Obesity associated with increased brain age from midlife

Maintaining Brain Health: The Impact of Physical Activity and Fitness on the Aging Brain-A UK Biobank Study

The growing prevalence of physical and neurological disorders linked to aging poses significant challenges for society. Many of these disorders are closely linked to changes in brain structure and function, highlighting the importance of identifying protective factors that can preserve brain structure in later life and mitigate age-related decline. Physical activity (PA) is consistently linked to physical health and was found to mitigate age-related disorders. However, its effects on markers of brain aging remain inconclusive, partly due to reliance on underpowered studies and self-reported data. We investigated the effects of accelerometer-measured PA and physical fitness on BrainAGE, a machine-learning-derived marker of brain aging, in a large UK Biobank cohort. Using cortical and subcortical neuroimaging-derived features, a BrainAGE model was trained on 21,442 participants (mean absolute error: 3.75 years) and applied to predict BrainAGE for an independent sample of 10,874 participants. Accelerometer-measured moderate-intensity PA, but not self-reported PA, was associated with decelerated brain aging, indicated by a negative BrainAGE. Further, higher hand grip strength, along with lower body mass index (BMI), diastolic blood pressure (DBP), and resting heart rate, was linked to decelerated aging. These fitness measures impacted BrainAGE independently of PA. Additionally, fitness partially accounted for the relationship between PA and BrainAGE. Specifically, BMI, DBP, and resting heart rate showed a significant mediating effect, while grip strength did not. These findings highlight the interplay between PA and fitness in maintaining brain health and provide valuable insights for neuroscience and preventive health measures.

Increased Brain Age Among Psychiatrically Healthy Adults Exposed to Childhood Trauma

BACKGROUND

Adults with childhood trauma exposure may exhibit brain changes typically associated with aging and neurodegeneration (e.g., reduced tissue volume or integrity) to a greater degree than their unexposed counterparts, suggesting accelerated brain aging. Machine learning methods that predict a person's age based on their magnetic resonance imaging (MRI) brain scan may be useful for investigating aberrant brain aging following childhood trauma exposure. Emerging evidence indicates altered brain aging in adolescents with childhood trauma exposure; however, this association has not been examined in healthy adults.

METHODS

We investigated the associations between childhood trauma exposure, including abuse and neglect, and brain-predicted age in psychiatrically healthy adults. "Brain age" predictions were generated from T1-weighted structural MRI scans using a pre-trained machine learning pipeline, namely brainageR. The differences between brain-predicted age and chronological age were calculated and associations with childhood trauma questionnaire scores were investigated using linear regression.

RESULTS

The final sample (n = 153; mean age 46 ± 16 years, 70% female) included 69 adults with childhood trauma exposure and 84 unexposed adults. Childhood sexual abuse was associated with an average increased brain age of 3.2 years, adjusting for chronological age and age-squared, sex, and scanner site; however, this finding did not survive correction for multiple comparisons.

CONCLUSIONS

To our knowledge, this study represents the first published investigation of brain age in adults with childhood trauma using a machine-learning-based prediction model. Our findings suggest a link between childhood trauma exposure, specifically sexual abuse, and accelerated brain aging in adulthood, but this association should be replicated in future work. Accentuated brain aging in adulthood may increase the risk of age-related cognitive and neurodegenerative decline and associated disorders later in life.

Allostatic load, a measure of cumulative physiological stress, impairs brain structure but not β-accumulation in older adults: an exploratory study

Introduction

Allostatic load (AL) is a composite score of progressive physiological dysregulations in response to long-term exposure to everyday stress. Despite growing interest, limited research has focused on links with cerebral and cognitive aspects of aging and with markers sensitive to Alzheimer's disease (AD) in a healthy elderly population and with a multimodal approach.

Methods

At baseline, 111 older adults (without cognitive impairment) from the Age-Well trial completed blood and anthropometric markers collection, cognitive assessments and multimodal neuroimaging within 3 months.

Results

AL was negatively associated with gray matter volume and white matter integrity within frontal and temporal regions and poorer attentional performance.

Discussion

AL is linked to structural brain integrity in aging- and stress-sensitive regions but not with AD-related markers (β-amyloid load) and only in two AD-sensitive brain regions in older adults. These results highlight the potential interest of AL as a sensitive index of stress-induced brain aging.

Intermittent fasting and neurodegenerative diseases: Molecular mechanisms and therapeutic potential

Neurodegenerative disorders are straining public health worldwide. During neurodegenerative disease progression, aberrant neuronal network activity, bioenergetic impairment, adaptive neural plasticity impairment, dysregulation of neuronal Ca2+ homeostasis, oxidative stress, and immune inflammation manifest as characteristic pathological changes in the cellular milieu of the brain. There is no drug for the treatment of neurodegenerative disorders, and therefore, strategies/treatments for the prevention or treatment of neurodegenerative disorders are urgently needed. Intermittent fasting (IF) is characterized as an eating pattern that alternates between periods of fasting and eating, requiring fasting durations that vary depending on the specific protocol implemented. During IF, depletion of liver glycogen stores leads to the production of ketone bodies from fatty acids derived from adipocytes, thereby inducing an altered metabolic state accompanied by cellular and molecular adaptive responses within neural networks in the brain. At the cellular level, adaptive responses can promote the generation of synapses and neurons. At the molecular level, IF triggers the activation of associated transcription factors, thereby eliciting the expression of protective proteins. Consequently, this regulatory process governs central and peripheral metabolism, oxidative stress, inflammation, mitochondrial function, autophagy, and the gut microbiota, all of which contribute to the amelioration of neurodegenerative disorders. Emerging evidence suggests that weight regulation significantly contributes to the neuroprotective effects of IF. By alleviating obesity-related factors such as blood-brain barrier dysfunction, neuroinflammation, and β-amyloid accumulation, IF enhances metabolic flexibility and insulin sensitivity, further supporting its potential in mitigating neurodegenerative disorders. The present review summarizes animal and human studies investigating the role and underlying mechanisms of IF in physiology and pathology, with an emphasis on its therapeutic potential. Furthermore, we provide an overview of the cellular and molecular mechanisms involved in regulating brain energy metabolism through IF, highlighting its potential applications in neurodegenerative disorders. Ultimately, our findings offer novel insights into the preventive and therapeutic applications of IF for neurodegenerative disorders.

Ageing-related changes in the regulation of microglia and their interaction with neurons

Ageing is one of the most important risk factors for chronic health conditions, including neurodegenerative diseases. Inflammation is a feature of ageing, as well as a key pathophysiological mechanism for degenerative diseases. Microglia play multiple roles in the central nervous system; their states entail a complex assemblage of responses reflecting the multiplicity of functions they fulfil both under homeostatic basal conditions and in response to stimuli. Whereas glial cells can promote neuronal homeostasis and limit neurodegeneration, age-related inflammation (i.e. inflammaging) leads to the functional impairment of microglia and astrocytes, exacerbating their response to stimuli. Thus, microglia are key mediators for age-dependent changes of the nervous system, participating in the generation of a less supportive or even hostile environment for neurons. Whereas multiple changes of ageing microglia have been described, here we will focus on the neuron-microglia regulatory crosstalk through fractalkine (CX3CL1) and CD200, and the regulatory cytokine Transforming Growth Factor β1 (TGFβ1), which is involved in immunomodulation and neuroprotection. Ageing results in a dysregulated activation of microglia, affecting neuronal survival, and function. The apparent unresponsiveness of aged microglia to regulatory signals could reflect a restriction in the mechanisms underlying their homeostatic and reactive states. The spectrum of functions, required to respond to life-long needs for brain maintenance and in response to disease, would progressively narrow, preventing microglia from maintaining their protective functions. This article is part of the Special Issue on "Microglia".

Western diet since adolescence impairs brain functional hyperemia at adulthood in mice: rescue by a balanced ω-3:ω-6 polyunsaturated fatty acids ratio

BACKGROUND/OBJECTIVE

Obesity is a devastating worldwide metabolic disease, with the highest prevalence in children and adolescents. Obesity impacts neuronal function but the fate of functional hyperemia, a vital mechanism making possible cerebral blood supply to active brain areas, is unknown in organisms fed a high-caloric Western Diet (WD) since adolescence.

SUBJECTS/METHODS

We mapped changes in cerebral blood volume (CBV) in the somatosensory cortex in response to whisker stimulation in adolescent, adult, and middle-aged mice fed a WD since adolescence. To this aim, we used non-invasive and high-resolution functional ultrasound imaging (fUS).

RESULTS

We efficiently mimicked the metabolic syndrome of adolescents in young mice with early weight gain, dysfunctional glucose homeostasis, and insulinemia. Functional hyperemia is compromised as early as 3 weeks of WD and remains impaired after that in adolescent mice. These findings highlight the cerebrovascular vulnerability to WD during adolescence. In WD, ω-6:ω-3 polyunsaturated fatty acids (PUFAs) ratio is unbalanced towards proinflammatory ω-6. A balanced ω-6:ω-3 PUFAs ratio in WD achieved by docosahexaenoic acid supplementation efficiently restores glucose homeostasis and functional hyperemia in adults.

