autism and psychiatric disorders, affect many people worldwide and threaten their lives and health by inducing movement disorders, behavioral disorders, or a combination of both. Oxidative stress and neuroinflammation play a central role in neuronal damage and neurological diseases induction and progression. In addition, protein homeostasis (proteostasis) impairment occurs in many neurodegenerative diseases, which plays a critical role in the progression of the pathology. Grape seed contains several flavonoids and non-flavonoids and exerts potent antioxidant and anti-inflammatory effects. In addition, polyphenols and flavanols can maintain cellular proteostasis. Since impaired proteostasis is closely involved in all amyloid diseases, particularly neurodegenerative diseases, grape seeds extract can be a valuable therapeutic agent. Therefore, this review discusses the protective and therapeutic mechanisms of grape seed against neurological disorders and, in the end, links GSE to microRNAs as future therapeutic developments.

Neuronal Prosurvival Role of Ceramide Synthase 2 by Olidogendrocyte-to-Neuron Extracellular Vesicle Transfer.

Ageing is associated with notorious alterations in neurons, i.e., in gene expression, mitochondrial function, membrane degradation or intercellular communication. However, neurons live for the entire lifespan of the individual. One of the reasons why neurons remain functional in elderly people is survival mechanisms prevail over death mechanisms. While many signals are either pro-survival or pro-death, others can play both roles. Extracellular vesicles (EVs) can signal both pro-toxicity and survival. We used young and old animals, primary neuronal and oligodendrocyte cultures and neuroblastoma and oligodendrocytic lines. We analysed our samples using a combination of proteomics and artificial neural networks, biochemistry and immunofluorescence approaches. We found an age-dependent increase in ceramide synthase 2 (CerS2) in cortical EVs, expressed by oligodendrocytes. In addition, we show that CerS2 is present in neurons via the uptake of oligodendrocyte-derived EVs. Finally, we show that age-associated inflammation and metabolic stress favour CerS2 expression and that oligodendrocyte-derived EVs loaded with CerS2 lead to the expression of the antiapoptotic factor Bcl2 in inflammatory conditions. Our study shows that intercellular communication is altered in the ageing brain, which favours neuronal survival through the transfer of oligodendrocyte-derived EVs containing CerS2.

Associations between alcohol use and accelerated biological ageing.

Harmful alcohol use is a leading cause of premature death and is associated with age-related disease. Biological ageing is highly variable between individuals and may deviate from chronological ageing, suggesting that biomarkers of biological ageing (derived from DNA methylation or brain structural measures) may be clinically relevant. Here, we investigated the relationships between alcohol phenotypes and both brain and DNA methylation age estimates. First, using data from UK Biobank and Generation Scotland, we tested the association between alcohol consumption (units/week) or hazardous use (Alcohol Use Disorders Identification Test [AUDIT] scores) and accelerated brain and epigenetic ageing in 20,258 and 8051 individuals, respectively. Second, we used Mendelian randomisation (MR) to test for a causal effect of alcohol consumption levels and alcohol use disorder (AUD) on biological ageing. Alcohol use showed a consistent positive association with higher predicted brain age (AUDIT-C: ß = 0.053, p = 3.16 × 10-13 ; AUDIT-P: ß = 0.052, p = 1.6 × 10-13 ; total AUDIT score: ß = 0.062, p = 5.52 × 10-16 ; units/week: ß = 0.078, p = 2.20 × 10-16 ), and two DNA methylation-based estimates of ageing, GrimAge (units/week: ß = 0.053, p = 1.48 × 10-7 ) and PhenoAge (units/week: ß = 0.077, p = 2.18x10-10 ). MR analyses revealed limited evidence for a causal effect of AUD on accelerated brain ageing (ß = 0.118, p = 0.044). However, this result should be interpreted cautiously as the significant effect was driven by a single genetic variant. We found no evidence for a causal effect of alcohol consumption levels on accelerated biological ageing. Future studies investigating the mechanisms associating alcohol use with accelerated biological ageing are warranted.

