Metabolites Associated with Early Cognitive Changes Implicated in Alzheimer's Disease

Oral prodrug of a novel glutathione surrogate reverses metabolic dysregulation and attenuates neurodegenerative process in APP/PS1 mice

Glycation-induced oxidative stress underlies the numerous metabolic ravages of Alzheimer's disease (AD). Reduced glutathione levels in AD lead to increased oxidative stress, including glycation-induced pathology. Previously, we showed that the accumulation of reactive 1,2-dicarbonyls such as methylglyoxal, the major precursor of non-enzymatic glycation products, was reduced by the increased function of GSH-dependent glyoxalase-1 enzyme in the brain. In this two-pronged study, we evaluate the therapeutic efficacy of an orally bioavailable prodrug of our lead glyoxalase substrate, pro-ψ-GSH, for the first time in a transgenic Alzheimer's disease mouse model. This prodrug delivers pharmacodynamically relevant brain concentrations of ψ-GSH upon oral delivery. Chronic oral dosing of pro-ψ-GSH effectively reverses the cognitive decline observed in the APP/PS1 mouse model. The prodrug successfully mirrors the robust effects of the parent drug i.e., reducing amyloid pathology, glycation stress, neuroinflammation, and the resultant neurodegeneration in these mice. We also report the first metabolomics study of such a treatment, which yields key biomarkers linked to the reversal of AD-related metabolic dysregulation. Collectively, this study establishes pro-ψ-GSH as a viable, disease-modifying therapy for AD and paves the way for further preclinical advancement of such therapeutics. Metabolomic signatures identified could prove beneficial in the development of treatment-specific clinically translatable biomarkers.

The blood metabolome of cognitive function and brain health in middle-aged adults - influences of genes, gut microbiome, and exposome

Increasing evidence suggests the involvement of metabolic alterations in neurological disorders, including Alzheimer's disease (AD), and highlights the significance of the peripheral metabolome, influenced by genetic factors and modifiable environmental exposures, for brain health. In this study, we examined 1,387 metabolites in plasma samples from 1,082 dementia-free middle-aged participants of the population-based Rotterdam Study. We assessed the relation of metabolites with general cognition (G-factor) and magnetic resonance imaging (MRI) markers using linear regression and estimated the variance of these metabolites explained by genes, gut microbiome, lifestyle factors, common clinical comorbidities, and medication using gradient boosting decision tree analysis. Twenty-one metabolites and one metabolite were significantly associated with total brain volume and total white matter lesions, respectively. Fourteen metabolites showed significant associations with G-factor, with ergothioneine exhibiting the largest effect (adjusted mean difference = 0.122, P = 4.65×10-7). Associations for nine of the 14 metabolites were replicated in an independent, older cohort. The metabolite signature of incident AD in the replication cohort resembled that of cognition in the discovery cohort, emphasizing the potential relevance of the identified metabolites to disease pathogenesis. Lifestyle, clinical variables, and medication were most important in determining these metabolites' blood levels, with lifestyle, explaining up to 28.6% of the variance. Smoking was associated with ten metabolites linked to G-factor, while diabetes and antidiabetic medication were associated with 13 metabolites linked to MRI markers, including N-lactoyltyrosine. Antacid medication strongly affected ergothioneine levels. Mediation analysis revealed that lower ergothioneine levels may partially mediate negative effects of antacids on cognition (31.5%). Gut microbial factors were more important for the blood levels of metabolites that were more strongly associated with cognition and incident AD in the older replication cohort (beta-cryptoxanthin, imidazole propionate), suggesting they may be involved later in the disease process. The detailed results on how multiple modifiable factors affect blood levels of cognition- and brain imaging-related metabolites in dementia-free participants may help identify new AD prevention strategies.

Identification of 7-HOCA as a Potential Biomarker in Glioblastoma: Evidence from Genome-Wide Association Study and Clinical Validation

Purpose

Glioblastoma (GBM) is associated with metabolic disturbances, yet the relationships between metabolites with GBM have not been comprehensively explored. This study aims to fill this gap by integrating Mendelian randomization (MR) analysis with clinical validation.

