Role of the metabolism of branched-chain amino acids in the development of Alzheimer's disease and other metabolic disorders

Identification of putative allosteric inhibitors of BCKDK via virtual screening and biological evaluation

Abnormal accumulation of branched-chain amino acids (BCAAs) can lead to metabolic diseases and cancers. Branched-chain α-keto acid dehydrogenase kinase (BCKDK) is a key negative regulator of BCAA catabolism, and targeting BCKDK provides a promising therapeutic approach for diseases caused by BCAA accumulation. Here, we screened PPHN and POAB as novel putative allosteric inhibitors by integrating allosteric binding site prediction, large-scale ligand database virtual screening, and bioactivity evaluation assays. Both of them showed a high binding affinity to BCKDK, with Kd values of 3.9 μM and 1.86 μM, respectively. In vivo experiments, the inhibitors demonstrated superior kinase inhibitory activity and notable antiproliferative and proapoptotic effects on diverse cancer cells. Finally, bulk RNA-seq analysis revealed that PPHN and POAB suppressed cell growth through a range of signalling pathways. Taken together, our findings highlight two novel BCKDK inhibitors as potent therapeutic candidates for metabolic diseases and cancers associated with BCAA dysfunctional metabolism.

Integrated Bulk and Single-Cell RNA-Sequencing Reveals the Effects of Circadian Rhythm Disruption on the Metabolic Reprogramming of CD4+ T Cells in Alzheimer's Disease

Although growing evidence suggests close correlations between Alzheimer's disease (AD) and circadian rhythm disruption (CRD), few studies have focused on the influence of circadian rhythm on levels of immune cells in AD. We aimed to delineate the mechanism underlying the effects of circadian related genes on T cell immune function in AD. A total of 112 brain samples were used to construct the CRD-related model by performing weighted gene co-expression network analysis and machine learning algorithms (LASSO, SVM-RFE, and RF). The ssGSEA method was used to calculate the CRDscore in order to quantify CRD status. Using single-cell transcriptome data of CSF cells, we investigated the CD4+ T cell metabolism and cell-cell communication in high- and low-risk CRD groups. Connectivity map (CMap) was applied to explore small molecule drugs targeting CRD, and the expression of the signature gene GPR4 was further validated in AD. The CRDscore algorithm, which is based on 23 circadian-related genes, can effectively classify the CRD status in AD datasets. The single-cell analysis revealed that the CD4+ T cells with high CRDscore were characterized by hypometabolism. Cell communication analysis revealed that CD4+ T cells might be involved in promoting CD8+ T cell adhesion under CRD, which may facilitate T cell infiltration into the brain parenchyma. Overall, this study indicates the potential connotation of circadian rhythm in AD, providing insights into understanding T cell metabolic reprogramming under CRD.

Association between Branched-Chain amino acids and Epilepsy: A Mendelian randomized study

BACKGROUND

Branched-chain amino acids (BCAAs) have been affected epilepsy, yet conclusions remain inconclusive, lacking causal evidence regarding whether BCAAs affect epilepsy. Systematic exploration of the causal relationship between BCAAs and epilepsy could hand out new ideas for the treatment of epilepsy.

METHODS

Utilizing bidirectional Mendelian randomization (MR) study, we investigated the causal relationship between BCAA levels and epilepsy. BCAA levels from genome-wide association studies (GWAS), including total BCAAs, leucine levels, isoleucine levels, and valine levels, were employed. Causal relationships were explored applying the method of inverse variance-weighted (IVW) and MR-Egger, followed by sensitivity analyses of the results to evaluate heterogeneity and pleiotropy.

RESULTS

Through strict genetic variant selection, we find some related SNPs, total BCAA levels (9), leucine levels (11), isoleucine levels (7), and valine levels (6) as instrumental variables for our MR analysis. Following IVW and sensitivity analysis, total BCAAs levels (OR = 1.14, 95 % CI = 1.019 ∼ 1.285, P = 0.022) and leucine levels (OR = 1.15, 95 % CI = 1.018 ∼ 1.304, P = 0.025) had significant correlation with epilepsy.

CONCLUSIONS

There exists a causal relationship between the levels of total BCAAs and leucine with epilepsy, offering the new ideas into epilepsy potential mechanisms, holding significant implications for its prevention and treatment.

A principal component analysis of metabolome and cognitive decline among Japanese older adults: cross-sectional analysis using Tohoku Medical Megabank Cohort Study

BackgroundDementia is the leading cause of disability and imposes a significant burden on society. Previous studies have suggested an association between metabolites and cognitive decline. Although the metabolite composition differs between Western and Asian populations, studies targeting Asian populations remain scarce.MethodsThis cross-sectional study used data from a cohort survey of community-dwelling older adults aged ≥ 60 years living in Miyagi, Japan, conducted by Tohoku Medical Megabank Organization between 2013 and 2016. Forty-three metabolite variables quantified using nuclear magnetic resonance spectroscopy were used as explanatory variables. Dependent variable was the presence of cognitive decline (≤ 23 points), assessed by the Mini-Mental State Examination. Principal component (PC) analysis was performed to reduce the dimensionality of metabolite variables, followed by logistic regression analysis to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for cognitive decline.ResultsA total of 2,940 participants were included (men: 49.0%, mean age: 67.6 years). Among them, 1.9% showed cognitive decline. The first 12 PC components (PC1-PC12) accounted for 71.7% of the total variance. Multivariate analysis showed that PC1, which mainly represented essential amino acids, was associated with lower odds of cognitive decline (OR = 0.89; 95% CI, 0.80-0.98). PC2, which mainly included ketone bodies, was associated with cognitive decline (OR = 1.29; 95% CI, 1.11-1.51). PC3, which included amino acids, was associated with lower odds of cognitive decline (OR = 0.81; 95% CI, 0.66-0.99).ConclusionAmino acids are protectively associated with cognitive decline, whereas ketone metabolites are associated with higher odds of cognitive decline.

Branched-chain amino acids and the risks of dementia, Alzheimer's disease, and Parkinson's disease

Background

We aimed to examine the association between blood levels of Branched-chain amino acids (BCAAs) - specifically isoleucine, leucine, and valine - and the susceptibility to three neurodegenerative disorders: dementia, Alzheimer's disease (AD), and Parkinson's disease (PD).

Methods

Based on data from the UK Biobank, a Cox proportional hazard regression model and a dose-response relationship were used to analyze the association between BCAAs and the risks of dementia, AD, and PD. We also generated a healthy lifestyle score and a polygenic risk score. Besides, we conducted a sensitivity analysis to ensure the robustness of our findings.

Results

After adjusting for multiple covariates, blood concentrations of isoleucine, leucine, and valine were significantly associated with a reduced risk of dementia and AD. This association remained robust even in sensitivity analyses. Similarly, higher levels of isoleucine and leucine in the blood were found to be associated with an increased risk of PD, but this positive correlation could potentially be explained by the presence of covariates. Further analysis using a dose-response approach revealed that a blood leucine concentration of 2.14 mmol/L was associated with the lowest risk of dementia.

Conclusion

BCAAs have the potential to serve as a biomarker for dementia and AD. However, the specific mechanism through which BCAAs are linked to the development of dementia, AD, and PD remains unclear and necessitates additional investigation.