Factors associated with brain ageing - a systematic review.

BACKGROUND: Brain age is a biomarker that predicts chronological age using neuroimaging features. Deviations of this predicted age from chronological age is considered a sign of age-related brain changes, or commonly referred to as brain ageing. The aim of this systematic review is to identify and synthesize the evidence for an association between lifestyle, health factors and diseases in adult populations, with brain ageing. METHODS: This systematic review was undertaken in accordance with the PRISMA guidelines. A systematic search of Embase and Medline was conducted to identify relevant articles using search terms relating to the prediction of age from neuroimaging data or brain ageing. The tables of two recent review papers on brain ageing were also examined to identify additional articles. Studies were limited to adult humans (aged 18 years and above), from clinical or general populations. Exposures and study design of all types were also considered eligible. RESULTS: A systematic search identified 52 studies, which examined brain ageing in clinical and community dwelling adults (mean age between 21 to 78 years, ~ 37% were female). Most research came from studies of individuals diagnosed with schizophrenia or Alzheimer's disease, or healthy populations that were assessed cognitively. From these studies, psychiatric and neurologic diseases were most commonly associated with accelerated brain ageing, though not all studies drew the same conclusions. Evidence for all other exposures is nascent, and relatively inconsistent. Heterogenous methodologies, or methods of outcome ascertainment, were partly accountable. CONCLUSION: This systematic review summarised the current evidence for an association between genetic, lifestyle, health, or diseases and brain ageing. Overall there is good evidence to suggest schizophrenia and Alzheimer's disease are associated with accelerated brain ageing. Evidence for all other exposures was mixed or limited. This was mostly due to a lack of independent replication, and inconsistency across studies that were primarily cross sectional in nature. Future research efforts should focus on replicating current findings, using prospective datasets. TRIAL REGISTRATION: A copy of the review protocol can be accessed through PROSPERO, registration number CRD42020142817 .

A venous mechanism of ventriculomegaly shared between traumatic brain injury and normal ageing.

Recently, age-related timing dissociation between the superficial and deep venous systems has been observed; this was particularly pronounced in patients with normal pressure hydrocephalus, suggesting a common mechanism of ventriculomegaly. Establishing the relationship between venous drainage and ventricular enlargement would be clinically relevant and could provide insight into the mechanisms underlying brain ageing. To investigate a possible link between venous drainage and ventriculomegaly in both normal ageing and pathological conditions, we compared 225 healthy subjects (137 males and 88 females) and 71 traumatic brain injury patients of varying ages (53 males and 18 females) using MRI-based volumetry and a novel perfusion-timing analysis. Volumetry, focusing on the CSF space, revealed that the sulcal space and ventricular size presented different lifespan profiles with age; the latter presented a quadratic, rather than linear, pattern of increase. The venous timing shift slightly preceded this change, supporting a role for venous drainage in ventriculomegaly. In traumatic brain injury, a small but significant disease effect, similar to idiopathic normal pressure hydrocephalus, was found in venous timing, but it tended to decrease with age at injury, suggesting an overlapping mechanism with normal ageing. Structural bias due to, or a direct causative role of ventriculomegaly was unlikely to play a dominant role, because of the low correlation between venous timing and ventricular size after adjustment for age in both patients and controls. Since post-traumatic hydrocephalus can be asymptomatic and occasionally overlooked, the observation suggested a link between venous drainage and CSF accumulation. Thus, hydrocephalus, involving venous insufficiency, may be a part of normal ageing, can be detected non-invasively, and is potentially treatable. Further investigation into the clinical application of this new marker of venous function is therefore warranted.

[A review on brain age prediction in brain ageing].