Patients and Methods

Summary data from genome-wide association study (GWAS) of cerebrospinal fluid (CSF) metabolites, plasma metabolites, and GBM were obtained separately. A total of 338 CSF metabolites and 1400 plasma metabolites were utilized as exposures. Concurrently, GBM was designated as the outcome. A two-sample bidirectional MR study was conducted to investigate the potential association. The inverse variance weighted (IVW) analyses were conducted as causal estimates, accompanied by a series of sensitivity analyses to evaluate the robustness of the results. Additionally, metabolite levels in clinical plasma and CSF samples were quantified using liquid chromatography-mass spectrometry to validate the findings.

Results

MR analysis identified eight CSF metabolites and six plasma metabolites that were closely associated with GBM. Among these, elevated levels of 7-alpha-hydroxy-3-oxo-4-cholestenoate (7-HOCA) in both CSF and plasma were found to promote GBM. In terms of clinical validation, compared to the control group, 7-HOCA levels were significantly higher in both the CSF and plasma of GBM group.

Conclusion

This study provides a comprehensive analysis of the metabolic factors contributing to GBM. The identification of specific metabolites, particularly 7-HOCA, that have vital roles in GBM pathogenesis suggests new biomarkers and therapeutic targets, offering potential pathways for improved diagnosis and treatment of GBM.

Interplay between immune cells and metabolites in epilepsy: insights from a Mendelian randomization analysis

Background

Epilepsy is associated with the immune system and metabolism; however, its etiology remains insufficiently understood. Here, we aim to elucidate whether circulating immune cell profiles and metabolites impact the susceptibility to epilepsy.

Methods

We used publicly available genetic data and two-sample Mendelian randomization (MR) analyses to establish causal relationships and mediating effects between 731 immune cells and 1,400 metabolites associated with epilepsy. Sensitivity analyses were conducted to detect heterogeneity and horizontal pleiotropy in the study results.

Results

MR analysis examining the relationship between immune cells, metabolites, and epilepsy revealed significant causal associations with 28 different subtypes of immune cells and 14 metabolites. Besides, the mediation effects analysis revealed that eight metabolites mediated the effects of six types of immune cells on epilepsy and that 3-hydroxyoctanoylcarnitine (2) levels exhibited the highest mediating effect, mediating 15.3% (95%CI, -0.008, -30.6%, p = 0.049) of the effect of DN (CD4-CD8-) AC on epilepsy. 1-(1-enyl-stearoyl)-2-linoleoyl-GPE (p-18:0/18:2) levels (95%CI, 0.668, 10.6%, p = 0.026) and X-12544 levels (95%CI, -15.1, -0.856%, p = 0.028) contributed 5.63 and 8%, respectively, to the causal effect of FSC-A on myeloid DC on epilepsy.

Conclusion

This study revealed a significant causal link between immune cells, metabolites, and epilepsy. It remarkably enhances our understanding of the interplay between immune responses, metabolites, and epilepsy risk, providing insights into the development of therapeutic strategies from both immune and metabolic perspectives.

A Comprehensive Investigation of the Potential Role of Lipoproteins and Metabolite Profile as Biomarkers of Alzheimer's Disease Compared to the Known CSF Biomarkers

Introduction

While cerebrospinal fluid (CSF) core biomarkers have been considered diagnostic biomarkers for a long time, special attention has been recently dedicated to lipoproteins and metabolites that could be potentially associated with Alzheimer's disease (AD) neurodegeneration. Herein, we aimed to investigate the relationship between the levels of CSF core biomarkers including Aβ-42, TAU, and P-TAU and plasma lipoproteins and metabolites of patients with AD from the baseline cohort of the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

Method

Using the ADNI database, fourteen subclasses of lipoproteins as well as a number of lipids and fatty acids and low-molecular metabolites including amino acids, ketone bodies, and glycolysis-related metabolites in blood samples were measured as potential noninvasive markers, and their association with the CSF core biomarkers was statistically investigated controlling for age and gender.

Results

A total number of 251 AD subjects were included, among whom 71 subjects were negative for the Apo-E ε4 allele and 150 were positive. There was no significant difference between the two groups regarding cognitive assessments, CSF core biomarkers, and lipoproteins and metabolites except the level of Aβ-42 (p < 0.001) and phenylalanine (p = 0.049), which were higher in the negative group. CSF TAU and P-TAU were significantly correlated with medium and small HDL in the negative group, and with extremely large VLDL in the positive group. Our results also indicated significant correlations of metabolites including unsaturated fatty acids, glycerol, and leucine with CSF core biomarkers.

