Changes In Brain Metabolism Research Articles

Metabolic-driven analytics of traumatic brain injury and neuroprotection by ethyl pyruvate.

Research on traumatic brain injury (TBI) highlights the significance of counteracting its metabolic impact via exogenous fuels to support metabolism and diminish cellular damage. While ethyl pyruvate (EP) treatment shows promise in normalizing cellular metabolism and providing neuroprotection, there is a gap in understanding the precise metabolic pathways involved. Metabolomic analysis of the acute post-injury metabolic effects, with and without EP treatment, aims to deepen our knowledge by identifying and comparing the metabolite profiles, thereby illuminating the injury's effects and EP's therapeutic potential. In the current study, an untargeted metabolomics approach was used to reveal brain metabolism changes in rats 24h after a controlled cortical impact (CCI) injury, with or without EP treatment. Using principal component analysis (PCA), volcano plots, Random Forest and pathway analysis we differentiated the brain metabolomes of CCI and sham injured animals treated with saline (Veh) or EP, identifying key metabolites and pathways affected by injury. Additionally, the effect of EP on the non-injured brain was also explored. PCA showed a clear separation of the four study groups (sham-Veh, CCI-Veh, sham-EP, CCI-EP) based on injury. Following CCI injury (CCI-Veh), 109 metabolites belonging to the amino acid, carbohydrate, lipid, nucleotide, and xenobiotic families exhibited a twofold change at 24h compared to the sham-Veh group, with 93 of these significantly increasing and 16 significantly decreasing (p < 0.05). CCI animals were treated with EP (CCI-EP) showed only 5 metabolites in the carbohydrate, amino acids, peptides, nucleotides, lipids, and xenobiotics super families that exhibited a twofold change, compared to the CCI-Veh group (p < 0.05). In the non-injured brain, EP treatment (sham-EP) resulted in a twofold change in 6 metabolites within the amino acid, peptide, nucleotide, and lipid super families compared to saline treated sham animals (sham-Veh, p < 0.05). This study delineates the unique metabolic signatures resulting from a CCI injury and those related to EP treatment in both the injured and non-injured brain, underscoring the metabolic adaptations to brain injury and the effects of EP. Our analysis uncovers significant shifts in metabolites associated with inflammation, energy metabolism, and neuroprotection after injury, and demonstrates how EP intervention after injury alters metabolites associated with mitigating inflammation and oxidative damage.

Circadian Alterations in Brain Metabolism Linked to Cognitive Deficits During Hepatic Ischemia-Reperfusion Injury Using [1H-13C]-NMR Metabolomics

Background: Hepatic ischemia-reperfusion injury (HIRI) is known to affect cognitive functions, with particular concern for its impact on brain metabolic dynamics. Circadian rhythms, as a crucial mechanism for internal time regulation within organisms, significantly influence metabolic processes in the brain. This study aims to explore how HIRI affects hippocampal metabolism and its circadian rhythm differences in mice, and to analyze how these changes are associated with cognitive impairments. Methods: A C57BL/6 male mouse model was used, simulating HIRI through hepatic ischemia-reperfusion surgery, with a sham operation conducted for the control group. Cognitive functions were evaluated using open field tests, Y-maze tests, and novel object recognition tests. Magnetic resonance spectroscopic imaging (MRSI) technology, combined with intravenous injection of [2-13C]-acetate and [1-13C]-glucose, was utilized to analyze metabolic changes in the hippocampus of HIRI mice at different circadian time points (Zeitgeber Time ZT0, 8:00 and ZT12, 20:00). Circadian rhythms regulate behavioral, physiological, and metabolic rhythms through transcriptional feedback loops, with ZT0 at dawn (lights on) and ZT12 at dusk (lights off). Results: HIRI mice exhibited significant cognitive impairments in behavioral tests, particularly in spatial memory and learning abilities. MRSI analysis revealed significant circadian rhythm differences in the concentration of metabolites in the hippocampus, with the enrichment concentrations of lactate, alanine, glutamate, and taurine showing different trends at ZT0 compared to ZT12, highlighting the important influence of circadian rhythms on metabolic dysregulation induced by HIRI. Conclusions: This study highlights the significant impact of HIRI on brain metabolic dynamics in mice, especially in the hippocampal area, and for the first time reveals the differences in these effects within circadian rhythms. These findings not only emphasize the association between HIRI-induced cognitive impairments and changes in brain metabolism but also point out the crucial role of circadian rhythms in this process, offering new metabolic targets and timing considerations for therapeutic strategies against HIRI-related cognitive disorders.