The human brain deteriorates as we age, and the rate and the trajectories of these changes significantly vary among brain regions and among individuals. Because neuroimaging data are potentially important indicators of individual's brain health, they are commonly used in brain age prediction. In this review, we summarize brain age prediction model from neuroimaging-based studies in the last ten years. The studies are categorized based on their image modalities and feature types. The results indicate that the prediction frameworks based on neuroimaging holds promise toward individualized brain age prediction. Finally, we addressed the challenges in brain age prediction and suggested some future research directions.

Prevalence of transactive response DNA-binding protein 43 (TDP-43) proteinopathy in cognitively normal older adults: systematic review and meta-analysis.

OBJECTIVE: To perform a systematic review and meta-analysis on the prevalence of transactive response DNA-binding protein 43 (TDP-43) proteinopathy in cognitively normal older adults. METHODS: We systematically reviewed and performed a meta-analysis on the prevalence of TDP-43 proteinopathy in older adults with normal cognition, evaluated by the Mini-Mental State Examination or the Clinical Dementia Rating. We estimated the overall prevalence of TDP-43 using random-effect models, and stratified by age, sex, sample size, study quality, antibody used to assess TDP-43 aggregates, analysed brain regions, Braak stage, Consortium to Establish a Registry for Alzheimer's Disease score, hippocampal sclerosis and geographic location. RESULTS: A total of 505 articles were identified in the systematic review, and 7 were included in the meta-analysis with 1196 cognitively normal older adults. We found an overall prevalence of TDP-43 proteinopathy of 24%. Prevalence of TDP-43 proteinopathy varied widely across geographic location (North America: 37%, Asia: 29%, Europe: 14%, and Latin America: 11%). Estimated prevalence of TDP-43 proteinopathy also varied according to study quality (quality score >7: 22% vs. quality score <7: 42%), antibody used to assess TDP-43 proteinopathy (native: 18% vs. hyperphosphorylated: 24%) and presence of hippocampal sclerosis (without 24% vs. with hippocampal sclerosis: 48%). Other stratified analyses by age, sex, analysed brain regions, sample size and severity of AD neuropathology showed similar pooled TDP-43 prevalence. CONCLUSIONS: Different methodology to access TDP-43, and also differences in lifestyle and genetic factors across different populations could explain our results. Standardization of TDP-43 measurement, and future studies about the impact of genetic and lifestyle characteristics on the development of neurodegenerative diseases are needed.

Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker.

Machine learning analysis of neuroimaging data can accurately predict chronological age in healthy people. Deviations from healthy brain ageing have been associated with cognitive impairment and disease. Here we sought to further establish the credentials of 'brain-predicted age' as a biomarker of individual differences in the brain ageing process, using a predictive modelling approach based on deep learning, and specifically convolutional neural networks (CNN), and applied to both pre-processed and raw T1-weighted MRI data. Firstly, we aimed to demonstrate the accuracy of CNN brain-predicted age using a large dataset of healthy adults (N = 2001). Next, we sought to establish the heritability of brain-predicted age using a sample of monozygotic and dizygotic female twins (N = 62). Thirdly, we examined the test-retest and multi-centre reliability of brain-predicted age using two samples (within-scanner N = 20; between-scanner N = 11). CNN brain-predicted ages were generated and compared to a Gaussian Process Regression (GPR) approach, on all datasets. Input data were grey matter (GM) or white matter (WM) volumetric maps generated by Statistical Parametric Mapping (SPM) or raw data. CNN accurately predicted chronological age using GM (correlation between brain-predicted age and chronological age r = 0.96, mean absolute error [MAE] = 4.16 years) and raw (r = 0.94, MAE = 4.65 years) data. This was comparable to GPR brain-predicted age using GM data (r = 0.95, MAE = 4.66 years). Brain-predicted age was a heritable phenotype for all models and input data (h2 ≥ 0.5). Brain-predicted age showed high test-retest reliability (intraclass correlation coefficient [ICC] = 0.90-0.99). Multi-centre reliability was more variable within high ICCs for GM (0.83-0.96) and poor-moderate levels for WM and raw data (0.51-0.77). Brain-predicted age represents an accurate, highly reliable and genetically-influenced phenotype, that has potential to be used as a biomarker of brain ageing. Moreover, age predictions can be accurately generated on raw T1-MRI data, substantially reducing computation time for novel data, bringing the process closer to giving real-time information on brain health in clinical settings.