CONCLUSIONS

WD triggers a rapid impairment in cerebrovascular activity in adolescence, which is maintained at older ages, and can be rescued by a PUFA-based nutraceutical approach.

Immune control of brain physiology

The peripheral immune system communicates with the brain through complex anatomical routes involving the skull, the brain borders, circumventricular organs and peripheral nerves. These immune-brain communication pathways were classically considered to be dormant under physiological conditions and active only in cases of infection or damage. Yet, peripheral immune cells and signals are key in brain development, function and maintenance. In this Perspective, we propose an alternative framework for understanding the mechanisms of immune-brain communication. During brain development and in homeostasis, these anatomical structures allow selected elements of the peripheral immune system to affect the brain directly or indirectly, within physiological limits. By contrast, in ageing and pathological settings, detrimental peripheral immune signals hijack the existing communication routes or alter their structure. We discuss why a diversity of communication channels is needed and how they work in relation to one another to maintain homeostasis of the brain.

Update on Hypothalamic Inflammation and Gliosis: Expanding Evidence of Relevance Beyond Obesity

PURPOSE OF REVIEW

To evaluate the role of hypothalamic inflammation and gliosis in human obesity pathogenesis and other disease processes influenced by obesity.

RECENT FINDINGS

Recent studies using established and novel magnetic resonance imaging (MRI) techniques to assess alterations in hypothalamic microarchitecture in humans support the presence of hypothalamic inflammation and gliosis in adults and children with obesity. Studies also identify prenatal exposure to maternal obesity or diabetes as a risk factor for hypothalamic inflammation and gliosis and increased obesity risk in offspring. Hypothalamic inflammation and gliosis have been further implicated in reproductive dysfunction (specifically polycystic ovarian syndrome and male hypogonadism), cardiovascular disease namely hypertension, and alterations in the gut microbiome, and may also accelerate neurocognitive aging. The most recent translational studies support the link between hypothalamic inflammation and gliosis and obesity pathogenesis in humans and expand our understanding of its influence on broader aspects of human health.

Hypothalamic volume is associated with age, sex and cognitive function across lifespan: a comparative analysis of two large population-based cohort studies

BACKGROUND

Emerging findings indicate that the hypothalamus, the body's principal homeostatic centre, plays a crucial role in modulating cognition, but comprehensive population-based studies are lacking.

METHODS

We used cross-sectional data from the Rhineland Study (N = 5812, 55.2 ± 13.6 years, 58% women) and the UK Biobank Imaging Study (UKB) (N = 45,076, 64.2 ± 7.7 years, 53% women), two large-scale population-based cohort studies. Volumes of hypothalamic structures were obtained from 3T structural magnetic resonance images through an automatic parcellation procedure (FastSurfer-HypVINN). The standardised cognitive domain scores were derived from extensive neuropsychological test batteries. We employed multivariable linear regression to assess associations of hypothalamic volumes with age, sex and cognitive performance.

FINDINGS

In older individuals, volumes of total, anterior and posterior hypothalamus, and mammillary bodies were smaller, while those of medial hypothalamus and tuberal region were larger. Larger medial hypothalamus volume was related to higher cortisol levels in older individuals, providing functional validation. Volumes of all hypothalamic structures were larger in men compared to women. In both sexes, larger volumes of total, anterior and posterior hypothalamus, and mammillary bodies were associated with better domain-specific cognitive performance, whereas larger volumes of medial hypothalamus and tuberal region were associated with worse domain-specific cognitive performance.

INTERPRETATION

We found strong age and sex effects on hypothalamic structures, as well as robust associations between these structures and domain-specific cognitive functions. Overall, these findings thus implicate specific hypothalamic subregions as potential therapeutic targets against age-associated cognitive decline.

FUNDING

Institutional funds, Federal Ministry of Education and Research of Germany, Alzheimer's Association.

Evaluation of Brain Age as a Specific Marker of Brain Health

Brain age is a powerful marker of general brain health. Furthermore, brain age models are trained on large datasets, thus giving them a potential advantage in predicting specific outcomes - much like the success of finetuning large language models for specific applications. However, it is also well-accepted in machine learning that models trained to directly predict specific outcomes (i.e., direct models) often perform better than those trained on surrogate outcomes. Therefore, despite their much larger training data, it is unclear whether brain age models outperform direct models in predicting specific brain health outcomes. Here, we compare large-scale brain age models and direct models for predicting specific health outcomes in the context of Alzheimer's Disease (AD) dementia. Using anatomical T1 scans from three continents (N = 1,848), we find that direct models outperform brain age models without finetuning. Finetuned brain age models yielded similar performance as direct models, but importantly, did not outperform direct models although the brain age models were pretrained on 1000 times more data than the direct models: N = 53,542 vs N = 50. Overall, our results do not discount brain age as a useful marker of general brain health. However, in this era of large-scale brain age models, our results suggest that small-scale, targeted approaches for extracting specific brain health markers still hold significant value.

Treatment with brain specific estrogen prodrug ameliorates cognitive effects of surgical menopause in mice

Menopause is an endocrine shift leading to increased vulnerability for cognitive impairment and dementia risk factors, in part due to loss of neuroprotective circulating estrogens. Systemic replacement of estrogen post-menopause has limitations, including risk for estrogen-sensitive cancers. A promising therapeutic approach therefore might be to deliver estrogen only to the brain. We examined whether we could enhance cognitive performance by delivering estrogen exclusively to the brain in ovariectomized mice (a surgical menopause model). We treated mice with the prodrug 10β,17β-dihydroxyestra-1,4-dien-3-one (DHED), which can be administered systemically but is converted to 17β-estradiol only in the brain. Young and middle-aged C57BL/6 J mice received ovariectomy and subcutaneous implant containing vehicle or DHED and underwent cognitive testing to assess memory after 1-3.5 months of treatment. Low and medium doses of DHED did not alter metabolic status in middle-aged mice. In both age groups, DHED treatment improved spatial memory in ovariectomized mice. Additional testing in middle-aged mice showed that DHED treatment improved working and recognition memory in ovariectomized mice. These results lay the foundation for future studies determining if this intervention is as efficacious in models of dementia with comorbid risk factors.

Sex as a Determinant of Age-Related Changes in the Brain

The notion of notable anatomical, biochemical, and behavioral distinctions within male and female brains has been a contentious topic of interest within the scientific community over several decades. Advancements in neuroimaging and molecular biological techniques have increasingly elucidated common mechanisms characterizing brain aging while also revealing disparities between sexes in these processes. Variations in cognitive functions; susceptibility to and progression of neurodegenerative conditions, notably Alzheimer's and Parkinson's diseases; and notable disparities in life expectancy between sexes, underscore the significance of evaluating aging within the framework of gender differences. This comprehensive review surveys contemporary literature on the restructuring of brain structures and fundamental processes unfolding in the aging brain at cellular and molecular levels, with a focus on gender distinctions. Additionally, the review delves into age-related cognitive alterations, exploring factors influencing the acceleration or deceleration of aging, with particular attention to estrogen's hormonal support of the central nervous system.

The mitochondrial quality control system: a new target for exercise therapeutic intervention in the treatment of brain insulin resistance-induced neurodegeneration in obesity

Obesity is a major global health concern because of its strong association with metabolic and neurodegenerative diseases such as diabetes, dementia, and Alzheimer's disease. Unfortunately, brain insulin resistance in obesity is likely to lead to neuroplasticity deficits. Since the evidence shows that insulin resistance in brain regions abundant in insulin receptors significantly alters mitochondrial efficiency and function, strategies targeting the mitochondrial quality control system may be of therapeutic and practical value in obesity-induced cognitive decline. Exercise is considered as a powerful stimulant of mitochondria that improves insulin sensitivity and enhances neuroplasticity. It has great potential as a non-pharmacological intervention against the onset and progression of obesity associated neurodegeneration. Here, we integrate the current knowledge of the mechanisms of neurodegenration in obesity and focus on brain insulin resistance to explain the relationship between the impairment of neuronal plasticity and mitochondrial dysfunction. This knowledge was synthesised to explore the exercise paradigm as a feasible intervention for obese neurodegenration in terms of improving brain insulin signals and regulating the mitochondrial quality control system.

Astrocytes at the intersection of ageing, obesity, and neurodegeneration

Once considered passive cells of the central nervous system (CNS), glia are now known to actively maintain the CNS parenchyma; in recent years, the evidence for glial functions in CNS physiology and pathophysiology has only grown. Astrocytes, a heterogeneous group of glial cells, play key roles in regulating the metabolic and inflammatory landscape of the CNS and have emerged as potential therapeutic targets for a variety of disorders. This review will outline astrocyte functions in the CNS in healthy ageing, obesity, and neurodegeneration, with a focus on the inflammatory responses and mitochondrial function, and will address therapeutic outlooks.

