Lower brain glucose metabolism in normal ageing is predominantly frontal and temporal: A systematic review and pooled effect size and activation likelihood estimates meta-analyses

Impaired brain ability of older adults to transit and persist to latent states with well-organized structures at wakeful rest

The intrinsic brain functional network organization continuously changes with aging. By integrating spatial and temporal information, the process of how brain networks temporally reconfigure and remain well-organized spatial structure largely reflects the brain function, thereby holds the potential to capture its age-related declines. In this study, we examined the spatiotemporal brain dynamics from resting-state functional Magnetic Resonance Imaging (fMRI) data of healthy young and older adults using a Hidden Markov Model (HMM). Six brain states were generated by HMM, with the young group showing higher fractional occupancy and mean dwell time in states 1, 3, and 4 (SY1, SY2 and SY3), and the older group in states 2, 5, and 6 (SO1, SO2 and SO3). Importantly, comparisons of transition probabilities revealed that the older group showed a reduced brain ability to transition into states dominated by the younger group, as well as a diminished capacity to persist in them. Moreover, graph analysis revealed that these young-specific states exhibited higher modularity and k-coreness. Collectively, these findings suggested that the older group showed impaired brain ability of both transition into and sustain well spatially organized states. This emphasized that the temporal changes in brain state organization, rather than its static mode, could be a key biomarker for detecting age-related functional decline. These insights may pave the way for targeted interventions aimed at mitigating cognitive decline in the aging population.

Association Between Lifestyle at Different Life Periods and Brain Integrity in Older Adults

BACKGROUND AND OBJECTIVES

Lifestyle behaviors, including engagement in complex mental activities, have been associated with dementia risk and neuroimaging markers of aging and Alzheimer disease. However, the life period(s) at which lifestyle factors have the greatest influence on brain health remains unclear. Our objective was to determine the relative influence of lifestyle (i.e., engagement in complex mental activities) at different life periods on older adults' brain health.

METHODS

This observational study included community-dwelling cognitively unimpaired seniors (older than 65 years) from the Age-Well randomized controlled trial (Caen, France). All participants completed at baseline the Lifetime of Experiences Questionnaire, assessing engagement in complex mental activities during young adulthood (13-30 years: LEQ-young), midlife (30-65 years: LEQ-midlife), and late-life (older than 65 years: LEQ-late). LEQ scores were divided into specific and non-specific activities. Multiple regressions were conducted including LEQ scores at the 3 life periods (same model) to predict gray matter volume (GMv; structural-MRI), glucose metabolism (fluorodeoxyglucose-PET), perfusion (early-Florbetapir-PET), or amyloid burden (late-Florbetapir-PET), both in AD-signature regions and voxel-wise (significance for voxel-wise analyses: p < 0.005uncorrected, k > 100). Correlations between LEQ and neuroimaging outcomes were then compared between (1) life periods and (2) specific and non-specific activities. Analyses were controlled for age and sex.

RESULTS

In 135 older adults (mean age = 69.3 years; women = 61.5%), no associations were found within AD-signature regions (all p > 0.25). Voxel-wise analyses revealed no association between LEQ-young and neuroimaging. LEQ-midlife showed stronger voxel-wise associations than the other periods with GMv, notably in the anterior cingulate cortex, and with amyloid burden in the precuneus. These correlations were stronger for the LEQ-midlife specific (i.e., occupation) than the non-specific subscore (GMv: z = 3.25, p < 0.001, 95% CI [0.1292-0.5135]; amyloid: z = -1.88, p < 0.05, 95% CI [-0.3810 to -0.0113]). LEQ-late showed stronger voxel-wise associations than the other periods with perfusion and glucose metabolism in medial frontal regions. The correlation of perfusion with LEQ-late was stronger for non-specific than specific subscore (z = 2.88, p < 0.01, 95% CI [0.0894-0.4606]).