Testing Neuroprotective Strategies in Prolonged Field Care Model of Traumatic Brain Injury and Hemorrhagic Shock.

Prolonged Field Care (PFC) is a military adaptation of Tactical Combat Casualty Care providing extended pre-hospital management during delayed extrication. Effects of addition of Valproic Acid (VPA) to Fresh Frozen Plasma (FFP) in a PFC model of hemorrhagic shock and traumatic brain injury (TBI) are not known. We hypothesized that VPA is associated with decreased neurological impairment, and its protective changes are detected at the transcriptomic level. Swine underwent TBI and 40%-blood volume hemorrhage. After 2-hours of shock, they were randomized to: 1)normal saline (NS), 2)NS+250 ml FFP (NS+FFP), or 3)NS+FFP+150 mg/kgVPA(NS+FFP+VPA). At 72-hours, they were transfused packed red blood cells before being euthanized. Intraoperative variables and neurological outcomes were compared. Brain lesion size was measured, and gene expression profiles were analyzed using RNA-sequencing. Pathway and network analyses were performed on differentially expressed genes. Real-time PCR was performed to validate key genes. NS+FFP and NS+FFP+VPA required significantly less crystalloid resuscitation(974 ml-NS+FFP; 1461ml-NS+FFP+VPA vs. 4540 ml-NS, p<0.001), had smaller brain lesion size(2477mm3-NS+FFP; 3018.0mm3-NS+FFP+VPA vs. 4517.0mm3-NS, p<0.01), and less functional neurologic impairment compared to NS. Per pathway analysis of differentially expressed genes, VPA was associated with enrichment of numerous metabolic changes in injured brains, which were not observed with FFP. Network analysis showed enrichment of various gene networks. MT-ATP8 gene was downregulated in VPA-treated animals. The addition of FFP to the resuscitation protocol resulted in a significant reduction in crystalloid requirements. Both, the FFP and FFP+VPA groups showed improved neurological recovery compared to NS alone and had distinctive transcriptomic profiles in injured brains at 72-hours. MT-ATP8, involved in worsening ischemia following brain injury, was down-regulated in VPA-treated animals.

"Monitoring inflammatory, immune system mediators, and mitochondrial changes related to brain metabolism during space flight".

The possibility of impaired cognitive function during deep space flight missions or while living on a Martian colony is a critical point of concern and pleads for further research. In addition, a fundamental gap exists both in our understanding and application of countermeasures for the consequences of long duration space travel and/or living in an extreme environment such as on the Moon or Mars. Previous studies, while heavily analyzing pre- and post-flight conditions, mostly fail to appreciate the cognitive stressors associated with space radiation, microgravity, confinement, hostile or closed environments, and the long distances from earth. A specific understanding of factors that affect cognition as well as structural and/or physiological changes in the brains of those on a space mission in addition to new countermeasures should result in improved health of our astronauts and reduce risks. At the core of cognitive changes are mechanisms we typically associate with aging, such as inflammatory responses, changes in brain metabolism, depression, and memory impairments. In fact, space flight appears to accelerate aging. In this review, we will discuss the importance of monitoring inflammatory and immune system mediators such as nuclear factor kappa B (NF-κB), and mitochondrial changes related to brain metabolism. We conclude with our recommended countermeasures that include pharmacological, metabolic, and nutritional considerations for the risks on cognition during space missions.

The combination of 18F-fluorodeoxyglucose and 18F 9-fluoropropyl-(+)-dihydrotetrabenazine positron emission tomography for distinguishing between early-onset and late-onset idiopathic Parkinson disease and analyzing influencing factors.