White matter hyperintensities and imaging patterns of brain ageing in the general population.

White matter hyperintensities are associated with increased risk of dementia and cognitive decline. The current study investigates the relationship between white matter hyperintensities burden and patterns of brain atrophy associated with brain ageing and Alzheimer's disease in a large populatison-based sample (n = 2367) encompassing a wide age range (20-90 years), from the Study of Health in Pomerania. We quantified white matter hyperintensities using automated segmentation and summarized atrophy patterns using machine learning methods resulting in two indices: the SPARE-BA index (capturing age-related brain atrophy), and the SPARE-AD index (previously developed to capture patterns of atrophy found in patients with Alzheimer's disease). A characteristic pattern of age-related accumulation of white matter hyperintensities in both periventricular and deep white matter areas was found. Individuals with high white matter hyperintensities burden showed significantly (P < 0.0001) lower SPARE-BA and higher SPARE-AD values compared to those with low white matter hyperintensities burden, indicating that the former had more patterns of atrophy in brain regions typically affected by ageing and Alzheimer's disease dementia. To investigate a possibly causal role of white matter hyperintensities, structural equation modelling was used to quantify the effect of Framingham cardiovascular disease risk score and white matter hyperintensities burden on SPARE-BA, revealing a statistically significant (P < 0.0001) causal relationship between them. Structural equation modelling showed that the age effect on SPARE-BA was mediated by white matter hyperintensities and cardiovascular risk score each explaining 10.4% and 21.6% of the variance, respectively. The direct age effect explained 70.2% of the SPARE-BA variance. Only white matter hyperintensities significantly mediated the age effect on SPARE-AD explaining 32.8% of the variance. The direct age effect explained 66.0% of the SPARE-AD variance. Multivariable regression showed significant relationship between white matter hyperintensities volume and hypertension (P = 0.001), diabetes mellitus (P = 0.023), smoking (P = 0.002) and education level (P = 0.003). The only significant association with cognitive tests was with the immediate recall of the California verbal and learning memory test. No significant association was present with the APOE genotype. These results support the hypothesis that white matter hyperintensities contribute to patterns of brain atrophy found in beyond-normal brain ageing in the general population. White matter hyperintensities also contribute to brain atrophy patterns in regions related to Alzheimer's disease dementia, in agreement with their known additive role to the likelihood of dementia. Preventive strategies reducing the odds to develop cardiovascular disease and white matter hyperintensities could decrease the incidence or delay the onset of dementia.

Parental longevity is associated with cognition and brain ageing in middle-aged offspring.

BACKGROUND: offspring of long-lived individuals have lower risk for dementia. We examined the relation between parental longevity and cognition and subclinical markers of brain ageing in community-dwelling adult offspring. METHODS: offspring participants with both parents in the Framingham Heart Study, aged ≥55 years and dementia-free underwent baseline and repeat neuropsychological (NP) testing and brain magnetic resonance imaging (MRI). Parental longevity was defined as having at least one parent survive to age ≥85 years. To test the association between parental longevity and measures of cognition and brain volumes, we used multivariable linear and logistic regression adjusting for age, sex, education and time to NP testing or brain MRI. RESULTS: of 728 offspring (mean age 66 years, 54% women), 407 (56%) had ≥1 parent achieve longevity. In cross-sectional analysis, parental longevity was associated with better scores on attention (beta 0.21 ± 0.08, P = 0.006) and a lower odds of extensive white matter hyperintensity on brain MRI (odds ratio 0.59, 95% CI: 0.38, 0.92, P = 0.019). The association with white matter hyperintensity was no longer significant in models adjusted for cardiovascular risk factors and disease. In longitudinal analysis (6.7 ± 1.7 years later), offspring with parental longevity had slower decline in attention (0.18 ± 0.08, P = 0.038), executive function (beta 0.19 ± 0.09, P = 0.031) and visual memory (beta -0.18 ± 0.08, P = 0.023), and less increase in temporal horn volume (beta -0.25 ± 0.09, P = 0.005). The associations persisted in fully adjusted models. CONCLUSION: parental longevity is associated with better brain ageing in middle-aged offspring.