Conclusion

Based on our findings, a number of lipoproteins and metabolites were associated with CSF core biomarkers of AD. These correlations showed some differences in Apo-E ε4 positive and negative groups, which reminds the role of Apo-E gene status in the pathophysiology of AD development. However, further research is warranted to explore the exact association of lipoproteins and other metabolites with AD core biomarkers and pathology.

Metabolic reprogramming enables the auxiliary diagnosis of breast cancer by automated breast volume scanner

Breast cancer is the leading cause of female cancer-related deaths worldwide. New technologies with enhanced sensitivity and specificity for early diagnosis and monitoring of postoperative recurrence are in critical demand. Automatic breast full volume scanning system (ABVS) is an emerging technology used as an alternative imaging method for breast cancer screening. Despite its improved detection rate of malignant tumors, ABVS cannot accurately stage breast cancer preoperatively in 30–40% of cases. As a major hallmark of breast cancer, the characteristic metabolic reprogramming may provide potential biomarkers as an auxiliary method for ABVS.

Objective

The objective of this study was to identify differential metabolomic signatures between benign and malignant breast tumors and among different subtypes of breast cancer patients based on untargeted metabolomics and improve breast cancer detection rate by combining key metabolites and ABVS.

Methods

Untargeted metabolomics approach was used to profile serum samples from 70 patients with different subtypes of breast cancer and benign breast tumor to determine specific metabolomic profiles through univariate and multivariate statistical data analysis.

Results

Metabolic profiles correctly distinguished benign and malignant breast tumors patients, and a total of 791 metabolites were identified. There were 54 different metabolites between benign and malignant breast tumors and 17 different metabolites between invasive and non-invasive breast cancer. Notably, the missed diagnosis rate of ABVS could be reduced by differential metabolite analysis. Moreover, the diagnostic performance analyses of combined metabolites (pelargonic acid, N-acetylasparagine, and cysteine-S-sulfate) with ABVS performance gave a ROC area under the curve of 0.967 (95% CI: 0.926, 0.993).

Conclusions

Our study identified metabolic features both in benign and malignant breast tumors and in invasive and non-invasive breast cancer. Combined ultrasound ABVS and a panel of differential serum metabolites could further improve the accuracy of preoperative diagnosis of breast cancer and guide surgical therapy.

Metabolites Associated with Memory and Gait: A Systematic Review

We recently found that dual decline in memory and gait speed was consistently associated with an increased risk of dementia compared to decline in memory or gait only or no decline across six aging cohorts. The mechanisms underlying this relationship are unknown. We hypothesize that individuals who experience dual decline may have specific pathophysiological pathways to dementia which can be indicated by specific metabolomic signatures. Here, we summarize blood-based metabolites that are associated with memory and gait from existing literature and discuss their relevant pathways. A total of 39 eligible studies were included in this systematic review. Metabolites that were associated with memory and gait belonged to five shared classes: sphingolipids, fatty acids, phosphatidylcholines, amino acids, and biogenic amines. The sphingolipid metabolism pathway was found to be enriched in both memory and gait impairments. Existing data may suggest that metabolites from sphingolipids and the sphingolipid metabolism pathway are important for both memory and gait impairments. Future studies using empirical data across multiple cohorts are warranted to identify metabolomic signatures of dual decline in memory and gait and to further understand its relationship with future dementia risk.

Current research status of blood biomarkers in Alzheimer's disease: Diagnosis and prognosis

Alzheimer's disease (AD), which mainly occurs in the elderly, is a neurodegenerative disease with a hidden onset, which leads to progressive cognitive and behavioral changes. The annually increasing prevalence rate and number of patients with AD exert great pressure on the society. No effective disease-modifying drug treatments are available; thus, there is no cure yet. The disease progression can only be delayed through early detection and drug assistance. Therefore, the importance of exploring associated biomarkers for the early diagnosis and prediction of the disease progress is highlighted. The National Institute on Aging- Alzheimer's Association (NIA-AA) proposed A/T/N diagnostic criteria in 2018, including Aβ42, p-tau, t-tau in cerebrospinal fluid (CSF), and positron emission tomography (PET). However, the invasiveness of lumbar puncture for CSF assessment and non-popularity of PET have prompted researchers to look for minimally invasive, easy to collect, and cost-effective biomarkers. Therefore, studies have largely focused on some novel molecules in the peripheral blood. This is an emerging research field, facing many obstacles and challenges while achieving some promising results.