Childhood maltreatment influences adult brain structure through its effects on immune, metabolic, and psychosocial factors

Childhood maltreatment (CM) leads to a lifelong susceptibility to mental ill-health which might be reflected by its effects on adult brain structure, perhaps indirectly mediated by its effects on adult metabolic, immune, and psychosocial systems. Indexing these systemic factors via body mass index (BMI), C-reactive protein (CRP), and rates of adult trauma (AT), respectively, we tested three hypotheses: (H1) CM has direct or indirect effects on adult trauma, BMI, and CRP; (H2) adult trauma, BMI, and CRP are all independently related to adult brain structure; and (H3) childhood maltreatment has indirect effects on adult brain structure mediated in parallel by BMI, CRP, and AT. Using path analysis and data from N = 116,887 participants in UK Biobank, we find that CM is related to greater BMI and AT levels, and that these two variables mediate CM's effects on CRP [H1]. Regression analyses on the UKB MRI subsample (N = 21,738) revealed that greater CRP and BMI were both independently related to a spatially convergent pattern of cortical effects (Spearman's ρ = 0.87) characterized by fronto-occipital increases and temporo-parietal reductions in thickness. Subcortically, BMI was associated with greater volume, AT with lower volume and CPR with effects in both directions [H2]. Finally, path models indicated that CM has indirect effects in a subset of brain regions mediated through its direct effects on BMI and AT and indirect effects on CRP [H3]. Results provide evidence that childhood maltreatment can influence brain structure decades after exposure by increasing individual risk toward adult trauma, obesity, and inflammation.

Dissecting unique and common variance across body and brain health indicators using age prediction

Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict 'body age'. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion-based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle-fat infiltration were related to older-appearing body age compared to brain age. Conversely, higher hand-grip strength and muscle volume were related to a younger-appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals.

Sarcopenic obesity is part of obesity paradox in dementia development: evidence from a population-based cohort study

BACKGROUND

Sarcopenic obesity, a clinical and functional condition characterized by the coexistence of obesity and sarcopenia, has not been investigated in relation to dementia risk and its onset.

METHODS

We included 208,867 participants from UK biobank, who aged 60 to 69 years at baseline. Dementia diagnoses were identified using hospital records and death register data. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models to evaluate the associations of obesity, sarcopenia, and sarcopenic obesity with dementia risk, stratified by sex. Stratified analyses were performed across dementia-related polygenic risk score (PRS). Restricted mean survival time models were established to estimate the difference and 95%CIs of dementia onset across different status. Additionally, linear regression models were employed to estimate associations of different status with brain imaging parameters. The mediation effects of chronic diseases were also examined.

RESULTS

Obese women with high PRS had a decreased risk (HR = 0.855 [0.761-0.961]), but obese men with low PRS had an increased risk (HR = 1.223 [1.045-1.431]). Additionally, sarcopenia was associated with elevated dementia risk (HRwomen = 1.323 [1.064-1.644]; HRmen = 2.144 [1.753-2.621]) in those with low PRS. Among those with high PRS, however, the association was only significant in early-life (HRwomen = 1.679 [1.355-2.081]; HRmen = 2.069 [1.656-2.585]). Of note, sarcopenic obesity was associated with higher dementia risk (HRwomen = 1.424 [1.227-1.653]; HRmen = 1.989 [1.702-2.323]), and results remained similar stratified by PRS. Considering dementia onset, obesity was associated with dementia by 1.114 years delayed in women, however, 0.170 years advanced in men. Sarcopenia (women: 0.080 years; men: 0.192 years) and sarcopenic obesity (women: 0.109 years; men: 0.511 years) respectively advanced dementia onset. Obesity, sarcopenia, and sarcopenic obesity were respectively related to alterations in different brain regions. Association between sarcopenic obesity and dementia was mediated by chronic diseases.

CONCLUSIONS

Sarcopenic obesity and sarcopenia were respectively associated with increased dementia risk and advanced dementia onset to vary degree. The role of obesity in dementia may differ by sex and genetic background.

Fasting-mimicking diet causes hepatic and blood markers changes indicating reduced biological age and disease risk

In mice, periodic cycles of a fasting mimicking diet (FMD) protect normal cells while killing damaged cells including cancer and autoimmune cells, reduce inflammation, promote multi-system regeneration, and extend longevity. Here, we performed secondary and exploratory analysis of blood samples from a randomized clinical trial (NCT02158897) and show that 3 FMD cycles in adult study participants are associated with reduced insulin resistance and other pre-diabetes markers, lower hepatic fat (as determined by magnetic resonance imaging) and increased lymphoid to myeloid ratio: an indicator of immune system age. Based on a validated measure of biological age predictive of morbidity and mortality, 3 FMD cycles were associated with a decrease of 2.5 years in median biological age, independent of weight loss. Nearly identical findings resulted from  a second clinical study (NCT04150159). Together these results provide initial support for beneficial effects of the FMD on multiple cardiometabolic risk factors and biomarkers of biological age.

Exercise training improves long-term memory in obese mice

Obesity has been linked to a range of pathologies, including dementia. In contrast, regular physical activity is associated with the prevention or reduced progression of neurodegeneration. Specifically, physical activity can improve memory and spatial cognition, reduce age-related cognitive decline, and preserve brain volume, but the mechanisms are not fully understood. Accordingly, we investigated whether any detrimental effects of high-fat diet (HFD)-induced obesity on cognition, motor behavior, adult hippocampal neurogenesis, and brain-derived neurotrophic factor (BDNF) could be mitigated by voluntary exercise training in male C57Bl/6 mice. HFD-induced impairment of motor function was not reversed by exercise. Importantly, voluntary wheel running improved long-term memory and increased hippocampal neurogenesis, suggesting that regular physical activity may prevent cognitive decline in obesity.

Novel insights into brain lipid metabolism in Alzheimer's disease: Oligodendrocytes and white matter abnormalities

Alzheimer's disease (AD) is the most common cause of dementia. A genome-wide association study has shown that several AD risk genes are involved in lipid metabolism. Additionally, epidemiological studies have indicated that the levels of several lipid species are altered in the AD brain. Therefore, lipid metabolism is likely changed in the AD brain, and these alterations might be associated with an exacerbation of AD pathology. Oligodendrocytes are glial cells that produce the myelin sheath, which is a lipid-rich insulator. Dysfunctions of the myelin sheath have been linked to white matter abnormalities observed in the AD brain. Here, we review the lipid composition and metabolism in the brain and myelin and the association between lipidic alterations and AD pathology. We also present the abnormalities in oligodendrocyte lineage cells and white matter observed in AD. Additionally, we discuss metabolic disorders, including obesity, as AD risk factors and the effects of obesity and dietary intake of lipids on the brain.

Sex differences in response to obesity and caloric restriction on cognition and hippocampal measures of autophagic-lysosomal transcripts and signaling pathways

BACKGROUND

Obesity rates in the U.S. continue to increase, with nearly 50% of the population being either obese or morbidly obese. Obesity, along with female sex, are leading risk factors for sporadic Alzheimer's Disease (AD) necessitating the need to better understand how these variables impact cellular function independent of age or genetic mutations. Animal and clinical studies both indicate that autophagy-lysosomal pathway (ALP) dysfunction is among the earliest known cellular systems to become perturbed in AD, preceding cognitive decline, yet little is known about how obesity and sex affects these cellular functions in the hippocampus, a brain region uniquely susceptible to the negative effects of obesity. We hypothesized that obesity would negatively affect key markers of ALP in the hippocampus, effects would vary based on sex, and that caloric restriction would counteract obesity effects.

METHODS

Female and male mice were placed on an obesogenic diet for 10 months, at which point half were switched to caloric restriction for three months, followed by cognitive testing in the Morris watermaze. Hippocampus was analyzed by western blot and qPCR.

RESULTS

Cognitive function in female mice responded differently to caloric restriction based on whether they were on a normal or obesogenic diet; male cognition was only mildly affected by caloric restriction and not obesity. Significant male-specific changes occurred in cellular markers of autophagy, including obesity increasing pAkt, Slc38a9, and Atg12, while caloric restriction reduced pRPS6 and increased Atg7. In contrast females experienced changes due to diet/caloric restriction predominately in lysosomal markers including increased TFE3, FLCN, FNIP2, and pAMPK.

CONCLUSIONS

Results support that hippocampal ALP is a target of obesity and that sex shapes molecular responses, while providing insight into how dietary manipulations affect learning and memory based on sex.

Brain Age Is Associated with Cognitive Outcomes of Cholinesterase Inhibitor Treatment in Patients with Mild Cognitive Impairment

Background

The effect of cholinesterase inhibitor (ChEI) on mild cognitive impairment (MCI) is controversial. Brain age has been shown to predict Alzheimer's disease conversion from MCI.

Objective

The study aimed to show that brain age is related to cognitive outcomes of ChEI treatment in MCI.

Methods

Brain MRI, the Clinical Dementia Rating (CDR) and Mini-Mental State Exam (MMSE) scores were retrospectively retrieved from a ChEI treatment database. Patients who presented baseline CDR of 0.5 and received ChEI treatment for at least 2 years were selected. Patients with stationary or improved cognition as verified by the CDR and MMSE were categorized to the ChEI-responsive group, and those with worsened cognition were assigned to the ChEI-unresponsive group. A gray matter brain age model was built with a machine learning algorithm by training T1-weighted MRI data of 362 healthy participants. The model was applied to each patient to compute predicted age difference (PAD), i.e. the difference between brain age and chronological age. The PADs were compared between the two groups.