Brain structural covariances in the ageing brain in the UK Biobank.

The morphologic properties of brain regions co-vary or correlate with each other. Here we investigated the structural covariances of cortical thickness and subcortical volumes in the ageing brain, along with their associations with age and cognition, using cross-sectional data from the UK Biobank (N = 42,075, aged 45-83 years, 53% female). As the structural covariance should be estimated in a group of participants, all participants were divided into 84 non-overlapping, equal-sized age groups ranging from the youngest to the oldest. We examined 84 cortical thickness covariances and subcortical covariances. Our findings include: (1) there were significant differences in the variability of structural covariance in the ageing process, including an increased variance, and a decreased entropy. (2) significant enrichment in pairwise correlations between brain regions within the occipital lobe was observed in all age groups; (3) structural covariance in older age, especially after the age of around 64, was significantly different from that in the youngest group (median age 48 years); (4) sixty-two of the total 528 pairs of cortical thickness correlations and 10 of the total 21 pairs of subcortical volume correlations showed significant associations with age. These trends varied, with some correlations strengthening, some weakening, and some reversing in direction with advancing age. Additionally, as ageing was associated with cognitive decline, most of the correlations with cognition displayed an opposite trend compared to age associated patterns of correlations.

The Combined Antioxidant Effects of N-Acetylcysteine, Vitamin D3, and Glutathione from the Intestinal-Neuronal In Vitro Model.

Chronic oxidative stress has been consistently linked to age-related diseases, conditions, and degenerative syndromes. Specifically, the brain is the organ that significantly contributes to declining quality of life in ageing. Since the body cannot completely counteract the detrimental effects of oxidative stress, nutraceuticals' antioxidant properties have received significant attention in recent years. This study assesses the potential health benefits of a novel combination of glutathione, vitamin D3, and N-acetylcysteine. To examine the combination's absorption and biodistribution and confirm that it has no harmful effects, the bioavailability of the mixture was first evaluated in a 3D model that mimicked the intestinal barrier. Further analyses on the blood-brain barrier was conducted to determine the antioxidant effects of the combination in the nervous system. The results show that the combination reaches the target and successfully crosses the blood-brain and intestinal barriers, demonstrating enhanced advantages on the neurological system, such as a reduction (about 10.5%) in inflammation and enhancement in cell myelination (about 20.4%) and brain tropism (about 18.1%) compared to the control. The results support the cooperative effect of N-acetylcysteine, vitamin D3, and glutathione to achieve multiple health benefits, outlining the possibility of an alternative nutraceutical approach.

Exploring role of natural compounds in molecular alterations associated with brain ageing: A perspective towards nutrition for ageing brain.