DISCUSSION

Lifestyle at different life periods may have complementary benefits on brain health in regions related to reserve/resilience in aging. While past (midlife) engagement could promote resistance against structural/pathologic alterations, current (late-life) engagement could enhance cognitive reserve. Future larger longitudinal studies should explore mechanisms by which lifestyle promotes reserve.

Age- and Sex-Specific Patterns in Adult Brain Network Segregation

The human brain is organized into several segregated associative and sensory functional networks, each responsible for various aspects of cognitive and sensory processing. These functional networks become less segregated over the adult lifespan, possibly contributing to cognitive decline that is observed during advanced age. To date, a comprehensive understanding of decreasing network segregation with age has been hampered by (1) small sample sizes, (2) lack of investigation at different spatial scales, (3) the limited age range of participants, and more importantly (4) an inadequate consideration of sex (biological females and males) differences. This study aimed to address these shortcomings. Resting-state functional magnetic resonance imaging data were collected from 357 cognitively intact participants (18.2-91.8 years; 49.9 ± 17.1 years; 27.70 ± 1.72 MoCA score, 203 [56.8%] females), and the segregation index (defined as one minus the ratio of between-network connectivity to within-network connectivity) was calculated at three spatial scales of brain networks: whole-brain network, intermediate sensory and associative networks, as well as core visual (VIS), sensorimotor (SMN), frontoparietal (FPN), ventral attention (VAN), dorsal attention (DAN), and default mode networks (DMN). Where applicable, secondary within-, between-, and pairwise connectivity analyses were also conducted to investigate the origin of any observed age and sex effects on network segregation. For any given functional metric, linear and quadratic age effects, sex effects, and respective age by sex interaction effects were assessed using backwards iterative linear regression modeling. Replicating previous work, brain networks were found to become less segregated across adulthood. Specifically, negative quadratic decreases in whole-brain network, intermediate associative network, VAN, and DMN segregation index were observed. Intermediate sensory networks, VIS, and SMN exhibited negative linear decreases in segregation index. Secondary analysis revealed that this process of age-related functional reorganization was preferential as functional connectivity was observed to increase either between anatomically adjacent associative networks (DMN-DAN, FPN-DAN) or between anterior associative and posterior sensory networks (VIS-DAN, VIS-DMN, VIS-FPN, SMN-DMN, and SMN-FPN). Inherent sex differences in network segregation index were also observed. Specifically, whole-brain, associative, DMN, VAN, and FPN segregation index was greater in females compared to males, irrespective of age. Secondary analysis found that females have reduced functional connectivity between associative networks (DAN-VAN, VAN-FPN) compared to males and independent of age. A notable linear age-related decrease in FPN SI was also only observed for females and not males. The observed findings support the notion that functional networks reorganize across the adult lifespan, becoming less segregated. This decline may reflect underlying neurocognitive aging mechanisms like neural dedifferentiation, inefficiency, and compensation. The aging trajectories and rates of decreasing network segregation, however, vary across associative and sensory networks. This study also provides preliminary evidence of inherent sex differences in network organization, where associative networks are more segregated in females than males. These inherent sex differences suggest that female functional networks may be more efficient and functionally specialized compared to males across adulthood. Given these findings, future studies should take a more focused approach to examining sex differences across the lifespan, incorporating multimodal methodologies.

Metabolic connectivity has greater predictive utility for age and cognition than functional connectivity