The microbiota-gut-brain axis in Huntington's disease: pathogenic mechanisms and therapeutic targets

Huntington's disease (HD) is a currently incurable neurogenerative disorder and is typically characterized by progressive movement disorder (including chorea), cognitive deficits (culminating in dementia), psychiatric abnormalities (the most common of which is depression), and peripheral symptoms (including gastrointestinal dysfunction). There are currently no approved disease-modifying therapies available for HD, with death usually occurring approximately 10-25 years after onset, but some therapies hold promising potential. HD subjects are often burdened by chronic diarrhea, constipation, esophageal and gastric inflammation, and a susceptibility to diabetes. Our understanding of the microbiota-gut-brain axis in HD is in its infancy and growing evidence from preclinical and clinical studies suggests a role of gut microbial population imbalance (gut dysbiosis) in HD pathophysiology. The gut and the brain can communicate through the enteric nervous system, immune system, vagus nerve, and microbiota-derived-metabolites including short-chain fatty acids, bile acids, and branched-chain amino acids. This review summarizes supporting evidence demonstrating the alterations in bacterial and fungal composition that may be associated with HD. We focus on mechanisms through which gut dysbiosis may compromise brain and gut health, thus triggering neuroinflammatory responses, and further highlight outcomes of attempts to modulate the gut microbiota as promising therapeutic strategies for HD. Ultimately, we discuss the dearth of data and the need for more longitudinal and translational studies in this nascent field. We suggest future directions to improve our understanding of the association between gut microbes and the pathogenesis of HD, and other 'brain and body disorders'.

Gut microbiome and serum amino acid metabolome alterations in autism spectrum disorder

Gut microbiota and their metabolic products might play important roles in regulating the pathogenesis of autism spectrum disorder (ASD). The purpose of this study was to characterize gut microbiota and serum amino acid metabolome profiles in children with ASD. A non-randomized controlled study was carried out to analyze the alterations in the intestinal microbiota and their metabolites in patients with ASD (n = 30) compared with neurotypical controls (NC) (n = 30) by metagenomic sequencing to define the gut microbiota community and liquid chromatography/mass spectrometry (LC/MS) analysis to characterize the metabolite profiles. Compared with children in the NC group, those in the ASD group showed lower richness, higher evenness, and an altered microbial community structure. At the class level, Deinococci and Holophagae were significantly lower in children with ASD compared with TD. At the phylum level, Deinococcus-Thermus was significantly lower in children with ASD compared with TD. In addition, the functional properties (such as galactose metabolism) displayed significant differences between the ASD and NC groups. Five dominant altered species were identified and analyzed (LDA score > 2.0, P < 0.05), including Subdoligranulum, Faecalibacterium_praushitzii, Faecalibacterium, Veillonellaceae, and Rumminococcaceae. The peptides/nickel transport system was the main metabolic pathway involved in the differential species in the ASD group. Decreased ornithine levels and elevated valine levels may increase the risk of ASD through a metabolic pathway known as the nickel transport system. The microbial metabolism in diverse environments was negatively correlated with phascolarctobacterium succinatutens. Our study provides novel insights into compositional and functional alterations in the gut microbiome and metabolite profiles in ASD and the underlying mechanisms between metabolite and ASD.

Metabolites and MRI-Derived Markers of AD/ADRD Risk in a Puerto Rican Cohort

Objective

Several studies have examined metabolomic profiles in relation to Alzheimer's disease and related dementia (AD/ADRD) risk; however, few studies have focused on minorities, such as Latinos, or examined Magnetic-Resonance Imaging (MRI)-based outcomes.

Methods

We used multiple linear regression, adjusted for covariates, to examine the association between metabolite concentration and MRI-derived brain age deviation. Metabolites were measured at baseline with untargeted metabolomic profiling (Metabolon, Inc). Brain age deviation (BAD) was calculated at wave 4 (~ 9 years from Boston Puerto Rican Health Study (BPRHS) baseline) as chronologic age, minus MRI-estimated brain age, representing the rate of biological brain aging relative to chronologic age. We also examined if metabolites associated with BAD were similarly associated with hippocampal volume and global cognitive function at wave 4 in the BPRHS.

Results

Several metabolites, including isobutyrylcarnitine, propionylcarnitine, phenylacetylglutamine, phenylacetylcarnitine (acetylated peptides), p-cresol-glucuronide, phenylacetylglutamate, and trimethylamine N-oxide (TMAO) were inversely associated with brain age deviation. Taurocholate sulfate, a bile salt, was marginally associated with better brain aging. Most metabolites with negative associations with brain age deviation scores also were inversely associations with hippocampal volumes and wave 4 cognitive function.

Conclusion

The metabolites identifiedin this study are generally consistent with prior literature and highlight the role of BCAA, TMAO and microbially derived metabolites in cognitive decline.

Characterization of Hair Metabolome in 5xFAD Mice and Patients with Alzheimer's Disease Using Mass Spectrometry-Based Metabolomics

Hair emerged as a biospecimen for long-term investigation of endogenous metabolic perturbations, reflecting the chemical composition circulating in the blood over the past months. Despite its potential, the use of human hair for metabolomics in Alzheimer's disease (AD) research remains limited. Here, we performed both untargeted and targeted metabolomic approaches to profile the key metabolic pathways in the hair of 5xFAD mice, a widely used AD mouse model. Furthermore, we applied the discovered metabolites to human subjects. Hair samples were collected from 6-month-old 5xFAD mice, a stage marked by widespread accumulation of amyloid plaques in the brain, followed by sample preparation and high-resolution mass spectrometry analysis. Forty-five discriminatory metabolites were discovered in the hair of 6-month-old 5xFAD mice compared to wild-type control mice. Enrichment analysis revealed three key metabolic pathways: arachidonic acid metabolism, sphingolipid metabolism, and alanine, aspartate, and glutamate metabolism. Among these pathways, six metabolites demonstrated significant differences in the hair of 2-month-old 5xFAD mice, a stage prior to the onset of amyloid plaque deposition. These findings suggest their potential involvement in the early stages of AD pathogenesis. When evaluating 45 discriminatory metabolites for distinguishing patients with AD from nondemented controls, a combination of l-valine and arachidonic acid significantly differentiated these two groups, achieving a 0.88 area under the curve. Taken together, these findings highlight the potential of hair metabolomics in identifying disease-specific metabolic alterations and developing biomarkers for improving disease detection and monitoring.

Enhancing cognitive function in older adults: dietary approaches and implications

Natural aging encompasses physiological and psychological changes that impact overall health and quality of life. Mitigating these effects requires physical and mental exercise, coupled with proper nutrition. Notably, protein malnutrition emerges as a potential risk factor for senile dementia, with insufficient intake correlating with premature cognitive decline. Adequate protein intake in the elderly positively associates with memory function and lowers cognitive impairment risk. Considering diet as a modifiable risk factor for cognitive decline, extensive research has explored diverse dietary strategies to prevent dementia onset in older adults. However, conclusive results remain limited. This review aims to synthesize recent evidence on effective dietary approaches to enhance cognitive function and prognosis in older individuals. Specifically, the study evaluates complex multicomponent programs, protein-rich diets, and branched-chain amino acid supplementation. By addressing the nexus of nutrition and cognitive health, this review contributes to understanding viable interventions for promoting cognitive well-being in aging populations.

NMR analysis seeking for cognitive decline and dementia metabolic markers in plasma from aged individuals

BACKGROUND

Blood biomarkers can improve the ability to diagnose dementia, providing new information to better understand the pathophysiology and causes of the disease. Some studies with patients have already shown changes in metabolic profiles among patients with pathological cognitive decline or Alzheimer's disease, when compared to individuals with normal cognition.