Results

58 patients were found to fit the ChEI-responsive criteria in the patient data, and 58 matched patients that fit the ChEI-unresponsive criteria were compared. ChEI-unresponsive patients showed significantly larger PAD than ChEI-responsive patients (8.44±8.78 years versus 3.87±9.02 years, p = 0.0067).

Conclusions

Gray matter brain age is associated with cognitive outcomes after 2 years of ChEI treatment in patients with the CDR of 0.5. It might facilitate the clinical trials of novel therapeutics for MCI.

BASE: Brain Age Standardized Evaluation

Brain age, most commonly inferred from T1-weighted magnetic resonance images (T1w MRI), is a robust biomarker of brain health and related diseases. Superior accuracy in brain age prediction, often falling within a 2-3 year range, is achieved predominantly through deep neural networks. However, comparing study results is difficult due to differences in datasets, evaluation methodologies and metrics. Addressing this, we introduce Brain Age Standardized Evaluation (BASE), which includes (i) a standardized T1w MRI dataset including multi-site, new unseen site, test-retest and longitudinal data, and an associated (ii) evaluation protocol, including repeated model training and upon based comprehensive set of performance metrics measuring accuracy, robustness, reproducibility and consistency aspects of brain age predictions, and (iii) statistical evaluation framework based on linear mixed-effects models for rigorous performance assessment and cross-comparison. To showcase BASE, we comprehensively evaluate four deep learning based brain age models, appraising their performance in scenarios that utilize multi-site, test-retest, unseen site, and longitudinal T1w brain MRI datasets. Ensuring full reproducibility and application in future studies, we have made all associated data information and code publicly accessible at https://github.com/AralRalud/BASE.git.

Inflammatory Pathways in Overweight and Obese Persons as a Potential Mechanism for Cognitive Impairment and Earlier Onset Alzeihmer's Dementia in the General Population: A Narrative Review

The overweight status or obesity can be confirmed through classical methods such as the body mass index (BMI) and the waist-to-hip ratio (WHR). Apart from metabolic issues such as atherosclerosis, liver steatosis, or diabetes mellitus, long-term obesity or overweight status can pose a risk for cardiovascular and neurovascular complications. While some acute adverse events like coronary syndromes of strokes are well-documented to be linked to an increased body mass, there are also chronic processes that, due to their silent onset and evolution, are underdiagnosed and not as thoroughly studied. Through this review, we aimed to collect all relevant data with regard to the long-term impact of obesity on cognitive function in all ages and its correlation with an earlier onset of dementia such as Alzheimer's disease (AD). The exact mechanisms through which a decline in cognitive functions occurs in overweight or obese persons are still being discussed. A combination of factors has been acknowledged as potential triggers, such as a sedentary lifestyle and stress, as well as a genetic predisposition, for example, the apolipoprotein E (ApoE) alleles in AD. Most research highlights the impact of vascular dysfunction and systemic inflammation on the nervous system in patients with obesity and the subsequent neurological changes. Obesity during the early to mid-ages leads to an earlier onset of cognitive dysfunction in various forms. Also, lifestyle intervention can reverse cognitive dysfunction, especially dieting, to encourage weight loss.

Long-term lifestyle intervention is superior to transient modification for neuroprotection in D-galactose-induced aging rats

AIMS

To investigate whether transient dietary restriction or aerobic exercise in young adulthood exert long-lasting protection against brain aging later in life.

MAIN METHODS

Seven-week-old male Wistar rats were divided into 2 groups and given either normal saline as a vehicle (n = 8) or 150 mg/kg/day of D-galactose (n = 40) for 28 weeks, the D-galactose being used to induce aging. At week 13 of the experiment, D-galactose-treated rats were further divided into 5 groups, 1) no intervention, 2) transient dietary restriction for 6 weeks (week 13-18), 3) transient exercise for 6 weeks (week 13-18), 4) long-term dietary restriction for 16 weeks (week 13-28), and 5) long-term exercise for 16 weeks (week 13-28). At the end of week 28, cognitive function was examined, followed by molecular studies in the hippocampus.

KEY FINDINGS

Our results showed that either long-term dietary restriction or aerobic exercise effectively attenuated cognitive function in D-galactose-treated rats via the attenuation of oxidative stress, cellular senescence, Alzheimer's-like pathology, neuroinflammation, and improvements in mitochondria, brain metabolism, adult neurogenesis, and synaptic integrity. Although transient interventions provided benefits in some brain parameters in D-galactose-treated rats, an improvement in cognitive function was not observed.

SIGNIFICANCE

Our findings suggested that transient lifestyle interventions failed to exert a long-lasting protective effect against brain aging. Hence, novel drugs mimicking the neuroprotective effect of long-term dietary restriction or exercise and the combination of the two since young age appear to be more appropriate treatments for the elderly who are unable to engage in long-term dietary restriction or exercise.

Triangulating causality between childhood obesity and neurobehavior: Behavioral genetic and longitudinal evidence

Childhood obesity is a serious health concern that is not yet fully understood. Previous research has linked obesity with neurobehavioral factors such as behavior, cognition, and brain morphology. The causal directions of these relationships remain mostly untested. We filled this gap by using the Adolescent Brain Cognitive Development study cohort comprising 11,875 children aged 9-10. First, correlations between the age- and sex-specific 95th BMI percentile (%BMIp95) and neurobehavioral measures were cross-sectionally analyzed. Effects were then aggregated by neurobehavioral domain for causal analyses. Behavioral genetic Direction of Causation modeling was used to test the direction of each relationship. Findings were validated by longitudinal cross-lagged panel modeling. %BMIp95 correlated with impulsivity, motivation, psychopathology, eating behavior, and cognitive tests (executive functioning, language, memory, perception, working memory). Greater %BMIp95 was also associated with reduced cortical thickness in frontal and temporal brain areas but with increased thickness in parietal and occipital areas. Similar although weaker patterns emerged for cortical surface area and volume. Behavioral genetic modeling suggested causal effects of %BMIp95 on eating behavior (β = 0.26), cognition (β = 0.05), cortical thickness (β = 0.15), and cortical surface area (β = 0.07). Personality/psychopathology (β = 0.09) and eating behavior (β = 0.16) appeared to influence %BMIp95. Longitudinal evidence broadly supported these findings. Results regarding cortical volume were inconsistent. Results supported causal effects of obesity on brain functioning and morphology. The present study highlights the importance of physical health for brain development and may inform interventions aimed at preventing or reducing pediatric obesity. RESEARCH HIGHLIGHTS: A continuous measure related to obesity, %BMIp95, has correlations with various measures of brain functioning and structure Behavioral genetic and longitudinal modeling suggest causal links from personality, psychopathology, and eating behavior to %BMIp95 Results also indicate directional links from %BMIp95 to eating behavior, cognition, cortical thickness, and cortical surface area Obesity may play a role for healthy brain development during childhood.

Explainable Brain Age Prediction using coVariance Neural Networks

In computational neuroscience, there has been an increased interest in developing machine learning algorithms that leverage brain imaging data to provide estimates of "brain age" for an individual. Importantly, the discordance between brain age and chronological age (referred to as "brain age gap") can capture accelerated aging due to adverse health conditions and therefore, can reflect increased vulnerability towards neurological disease or cognitive impairments. However, widespread adoption of brain age for clinical decision support has been hindered due to lack of transparency and methodological justifications in most existing brain age prediction algorithms. In this paper, we leverage coVariance neural networks (VNN) to propose an explanation-driven and anatomically interpretable framework for brain age prediction using cortical thickness features. Specifically, our brain age prediction framework extends beyond the coarse metric of brain age gap in Alzheimer's disease (AD) and we make two important observations: (i) VNNs can assign anatomical interpretability to elevated brain age gap in AD by identifying contributing brain regions, (ii) the interpretability offered by VNNs is contingent on their ability to exploit specific eigenvectors of the anatomical covariance matrix. Together, these observations facilitate an explainable and anatomically interpretable perspective to the task of brain age prediction.

Machine-learning-derived heart and brain age are independently associated with cognition

BACKGROUND AND PURPOSE

A heart age biomarker has been developed using deep neural networks applied to electrocardiograms. Whether this biomarker is associated with cognitive function was investigated.

METHODS

Using 12-lead electrocardiograms, heart age was estimated for a population-based sample (N = 7779, age 40-85 years, 45.3% men). Associations between heart delta age (HDA) and cognitive test scores were studied adjusted for cardiovascular risk factors. In addition, the relationship between HDA, brain delta age (BDA) and cognitive test scores was investigated in mediation analysis.

RESULTS

Significant associations between HDA and the Word test, Digit Symbol Coding Test and tapping test scores were found. HDA was correlated with BDA (Pearson's r = 0.12, p = 0.0001). Moreover, 13% (95% confidence interval 3-36) of the HDA effect on the tapping test score was mediated through BDA.