Recently developed high temporal resolution functional (18F)-fluorodeoxyglucose positron emission tomography (fPET) offers promise as a method for indexing the dynamic metabolic state of the brain in vivo by directly measuring a time series of metabolism at the post-synaptic neuron. This is distinct from functional magnetic resonance imaging (fMRI) that reflects a combination of metabolic, haemodynamic and vascular components of neuronal activity. The value of using fPET to understand healthy brain ageing and cognition over fMRI is currently unclear. Here, we use simultaneous fPET/fMRI to compare metabolic and functional connectivity and test their predictive ability for ageing and cognition. Whole-brain fPET connectomes showed moderate topological similarities to fMRI connectomes in a cross-sectional comparison of 40 younger (mean age 27.9 years; range 20-42) and 46 older (mean 75.8; 60-89) adults. There were more age-related within- and between-network connectivity and graph metric differences in fPET than fMRI. fPET was also associated with performance in more cognitive domains than fMRI. These results suggest that ageing is associated with a reconfiguration of metabolic connectivity that differs from haemodynamic alterations. We conclude that metabolic connectivity has greater predictive utility for age and cognition than functional connectivity and that measuring glucodynamic changes has promise as a biomarker for age-related cognitive decline.

Age-Related Changes in Caudate Glucose Metabolism: Insights from Normative Modeling Study in Healthy Subjects

BACKGROUND

As the global population ages, the prevalence of neurodegenerative conditions, such as Alzheimer's disease (AD), Parkinson's disease (PD), dementia with Lewy bodies, and frontotemporal dementia, continues to rise. Understanding the impact of aging on striatal glucose metabolism is pivotal in identifying potential biomarkers for the early detection of these disorders.

METHODS

We investigated age-related changes in striatal glucose metabolism using both region of interest (ROI)-based and voxel-wise correlation analyses. Additionally, we employed a normative modeling approach to establish age-related metabolic trajectories and assess individual deviations from these normative patterns. In vivo cerebral glucose metabolism was quantified using a molecular neuroimaging technique, 18F-FDG PET.

RESULTS

Our results revealed significant negative correlations between age and glucose metabolism in the bilateral caudate. Furthermore, the normative modeling demonstrated a clear, progressive decline in caudate metabolism with advancing age, and the most pronounced reductions were observed in older individuals.

CONCLUSIONS

These findings suggest that metabolic reductions in the caudate may serve as a sensitive biomarker for normal aging and offer valuable insights into the early stages of neurodegenerative diseases. Moreover, by establishing age-specific reference values for caudate glucose metabolism, the normative model provides a framework for detecting deviations from expected metabolic patterns, which may facilitate the early identification of metabolic alterations that could precede clinical symptoms of neurodegenerative processes.

Atlas of plasma metabolic markers linked to human brain morphology

Background

Metabolic processes form the basis of the development, functioning and maintenance of the brain. Despite accumulating evidence of the vital role of metabolism in brain health, no study to date has comprehensively investigated the link between circulating markers of metabolic activity and in vivo brain morphology in the general population.

Methods

We performed uni- and multivariate regression on metabolomics and MRI data from 24,940 UK Biobank participants, to estimate the individual and combined associations of 249 circulating metabolic markers with 91 measures of global and regional cortical thickness, surface area and subcortical volume. We investigated similarity of the identified spatial patterns with brain maps of neurotransmitters, and used Mendelian randomization to uncover causal relationships between metabolites and the brain.

Results

Intracranial volume and total surface area were highly significantly associated with circulating lipoproteins and glycoprotein acetyls, with correlations up to .15. There were strong regional associations of individual markers with mixed effect directions, with distinct patterns involving frontal and temporal cortical thickness, brainstem and ventricular volume. Mendelian randomization provided evidence of bidirectional causal effects, with the majority of markers affecting frontal and temporal regions.

Discussion

The results indicate strong bidirectional causal relationships between circulating metabolic markers and distinct patterns of global and regional brain morphology. The generated atlas of associations provides a better understanding of the role of metabolic pathways in structural brain development and maintenance, in both health and disease.

The metabolic costs of cognition

Cognition and behavior are emergent properties of brain systems that seek to maximize complex and adaptive behaviors while minimizing energy utilization. Different species reconcile this trade-off in different ways, but in humans the outcome is biased towards complex behaviors and hence relatively high energy use. However, even in energy-intensive brains, numerous parsimonious processes operate to optimize energy use. We review how this balance manifests in both homeostatic processes and task-associated cognition. We also consider the perturbations and disruptions of metabolism in neurocognitive diseases.