The classification of Parkinson disease by age of onset has proven to be a valuable method for subtyping, given its practical application in clinical settings. However, the interactions between the metabolic brain changes, dopaminergic dysfunction, and clinical manifestations in patients with early-onset (early-iPD) and late-onset (late-iPD) idiopathic Parkinson disease have not been adequately evaluated. Therefore, this study aimed to investigate the difference in cerebral metabolism and presynaptic dopaminergic function between patients with early-iPD and those with late-onset disease using 18F-fluorodeoxyglucose (18F-FDG) and [18F] 9-fluoropropyl-(+)-dihydrotetrabenazine (18F-FP-DTBZ) positron emission tomography (PET). Furthermore, the goal was to further explore the correlation between imaging measurements and clinical manifestations in the early and late idiopathic patients with Parkinson disease. This cross-sectional study included 80 patients with idiopathic Parkinson disease and 29 healthy control participants who underwent 18F-FDG and18F-FP-DTBZ PET imaging at Xuanwu Hospital, Capital Medical University from August 2022 to August 2023. The patients were categorized into early-iPD (n=27) and late-iPD (n=53) groups based on an age threshold of 50 years. The mean standardized uptake value of 18F-FDG and the standardized uptake value ratio (SUVR) of 18F-FP-DTBZ were compared between the early-iPD and late-iPD groups using unpaired Student t-tests. Furthermore, pairwise correlations among cerebral metabolism, dopaminergic function, and corresponding clinical ratings in all patients were conducted using Pearson correlation analysis. Patients with late-iPD exhibited a significant metabolic decrease in the frontal, parietal, and temporal cortex, along with the globus pallidus, putamen, thalamus, and cerebellum, compared to those with early-iPD in 18F-FDG PET imaging (all P values <0.05). Furthermore, the 18F-FP-DTBZ binding potential was significantly lower in the contralateral caudate and anterior putamen of patients with late-iPD compared to those with early-iPD (contralateral caudate: 3.16±1.2 vs. 2.63±0.7, P=0.020; contralateral anterior putamen: 2.49±1.2 vs. 2.05±0.7, P=0.040). Further analysis of the correlations between imaging clinical features revealed that glucose metabolism increases and dopaminergic function decreases with higher motor ratings. 18F-FDG and 18F-FP-DTBZ PET offer an objective molecular imaging basis for distinguishing between early-onset and late-onset idiopathic with Parkinson disease. Additionally, correlation analysis between imaging and clinical data represents a new approach for exploring the potential applications in future studies involving patients with early-iPD and late-iPD.

Cardiovascular Disease, Brain Glucose Metabolism, and Neurocognitive Decline in People With Human Immunodeficiency Virus.

Cardiovascular disease (CVD) and neuroinflammation are thought to exacerbate neurocognitive dysfunction in treated people with human immunodeficiency virus (PWH). Here, we longitudinally measured brain glucose metabolism as a measure of neuronal integrity in treated PWH using [18F]Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in correlation with atherosclerotic cardiovascular disease (ASCVD) scores, cerebrospinal fluid (CSF) neuroinflammatory markers, neurocognitive outcomes, and other clinical and laboratory variables (CLVs). Well-controlled PWH (n = 36) underwent baseline and follow-up FDG PET/CT obtained 3.5 years apart on average. Longitudinal changes in whole brain and regional relative FDG uptake, brain volumes, CLVs, CSF cytokines, and neuropsychological measures were measured. A variable selection model identified baseline variables related to future brain metabolic changes while multivariable models explored neuropsychological implications of brain metabolism and volumetrics. High ASCVD scores predicted future decreased thalamic uptake (slope = -0.0068, P = .027) and decreasing thalamic uptake correlated with worsening cognition (slope = 15.80, P = .020). Despite longitudinal greater than expected gray matter loss, whole brain FDG uptake did not change over the follow-up period. Most CSF cytokines decreased longitudinally but were not predictive of FDG changes. We found that high ASCVD scores in a group of treated PWH were related to thalamic hypometabolism, which in turn correlated with neurocognitive decline. Our findings support the contribution of CVD to neurocognitive dysfunction. More proactive CVD management may have a role in mitigating progression of cognitive impairment. Lack of change in global brain glucose metabolism despite documented accelerated gray matter volume loss over the same period suggests that FDG PET might underestimate neuronal injury in PWH compared to structural magnetic resonance imaging.

Assessment of Mannitol-Induced Chronic Blood-Brain Barrier Dysfunction In Vivo Using Magnetic Resonance.

The blood-brain barrier (BBB) is essential for protection and plays a crucial role in chronic neurological disorders like small-vessel disease and Alzheimer's disease. Its complexity poses significant challenges for effective diagnostics and treatments, highlighting the need for novel animal models and comprehensive BBB dysfunction studies. This study investigates chronic BBB dysfunction induction using osmotic disruption via mannitol in healthy adult male Sprague Dawley rats over 12 weeks. Group 1 received 1 bolus/week (2.0 g/kg), Group 2 received 3 boluses/week (1.5 g/kg), and Group 3 received 3 boluses/week (2.5 g/kg). BBB dysfunction was assessed using gadolinium (Gd) infusion and MRI to evaluate location, severity, evolution, and persistence. MR spectroscopy (MRS) examined the brain metabolism changes due to intravenous mannitol, with T2-weighted MRI assessing brain lesions. Biomarkers of neuroinflammation were analyzed in the highest mannitol dose group. Our data show chronic BBB dysfunction primarily in the cortex, hippocampus, and striatum, but not in the corpus callosum of rats under periodic mannitol dosing in groups 1 and 2. MRS identified a distinctive metabolite signature, including changes in alanine, choline, and N-acetyl aspartate in the striatum of Group 1. No significant differences were found in the serum levels of all pro- and anti-inflammatory cytokines analyzed in the high-dose Group 3. This study underscores the feasibility and implications of using osmotic disruption to model chronic BBB dysfunction, offering insights for future neuroprotection and therapeutic strategies research.