DISCUSSION

Heart delta age, representing the cumulative effects of life-long exposures, was associated with brain age. HDA was associated with cognitive function that was minimally explained through BDA.

Brain Specific Estrogen Ameliorates Cognitive Effects of Surgical Menopause in Mice

Menopause is a major endocrinological shift that leads to an increased vulnerability to the risk factors for cognitive impairment and dementia. This is thought to be due to the loss of circulating estrogens, which exert many potent neuroprotective effects in the brain. Systemic replacement of estrogen post-menopause has many limitations, including increased risk for estrogen-sensitive cancers. A more promising therapeutic approach therefore might be to deliver estrogen only to the brain thus limiting adverse peripheral side effects. We examined whether we could enhance cognitive performance by delivering estrogen exclusively to the brain in post-menopausal mice. We modeled surgical menopause via bilateral ovariectomy (OVX). We treated mice with the pro-drug 10β,17β-dihydroxyestra-1,4-dien-3-one (DHED), which can be administered systemically but is converted to 17β-estradiol only in the brain. Young (2.5-month) and middle-aged (11-month-old) female C57BL/6J mice received ovariectomy and a subcutaneous implant containing vehicle (cholesterol) or DHED. At 3.5 months old (young group) and 14.5 months old (middle-aged group), mice underwent behavior testing to assess memory. DHED did not significantly alter metabolic status in middle-aged, post-menopausal mice. In both young and middle-aged mice, the brain-specific estrogen DHED improved spatial memory. Additional testing in middle-aged mice also showed that DHED improved working and recognition memory. These promising results lay the foundation for future studies aimed at determining if this intervention is as efficacious in models of dementia that have comorbid risk factors.

Brain age and cognitive functioning in first-episode bipolar disorder

BACKGROUND

There is significant heterogeneity in cognitive function in patients with bipolar I disorder (BDI); however, there is a dearth of research into biological mechanisms that might underlie cognitive heterogeneity, especially at disease onset. To this end, this study investigated the association between accelerated or delayed age-related brain structural changes and cognition in early-stage BDI.

METHODS

First episode patients with BDI (n = 80) underwent cognitive assessment to yield demographically normed composite global and domain-specific scores in verbal memory, non-verbal memory, working memory, processing speed, attention, and executive functioning. Structural magnetic resonance imaging data were also collected from all participants and subjected to machine learning to compute the brain-predicted age difference (brainPAD), calculated by subtracting chronological age from age predicted by neuroimaging data (positive brainPAD values indicating age-related acceleration in brain structural changes and negative values indicating delay). Patients were divided into tertiles based on brainPAD values, and cognitive performance compared amongst tertiles with ANCOVA.

RESULTS

Patients in the lowest (delayed) tertile of brainPAD values (brainPAD range -17.9 to -6.5 years) had significantly lower global cognitive scores (p = 0.025) compared to patients in the age-congruent tertile (brainPAD range -5.3 to 2.4 yrs), and significantly lower verbal memory scores (p = 0.001) compared to the age-congruent and accelerated (brainPAD range 2.8 to 16.1 yrs) tertiles.

CONCLUSION

These results provide evidence linking cognitive dysfunction in the early stage of BDI to apparent delay in typical age-related brain changes. Further studies are required to assess how age-related brain changes and cognitive functioning evolve over time.

Neuro-Vulnerability in Energy Metabolism Regulation: A Comprehensive Narrative Review

This comprehensive narrative review explores the concept of neuro-vulnerability in energy metabolism regulation and its implications for metabolic disorders. The review highlights the complex interactions among the neural, hormonal, and metabolic pathways involved in the regulation of energy metabolism. The key topics discussed include the role of organs, hormones, and neural circuits in maintaining metabolic balance. The review investigates the association between neuro-vulnerability and metabolic disorders, such as obesity, insulin resistance, and eating disorders, considering genetic, epigenetic, and environmental factors that influence neuro-vulnerability and subsequent metabolic dysregulation. Neuroendocrine interactions and the neural regulation of food intake and energy expenditure are examined, with a focus on the impact of neuro-vulnerability on appetite dysregulation and altered energy expenditure. The role of neuroinflammation in metabolic health and neuro-vulnerability is discussed, emphasizing the bidirectional relationship between metabolic dysregulation and neuroinflammatory processes. This review also evaluates the use of neuroimaging techniques in studying neuro-vulnerability and their potential applications in clinical settings. Furthermore, the association between neuro-vulnerability and eating disorders, as well as its contribution to obesity, is examined. Potential therapeutic interventions targeting neuro-vulnerability, including pharmacological treatments and lifestyle modifications, are reviewed. In conclusion, understanding the concept of neuro-vulnerability in energy metabolism regulation is crucial for addressing metabolic disorders. This review provides valuable insights into the underlying neurobiological mechanisms and their implications for metabolic health. Targeting neuro-vulnerability holds promise for developing innovative strategies in the prevention and treatment of metabolic disorders, ultimately improving metabolic health outcomes.

Associations Between Socioeconomic Status, Obesity, Cognition, and White Matter Microstructure in Children

Importance

Lower neighborhood and household socioeconomic status (SES) are associated with negative health outcomes and altered brain structure in children. It is unclear whether such findings extend to white matter and via what mechanisms.

Objective

To assess whether and how neighborhood and household SES are independently associated with children's white matter microstructure and examine whether obesity and cognitive performance (reflecting environmental cognitive and sensory stimulation) are plausible mediators.

Design, Setting, and Participants

This cross-sectional study used baseline data from participants in the Adolescent Brain Cognitive Development (ABCD) study. Data were collected at 21 US sites, and school-based recruitment was used to represent the US population. Children aged 9 to 11 years and their parents or caregivers completed assessments between October 1, 2016, and October 31, 2018. After exclusions, 8842 of 11 875 children in the ABCD study were included in the analyses. Data analysis was conducted from July 11 to December 19, 2022.

Exposures

Neighborhood disadvantage was derived from area deprivation indices at participants' primary residence. Household SES factors were total income and highest parental educational attainment.

Main Outcomes and Measures

A restriction spectrum imaging (RSI) model was used to quantify restricted normalized directional (RND; reflecting oriented myelin organization) and restricted normalized isotropic (RNI; reflecting glial and neuronal cell bodies) diffusion in 31 major white matter tracts. The RSI measurements were scanner harmonized. Obesity was assessed through body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), age- and sex-adjusted BMI z scores, and waist circumference, and cognition was assessed through the National Institutes of Health Toolbox Cognition Battery. Analyses were adjusted for age, sex, pubertal development stage, intracranial volume, mean head motion, and twin or siblingship.

Results

Among 8842 children, 4543 (51.4%) were boys, and the mean (SD) age was 9.9 (0.7) years. Linear mixed-effects models revealed that greater neighborhood disadvantage was associated with lower RSI-RND in the left superior longitudinal fasciculus (β = -0.055; 95% CI, -0.081 to -0.028) and forceps major (β = -0.040; 95% CI, -0.067 to -0.013). Lower parental educational attainment was associated with lower RSI-RND in the bilateral superior longitudinal fasciculus (eg, right hemisphere: β = 0.053; 95% CI, 0.025-0.080) and bilateral corticospinal or pyramidal tract (eg, right hemisphere: β = 0.042; 95% CI, 0.015-0.069). Structural equation models revealed that lower cognitive performance (eg, lower total cognition score and higher neighborhood disadvantage: β = -0.012; 95% CI, -0.016 to -0.009) and greater obesity (eg, higher BMI and higher neighborhood disadvantage: β = -0.004; 95% CI, -0.006 to -0.001) partially accounted for the associations between SES and RSI-RND. Lower household income was associated with higher RSI-RNI in most tracts (eg, right inferior longitudinal fasciculus: β = -0.042 [95% CI, -0.073 to -0.012]; right anterior thalamic radiations: β = -0.045 [95% CI, -0.075 to -0.014]), and greater neighborhood disadvantage had similar associations in primarily frontolimbic tracts (eg, right fornix: β = 0.046 [95% CI, 0.019-0.074]; right anterior thalamic radiations: β = 0.045 [95% CI, 0.018-0.072]). Lower parental educational attainment was associated with higher RSI-RNI in the forceps major (β = -0.048; 95% CI, -0.077 to -0.020). Greater obesity partially accounted for these SES associations with RSI-RNI (eg, higher BMI and higher neighborhood disadvantage: β = 0.015; 95% CI, 0.011-0.020). Findings were robust in sensitivity analyses and were corroborated using diffusion tensor imaging.

Conclusions and Relevance

In this cross-sectional study, both neighborhood and household contexts were associated with white matter development in children, and findings suggested that obesity and cognitive performance were possible mediators in these associations. Future research on children's brain health may benefit from considering these factors from multiple socioeconomic perspectives.

Sex differences in the effects of high fat diet on underlying neuropathology in a mouse model of VCID

BACKGROUND

Damage to the cerebral vasculature can lead to vascular contributions to cognitive impairment and dementia (VCID). A reduction in blood flow to the brain leads to neuropathology, including neuroinflammation and white matter lesions that are a hallmark of VCID. Mid-life metabolic disease (obesity, prediabetes, or diabetes) is a risk factor for VCID which may be sex-dependent (female bias).