Structural and Molecular Imaging of Aging Brain: A Focus on MR Imaging and PET Modalities

The process of aging in the brain is reflective of various factors including the environment, lifestyle, genetics, and management of concurrent chronic conditions. Aging in the brain leads to observable structural changes on neuroimaging, such as brain volume reduction, neuronal atrophy, and synaptic loss, which affect higher cognitive functions. Positron emission tomography imaging can help visualize these changes earlier before structural changes even take place and the associated decline in brain function, revealing important insights into how the brain ages and the impact on neural connectivity and cognitive abilities.

Patterns of glucose hypometabolism can help differentiate FTLD-FET from other types of FTLD

INTRODUCTION

FTLD-FET is a newly described subtype of frontotemporal lobar degeneration (FTLD characterized by pathologic inclusions of FET proteins: fused in sarcoma (FUS), Ewing sarcoma, and TATA-binding protein-associated factor 2N (TAF15)). Severe caudate volume loss on MRI has been linked to FTLD-FUS, yet glucose hypometabolism in FTLD-FET has not been studied. We assessed [18F] fluorodeoxyglucose PET (FDG-PET) hypometabolism in FTLD-FET subtypes and compared metabolism to FTLD-tau and FTLD-TDP.

METHODS

We retrospectively reviewed medical records of 26 autopsied FTLD patients (six FTLD-FET, ten FTLD-Tau, and ten FTLD-TDP) who had completed antemortem FDG-PET. We evaluated five regions, caudate nucleus, medial frontal cortex, lateral frontal cortex, and medial temporal using a 0-3 visual rating scale and validated our findings quantitatively using CORTEX-ID suite Z scores.

RESULTS

Of the six FTLD-FET cases (three females) with median age at onset = 36, three were atypical FTLD-U (aFTLD-U) and three were neuronal intermediate filament inclusion disease (NIFID). bvFTD was the most common presentation. Four of the six FTLD cases (3 aFTLD-U + 1 NIFID) showed prominent caudate hypometabolism relatively early in the disease course. FTLD-tau and FTLD-TDP did not show early prominent caudate hypometabolism. Hypometabolism in medial and lateral temporal cortex was associated with FTLD-TDP, while FTLD-tau had normal-minimal regional metabolism.

DISCUSSION

Prominent caudate hypometabolism, especially early in the disease course, appears to be a hallmark feature of the aFTLD-U subtype of FTLD-FET. Assessing caudate and temporal hypometabolism on FDG-PET will help to differentiate FTLD-FET from FTLD-tau and FTLD-TDP.

Synaptic signaling modeled by functional connectivity predicts metabolic demands of the human brain

PURPOSE

The human brain is characterized by interacting large-scale functional networks fueled by glucose metabolism. Since former studies could not sufficiently clarify how these functional connections shape glucose metabolism, we aimed to provide a neurophysiologically-based approach.

METHODS

51 healthy volunteers underwent simultaneous PET/MRI to obtain BOLD functional connectivity and [18F]FDG glucose metabolism. These multimodal imaging proxies of fMRI and PET were combined in a whole-brain extension of metabolic connectivity mapping. Specifically, functional connectivity of all brain regions were used as input to explain glucose metabolism of a given target region. This enabled the modeling of postsynaptic energy demands by incoming signals from distinct brain regions.

RESULTS

Functional connectivity input explained a substantial part of metabolic demands but with pronounced regional variations (34 - 76%). During cognitive task performance this multimodal association revealed a shift to higher network integration compared to resting state. In healthy aging, a dedifferentiation (decreased segregated/modular structure of the brain) of brain networks during rest was observed. Furthermore, by including data from mRNA maps, [11C]UCB-J synaptic density and aerobic glycolysis (oxygen-to-glucose index from PET data), we show that whole-brain functional input reflects non-oxidative, on-demand metabolism of synaptic signaling. The metabolically-derived directionality of functional inputs further marked them as top-down predictions. In addition, the approach uncovered formerly hidden networks with superior efficiency through metabolically informed network partitioning.