Early brain neuroinflammatory and metabolic changes identified by dual tracer microPET imaging in mice with acute liver injury.

Acute liver injury (ALI) that progresses into acute liver failure (ALF) is a life-threatening condition with an increasing incidence and associated costs. Acetaminophen (N-acetyl-p-aminophenol, APAP) overdosing is among the leading causes of ALI and ALF in the Northern Hemisphere. Brain dysfunction defined as hepatic encephalopathy is one of the main diagnostic criteria for ALF. While neuroinflammation and brain metabolic alterations significantly contribute to hepatic encephalopathy, their evaluation at early stages of ALI remained challenging. To provide insights, we utilized post-mortem analysis and non-invasive brain micro positron emission tomography (microPET) imaging of mice with APAP-induced ALI. Male C57BL/6 mice were treated with vehicle or APAP (600 mg/kg, i.p.). Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), liver damage (using H&E staining), hepatic and serum IL-6 levels, and hippocampal IBA1 (using immunolabeling) were evaluated at 24h and 48h. Vehicle and APAP treated animals also underwent microPET imaging utilizing a dual tracer approach, including [ 11 C]-peripheral benzodiazepine receptor ([ 11 C]PBR28) to assess microglia/astrocyte activation and [ 18 F]-fluoro-2-deoxy-2-D-glucose ([ 18 F]FDG) to assess energy metabolism. Brain images were pre-processed and evaluated using conjunction and individual tracer uptake analysis. APAP-induced ALI and hepatic and systemic inflammation were detected at 24h and 48h by significantly elevated serum ALT and AST levels, hepatocellular damage, and increased hepatic and serum IL-6 levels. In parallel, increased microglial numbers, indicative for neuroinflammation were observed in the hippocampus of APAP-treated mice. MicroPET imaging revealed overlapping increases in [ 11 C]PBR28 and [ 18 F]FDG uptake in the hippocampus, thalamus, and habenular nucleus indicating microglial/astroglial activation and increased energy metabolism in APAP-treated mice (vs. vehicle-treated mice) at 24h. Similar significant increases were also found in the hypothalamus, thalamus, and cerebellum at 48h. The individual tracer uptake analyses (APAP vs vehicle) at 24h and 48h confirmed increases in these brain areas and indicated additional tracer- and region-specific effects including hippocampal alterations. Peripheral manifestations of APAP-induced ALI in mice are associated with brain neuroinflammatory and metabolic alterations at relatively early stages of disease progression, which can be non-invasively evaluated using microPET imaging and conjunction analysis. These findings support further PET-based investigations of brain function in ALI/ALF that may inform timely therapeutic interventions.

Omics-derived biological modules reflect metabolic brain changes in Alzheimer's disease.

Brain glucose hypometabolism, indexed by the fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) imaging, is a metabolic signature of Alzheimer's disease (AD). However, the underlying biological pathways involved in these metabolic changes remain elusive. Here, we integrated [18F]FDG-PET images with blood and hippocampal transcriptomic data from cognitively unimpaired (CU, n=445) and cognitively impaired (CI, n=749) individuals using modular dimension reduction techniques and voxel-wise linear regression analysis. Our results showed that multiple transcriptomic modules are associated with brain [18F]FDG-PET metabolism, with the top hits being a protein serine/threonine kinase activity gene cluster (peak-t(223)=4.86, P value<0.001) and zinc-finger-related regulatory units (peak-t(223)=3.90, P value<0.001). By integrating transcriptomics with PET imaging data, we identified that serine/threonine kinase activity-associated genes and zinc-finger-related regulatory units are highly associated with brain metabolic changes in AD. We conducted an integrated analysis of system-based transcriptomics and fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) at the voxel level in Alzheimer's disease (AD). The biological process of serine/threonine kinase activity was the most associated with [18F]FDG-PET in the AD brain. Serine/threonine kinase activity alterations are associated with brain vulnerable regions in AD [18F]FDG-PET. Zinc-finger transcription factor targets were associated with AD brain [18F]FDG-PET metabolism.