METHODS

We compared the effects of mid-life metabolic disease between males and females in a chronic cerebral hypoperfusion mouse model of VCID. C57BL/6J mice were fed a control or high fat (HF) diet starting at ~ 8.5 months of age. Three months after diet initiation, sham or unilateral carotid artery occlusion surgery (VCID model) was performed. Three months later, mice underwent behavior testing and brains were collected to assess pathology.

RESULTS

We have previously shown that in this VCID model, HF diet causes greater metabolic impairment and a wider array of cognitive deficits in females compared to males. Here, we report on sex differences in the underlying neuropathology, specifically white matter changes and neuroinflammation in several areas of the brain. White matter was negatively impacted by VCID in males and HF diet in females, with greater metabolic impairment correlating with less myelin markers in females only. High fat diet led to an increase in microglia activation in males but not in females. Further, HF diet led to a decrease in proinflammatory cytokines and pro-resolving mediator mRNA expression in females but not males.

CONCLUSIONS

The current study adds to our understanding of sex differences in underlying neuropathology of VCID in the presence of a common risk factor (obesity/prediabetes). This information is crucial for the development of effective, sex-specific therapeutic interventions for VCID.

Brain structural and functional alterations in individuals with combined overweight/obesity and mood disorders: A systematic review of neuroimaging studies

Growing evidence suggests there is a bidirectional relationship between depression and obesity, which are associated with structural and functional brain abnormalities. However, the underlying neurobiological mechanisms subserving the foregoing associations have yet to be characterized. It is necessary to summarize the neuroplastic brain changes in relation to depression and obesity. We systematically searched articles from 1990 to November 2022 on databases including MEDLINE/PubMed, Web of Science, PsycINFO. Only neuroimaging studies within the scope of potential differences in brain function and structure in individuals with depression and obesity/ BMI changes were included. Twenty-four eligible studies were included in the review herein, consisting of 17 studies reporting changes in brain structure, 4 studies reporting abnormal brain function, and 3 studies reporting both changes in brain structure and function. Results indicated an interaction between depression and obesity on brain functions, and their influence on brain structure is both extensive and specific. Overall, reduced whole brain, intracranial, and gray matter volume (e.g. frontal, temporal gyri, thalamic, and hippocampal) and impaired white matter integrity was observed in persons with depression and obesity comorbidity. Additional evidence on resting state fMRI reveals select brain regions associated with cognitive control, emotion regulation, and reward functions. Due to the diversity of tasks in task fMRI, the distinct neural activation patterns are revealed separately. The bidirectional relationship between depression and obesity reflects different characteristics in brain structure and function. Longitudinal designs should be reinforced in follow-up studies.

The effect of weight loss following 18 months of lifestyle intervention on brain age assessed with resting-state functional connectivity

Background

Obesity negatively impacts multiple bodily systems, including the central nervous system. Retrospective studies that estimated chronological age from neuroimaging have found accelerated brain aging in obesity, but it is unclear how this estimation would be affected by weight loss following a lifestyle intervention.

Methods

In a sub-study of 102 participants of the Dietary Intervention Randomized Controlled Trial Polyphenols Unprocessed Study (DIRECT-PLUS) trial, we tested the effect of weight loss following 18 months of lifestyle intervention on predicted brain age based on magnetic resonance imaging (MRI)-assessed resting-state functional connectivity (RSFC). We further examined how dynamics in multiple health factors, including anthropometric measurements, blood biomarkers, and fat deposition, can account for changes in brain age.

Results

To establish our method, we first demonstrated that our model could successfully predict chronological age from RSFC in three cohorts (n=291;358;102). We then found that among the DIRECT-PLUS participants, 1% of body weight loss resulted in an 8.9 months' attenuation of brain age. Attenuation of brain age was significantly associated with improved liver biomarkers, decreased liver fat, and visceral and deep subcutaneous adipose tissues after 18 months of intervention. Finally, we showed that lower consumption of processed food, sweets and beverages were associated with attenuated brain age.

Conclusions

Successful weight loss following lifestyle intervention might have a beneficial effect on the trajectory of brain aging.

Funding

The German Research Foundation (DFG), German Research Foundation - project number 209933838 - SFB 1052; B11, Israel Ministry of Health grant 87472511 (to I Shai); Israel Ministry of Science and Technology grant 3-13604 (to I Shai); and the California Walnuts Commission 09933838 SFB 105 (to I Shai).

The Preventive Effect of Exercise and Oral Branched-Chain Amino Acid Supplementation on Obesity-Induced Brain Changes in Ldlr−/−.Leiden Mice

Exercise and dietary interventions are promising approaches to tackle obesity and its obesogenic effects on the brain. We investigated the impact of exercise and possible synergistic effects of exercise and branched-chain amino acids (BCAA) supplementation on the brain and behavior in high-fat-diet (HFD)-induced obese Ldlr−/−.Leiden mice. Baseline measurements were performed in chow-fed Ldlr−/−.Leiden mice to assess metabolic risk factors, cognition, and brain structure using magnetic resonance imaging. Thereafter, a subgroup was sacrificed, serving as a healthy reference. The remaining mice were fed an HFD and divided into three groups: (i) no exercise, (ii) exercise, or (iii) exercise and dietary BCAA. Mice were followed for 6 months and aforementioned tests were repeated. We found that exercise alone changed cerebral blood flow, attenuated white matter loss, and reduced neuroinflammation compared to non-exercising HFD-fed mice. Contrarily, no favorable effects of exercise on the brain were found in combination with BCAA, and neuroinflammation was increased. However, cognition was slightly improved in exercising mice on BCAA. Moreover, BCAA and exercise increased the percentage of epididymal white adipose tissue and muscle weight, decreased body weight and fasting insulin levels, improved the circadian rhythm, and transiently improved grip strength. In conclusion, BCAA should be supplemented with caution, although beneficial effects on metabolism, behavior, and cognition were observed.

Associations between socioeconomic status and white matter microstructure in children: indirect effects via obesity and cognition

Importance

Both neighborhood and household socioeconomic disadvantage relate to negative health outcomes and altered brain structure in children. It is unclear whether such findings extend to white matter development, and via what mechanisms socioeconomic status (SES) influences the brain.

Objective

To test independent associations between neighborhood and household SES indicators and white matter microstructure in children, and examine whether body mass index and cognitive function (a proxy of environmental cognitive/sensory stimulation) may plausibly mediate these associations.

Design

This cross-sectional study used baseline data from the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing 10-year cohort study tracking child health.

Setting

School-based recruitment at 21 U.S. sites.

Participants

Children aged 9 to 11 years and their parents/caregivers completed baseline assessments between October 1 st , 2016 and October 31 st , 2018. Data analysis was conducted from July to December 2022.

Exposures

Neighborhood disadvantage was derived from area deprivation indices at primary residence. Household SES indicators were total income and the highest parental education attainment.

Main Outcomes and Measures

Thirty-one major white matter tracts were segmented from diffusion-weighted images. The Restriction Spectrum Imaging (RSI) model was implemented to measure restricted normalized directional (RND; reflecting oriented myelin organization) and isotropic (RNI; reflecting glial/neuronal cell bodies) diffusion in each tract. Obesity-related measures were body mass index (BMI), BMI z -scores, and waist circumference, and cognitive performance was assessed using the NIH Toolbox Cognition Battery. Linear mixed-effects models tested the associations between SES indicators and scanner-harmonized RSI metrics. Structural equation models examined indirect effects of obesity and cognitive performance in the significant associations between SES and white mater microstructure summary principal components. Analyses were adjusted for age, sex, pubertal development stage, intracranial volume, and head motion.

Results

The analytical sample included 8842 children (4299 [48.6%] girls; mean age [SD], 9.9 [0.7] years). Greater neighborhood disadvantage and lower parental education were independently associated with lower RSI-RND in forceps major and corticospinal/pyramidal tracts, and had overlapping associations in the superior longitudinal fasciculus. Lower cognition scores and greater obesity-related measures partially accounted for these SES associations with RSI-RND. Lower household income was related to higher RSI-RNI in almost every tract, and greater neighborhood disadvantage had similar effects in primarily frontolimbic tracts. Lower parental education was uniquely linked to higher RSI-RNI in forceps major. Greater obesity-related measures partially accounted for these SES associations with RSI-RNI. Findings were robust in sensitivity analyses and mostly corroborated using traditional diffusion tensor imaging (DTI).

Conclusions and Relevance

These cross-sectional results demonstrate that both neighborhood and household contexts are relevant to white matter development in children, and suggest cognitive performance and obesity as possible pathways of influence. Interventions targeting obesity reduction and improving cognition from multiple socioeconomic angles may ameliorate brain health in low-SES children.

Key Points

Question: Are neighborhood and household socioeconomic levels associated with children’s brain white matter microstructure, and if so, do obesity and cognitive performance (reflecting environmental stimulation) mediate the associations?Findings: In a cohort of 8842 children, higher neighborhood disadvantage, lower household income, and lower parental education had independent and overlapping associations with lower restricted directional diffusion and greater restricted isotropic diffusion in white matter. Greater body mass index and poorer cognitive performance partially mediated these associations.Meaning: Both neighborhood and household poverty may contribute to altered white matter development in children. These effects may be partially explained by obesity incidence and poorer cognitive performance.