METHODS

To search for new metabolic biomarkers of dementia, we analyzed serum levels of several metabolites, measured by nuclear magnetic resonance spectroscopy, in elderly individuals, a group with normal cognitive decline (control), and three other groups with cognitive decline. pathological (low, moderate, and severe).

RESULTS

Decreased plasma levels of tyrosine, glutamate, valine, leucine, and isoleucine are associated with worsening of pathological cognitive decline. However, the area under analysis of receptor operating characteristics suggests that tyrosine and glutamate have low specificity and sensitivity. Valine, leucine, and isoleucine are influenced by blood glucose or diabetes, but these conditions do not seem to be of great influence in the differences observed. Isobutyrate, histidine, acetone and unknown-1 metabolite also decrease their plasma levels with increasing CD. Isobutyrate ad histidine could have neuroprotective and antioxidant actions, respectively. To elucidate the role of decreased unknown metabolite-1 as a CD biomarker, it will be necessary to previously investigate its identity. To define and elucidate the role of acetone in pathological CD, additional laboratory and clinical studies must be performed. All these metabolites together may constitute a set of biomarkers with capability to identify pathological CD or dementia.

SIGNIFICANCE AND NOVELTY

Decrease of glutamate, tyrosine, valine, leucine, isoleucine, histidine, isobutyrate, acetone and unknown-1 metabolite together are a set of biomarkers able to identify pathological CD or dementia. Histidine, isobutyrate, acetone and unknown-1 metabolite are more specific biomarkers of CD.

Impaired glucose utilization in the brain of patients with delirium following hip fracture

Alterations in brain energy metabolism have long been proposed as one of several neurobiological processes contributing to delirium. This is supported by previous findings of altered CSF lactate and neuron-specific enolase concentrations and decreased glucose uptake on brain-PET in patients with delirium. Despite this, there are limited data on metabolic alterations found in CSF samples, and targeted metabolic profiling of CSF metabolites involved in energy metabolism has not been performed. The aim of the study was to investigate whether metabolites related to energy metabolism in the serum and CSF of patients with hip fracture are associated with delirium. The study cohort included 406 patients with a mean age of 81 years (standard deviation 10 years), acutely admitted to hospital for surgical repair of a hip fracture. Delirium was assessed daily until the fifth postoperative day. CSF was collected from all 406 participants at the onset of spinal anaesthesia, and serum samples were drawn concurrently from 213 participants. Glucose and lactate in CSF were measured using amperometry, whereas plasma glucose was measured in the clinical laboratory using enzymatic photometry. Serum and CSF concentrations of the branched-chain amino acids, 3-hydroxyisobutyric acid, acetoacetate and β-hydroxybutyrate were measured using gas chromatography-tandem mass spectrometry (GC-MS/MS). In total, 224 (55%) patients developed delirium pre- or postoperatively. Ketone body concentrations (acetoacetate, β-hydroxybutyrate) and branched-chain amino acids were significantly elevated in the CSF but not in serum among patients with delirium, despite no group differences in glucose concentrations. The level of 3-hydroxyisobutyric acid was significantly elevated in both CSF and serum. An elevation of CSF lactate during delirium was explained by age and comorbidity. Our data suggest that altered glucose utilization and a shift to ketone body metabolism occurs in the brain during delirium.

Branched-Chain Amino Acid Accumulation Fuels the Senescence-Associated Secretory Phenotype

The essential branched-chain amino acids (BCAAs) leucine, isoleucine, and valine play critical roles in protein synthesis and energy metabolism. Despite their widespread use as nutritional supplements, BCAAs' full effects on mammalian physiology remain uncertain due to the complexities of BCAA metabolic regulation. Here a novel mechanism linking intrinsic alterations in BCAA metabolism is identified to cellular senescence and the senescence-associated secretory phenotype (SASP), both of which contribute to organismal aging and inflammation-related diseases. Altered BCAA metabolism driving the SASP is mediated by robust activation of the BCAA transporters Solute Carrier Family 6 Members 14 and 15 as well as downregulation of the catabolic enzyme BCAA transaminase 1 during onset of cellular senescence, leading to highly elevated intracellular BCAA levels in senescent cells. This, in turn, activates the mammalian target of rapamycin complex 1 (mTORC1) to establish the full SASP program. Transgenic Drosophila models further indicate that orthologous BCAA regulators are involved in the induction of cellular senescence and age-related phenotypes in flies, suggesting evolutionary conservation of this metabolic pathway during aging. Finally, experimentally blocking BCAA accumulation attenuates the inflammatory response in a mouse senescence model, highlighting the therapeutic potential of modulating BCAA metabolism for the treatment of age-related and inflammatory diseases.

Addressing the Discrepancies Between Animal Models and Human Alzheimer's Disease Pathology: Implications for Translational Research

Animal models, particularly transgenic mice, are extensively used in Alzheimer's disease (AD) research to emulate key disease hallmarks, such as amyloid plaques and neurofibrillary tangles formation. Although these models have contributed to our understanding of AD pathogenesis and can be helpful in testing potential therapeutic interventions, their reliability is dubious. While preclinical studies have shown promise, clinical trials often yield disappointing results, highlighting a notable gap and disparity between animal models and human AD pathology. Existing models frequently overlook early-stage human pathologies and other key AD characteristics, thereby limiting their application in identifying optimal therapeutic interventions. Enhancing model reliability necessitates rigorous study design, comprehensive behavioral evaluations, and biomarker utilization. Overall, a nuanced understanding of each model's neuropathology, its fidelity to human AD, and its limitations is essential for accurate interpretation and successful translation of findings. This article analyzes the discrepancies between animal models and human AD pathology that complicate the translation of findings from preclinical studies to clinical applications. We also delve into AD pathogenesis and attributes to propose a new perspective on this pathology and deliberate over the primary limitations of key experimental models. Additionally, we discuss several fundamental problems that may explain the translational failures and suggest some possible directions for more effective preclinical studies.

The SLC6A15-SLC6A20 Neutral Amino Acid Transporter Subfamily: Functions, Diseases, and Their Therapeutic Relevance

The neutral amino acid transporter subfamily that consists of six members, consecutively SLC6A15-SLC620, also called orphan transporters, represents membrane, sodium-dependent symporter proteins that belong to the family of solute carrier 6 (SLC6). Primarily, they mediate the transport of neutral amino acids from the extracellular milieu toward cell or storage vesicles utilizing an electric membrane potential as the driving force. Orphan transporters are widely distributed throughout the body, covering many systems; for instance, the central nervous, renal, or intestinal system, supplying cells into molecules used in biochemical, signaling, and building pathways afterward. They are responsible for intestinal absorption and renal reabsorption of amino acids. In the central nervous system, orphan transporters constitute a significant medium for the provision of neurotransmitter precursors. Diseases related with aforementioned transporters highlight their significance; SLC6A19 mutations are associated with metabolic Hartnup disorder, whereas altered expression of SLC6A15 has been associated with a depression/stress-related disorders. Mutations of SLC6A18-SLCA20 cause iminoglycinuria and/or hyperglycinuria. SLC6A18-SLC6A20 to reach the cellular membrane require an ancillary unit ACE2 that is a molecular target for the spike protein of the SARS-CoV-2 virus. SLC6A19 has been proposed as a molecular target for the treatment of metabolic disorders resembling gastric surgery bypass. Inhibition of SLC6A15 appears to have a promising outcome in the treatment of psychiatric disorders. SLC6A19 and SLC6A20 have been suggested as potential targets in the treatment of COVID-19. In this review, we gathered recent advances on orphan transporters, their structure, functions, related disorders, and diseases, and in particular their relevance as therapeutic targets. SIGNIFICANCE STATEMENT: The following review systematizes current knowledge about the SLC6A15-SLCA20 neutral amino acid transporter subfamily and their therapeutic relevance in the treatment of different diseases.