Maternal gut Bifidobacterium breve modifies fetal brain metabolism in germ-free mice

BackgroundRecent advances have significantly expanded our understanding of the gut microbiome's influence on host physiology and metabolism. However, the specific role of certain microorganisms in gestational health and fetal development remains underexplored. ObjectiveThis study investigates the impact of Bifidobacterium breve UCC2003 on fetal brain metabolism when colonized in the maternal gut during pregnancy. MethodsGerm-free pregnant mice were colonized with or without B. breve UCC2003 during pregnancy. The metabolic profiles of fetal brains were analyzed, focusing on the presence of key metabolites and the expression of critical metabolic and cellular pathways. ResultsMaternal colonization with B. breve resulted in significant metabolic changes in the fetal brain. Specifically, ten metabolites, including citrate, 3-hydroxyisobutyrate, and carnitine, were reduced in the fetal brain. These alterations were accompanied by increased abundance of transporters involved in glucose and branched-chain amino acid uptake. Furthermore, supplementation with this bacterium was associated with elevated expression of critical metabolic pathways such as PI3K-AKT, AMPK, STAT5, and Wnt-β-catenin signaling, including its receptor Frizzled-7. Additionally, there was stabilization of HIF-2 protein and modifications in genes and proteins related to cellular growth, axogenesis, and mitochondrial function. ConclusionsThe presence of maternal B. breve during pregnancy plays a crucial role in modulating fetal brain metabolism and growth. These findings suggest that Bifidobacterium could modify fetal brain development, potentially offering new avenues for enhancing gestational health and fetal development through microbiota-targeted interventions.

Decreased Cerebral Creatine and N-Acetyl Aspartate Concentrations after Severe COVID-19 Infection: A Magnetic Resonance Spectroscopy Study.

Background/Objectives: The aim of this study was to evaluate brain metabolism using MR spectroscopy (MRS) after recovery from Coronavirus disease (COVID-19) and to test the impact of disease severity on brain metabolites. Methods: We performed MRS on 81 individuals (45 males, 36 females, aged 40-60), who had normal MRI findings and had recovered from COVID-19, classifying them into mild (17), moderate (36), and severe (28) groups based on disease severity during the acute phase. The study employed two-dimensional spectroscopic imaging above the corpus callosum, focusing on choline (Cho), creatine (Cr), and N-acetylaspartate (NAA). We analyzed Cho/Cr and NAA/Cr ratios as well as absolute concentrations using water as an internal reference. Results: Results indicated that the Cho/Cr ratio was higher with increasing disease severity, while absolute Cho and NAA/Cr ratios showed no significant differences across the groups. Notably, absolute Cr and NAA levels were significantly lower in patients with severe disease. Conclusions: These findings suggest that the severity of COVID-19 during the acute phase is associated with significant changes in brain metabolism, marked by an increase in Cho/Cr ratios and a reduction in Cr and NAA levels, reflecting substantial metabolic alterations post-recovery.

Do toenail manganese and iron levels reflect brain metal levels or brain metabolism in welders?

Inhalation of welding fumes can cause metal accumulation in the brain, leading to Parkinsonian-like symptoms. Metal accumulation and altered neurochemical profiles have been observed using magnetic resonance imaging (MRI) in highly exposed welders, being associated with decreased motor function and cognition. While MRI is impractical to use as a health risk assessment tool in occupational settings, toenail metal levels are easier to assess and have been demonstrated to reflect an exposure window of 7–12 months in the past. Yet, it is unclear whether toenail metal levels are associated with brain metal levels or changes in metabolism, which are the root of potential health concerns. This study investigates whether toenail manganese (Mn) and iron (Fe) levels, assessed at several time points, correlate with brain Mn and Fe levels, measured by MRI, as well as brain GABA, glutamate (Glu), and glutathione (GSH) levels, measured by Magnetic Resonance Spectroscopy (MRS), in seventeen Mn-exposed welders. Quantitative T1 and R2* MRI maps of the whole brain, along with GABA, Glu, and GSH MRS measurements from the thalamus and cerebellum were acquired at baseline (T0). Toenail clippings were collected at T0 and every three months after the MRI for a year to account for different exposure periods being reflected by toenail clippings and MRI. Spearman correlations of toenail metal levels were run against brain metal and metabolite levels, but no significant associations were found for Mn at any timepoint. Cerebellar GSH positively correlated with toenail Fe clipped twelve months after the MRI (p = 0.05), suggesting an association with Fe exposure at the time of the MRI. Neither thalamic GABA nor Glu correlated with toenail Fe levels. In conclusion, this study cannot support toenail Mn as a proxy for brain Mn levels or metabolic changes, while toenail Fe appears linked to brain metabolic alterations, underscoring the importance of considering other metals, including Fe, in studying Mn neurotoxicity.