Naringin Alleviates Glucose-Induced Aging by Reducing Fat Accumulation and Promoting Autophagy in Caenorhabditis elegans

Naringin (Nar) is a dihydroflavonoid compound, widely found in citrus fruit and used in Chinese herbal medicine. As a phytochemical, it acts as a dietary supplement that can delay aging and prevent aging-related disease, such as obesity and diabetes. However, its exact mechanism remains unclear. In this study, the high-glucose-induced (HGI) Caenorhabditis elegans model was used to evaluate the anti-aging and anti-obesity effects of Nar. The mean lifespan and fast movement span of HGI worms were extended roughly 24% and 11%, respectively, by Nar treatment. Oil red O staining revealed a significant reduction in fat accumulation and dFP::LGG-labeled worms showed the promotion of autophagy. Additionally, whole transcriptome sequencing and gene set variation analysis suggested that Nar upregulated the lipid biosynthesis and metabolism pathways, as well as the TGF-β, Wnt and longevity signaling pathways. Protein-protein interaction (PPI) network analysis identified hub genes in these pathways for further analysis. Mutant worms and RNA interference were used to study mechanisms; the suppression of hlh-30, lgg-1, unc-51, pha-4, skn-1 and yap-1 disabled the fat-lowering, lifespan-prolonging, and health-promoting properties of Nar. Collectively, our findings indicate that Nar plays an important role in alleviating HGI-aging and anti-obesity effects by reducing fat accumulation and promoting autophagy.

Relationship Between Weight-Change Patterns and Cognitive Function: A Retrospective Study

BACKGROUND

Obesity has been linked to cognitive impairment. However, how changes in body mass index (BMI) over the life course influence cognitive function remains unclear.

OBJECTIVE

The influence of distinct weight-change patterns from young adulthood to midlife and late adulthood on cognitive function in older adults was explored.

METHODS

A total of 5,809 individuals aged≥60 years were included and categorized into four groups on the basis of BMI change patterns. Cognitive function was assessed using four cognition tests in the baseline survey. The relationship between the weight-change patterns and cognition was evaluated using regression models.

RESULTS

In comparison with participants who remained at non-obese, those moving from the non-obese to obese weight-change pattern from young (25 years of age) to middle adulthood showed lower Digit Symbol Substitution Test (DSST) scores (β= -1.28; 95% confidence interval [CI]: -2.24 to -0.32). A non-obese to obese change pattern from age 25 years of age to 10 years before baseline was associated with a higher risk of DSST impairment (odds ratio = 1.40; 95% CI: 1.09 to 1.79). In comparison with participants whose heaviest weight was recorded after 60 years of age, those with the heaviest weight between 18 and 40 years of age had lower DSST scores (β= -1.46; 95% CI: -2.77 to -1.52).

CONCLUSION

Our results suggest that the transition from the non-obese to obese category in early adulthood and appearance of the heaviest weight between 18 and 40 years of age are associated with lower cognitive function in later life.

Distinct components of cardiovascular health are linked with age-related differences in cognitive abilities

Cardiovascular ageing contributes to cognitive impairment. However, the unique and synergistic contributions of multiple cardiovascular factors to cognitive function remain unclear because they are often condensed into a single composite score or examined in isolation. We hypothesized that vascular risk factors, electrocardiographic features and blood pressure indices reveal multiple latent vascular factors, with independent contributions to cognition. In a population-based deep-phenotyping study (n = 708, age 18-88), path analysis revealed three latent vascular factors dissociating the autonomic nervous system response from two components of blood pressure. These three factors made unique and additive contributions to the variability in crystallized and fluid intelligence. The discrepancy in fluid relative to crystallized intelligence, indicative of cognitive decline, was associated with a latent vascular factor predominantly expressing pulse pressure. This suggests that higher pulse pressure is associated with cognitive decline from expected performance. The effect was stronger in older adults. Controlling pulse pressure may help to preserve cognition, particularly in older adults. Our findings highlight the need to better understand the multifactorial nature of vascular aging.

Modifiable risk factors of dementia linked to excitation-inhibition imbalance

Recent evidence identifies 12 potentially modifiable risk factors for dementia to which 40% of dementia cases are attributed. While the recognition of these risk factors has paved the way for the development of new prevention measures, the link between these risk factors and the underlying pathophysiology of dementia is yet not well understood. A growing number of recent clinical and preclinical studies support a role of Excitation-Inhibition (E-I) imbalance in the pathophysiology of dementia. In this review, we aim to propose a conceptual model on the links between the modifiable risk factors and the E-I imbalance in dementia. This model, which aims to address the current gap in the literature, is based on 12 mediating common mechanisms: the hypothalamic-pituitary-adrenal (HPA) axis dysfunction, neuroinflammation, oxidative stress, mitochondrial dysfunction, cerebral hypo-perfusion, blood-brain barrier (BBB) dysfunction, beta-amyloid deposition, elevated homocysteine level, impaired neurogenesis, tau tangles, GABAergic dysfunction, and glutamatergic dysfunction. We believe this model serves as a framework for future studies in this field and facilitates future research on dementia prevention, discovery of new biomarkers, and developing new interventions.

Improving performance robustness of subject-based brain segmentation software

Purpose

Artificial intelligence (AI)-based image analysis tools to quantify the brain have become commercialized. However, insufficient data for learning and scanner specificity is a limitation for achieving high quality. In the present study, the performance of personalized brain segmentation software when applied to multicenter data using an AI model trained on data from a single institution was improved.

Methods

Preindicators of brain white matter (WM) information from the training dataset were utilized for preprocessing. During learning, data of cognitively normal (CN) individuals from a single center were utilized, and data of CN individuals and Alzheimer disease (AD) patients enrolled in multiple centers were considered the test set.

Results

The preprocessing based on the preindicator (dice similarity coefficient [DSC], 0.8567) resulted in a better performance than without (DSC, 0.7921). The standard deviation (SD) of the WM region intensity (DSC, 0.8303) had a more substantial influence on the performance than the average intensity (DSC, 0.6591). When the SD of the test data WM intensity was smaller than the learning data, the performance improved (0.03 increase in lower SD, 0.05 decrease in higher SD). Furthermore, preindicator-based pretreatment increased the correlation of mean cortical thickness of the entire gray matter between Atroscan and FreeSurfer, and data augmentation without preprocessing did not.Both preindicator processing and data augmentation improved the correlation coefficient from 0.7584 to 0.8165.

Conclusion

Data augmentation and preindicator-based preprocessing of training data can improve the performance of AI-based brain segmentation software, both increasing the generalizability and stability of brain segmentation software.

Correlation between Body Mass Index and Cognitive Function in Patients with Atrial Fibrillation

Background

Evidence regarding the relationship between body mass index (BMI) and cognitive function was limited. Therefore, the objective of this research is to investigate whether BMI is independently related to cognitive function in Chinese patients with atrial fibrillation after adjusting for other covariates.

Methods

The present study is a cross-sectional study. A total of 281 patients with atrial fibrillation who were hospitalized at the Affiliated Hospital of Jining Medical University in Shandong Province from January 2021 to November 2021 were included in the study. The target independent variable and the dependent variable were BMI and cognitive function in patients with atrial fibrillation, respectively. The patients' general information, BMI, past history, medication history, and other disease-related data were collected. The Montreal cognitive assessment scale (MoCA) was used to evaluate cognitive function.

Results

A total of 244 patients with atrial fibrillation were collected in this study, with an average age of (67.28 ± 10.33) years, of whom 55.3% were male. The average BMI was (25.33 ± 4.27) kg/m², and the average cognitive function score was (19.25 ± 6.88) points. The results of the smooth curve fitting and threshold effect tests showed that there was a curve correlation between BMI and cognitive function score, and its inflection point was 24.56 kg/m². To the left of the inflection point, the relationship was significant; the effect size and the confidence interval were 0.43 and 0.01-0.85, respectively. To the right of the inflection point, there was no significant correlation between BMI and cognitive function (P=0.152).

Conclusion

When BMI is lower than 24.56 kg/m², the cognitive function score increases by 0.43 points for each unit increase in BMI in patients with atrial fibrillation. An increase in BMI at this time is a protective factor for cognitive function. Within the normal range of BMI, the higher the BMI in atrial fibrillation patients, the higher the cognitive function score. We encourage atrial fibrillation patients with normal BMI to maintain their current weight.

Prediction of brain age using quantitative parameters of synthetic magnetic resonance imaging

Objective

Brain tissue changes dynamically during aging. The purpose of this study was to use synthetic magnetic resonance imaging (syMRI) to evaluate the changes in relaxation values in different brain regions during brain aging and to construct a brain age prediction model.