Inference of causal metabolite networks in the presence of invalid instrumental variables with GWAS summary data

We propose structural equation models (SEMs) as a general framework to infer causal networks for metabolites and other complex traits. Traditionally SEMs are used only for individual-level data under the assumption that all instrumental variables (IVs) are valid. To overcome these limitations, we propose both one- and two-sample approaches for causal network inference based on SEMs that can: (1) perform causal analysis and discover causal relationships among multiple traits; (2) account for the possible presence of some invalid IVs; (3) allow for data analysis using only genome-wide association studies (GWAS) summary statistics when individual-level data are not available; (4) consider the possibility of bidirectional relationships between traits. Our method employs a simple stepwise selection to identify invalid IVs, thus avoiding false positives while possibly increasing true discoveries based on two-stage least squares (2SLS). We use both real GWAS data and simulated data to demonstrate the superior performance of our method over the standard 2SLS/SEMs. For real data analysis, our proposed approach is applied to a human blood metabolite GWAS summary data set to uncover putative causal relationships among the metabolites; we also identify some metabolites (putative) causal to Alzheimer's disease (AD), which, along with the inferred causal metabolite network, suggest some possible pathways of metabolites involved in AD.

Cerebral venous congestion alters brain metabolite profiles, impairing cognitive function

Vascular cognitive impairment (VCI) represents the second most common cause of dementia after Alzheimer's disease, and pathological changes in cerebral vascular structure and function are pivotal causes of VCI. Cognitive impairment caused by arterial ischemia has been extensively studied the whole time; the influence of cerebral venous congestion on cognitive impairment draws doctors' attention in recent clinical practice, but the underlying neuropathophysiological alterations are not completely understood. This study elucidated the specific pathogenetic role of cerebral venous congestion in cognitive-behavioral deterioration and possible electrophysiological mechanisms. Using cerebral venous congestion rat models, we found these rats exhibited decreased long-term potentiation (LTP) in the hippocampal dentate gyrus and impaired spatial learning and memory. Based on untargeted metabolomics, N-acetyl-L-cysteine (NAC) deficiency was detected in cerebral venous congestion rats; supplementation with NAC appeared to ameliorate synaptic deficits, rescue impaired LTP, and mitigate cognitive impairment. In a cohort of cerebral venous congestion patients, NAC levels were decreased; NAC concentration was negatively correlated with subjective cognitive decline (SCD) score but positively correlated with mini-mental state examination (MMSE) score. These findings provide a new perspective on cognitive impairment and support further exploration of NAC as a therapeutic target for the prevention and treatment of VCI.

Investigating the relationship between non-occupational pesticide exposure and metabolomic biomarkers

The relationship between pesticide exposures and metabolomics biomarkers is not well understood. We examined the changes in the serum metabolome (early biomarkers) and the metabolic pathways associated with various pesticide exposure scenarios (OPE: overall exposure, PEM: exposure in months, PEY: exposure in years, and PEU: reported specific pesticides use) using data from the Northern Finland Birth Cohort 1966 31-year cross-sectional examination. We utilized questionnaire data on pesticide exposures and serum samples for nuclear magnetic resonance (NMR)-based metabolomics analyses. For exposures and metabolites associations, participants size varied between 2,361 and 5,035. To investigate associations between metabolomics biomarkers and exposure to pesticide scenarios compared to those who reported no exposures multivariable regression analyses stratified by sex and adjustment with covariates (season of pesticide use, socioeconomic position (SEP), alcohol consumption, BMI, and latitude of residence) were performed. Multiple testing by Benjamini-Hochberg false discovery rate (FDR) correction applied. Pesticide exposures differed by sex, season of pesticide use, alcohol, SEP, latitude of residence. Our results showed that all pesticide exposure scenarios were negatively associated with decreased HDL concentrations across all lipoprotein subclasses in women. OPE, PEY, and PEU were associated with decreased branched-chain amino acid concentrations in men and decreased albumin concentrations in women. OPE, PEY and PEU were also associated with changes in glycolysis metabolites and ketone bodies in both sexes. Specific pesticides exposure was negatively associated with sphingolipids and inflammatory biomarkers in men. In women, OPE, PEM, and PEU were associated with decreased apolipoprotein A1 and increased apolipoprotein B/apolipoprotein A1 ratio. Our findings suggest that identification of early biomarkers of disease risk related to pesticide exposures can inform strategies to reduce exposure and investigate causal pathways. Women may be more susceptible to non-occupational pesticide exposures when compared to men, and future sex-specific studies are warranted.

Inflammation and the pathological progression of Alzheimer's disease are associated with low circulating choline levels

Deficiency of dietary choline, an essential nutrient, is observed worldwide, with ~ 90% of Americans being deficient. Previous work highlights a relationship between decreased choline intake and an increased risk for cognitive decline and Alzheimer's disease (AD). The associations between blood circulating choline and the pathological progression in both mild cognitive impairment (MCI) and AD remain unknown. Here, we examined these associations in a cohort of patients with MCI with presence of either sparse or high neuritic plaque density and Braak stage and a second cohort with either moderate AD (moderate to frequent neuritic plaques, Braak stage = IV) or severe AD (frequent neuritic plaques, Braak stage = VI), compared to age-matched controls. Metabolomic analysis was performed on serum from the AD cohort. We then assessed the effects of dietary choline deficiency (Ch-) in 3xTg-AD mice and choline supplementation (Ch+) in APP/PS1 mice, two rodent models of AD. The levels of circulating choline were reduced while pro-inflammatory cytokine TNFα was elevated in serum of both MCI sparse and high pathology cases. Reduced choline and elevated TNFα correlated with higher neuritic plaque density and Braak stage. In AD patients, we found reductions in choline, its derivative acetylcholine (ACh), and elevated TNFα. Choline and ACh levels were negatively correlated with neuritic plaque load, Braak stage, and TNFα, but positively correlated with MMSE, and brain weight. Metabolites L-Valine, 4-Hydroxyphenylpyruvic, Methylmalonic, and Ferulic acids were significantly associated with circuiting choline levels. In 3xTg-AD mice, the Ch- diet increased amyloid-β levels and tau phosphorylation in cortical tissue, and TNFα in both blood and cortical tissue, paralleling the severe human-AD profile. Conversely, the Ch+ diet increased choline and ACh while reducing amyloid-β and TNFα levels in brains of APP/PS1 mice. Collectively, low circulating choline is associated with AD-neuropathological progression, illustrating the importance of adequate dietary choline intake to offset disease.