CONCLUSIONS

Applying multimodal imaging, we decipher a crucial part of the metabolic and neurophysiological basis of functional connections in the brain as interregional on-demand synaptic signaling fueled by anaerobic metabolism. The observed task- and age-related effects indicate promising future applications to characterize human brain function and clinical alterations.

The association of regional cerebral blood flow and glucose metabolism in normative ageing and insulin resistance

Rising rates of insulin resistance and an ageing population are set to exact an increasing toll on individuals and society. Here we examine the contribution of age and insulin resistance to the association of cerebral blood flow and glucose metabolism; both critical process in the supply of energy for the brain. Thirty-four younger (20-42 years) and 41 older (66-86 years) healthy adults underwent a simultaneous resting state MR/PET scan, including arterial spin labelling. Rates of cerebral blood flow and glucose metabolism were derived using a functional atlas of 100 brain regions. Older adults had lower cerebral blood flow than younger adults in 95 regions, reducing to 36 regions after controlling for cortical atrophy and blood pressure. Lower cerebral blood flow was also associated with worse working memory and slower reaction time in tasks requiring cognitive flexibility and response inhibition. Younger and older insulin sensitive adults showed small, negative correlations between relatively high rates of regional cerebral blood flow and glucose metabolism. This pattern was inverted in insulin resistant older adults, who showed hypoperfusion and hypometabolism across the cortex, and a positive correlation. In insulin resistant younger adults, the association showed inversion to positive correlations, although not to the extent seen in older adults. Our findings suggest that the normal course of ageing and insulin resistance alter the rates of and associations between cerebral blood flow and glucose metabolism. They underscore the criticality of insulin sensitivity to brain health across the adult lifespan.

Systemic lupus erythematosus-related brain abnormalities in the default mode network and the limbic system: A resting-state fMRI meta-analysis

BACKGROUND

Systemic lupus erythematosus (SLE) is an immune-mediated and multi-systemic disease which may affect the nervous system, causing neuropsychiatric SLE (NPSLE). Recent neuroimaging studies have examined brain functional alterations in SLE. However, discrepant findings were reported. This meta-analysis aims to identify consistent resting-state functional abnormalities in SLE.

METHODS

PubMed and Web of Science were searched to identify candidate resting-state functional MRI studies assessing SLE. A voxel-based meta-analysis was performed using the anisotropic effect-size version of the seed-based d mapping (AES-SDM). The abnormal intrinsic functional patterns extracted from SDM were mapped onto the brain functional network atlas to determine brain abnormalities at a network level.

RESULTS

Twelve studies evaluating fifteen datasets were included in this meta-analysis, comprising 572 SLE patients and 436 healthy controls (HCs). Compared with HCs, SLE patients showed increased brain activity in the bilateral hippocampus and right superior temporal gyrus, and decreased brain activity in the left superior frontal gyrus, left middle temporal gyrus, bilateral thalamus, left inferior frontal gyrus and right cerebellum. Mapping the abnormal patterns to the network atlas revealed the default mode network and the limbic system as core neural systems commonly affected in SLE.

LIMITATIONS

The number of included studies is relatively small, with heterogeneous analytic methods and a risk of publication bias.

CONCLUSIONS

Brain functional alterations in SLE are predominantly found in the default mode network and the limbic system. These findings uncovered a consistent pattern of resting-state functional network abnormalities in SLE which may serve as a potential objective neuroimaging biomarker.