Aging refers to complete deterioration of physiological integrity and function. By midcentury, adults over 60 years of age and children under 15 years will begin to outnumber people in working age. This shift will bring multiple global challenges for economy, health, and society. Eventually, aging is a natural process playing a vital function in growth and development during pediatric stage, maturation during adult stage, and functional depletion. Tissues experience negative consequences with enhanced genomic instability, deregulated nutrient sensing, mitochondrial dysfunction, and decline in performance on cognitive tasks. As brain ages, its volume decreases, neurons & glia get inflamed, vasculature becomes less developed, blood pressure increases with a risk of stroke, ischemia, and cognitive deficits. Diminished cellular functions leads to progressive reduction in functional and emotional capacity with higher possibility of disease and finally death. This review overviews cellular as well as molecular aspects of aging, biological pathway related to accelerated brain aging, and strategies minimizing cognitive aging. Age-related changes include altered bioenergetics, decreased neuroplasticity and flexibility, aberrant neural activity, deregulated Ca2+ homeostasis in neurons, buildup of reactive oxygen species, and neuro-inflammation. Unprecedented progress has been achieved in recent studies, particularly in terms of how herbal or natural substances affect genetic pathways and biological functions that have been preserved through evolution. Herein, the present work provides an overview of ageing and age-related disorders and explore the molecular mechanisms that underlie therapeutic effects of herbal and natural chemicals on neuropathological signs of brain aging.

Cognitive Function Is Associated with the Genetically Determined Efficiency of DNA Repair Mechanisms.

Several modifiable risk factors for neurodegeneration and dementia have been identified, although individuals vary in their vulnerability despite a similar risk of exposure. This difference in vulnerability could be explained at least in part by the variability in DNA repair mechanisms' efficiency between individuals. Therefore, the aim of this study was to test associations between documented, prevalent genetic variation (single nucleotide polymorphism, SNP) in DNA repair genes, cognitive function, and brain structure. Community-living participants (n = 488,159; 56.54 years (8.09); 54.2% female) taking part in the UK Biobank study and for whom cognitive and genetic measures were available were included. SNPs in base excision repair (BER) genes of the bifunctional DNA glycosylases OGG1 (rs1052133, rs104893751), NEIL1 (rs7402844, rs5745906), NEIL2 (rs6601606), NEIL3 (rs10013040, rs13112390, rs13112358, rs1395479), MUTYH (rs34612342, rs200165598), NTHL1 (rs150766139, rs2516739) were considered. Cognitive measures included fluid intelligence, the symbol-digit matching task, visual matching, and trail-making. Hierarchical regression and latent class analyses were used to test the associations between SNPs and cognitive measures. Associations between SNPs and brain measures were also tested in a subset of 39,060 participants. Statistically significant associations with cognition were detected for 12 out of the 13 SNPs analyzed. The strongest effects amounted to a 1-6% difference in cognitive function detected for NEIL1 (rs7402844), NEIL2 (rs6601606), and NTHL1 (rs2516739). Associations varied by age and sex, with stronger effects detected in middle-aged women. Weaker associations with brain measures were also detected. Variability in some BER genes is associated with cognitive function and brain structure and may explain variability in the risk for neurodegeneration and dementia.

Thermodynamic Analysis to Evaluate the Effect of Diet on Brain Glucose Metabolism: The Case of Fish Oil.

Inefficient glucose metabolism and decreased ATP production in the brain are linked to ageing, cognitive decline, and neurodegenerative diseases (NDDs). This study employed thermodynamic analysis to assess the effect of fish oil supplementation on glucose metabolism in ageing brains. Data from previous studies on glucose metabolism in the aged human brain and grey mouse lemur brains were examined. The results demonstrated that Omega-3 fish oil supplementation in grey mouse lemurs increased entropy generation and decreased Gibbs free energy across all brain regions. Specifically, there was a 47.4% increase in entropy generation and a 47.4 decrease in Gibbs free energy in the whole brain, indicating improved metabolic efficiency. In the human model, looking at the specific brain regions, supplementation with Omega-3 polyunsaturated fatty acids (n-3 PUFAs) reduced the entropy generation difference between elderly and young individuals in the cerebellum and particular parts of the brain cortex, namely the anterior cingulate and occipital lobe, with 100%, 14.29%, and 20% reductions, respectively. The Gibbs free energy difference was reduced only in the anterior cingulate by 60.64%. This research underscores that the application of thermodynamics is a comparable and powerful tool in comprehending the dynamics and metabolic intricacies within the brain.