Metabolomic Signatures of Alzheimer's Disease Indicate Brain Region-Specific Neurodegenerative Progression

Pathological mechanisms contributing to Alzheimer's disease (AD) are still elusive. Here, we identified the metabolic signatures of AD in human post-mortem brains. Using 1H NMR spectroscopy and an untargeted metabolomics approach, we identified (1) metabolomic profiles of AD and age-matched healthy subjects in post-mortem brain tissue, and (2) region-common and region-unique metabolome alterations and biochemical pathways across eight brain regions revealed that BA9 was the most affected. Phenylalanine and phosphorylcholine were mainly downregulated, suggesting altered neurotransmitter synthesis. N-acetylaspartate and GABA were upregulated in most regions, suggesting higher inhibitory activity in neural circuits. Other region-common metabolic pathways indicated impaired mitochondrial function and energy metabolism, while region-unique pathways indicated oxidative stress and altered immune responses. Importantly, AD caused metabolic changes in brain regions with less well-documented pathological alterations that suggest degenerative progression. The findings provide a new understanding of the biochemical mechanisms of AD and guide biomarker discovery for personalized risk prediction and diagnosis.

AmorProt: Amino Acid Molecular Fingerprints Repurposing-Based Protein Fingerprint

As protein therapeutics play an important role in almost all medical fields, numerous studies have been conducted on proteins using artificial intelligence. Artificial intelligence has enabled data-driven predictions without the need for expensive experiments. Nevertheless, unlike the various molecular fingerprint algorithms that have been developed, protein fingerprint algorithms have rarely been studied. In this study, we proposed the amino acid molecular fingerprints repurposing-based protein (AmorProt) fingerprint, a protein sequence representation method that effectively uses the molecular fingerprints corresponding to 20 amino acids. Subsequently, the performances of the tree-based machine learning and artificial neural network models were compared using (1) amyloid classification and (2) isoelectric point regression. Finally, the applicability and advantages of the developed platform were demonstrated through a case study and the following experiments: (3) comparison of dataset dependence with feature-based methods, (4) feature importance analysis, and (5) protein space analysis. Consequently, the significantly improved model performance and data-set-independent versatility of the AmorProt fingerprint were verified. The results revealed that the current protein representation method can be applied to various fields related to proteins, such as predicting their fundamental properties or interaction with ligands.

A paper-based chemical tongue based on the charge transfer complex of ninhydrin with an array of metal-doped carbon dots discriminates natural amino acids and several of their enantiomers

Simultaneous detection of multiple amino acids (AAs) instead of individual AAs is inherently worthwhile for improving diagnostic accuracy in clinical applications. Here, a facile and reliable colorimetric microfluidic paper-based analytical device (μPAD) using carbon dots doped with transition metals (Cr3+, Mn2+, Fe3+, Co2+, Ni2+, Cu2+, and Zn2+) has been provided to detect and discriminate 20 natural amino acids. To make the colourless metal-doped carbon dots suitable for colorimetric assays, they were mixed with ninhydrin to form a charge transfer complex. This optical tongue system, which was constructed by dropping mixtures of ninhydrin with a series of metal-doped carbon dots on a paper substrate in an array format, represented obvious but different colorimetric signatures for every examined amino acid. Since bovine serum albumin was used as a chiral selector reagent for synthesizing the CDs, the sensor device represented excellent selectivity to identify enantiomeric species of AAs. This is the first optical array device that can simultaneously discriminate AAs and several of their enantiomers. We employed various statistical and chemometric methods to analyze the digital data library collected by Image J software, including principal component analysis (PCA), linear discriminant analysis (LDA), and hierarchical cluster analysis (HCA). Twenty AAs could be well distinguished at various concentrations (10.00, 5.00, 2.50, and 1.25 mM). The colorimetric patterns were highly repeatable and were characteristic of individual AAs. Besides qualitative analysis, the designed μPAD-based optical tongue represented quantitative analysis ability, e.g., for lysine in the concentration ranges of 0.005-20.0 mM with a detection limit of 1.0 × 10-6 M and for arginine in the concentration range of 0.12-20.00 mM with a detection limit of 80.0 × 10-6 M. In addition, the binary, ternary, and quaternary mixtures of AAs could also be well recognized with this sensor.

Targeting the metabolic profile of amino acids to identify the key metabolic characteristics in cerebral palsy

Background

Cerebral palsy (CP) is a neurodevelopmental disorder characterized by motor impairment. In this study, we aimed to describe the characteristics of amino acids (AA) in the plasma of children with CP and identify AA that could play a potential role in the auxiliary diagnosis and treatment of CP.

Methods

Using high performance liquid chromatography, we performed metabolomics analysis of AA in plasma from 62 CP children and 60 healthy controls. Univariate and multivariate analyses were then applied to characterize different AA. AA markers associated with CP were then identified by machine learning based on the Lasso regression model for the validation of intra-sample interactions. Next, we calculated a discriminant formula and generated a receiver operating characteristic (ROC) curve based on the marker combination in the discriminant diagnostic model.

Results

A total of 33 AA were detected in the plasma of CP children and controls. Compared with controls, 5, 7, and 10 different AA were identified in total participants, premature infants, and full-term infants, respectively. Of these, β-amino-isobutyric acid [p = 2.9*10(-4), Fold change (FC) = 0.76, Variable importance of protection (VIP) = 1.75], tryptophan [p = 5.4*10(-4), FC = 0.87, VIP = 2.22], and asparagine [p = 3.6*10(-3), FC = 0.82, VIP = 1.64], were significantly lower in the three groups of CP patients than that in controls. The combination of β-amino-isobutyric acid, tryptophan, and taurine, provided high levels of diagnostic classification and risk prediction efficacy for preterm children with an area under the curve (AUC) value of 0.8741 [95% confidence interval (CI): 0.7322-1.000]. The discriminant diagnostic formula for preterm infant with CP based on the potential marker combination was defined by p = 1/(1 + e-(8.295-0.3848* BAIBA-0.1120*Trp + 0.0108*Tau)).

Conclusion

Full-spectrum analysis of amino acid metabolomics revealed a distinct profile in CP, including reductions in the levels of β-amino-isobutyric acid, tryptophan, and taurine. Our findings shed new light on the pathogenesis and diagnosis of premature infants with CP.

Circulating Neurofilament Light Chain Levels Increase with Age and Are Associated with Worse Physical Function and Body Composition in Men but Not in Women

This study aimed to assess the relationship between age-related changes in Neurofilament Light Chain (NFL), a marker of neuronal function, and various factors including muscle function, body composition, and metabolomic markers. The study included 40 participants, aged 20 to 85 years. NFL levels were measured, and muscle function, body composition, and metabolomic markers were assessed. NFL levels increased significantly with age, particularly in men. Negative correlations were found between NFL levels and measures of muscle function, such as grip strength, walking speed, and chair test performance, indicating a decline in muscle performance with increasing NFL. These associations were more pronounced in men. NFL levels also negatively correlated with muscle quality in men, as measured by 50 kHz phase angle. In terms of body composition, NFL was positively correlated with markers of fat mass and negatively correlated with markers of muscle mass, predominantly in men. Metabolomic analysis revealed significant associations between NFL levels and specific metabolites, with gender-dependent relationships observed. This study provides insights into the relationship between circulating serum NFL, muscle function, and aging. Our findings hint at circulating NFL as a potential early marker of age-associated neurodegenerative processes, especially in men.

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.