Materials and methods

Quantitative MRI was performed on 1,000 healthy people (≥ 18 years old) from September 2020 to October 2021. T1, T2 and proton density (PD) values were simultaneously measured in 17 regions of interest (the cerebellar hemispheric cortex, pons, amygdala, hippocampal head, hippocampal tail, temporal lobe, occipital lobe, frontal lobe, caudate nucleus, lentiform nucleus, dorsal thalamus, centrum semiovale, parietal lobe, precentral gyrus, postcentral gyrus, substantia nigra, and red nucleus). The relationship between the relaxation values and age was investigated. In addition, we analyzed the relationship between brain tissue values and sex. Finally, the participants were divided into two age groups: < 60 years old and ≥ 60 years old. Logistic regression analysis was carried out on the two groups of data. According to the weight of related factors, a brain age prediction model was established and verified.

Results

We obtained the specific reference value range of different brain regions of individuals in different age groups and found that there were differences in relaxation values in brain tissue between different sexes in the same age group. Moreover, the relaxation values of most brain regions in males were slightly higher than those in females. In the study of age and brain relaxation, it was found that brain relaxation values were correlated with age. The T1 values of the centrum semiovale increased with age, the PD values of the centrum semiovale increased with age, while the T2 values of the caudate nucleus and lentiform nucleus decreased with age. Seven brain age prediction models were constructed with high sensitivity and specificity, among which the combined T1, T2 and PD values showed the best prediction efficiency. In the training set, the area under the curve (AUC), specificity and sensitivity were 0.959 [95% confidence interval (CI): 0.945–0.974], 91.51% and 89.36%, respectively. In the test cohort, the above indicators were 0.916 (95% CI: 0.882–0.951), 89.24% and 80.33%, respectively.

Conclusion

Our study provides specific reference ranges of T1, T2, and PD values in different brain regions from healthy adults of different ages. In addition, there are differences in brain relaxation values in some brain regions between different sexes, which help to provide new ideas for brain diseases that differ according to sex. The brain age model based on synthetic MRI is helpful to determine brain age.

Cerebral Blood Flow Alterations and Obesity: A Systematic Review and Meta-Analysis

Background: Reduction in cerebral blood flow (CBF) plays an essential role in the cognitive impairment and dementia in obesity. However, current conclusions regarding CBF changes in patients with obesity are inconsistent. Objective: A systematic review and meta-analysis was performed to evaluate the relationship between obesity and CBF alterations. Methods: We systematically screened published cross-sectional and longitudinal studies focusing on the differences in CBF between obese and normal-weight individuals. Eighteen studies including 24,866 participants, of which seven articles reported longitudinal results, were evaluated in the present study. Results: The results of the meta-analysis showed that in cross-sectional studies, body mass index (BMI) was negatively associated with CBF (β= –0.31, 95% confidence interval [CI]: –0.44, –0.19). Moreover, this systematic review demonstrated that obese individuals showed global and regional reductions in the CBF and increased CBF in diverse functional areas of the frontal lobe, including the prefrontal cortex, left frontal superior orbital, right frontal mid-orbital cortex, and left premotor superior frontal gyrus. Conclusion: Our findings suggest that BMI, rather than waist circumference and waist-to-hip ratio, is inversely associated with CBF in cross-sectional studies. The CBF of obese individuals showed global and regional reductions, including the frontal lobe, temporal and parietal lobes, cerebellum, hippocampus, and thalamus.

Mechanisms linking obesity and its metabolic comorbidities with cerebral grey and white matter changes

Obesity is a preventable risk factor for cerebrovascular disorders and it is associated with cerebral grey and white matter changes. Specifically, individuals with obesity show diminished grey matter volume and thickness, which seems to be more prominent among fronto-temporal regions in the brain. At the same time, obesity is associated with lower microstructural white matter integrity, and it has been found to precede increases in white matter hyperintensity load. To date, however, it is unclear whether these findings can be attributed solely to obesity or whether they are a consequence of cardiometabolic complications that often co-exist with obesity, such as low-grade systemic inflammation, hypertension, insulin resistance, or dyslipidemia. In this narrative review we aim to provide a comprehensive overview of the potential impact of obesity and a number of its cardiometabolic consequences on brain integrity, both separately and in synergy with each other. We also identify current gaps in knowledge and outline recommendations for future research.

Impact of Weight Loss on Brain Age: Improved Brain Health Following Bariatric Surgery

Individuals living with obesity tend to have increased brain age, reflecting poorer brain health likely due to grey and white matter atrophy related to obesity. However, it is unclear if older brain age associated with obesity can be reversed following weight loss and cardiometabolic health improvement. The aim of this study was to assess the impact of weight loss and cardiometabolic improvement following bariatric surgery on brain health, as measured by change in brain age estimated based on voxel-based morphometry (VBM) measurements. We used three distinct datasets to perform this study: 1) CamCAN dataset to train the brain age prediction model, 2) Human Connectome Project (HCP) dataset to investigate whether individuals with obesity have greater brain age than individuals with normal weight, and 3) pre-surgery, as well as 4, 12, and 24 month post-surgery data from participants (n=87, age: 44.0±9.2 years, BMI: 43.9±4.2 kg/m2) who underwent a bariatric surgery to investigate whether weight loss and cardiometabolic improvement as a result of bariatric surgery lowers the brain age. As expected, our results from the HCP dataset showed a higher brain age for individuals with obesity compared to individuals with normal weight (T-value = 7.08, p-value < 0.0001). We also found significant improvement in brain health, indicated by a decrease of 2.9 and 5.6 years in adjusted delta age at 12 and 24 months following bariatric surgery compared to baseline (p-value < 0.0005 for both). While the overall effect seemed to be driven by a global change across all brain regions and not from a specific region, our exploratory analysis showed lower delta age in certain brain regions (mainly in somatomotor, visual, and ventral attention networks) at 24 months. This reduced age was also associated with post-surgery improvements in BMI, systolic/diastolic blood pressure, and HOMA-IR (T-value_BMI=4.29, T-value_SBP=4.67, T-value_DBP=4.12, T-value_HOMA-IR=3.16, all p-values < 0.05). In conclusion, these results suggest that obesity-related brain health abnormalities (as measured by delta age) might be reversed by bariatric surgery-induced weight loss and widespread improvements in cardiometabolic alterations.

Alteration in peritoneal cells with the chemokine CX3CL1 reverses age-associated impairment of recognition memory

Cognitive function progressively declines with advancing age. The aging process can be promoted by obesity and attenuated by exercise. Both conditions affect levels of the chemokine CX3CL1 in peripheral tissues; however, its role in cognitive aging is unknown. In the current study, we administered CX3CL1 into the peritoneal cavity of aged mice to investigate its impact on the aging process. In the peritoneal cavity, CX3CL1 not only reversed the age-associated accumulation of cells expressing the senescence marker p16^INK4a but also increased peritoneal phagocytic activity, indicating that CX3CL1 affected the phenotypes of peritoneal cells. In the hippocampus of aged mice, intraperitoneal administration of CX3CL1 increased the number of Type-2 neural stem cells and promoted brain-derived neurotrophic factor (BDNF) expression. This treatment, furthermore, improved novel object recognition memory impaired with advancing age. Intraperitoneal transplantation of peritoneal cells from CX3CL1-treated aged mice improved novel object recognition memory in recipient aged mice. It indicates that peritoneal cells have a critical role in the CX3CL1-induced improvement of recognition memory in aged mice. Vagotomy inhibited the CX3CL1-induced increase in BDNF expression, demonstrating that the vagus nerve is involved in the hippocampal BDNF expression induced by intraperitoneal administration of CX3CL1. Thus, our results demonstrate that a novel connection among the peritoneal cells, the vagus nerve, and the hippocampus can reverse the age-associated decline in recognition memory.

Brain Age Difference at Baseline Predicts Clinical Dementia Rating Change in Approximately Two Years

BACKGROUND

The Clinical Dementia Rating (CDR) has been widely used to assess dementia severity, but it is limited in predicting dementia progression, thus unable to advise preventive measures to those who are at high risk.

OBJECTIVE

Predicted age difference (PAD) was proposed to predict CDR change.

METHODS

All diffusion magnetic resonance imaging and CDR scores were obtained from the OASIS-3 databank. A brain age model was trained by a machine learning algorithm using the imaging data of 258 cognitively healthy adults. Two diffusion indices, i.e., mean diffusivity and fractional anisotropy, over the whole brain white matter were extracted to serve as the features for model training. The validated brain age model was applied to a longitudinal cohort of 217 participants who had CDR = 0 (CDR0), 0.5 (CDR0.5), and 1 (CDR1) at baseline. Participants were grouped according to different baseline CDR and their subsequent CDR in approximately 2 years of follow-up. PAD was compared between different groups with multiple comparison correction.

RESULTS

PADs were significantly different among participants with different baseline CDRs. PAD in participants with relatively stable CDR0.5 was significantly smaller than PAD in participants who had CDR0.5 at baseline but converted to CDR1 in the follow-up. Similarly, participants with relatively stable CDR0 had significantly smaller PAD than those who were CDR0 at baseline but converted to CDR0.5 in the follow-up.

CONCLUSION

Our results imply that PAD might be a potential imaging biomarker for predicting CDR outcomes in patients with CDR0 or CDR0.5.