Regional changes in brain metabolism during the progression of mild cognitive impairment: a longitudinal study based on radiomics

BackgroundThis study aimed to establish radiomics models based on positron emission tomography (PET) images to longitudinally predict transition from mild cognitive impairment (MCI) to Alzheimer's disease (AD).MethodsIn our study, 278 MCI patients from the ADNI database were analyzed, where 60 transitioned to AD (pMCI) and 218 remained stable (sMCI) over 48 months. Patients were divided into a training set (n = 222) and a validation set (n = 56). We first employed voxel-based analysis of 18F-FDG PET images to identify brain regions that present significant SUV difference between pMCI and sMCI groups. Radiomic features were extracted from these regions, key features were selected, and predictive models were developed for individual and combined brain regions. The models' effectiveness was evaluated using metrics like AUC to determine the most accurate predictive model for MCI progression.ResultsVoxel-based analysis revealed four brain regions implicated in the progression from MCI to AD. These include ROI1 within the Temporal lobe, ROI2 and ROI3 in the Thalamus, and ROI4 in the Limbic system. Among the predictive models developed for these individual regions, the model utilizing ROI4 demonstrated superior predictive accuracy. In the training set, the AUC for the ROI4 model was 0.803 (95% CI 0.736, 0.865), and in the validation set, it achieved an AUC of 0.733 (95% CI 0.559, 0.893). Conversely, the model based on ROI3 showed the lowest performance, with an AUC of 0.75 (95% CI 0.685, 0.809). Notably, the comprehensive model encompassing all identified regions (ROI total) outperformed the single-region models, achieving an AUC of 0.884 (95% CI 0.845, 0.921) in the training set and 0.816 (95% CI 0.705, 0.909) in the validation set, indicating significantly enhanced predictive capability for MCI progression to AD.ConclusionOur findings underscore the Limbic system as the brain region most closely associated with the progression from MCI to AD. Importantly, our study demonstrates that a PET brain radiomics model encompassing multiple brain regions (ROI total) significantly outperforms models based on single brain regions. This comprehensive approach more accurately identifies MCI patients at high risk of progressing to AD, offering valuable insights for non-invasive diagnostics and facilitating early and timely interventions in clinical settings.

Establishment of a normal control model of children's brain 18-fluorodeoxyglucose positron emission tomography and analysis of the changing pattern in patients aged 0-14 years.

It is difficult to obtain 18-fluorodeoxyglucose positron emission tomography (18FDG-PET) data from normal children, and changes in brain metabolism in children due to growth and development are poorly understood. For the first time, we established a normal control model of brain 18FDG-PET in children and evaluated its feasibility. The association of PET with age in children aged 0-14 years was analyzed. This study aimed to establish a normal control model of brain 18FDG-PET in children for the first time and to verify its feasibility, and to analyze the trend of PET with age in children aged 0-14 years. In this retrospective cohort study, the 18FDG-PET imaging data of patients with no epileptiform discharge involvement contralateral to the epileptogenic zone were consecutively collected from January 2015 to June 2022 according to strictly defined screening criteria. For the normal control data, the hemisphere contralateral to the epileptogenic zone was mirrored and spliced to form an intact brain. The cohort of children aged 0-14 years was divided into 14 groups according age by year. Subsequently, patients who underwent lesionectomy with clear hypometabolism that roughly coincided with the extent of surgical resection were examined. The PET scan was compared with the control model, and the ratio of overlapping parts (hypometabolic areas ∩ surgical resection area) to hypometabolic parts (ROH) was calculated. Multiple regression analysis was performed on the normal control model for every 3- to 4-year age interval. A total of 159 normal control models were established. Five patients were randomly selected to verify the reliability of each yearly model. The average ROH was 0.968. Metabolism increasing with age in the different brain regions was observed at ages 0-2~, 3-5~, and 6-10 years. No age-related metabolic increase or decrease was found in the 10- to 14-year-old group. The metabolism in the 7- to 8-year-old group was higher than that in the 13- to 14-year-old group. With strict screening criteria, the method of mirroring the contralateral hemisphere of the epileptic zone and splicing it into a complete brain as a means of creating a normal control group is feasible. The method offers convenience to the studies that lack healthy pediatric controls. Children under 10 years of age (especially 0-6 years old) experience considerable metabolic changes year on year. After the age of 10 years, the changes in metabolism gradually decrease, and metabolism also slowly decreases. Our findings provide guidance the clinical interpretation of areas with hypometabolism and emphasize the importance of establishing a normal control model of the child's brain, which should not be replaced by an adult model.