Gut Microbiota is an Impact Factor based on the Brain-Gut Axis to Alzheimer's Disease: A Systematic Review

Alzheimer's disease (AD) is a degenerative disease of the central nervous system. The pathogenesis of AD has been explained using cholinergic, β-amyloid toxicity, tau protein hyperphosphorylation, and oxidative stress theories. However, an effective treatment method has not been developed. In recent years, with the discovery of the brain-gut axis (BGA) and breakthroughs made in Parkinson's disease, depression, autism, and other diseases, BGA has become a hotspot in AD research. Several studies have shown that gut microbiota can affect the brain and behavior of patients with AD, especially their cognitive function. Animal models, fecal microbiota transplantation, and probiotic intervention also provide evidence regarding the correlation between gut microbiota and AD. This article discusses the relationship and related mechanisms between gut microbiota and AD based on BGA to provide possible strategies for preventing or alleviating AD symptoms by regulating gut microbiota.

Low circulating choline, a modifiable dietary factor, is associated with the pathological progression and metabolome dysfunction in Alzheimer's disease

Most Americans (∼90%) are deficient in dietary choline, an essential nutrient. Associations between circulating choline and pathological progression in Alzheimer's disease (AD) remain unknown. Here, we examined these associations and performed a metabolomic analysis in blood serum from severe AD, moderate AD, and healthy controls. Additionally, to gain mechanistic insight, we assessed the effects of dietary choline deficiency (Ch-) in 3xTg-AD mice and choline supplementation (Ch+) in APP/PS1 mice. In humans, we found AD-associated reductions in choline, it's derivative acetylcholine (ACh), and elevated pro-inflammatory cytokine TNFα. Choline and ACh were negatively correlated with Plaque density, Braak stage, and TNFα, but positively correlated with MMSE and brain weight. Metabolites L-Valine, 4-Hydroxyphenylpyruvic, Methylmalonic, and Ferulic acids were associated with choline levels. In mice, Ch-paralleled AD severe, but Ch+ was protective. In conclusion, low circulating choline is associated with AD-neuropathological progression, illustrating the importance of dietary choline consumption to offset disease.

Exercise Alleviates Behavioral Disorders but Shapes Brain Metabolism of APP/PS1 Mice in a Region- and Exercise-Specific Manner

Exercise plays a beneficial role in the management of Alzheimer's disease (AD), but its effects on brain metabolism are still far from being understood. Here, we examined behavioral changes of APP/PS1 mice after high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) and analyzed metabolomics profiles in the hippocampus, cortex, and hypothalamus by using nuclear magnetic resonance spectroscopy to explore potential metabolic mechanisms. The results demonstrate that both HIIT and MICT alleviated anxiety/depressive-like behaviors as well as learning and memory impairments of AD mice. Metabolomics analysis reveals that energy metabolism, neurotransmitter metabolism, and membrane metabolism were significantly altered in all three brain regions after both types of exercises. Amino acid metabolism was detected to be affected in the cortex and hypothalamus after HIIT and in the hippocampus and hypothalamus after MICT. However, only HIIT significantly altered astrocyte-neuron metabolism in the hippocampus and hypothalamus of AD mice. Therefore, our study suggests that exercise can shape brain metabolism of AD mice in a region- and exercise-specific manner, indicating that the precise modification of brain metabolism by a specific type of exercise might be a novel perspective for the prevention and treatment of AD.

Investigating the causal association between branched-chain amino acids and Alzheimer's disease: A bidirectional Mendelian randomized study

Background

There are many metabolic pathway abnormalities in Alzheimer's disease (AD). Several studies have linked branched-chain amino acid (BCAA) metabolism disorders with AD but have not obtained consistent results. The purpose of this study is to explore the causal association between BCAA concentration and the risk of AD.

Methods

A bidirectional Mendelian randomized (MR) study was applied to explore the causal effect between BCAA level and the risk of AD. Genetic instrumental variables from the genome-wide association study (GWAS) of serum BCAA levels [total BCAAs (115,047 participants), valine (115,048 participants), leucine (115,074 participants), and isoleucine (115,075 participants)] from the UK Biobank and AD (21,982 AD cases and 41,944 controls) from the International Genomics of Alzheimer's Project were applied to explore the causal effect through the inverse variance-weighted (IVW) method, MR-Egger, and weighted median, accompanied by multiple pluripotency and heterogeneity tests.

Results

The forward MR analysis showed that there was no causal effect of total BCAAs (OR: 1.067, 95% CI: 0.838–1.358; p = 0.838), valine (OR: 1.106, 95% CI: 0.917–1.333; p = 0.292), leucine (OR: 1.096, 95% CI: 0.861–1.396; p = 0.659), and isoleucine (OR: 1.457, 95% CI: 1.024–2.742; p = 0.037) levels on the risk of AD. The reverse analysis showed that AD was related to reduced levels of total BCAAs (OR: 0.979, 95% CI: 0.989–0.990; p &lt; 0.001), valine (OR: 0.977, 95% CI: 0.963–0.991; p = 0.001), leucine (OR: 0.983, 95% CI: 0.973–0.994; p = 0.002), and isoleucine (OR: 0.982, 95% CI: 0.971–0.992; p = 0.001).

Conclusion

We provide robust evidence that AD was associated with a decreased level of BCAAs, which can serve as a marker for early diagnosis of AD.

Exploring the potential of ginseng glycoprotein to improve learning and memory in mice via Notch signaling pathway and structural analysis using multi-information fusion based on liquid chromatography-mass spectrometry

ETHNOPHARMACOLOGICAL RELEVANCE

Panax ginseng C.A. Meyer reportedly exhibits various beneficial pharmacological activities. Panax ginseng glycoproteins (PGG) are a class of glycosylated protein components extracted from ginseng and can exert significant activity for improving learning and memory abilities.

AIM OF THE STUDY

The objective of the present study was to investigate the PGG-mediated protective mechanism against neurodegenerative diseases via the Notch signaling pathway using proteomic methods.

MATERIALS AND METHODS

We examined learning and memory in mice using the Morris water maze and nest-building paradigms. The PGG structure was determined using multi-information fusion based on liquid chromatography-mass spectrometry (LC/MS). Accurate glycosylation sites of glycoproteins were identified using the advanced glycosylation analysis software Byonic. Furthermore, connection modes of the oligosaccharide chain were clarified by methylation analysis of sugar residues. The differentially expressed proteins (DEPs) between wild-type (WT) and APP/APS1 mice were measured and compared using label-free quantitative proteomics, and related signaling pathways were identified. For validation, we performed a series of in vitro tests, including an assessment of cell viability, apoptosis assay, quantitative real-time polymerase chain reaction, and western blotting.

RESULTS

In the Morris water maze and nesting experiments, PGG-treated WT mice exhibited significantly improved learning and memory. The structures of 171 glycoprotein fragments in PGG matched the credible score, and typical structures were identified using LC/MS data analysis. According to the proteomic analysis results, 188 DEPs were detected between the model and administration groups, and two downregulated DEPs were related to the Notch signaling pathway. Based on the in vitro verification tests, PGG significantly inhibited the expression of key proteins in the Notch signaling pathway in microglia.

CONCLUSIONS

PGG could prevent the development of neuroinflammation by inhibiting excessive activation of the Notch signaling pathway, thereby inhibiting neuroapoptosis.