Elevating understanding: Linking high-altitude hypoxia to brain aging through EEG functional connectivity and spectral analyses

High-altitude hypoxia triggers brain function changes reminiscent of those in healthy aging and Alzheimer's disease, compromising cognition and executive functions. Our study sought to validate high-altitude hypoxia as a model for assessing brain activity disruptions akin to aging. We collected EEG data from 16 healthy volunteers during acute high-altitude hypoxia (at 4,000 masl) and at sea level, focusing on relative changes in power and aperiodic slope of the EEG spectrum due to hypoxia. Additionally, we examined functional connectivity using wPLI, and functional segregation and integration using graph theory tools. High altitude led to slower brain oscillations, that is, increased δ and reduced α power, and flattened the 1/f aperiodic slope, indicating higher electrophysiological noise, akin to healthy aging. Notably, functional integration strengthened in the θ band, exhibiting unique topographical patterns at the subnetwork level, including increased frontocentral and reduced occipitoparietal integration. Moreover, we discovered significant correlations between subjects' age, 1/f slope, θ band integration, and observed robust effects of hypoxia after adjusting for age. Our findings shed light on how reduced oxygen levels at high altitudes influence brain activity patterns resembling those in neurodegenerative disorders and aging, making high-altitude hypoxia a promising model for comprehending the brain in health and disease.

Senescence and aging differentially alter key metabolic pathways in murine brain microglia

Microglia, the resident immune cells of the central nervous system, are critically involved in maintaining brain homeostasis. With age, microglia display morphological and functional alterations that have been associated with cognitive decline and neurodegeneration. Although microglia seem to participate in an increasing number of biological processes which require a high energy demand, little is known about their metabolic regulation under physiological and pathophysiological conditions and during aging/senescence. Here, we determined mRNA expression levels of critical rate limiting enzymes in several key metabolic pathways including glycolysis, pentose phosphate pathway, fatty acid oxidation and synthesis in association with oxidative phosphorylation in microglia, both under aging and senescent conditions. We found strong evidence for different metabolic changes occuring in senescent vs. aged microglia cells. While senescent microglia display a hypermetabolic state as indicated by increased expression of key enzymes involved in glycolysis and pentose phosphate pathway, aging microglia are rather in a state of hypometabolism. Our findings indicate that studies involving aging and senescent microglia require a clear differentiation between these microglial states due to profound metabolic differences observed here. Understanding metabolic changes in senescent and aged microglia may lead to novel strategies to decrease over-activation of these cells due to aging, which is associated to the process of inflamm-aging and neurodegeneration.

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.

Aging and Cerebral Glucose Metabolism: 18F-FDG-PET/CT Reveals Distinct Global and Regional Metabolic Changes in Healthy Patients

Alterations in cerebral glucose metabolism can be indicative of both normal and pathological aging processes. In this retrospective study, we evaluated global and regional neurological glucose metabolism in 73 healthy individuals (mean age: 35.8 ± 13.1 years; 82.5% female) using 18F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT). This population exhibited a low prevalence of comorbidities associated with cerebrovascular risk factors. We utilized 18F-FDG-PET/CT imaging and quantitative regional analysis to assess cerebral glucose metabolism. A statistically significant negative correlation was found between age and the global standardized uptake value mean (SUVmean) of FDG uptake (p = 0.000795), indicating a decrease in whole-brain glucose metabolism with aging. Furthermore, region-specific analysis identified significant correlations in four cerebral regions, with positive correlations in the basis pontis, cerebellar hemisphere, and cerebellum and a negative correlation in the lateral orbital gyrus. These results were further confirmed via linear regression analysis. Our findings reveal a nuanced understanding of how aging affects glucose metabolism in the brain, providing insight into normal neurology. The study underscores the utility of 18F-FDG-PET/CT as a sensitive tool in monitoring these metabolic changes, highlighting its potential for the early detection of neurological diseases and disorders related to aging.