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

Background:The prediction of Alzheimer’s disease (AD) progression from its early stages is a research priority. In this context, the use of Artificial Intelligence (AI) in AD has experienced a notable surge in recent years. However, existing investigations predominantly concentrate on distinguishing clinical phenotypes through cross-sectional approaches. This study aims to investigate the potential of modeling additional dimensions of the disease, such as variations in brain metabolism assessed via [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET), and utilize this information to identify patients with mild cognitive impairment (MCI) who will progress to dementia (pMCI). Methods:We analyzed data from 1,617 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) who had undergone at least one FDG-PET scan. We identified the brain regions with the most significant hypometabolism in AD and used Deep Learning (DL) models to predict future changes in brain metabolism. The best-performing model was then adapted under a multi-task learning framework to identify pMCI individuals. Finally, this model underwent further analysis using eXplainable AI (XAI) techniques. Results:Our results confirm a strong association between hypometabolism, disease progression, and cognitive decline. Furthermore, we demonstrated that integrating data on changes in brain metabolism during training enhanced the models’ ability to detect pMCI individuals (sensitivity=88.4%, specificity=86.9%). Lastly, the application of XAI techniques enabled us to delve into the brain regions with the most significant impact on model predictions, highlighting the importance of the hippocampus, cingulate cortex, and some subcortical structures. Conclusion:This study introduces a novel dimension to predictive modeling in AD, emphasizing the importance of projecting variations in brain metabolism under a multi-task learning paradigm.

Postmortem tissue biomarkers of menopausal transition.

The menopausal transition (MT) is associated with an increased risk for many disorders including neurological and mental disorders. Brain imaging studies in living humans show changes in brain metabolism and structure that may contribute to the MT-associated brain disease risk. Although deficits in ovarian hormones have been implicated, cellular and molecular studies of the brain undergoing MT are currently lacking, mostly due to a difficulty in studying MT in postmortem human brain. To enable this research, we explored 39 candidate biomarkers for menopausal status in 42 pre-, peri-, and post-menopausal subjects across three postmortem tissues: blood, the hypothalamus, and pituitary gland. We identified thirteen significant and seven strongest menopausal biomarkers across the three tissues. Using these biomarkers, we generated multi-tissue and tissue-specific composite measures that allow the postmortem identification of the menopausal status across different age ranges, including the "perimenopausal", 45-55-year-old group. Our findings enable the study of cellular and molecular mechanisms underlying increased neuropsychiatric risk during the MT, opening the path for hormone status-informed, precision medicine approach in women's mental health.

Effect of reducing isoflurane level on glucosamine uptake in the mouse brain during magnetic resonance imaging studies

Anesthesia is often required during magnetic resonance imaging (MRI) examinations in animal studies. Anesthetic drugs differ in their capacity to interfere with homeostatic mechanisms responsible for glucose metabolism in the brain, which may create a constraint in the study design. Recent studies suggest that the chemical exchange saturation transfer (CEST) MRI scanning technique can detect localized metabolic changes in rodent brains induced by the uptake of glucose or its analogs; however, most of these studies do not account for the impact of anesthesia type on the brain metabolism. Herein, we aimed to evaluate the effect of reduced isoflurane levels on the preclinical imaging of glucosamine (GlcN) uptake in healthy mouse brains to establish optimal conditions for future brain imaging studies using the CEST MRI technique. The commonly used anesthesia protocol for longitudinal MRI examinations using 1.5% isoflurane level was compared to that using a mixture of low isoflurane (0.8%) level combined with midazolam (2 mg/kg, SC). Magnetization transfer ratio asymmetry (MTRasym) and area under the curve (AUC) analyses were used to characterize GlcN signals in the brain. The results indicated that mice injected with GlcN and anesthetized with 1.5% isoflurane exhibited low and insignificant changes in the MTRasym and AUC signals in the frontal cortex, whereas mice administered with 0.8% isoflurane combined with midazolam demonstrated a significant increase in these signals in the frontal cortex. This study highlights the diverse GlcN metabolic changes observed in mouse brains under variable levels of isoflurane anesthesia using the CEST MRI method. The results suggest that it is feasible to maintain anesthesia with low-dose isoflurane by integrating midazolam, which may enable the investigation of GlcN uptake in the brain. Thus, reducing isoflurane levels may support studies into mouse brain metabolism using the CEST MRI method and should be considered in future studies.