Inflammatory bowel disease: A potential pathogenic factor of Alzheimer's disease

Alzheimer's disease (AD) is a central nervous system disease characterised by degenerative cognitive dysfunction and memory loss. In a society where the global population is gradually ageing, the health threats and financial burdens caused by AD are becoming increasingly severe since AD often occurs in old age. With the in-depth study of AD, many new pathogenic mechanisms have been proposed, among which bidirectional communication between intestinal microbes and the brain has attracted widespread attention. The aetiology of inflammatory bowel disease (IBD) is related to the imbalance of the gut microbiota. Epidemiological investigations have shown that patients with IBD are more likely to suffer from AD. Targeting IBD as a potential AD treatment target has attracted considerable interest. Here, we reviewed the link between chronic intestinal inflammation and central nervous system inflammation and found that IBD patients had a higher risk of AD than non-IBD patients. Preclinical models based on AD also showed that IBD aggravated the condition of AD. We discussed possible biological links between AD and IBD, including the gut-brain axis, autoimmunity, and the gut microbiota. In addition, IBD-induced changes in intestinal microbial metabolites, such as short-chain fatty acids, bile acids, and tryptophan, which aggravate the development of AD, were also discussed.

Decreased circulating branched-chain amino acids are associated with development of Alzheimer's disease in elderly individuals with mild cognitive impairment

Background

Nutritional epidemiology has shown that inadequate dietary protein intake is associated with poor brain function in the elderly population. The plasma free amino acid (PFAA) profile reflects nutritional status and may have the potential to predict future changes in cognitive function. Here, we report the results of a 2-year interim analysis of a 3-year longitudinal study following mild cognitive impairment (MCI) participants.

Method

In a multicenter prospective cohort design, MCI participants were recruited, and fasting plasma samples were collected. Based on clinical assessment of cognitive function up to 2 years after blood collection, MCI participants were divided into two groups: remained with MCI or reverted to cognitively normal ("MCI-stable," N = 87) and converted to Alzheimer's disease (AD) ("AD-convert," N = 68). The baseline PFAA profile was compared between the two groups. Stratified analysis based on apolipoprotein E ε4 (APOE ε4) allele possession was also conducted.

Results

Plasma concentrations of all nine essential amino acids (EAAs) were lower in the AD-convert group. Among EAAs, three branched-chain amino acids (BCAAs), valine, leucine and isoleucine, and histidine (His) exhibited significant differences even in the logistic regression model adjusted for potential confounding factors such as age, sex, body mass index (BMI), and APOE ε4 possession (p < 0.05). In the stratified analysis, differences in plasma concentrations of these four EAAs were more pronounced in the APOE ε4-negative group.

Conclusion

The PFAA profile, especially decreases in BCAAs and His, is associated with development of AD in MCI participants, and the difference was larger in the APOE ε4-negative population, suggesting that the PFAA profile is an independent risk indicator for AD development. Measuring the PFAA profile may have importance in assessing the risk of AD conversion in the MCI population, possibly reflecting nutritional status.

Clinical trial registration

[https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000025322], identifier [UMIN000021965].

Omics-based biomarkers discovery for Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorders presenting with the pathological hallmarks of amyloid plaques and tau tangles. Over the past few years, great efforts have been made to explore reliable biomarkers of AD. High-throughput omics are a technology driven by multiple levels of unbiased data to detect the complex etiology of AD, and it provides us with new opportunities to better understand the pathophysiology of AD and thereby identify potential biomarkers. Through revealing the interaction networks between different molecular levels, the ultimate goal of multi-omics is to improve the diagnosis and treatment of AD. In this review, based on the current AD pathology and the current status of AD diagnostic biomarkers, we summarize how genomics, transcriptomics, proteomics and metabolomics are all conducing to the discovery of reliable AD biomarkers that could be developed and used in clinical AD management.

Role of gut microbiota-derived branched-chain amino acids in the pathogenesis of Parkinson's disease: An animal study

Neuroinflammation caused by the disorder of gut microbiota and its metabolites is associated with the pathogenesis of Parkinson's disease (PD). Thus, it is necessary to identify certain molecules derived from gut microbiota to verify whether they could become intervention targets for the treatment of PD. The branched-chain amino acids (BCAAs), as a common dietary supplement, could modulate brain function. Herein, we investigated the longitudinal shifts of microbial community in mice treated with rotenone for 0, 3 and 4 weeks by 16S rRNA gene sequencing to identify the microbial markers at different PD stages. Serum BCAAs were determined by gas chromatography-mass spectrometry. Then, rotenone-induced mice were given a high BCAA diet to evaluate the motor and non-motor functions, dopaminergic neuron loss, and inflammation levels. Using a PD mouse model, we discovered that during PD progression, the alterations of gut microbiota compositions led to the peripheral decrease of BCAAs. Based on the serum lipopolysaccharide binding protein concentrations and the levels of pro-inflammatory factors (including tumor necrosis factor-α, interleukin [IL]-1β, and IL-6) in the colon and substantia nigra, we found that the high BCAA diet could attenuate the inflammatory levels in PD mice, and reverse motor and non-motor dysfunctions and dopaminergic neuron impairment. Together, our results emphasize the dynamic changes of gut microbiota and BCAA metabolism and propose a novel strategy for PD therapy: a high BCAA diet intervention could improve PD progression by regulating the levels of inflammation.

Air pollution exposure increases ABCB1 and ASCT1 transporter levels in mouse cortex

Membrane transporters are important for maintaining brain homeostasis by regulating the passage of solutes into, out of, and within the brain. Growing evidence suggests neurotoxic effects of air pollution exposure and its contribution to neurodegenerative disorders, including Alzheimer's disease (AD), yet limited knowledge is available on the exact cellular impacts of exposure. This study investigates how exposure to ubiquitous solid components of air pollution, ultrafine particles (UFPs), influence brain homeostasis by affecting protein levels of membrane transporters. Membrane transporters were quantified and compared in brain cortical samples of wild-type and the 5xFAD mouse model of AD in response to subacute exposure to inhaled UFPs. The cortical ASCT1 and ABCB1 transporter levels were elevated in wild-type and 5xFAD mice subjected to a 2-week UFP exposure paradigm, suggesting impairment of brain homeostatic mechanisms. This study provides new insight on the molecular mechanisms underlying adverse effects of air pollution on the brain.

Genetically predicted circulating levels of glycine, glutamate, and serotonin in relation to the risks of three major neurodegenerative diseases: A Mendelian randomization analysis

It has been previously postulated that blood neurotransmitters might affect risks of neurodegenerative diseases. Here, a Mendelian Randomization (MR) study was conducted to explore whether genetically predicted concentrations of glycine, glutamate and serotonin were associated with risks of Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). From three genome-wide association studies of European ancestry, single nucleotide polymorphisms strongly associated with glycine, glutamate and serotonin were selected as genetic instrumental variables. Corresponding summary statistics were also obtained from the latest genome-wide association meta-analyses of AD, PD and ALS. The inverse-variance weighted MR and multiple sensitivity analyses were performed to evaluate causal effects of genetically predicted levels of neurotransmitters on risks of neurodegenerative diseases. The statistical significance threshold was set at P < 0.0056 using the Bonferroni-correction, while 0.0056 < P < 0.05 was considered suggestive evidence for a causal association. There was a causal association of elevated blood glutamate levels with higher AD risks. The odds ratio (OR) of AD was 1.311 [95% confidence interval (CI), 1.087-1.580; P = 0.004] per one standard deviation increase in genetically predicted glutamate concentrations. There was suggestive evidence in support of a protective effect of blood serotonin on AD (OR = 0.607; 95% CI, 0.396-0.932; P = 0.022). Genetically predicted glycine levels were not associated with the risk of AD (OR = 1.145; 95% CI, 0.939-1.396; P = 0.180). Besides, MR analyses indicated no causal roles of three blood neurotransmitters in PD or ALS. In conclusion, the MR study provided evidence supporting the association of elevated blood glutamate levels with higher AD risks and the association of increased blood serotonin levels with lower AD risks. Triangulating evidence across further study designs is still warranted to elucidate the role of blood neurotransmitters in risks of neurodegenerative diseases.