The Role of One-Carbon Metabolism in Healthy Brain Aging

Aging results in more health challenges, including neurodegeneration. Healthy aging is possible through nutrition as well as other lifestyle changes. One-carbon (1C) metabolism is a key metabolic network that integrates nutritional signals with several processes in the human body. Dietary supplementation of 1C components, such as folic acid, vitamin B12, and choline are reported to have beneficial effects on normal and diseased brain function. The aim of this review is to summarize the current clinical studies investigating dietary supplementation of 1C, specifically folic acid, choline, and vitamin B12, and its effects on healthy aging. Preclinical studies using model systems have been included to discuss supplementation mechanisms of action. This article will also discuss future steps to consider for supplementation. Dietary supplementation of folic acid, vitamin B12, or choline has positive effects on normal and diseased brain function. Considerations for dietary supplementation to promote healthy aging include using precision medicine for individualized plans, avoiding over-supplementation, and combining therapies.

GlyNAC (Glycine and N-Acetylcysteine) Supplementation in Old Mice Improves Brain Glutathione Deficiency, Oxidative Stress, Glucose Uptake, Mitochondrial Dysfunction, Genomic Damage, Inflammation and Neurotrophic Factors to Reverse Age-Associated Cognitive Decline: Implications for Improving Brain Health in Aging

Cognitive decline frequently occurs with increasing age, but mechanisms contributing to age-associated cognitive decline (ACD) are not well understood and solutions are lacking. Understanding and reversing mechanisms contributing to ACD are important because increased age is identified as the single most important risk factor for dementia. We reported earlier that ACD in older humans is associated with glutathione (GSH) deficiency, oxidative stress (OxS), mitochondrial dysfunction, glucose dysmetabolism and inflammation, and that supplementing GlyNAC (glycine and N-acetylcysteine) improved these defects. To test whether these defects occur in the brain in association with ACD, and could be improved/reversed with GlyNAC supplementation, we studied young (20-week) and old (90-week) C57BL/6J mice. Old mice received either regular or GlyNAC supplemented diets for 8 weeks, while young mice received the regular diet. Cognition and brain outcomes (GSH, OxS, mitochondrial energetics, autophagy/mitophagy, glucose transporters, inflammation, genomic damage and neurotrophic factors) were measured. Compared to young mice, the old-control mice had significant cognitive impairment and multiple brain defects. GlyNAC supplementation improved/corrected the brain defects and reversed ACD. This study finds that naturally-occurring ACD is associated with multiple abnormalities in the brain, and provides proof-of-concept that GlyNAC supplementation corrects these defects and improves cognitive function in aging.

Multinuclear Magnetic Resonance Spectroscopy at Ultra-High-Field: Assessing Human Cerebral Metabolism in Healthy and Diseased States

The brain is a highly energetic organ. Although the brain can consume metabolic substrates, such as lactate, glycogen, and ketone bodies, the energy metabolism in a healthy adult brain mainly relies on glucose provided via blood. The cerebral metabolism of glucose produces energy and a wide variety of intermediate metabolites. Since cerebral metabolic alterations have been repeatedly implicated in several brain disorders, understanding changes in metabolite levels and corresponding cell-specific neurotransmitter fluxes through different substrate utilization may highlight the underlying mechanisms that can be exploited to diagnose or treat various brain disorders. Magnetic resonance spectroscopy (MRS) is a noninvasive tool to measure tissue metabolism in vivo. ¹H-MRS is widely applied in research at clinical field strengths (≤3T) to measure mostly high abundant metabolites. In addition, X-nuclei MRS including, ¹³C, ²H, ¹⁷O, and ³¹P, are also very promising. Exploiting the higher sensitivity at ultra-high-field (>4T; UHF) strengths enables obtaining unique insights into different aspects of the substrate metabolism towards measuring cell-specific metabolic fluxes in vivo. This review provides an overview about the potential role of multinuclear MRS (¹H, ¹³C, ²H, ¹⁷O, and ³¹P) at UHF to assess the cerebral metabolism and the metabolic insights obtained by applying these techniques in both healthy and diseased states.