Developmental pyrethroid exposure in mouse leads to disrupted brain metabolism in adulthood

Environmental and genetic risk factors, and their interactions, contribute significantly to the etiology of neurodevelopmental disorders (NDDs). Recent epidemiology studies have implicated pyrethroid pesticides as an environmental risk factor for autism and developmental delay. Our previous research showed that low-dose developmental exposure to the pyrethroid pesticide deltamethrin in mice caused male-biased changes in the brain and in NDD-relevant behaviors in adulthood. Here, we used a metabolomics approach to determine the broadest possible set of metabolic changes in the adult male mouse brain caused by low-dose pyrethroid exposure during development. Using a litter-based design, we exposed mouse dams during pregnancy and lactation to deltamethrin (3 mg/kg or vehicle every 3 days) at a concentration well below the EPA-determined benchmark dose used for regulatory guidance. We raised male offspring to adulthood and collected whole brain samples for untargeted high-resolution metabolomics analysis. Developmentally exposed mice had disruptions in 116 metabolites which clustered into pathways for folate biosynthesis, retinol metabolism, and tryptophan metabolism. As a cross-validation, we integrated metabolomics and transcriptomics data from the same samples, which confirmed previous findings of altered dopamine signaling. These results suggest that pyrethroid exposure during development leads to disruptions in metabolism in the adult brain, which may inform both prevention and therapeutic strategies.

Developmental pyrethroid exposure in mouse leads to disrupted brain metabolism in adulthood.

Environmental and genetic risk factors, and their interactions, contribute significantly to the etiology of neurodevelopmental disorders (NDDs). Recent epidemiology studies have implicated pyrethroid pesticides as an environmental risk factor for autism and developmental delay. Our previous research showed that low-dose developmental exposure to the pyrethroid pesticide deltamethrin in mice caused male-biased changes in the brain and in NDD-relevant behaviors in adulthood. Here, we used a metabolomics approach to determine the broadest possible set of metabolic changes in the adult male mouse brain caused by low-dose pyrethroid exposure during development. Using a litter-based design, we exposed mouse dams during pregnancy and lactation to deltamethrin (3 mg/kg or vehicle every 3 days) at a concentration well below the EPA-determined benchmark dose used for regulatory guidance. We raised male offspring to adulthood and collected whole brain samples for untargeted high-resolution metabolomics analysis. Developmentally exposed mice had disruptions in 116 metabolites which clustered into pathways for folate biosynthesis, retinol metabolism, and tryptophan metabolism. As a cross-validation, we integrated metabolomics and transcriptomics data from the same samples, which confirmed previous findings of altered dopamine signaling. These results suggest that pyrethroid exposure during development leads to disruptions in metabolism in the adult brain, which may inform both prevention and therapeutic strategies.

Validation of cardiac image-derived input functions for functional PET quantification

PurposeFunctional PET (fPET) is a novel technique for studying dynamic changes in brain metabolism and neurotransmitter signaling. Accurate quantification of fPET relies on measuring the arterial input function (AIF), traditionally achieved through invasive arterial blood sampling. While non-invasive image-derived input functions (IDIF) offer an alternative, they suffer from limited spatial resolution and field of view. To overcome these issues, we developed and validated a scan protocol for brain fPET utilizing cardiac IDIF, aiming to mitigate known IDIF limitations.MethodsTwenty healthy individuals underwent fPET/MR scans using [18F]FDG or 6-[18F]FDOPA, utilizing bed motion shuttling to capture cardiac IDIF and brain task-induced changes. Arterial and venous blood sampling was used to validate IDIFs. Participants performed a monetary incentive delay task. IDIFs from various blood pools and composites estimated from a linear fit over all IDIF blood pools (3VOI) and further supplemented with venous blood samples (3VOIVB) were compared to the AIF. Quantitative task-specific images from both tracers were compared to assess the performance of each input function to the gold standard.ResultsFor both radiotracer cohorts, moderate to high agreement (r: 0.60–0.89) between IDIFs and AIF for both radiotracer cohorts was observed, with further improvement (r: 0.87–0.93) for composite IDIFs (3VOI and 3VOIVB). Both methods showed equivalent quantitative values and high agreement (r: 0.975–0.998) with AIF-derived measurements.ConclusionOur proposed protocol enables accurate non-invasive estimation of the input function with full quantification of task-specific changes, addressing the limitations of IDIF for brain imaging by sampling larger blood pools over the thorax. These advancements increase applicability to any PET scanner and clinical research setting by reducing experimental complexity and increasing patient comfort.