Plasma metabolomic profiles of dementia: a prospective study of 110,655 participants in the UK Biobank

BACKGROUND

Plasma metabolomic profile is disturbed in dementia patients, but previous studies have discordant conclusions.

METHODS

Circulating metabolomic data of 110,655 people in the UK Biobank study were measured with nuclear magnetic resonance technique, and incident dementia records were obtained from national health registers. The associations between plasma metabolites and dementia were estimated using Cox proportional hazard models. The 10-fold cross-validation elastic net regression models selected metabolites that predicted incident dementia, and a 10-year prediction model for dementia was constructed by multivariable logistic regression. The predictive values of the conventional risk model, the metabolites model, and the combined model were discriminated by comparison of area under the receiver operating characteristic curves (AUCs). Net reclassification improvement (NRI) was used to estimate the change of reclassification ability when adding metabolites into the conventional prediction model.

RESULTS

Amongst 110,655 participants, the mean (standard deviation) age was 56.5 (8.1) years, and 51 186 (46.3%) were male. A total of 1439 (13.0%) developed dementia during a median follow-up of 12.2 years (interquartile range: 11.5-12.9 years). A total of 38 metabolites, including lipids and lipoproteins, ketone bodies, glycolysis-related metabolites, and amino acids, were found to be significantly associated with incident dementia. Adding selected metabolites (n=24) to the conventional dementia risk prediction model significantly improved the prediction for incident dementia (AUC: 0.824 versus 0.817, p =0.042) and reclassification ability (NRI = 4.97%, P = 0.009) for identifying high risk groups.

CONCLUSIONS

Our analysis identified various metabolomic biomarkers which were significantly associated with incident dementia. Metabolomic profiles also provided opportunities for dementia risk reclassification. These findings may help explain the biological mechanisms underlying dementia and improve dementia prediction.

The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach

The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.

Preventive Measures against the Development of Dementia in Old Age

Dementia is a neurological condition characterized by numerous types of central nervous system diseases, which gradually deteriorates an individual’s reasoning, rational thinking, and judgment abilities. As a serious public health concern that currently affects more than 50 million older adults, dementia is one of the most significant causes of incapacity, disability, and dependency among older adults. As new cases are expected to increase exponentially in the next three decades, dementia, which is not a normal feature of healthy aging despite the fact that it generally affects older adults disproportionately, requires enormous management and care efforts due to its associated socioeconomic, psychological, and physical burdens that involve the patient, their caregivers, guardians, family members, and society at large. Presently, there is no cure for dementia; however, this condition could be prevented. This narrative review aimed to provide a broad overview of studies detailing the alternative lifestyle modification-centered preventive measures against dementia. A comprehensive search of key databases to find articles related to this topic revealed that participating in regular physical activities, healthy eating and dieting, avoiding all forms of smoking, avoiding air pollutants, halting or reducing alcohol consumption, exercising the mind and being socially dynamic, getting enough rest and establishing good sleeping habits, infection prevention, stress prevention, avoidance of injuries, preventing the effects of social isolation and lockdowns, continuing education, and depression prevention are protective measures against the development of dementia.

Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep Learning

Swimmers must fully mobilize the muscles of the whole body during exercise, and it is necessary to study the protection of swimmers from muscle damage. Now, muscle damage is increasing year by year, and more athletes are affected. Therefore, studying the causes of muscle injuries and exploring more effective treatments have become important research topics in the field of sports medicine. This study is mainly based on deep learning to analyze the protective effect of branched-chain amino acids on swimming athletes' muscle injury. Due to the complex and changeable environment and the interference of unknown factors, a single sensor cannot meet the needs of obtaining information. Therefore, people have developed the technology of multisensor information fusion to obtain enough information. Multisensor data fusion technology can synthesize the information of each sensor and then obtain more comprehensive and accurate decision-making information. This study is mainly based on multisensor fusion and deep learning to analyze the impact of branched chain amino acids on Swimmers' muscle health information. Finally, two experiments were designed in this article. The first experimental result showed that the pain level of the experimental group who took BCAA supplements was 19% lower than that of the control group that did not take the BCAA supplement within three days after exercise. The results of the second experiment show the following: after exercise, the creatine kinase activity value of the experimental group taking BCAA supplement was 4.38 ± 1.45, and the creatine kinase activity value of the control group taking placebo was 5.42 ± 2.12. It proves that BBCA can protect muscle damage by reducing the activity of creatine kinase.

The Critical Role of the Branched Chain Amino Acids (BCAAs) Catabolism-Regulating Enzymes, Branched-Chain Aminotransferase (BCAT) and Branched-Chain α-Keto Acid Dehydrogenase (BCKD), in Human Pathophysiology

Branched chain amino acids (BCAAs), leucine, isoleucine and valine, are essential amino acids widely studied for their crucial role in the regulation of protein synthesis mainly through the activation of the mTOR signaling pathway and their emerging recognition as players in the regulation of various physiological and metabolic processes, such as glucose homeostasis. BCAA supplementation is primarily used as a beneficial nutritional intervention in chronic liver and kidney disease as well as in muscle wasting disorders. However, downregulated/upregulated plasma BCAAs and their defective catabolism in various tissues, mainly due to altered enzymatic activity of the first two enzymes in their catabolic pathway, BCAA aminotransferase (BCAT) and branched-chain α-keto acid dehydrogenase (BCKD), have been investigated in many nutritional and disease states. The current review focused on the underlying mechanisms of altered BCAA catabolism and its contribution to the pathogenesis of a numerous pathological conditions such as diabetes, heart failure and cancer. In addition, we summarize findings that indicate that the recovery of the dysregulated BCAA catabolism may be associated with an improved outcome and the prevention of serious disease complications.

The associations of serum valine with mild cognitive impairment and Alzheimer's disease

BACKGROUND

The introduction of metabolomics makes it possible to study the characteristic changes of peripheral metabolism in Alzheimer's disease (AD). Recent studies have found that the levels of valine are related to mild cognitive impairment (MCI) and AD.

AIMS

This study aimed to further clarify the characteristics of valine levels in MCI and AD.

METHODS

A total of 786 participants from the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1) cohort were selected to evaluate the relationships between serum valine and cerebrospinal fluid (CSF) biomarkers, brain structure (magnetic resonance imaging, MRI), cerebral glucose metabolism (¹⁸F-fluorodeoxyglucose-positron emission tomography, FDG-PET), and cognitive declines, through different cognitive subgroups.

RESULTS

Serum valine was decreased in patients with AD compared with cognitive normal (CN) and stable MCI (sMCI), and in progressive MCI (pMCI) compared with CN. Serum valine was negatively correlated with CSF total tau (t-tau) and phosphorylated tau (p-tau) in pMCI. Serum valine significantly predicted conversion from MCI to AD. In addition, serum valine was related to the rate of change of cerebral glucose metabolism during the follow-up period in pMCI.

CONCLUSIONS

Serum valine may be a peripheral biomarker of pMCI and AD, and its level predicts the progression of MCI to AD. Our study may help to reveal the metabolic changes during AD disease trajectory and its relationship to clinical phenotype.