Regulation of phase I and phase II neurosteroid enzymes in the hippocampus of an Alzheimer's disease rat model: A focus on sulphotransferases and UDP-glucuronosyltransferases

Propionic Acidemia, Methylmalonic Acidemia, and Cobalamin C Deficiency: Comparison of Untargeted Metabolomic Profiles

Methylmalonic acidemia (MMA), propionic acidemia (PA), and cobalamin C deficiency (cblC) share a defect in propionic acid metabolism. In addition, cblC is also involved in the process of homocysteine remethylation. These three diseases produce various phenotypes and complex downstream metabolic effects. In this study, we used an untargeted metabolomics approach to investigate the biochemical differences and the possible connections among the pathophysiology of each disease. The significantly changed metabolites in the untargeted urine metabolomic profiles of 21 patients (seven MMA, seven PA, seven cblC) were identified through statistical analysis (p < 0.05; log2FC > |1|) and then used for annotation. Annotated features were associated with different metabolic pathways potentially involved in the disease's development. Comparative statistics showed markedly different metabolomic profiles between MMA, PA, and cblC, highlighting the characteristic species for each disease. The most affected pathways were related to the metabolism of organic acids (all diseases), amino acids (all diseases), and glycine and its conjugates (in PA); the transsulfuration pathway; oxidative processes; and neurosteroid hormones (in cblC). The untargeted metabolomics study highlighted the presence of significant differences between the three diseases, pointing to the most relevant contrast in the cblC profile compared to MMA and PA. Some new biomarkers were proposed for PA, while novel data regarding the alterations of steroid hormone profiles and biomarkers of oxidative stress were obtained for cblC disease. The elevation of neurosteroids in cblC may indicate a potential connection with the development of ocular and neuronal deterioration.

Unraveling the enigma: housekeeping gene Ugt1a7c as a universal biomarker for microglia

Background

Microglia, brain resident macrophages, play multiple roles in maintaining homeostasis, including immunity, surveillance, and protecting the central nervous system through their distinct activation processes. Identifying all types of microglia-driven populations is crucial due to the presence of various phenotypes that differ based on developmental stages or activation states. During embryonic development, the E8.5 yolk sac contains erythromyeloid progenitors that go through different growth phases, eventually resulting in the formation of microglia. In addition, microglia are present in neurological diseases as a diverse population. So far, no individual biomarker for microglia has been discovered that can accurately identify and monitor their development and attributes.

Summary

Here, we highlight the newly defined biomarker of mouse microglia, UGT1A7C, which exhibits superior stability in expression during microglia development and activation compared to other known microglia biomarkers. The UGT1A7C sensing chemical probe labels all microglia in the 3xTG AD mouse model. The expression of Ugt1a7c is stable during development, with only a 4-fold variation, while other microglia biomarkers, such as Csf1r and Cx3cr1, exhibit at least a 10-fold difference. The UGT1A7C expression remains constant throughout its lifespan. In addition, the expression and activity of UGT1A7C are the same in response to different types of inflammatory activators' treatment in vitro.

Conclusion

We propose employing UGT1A7C as the representative biomarker for microglia, irrespective of their developmental state, age, or activation status. Using UGT1A7C can reduce the requirement for using multiple biomarkers, enhance the precision of microglia analysis, and even be utilized as a standard for gene/protein expression.

The potential impact of CYP and UGT drug-metabolizing enzymes on brain target site drug exposure

Drug metabolism is one of the critical determinants of drug disposition throughout the body. While traditionally associated with the liver, recent research has unveiled the presence and functional significance of drug-metabolizing enzymes (DMEs) within the brain. Specifically, cytochrome P-450 enzymes (CYPs) and UDP-glucuronosyltransferases (UGTs) enzymes have emerged as key players in drug biotransformation within the central nervous system (CNS). This comprehensive review explores the cellular and subcellular distribution of CYPs and UGTs within the CNS, emphasizing regional expression and contrasting profiles between the liver and brain, humans and rats. Moreover, we discuss the impact of species and sex differences on CYPs and UGTs within the CNS. This review also provides an overview of methodologies for identifying and quantifying enzyme activities in the brain. Additionally, we present factors influencing CYPs and UGTs activities in the brain, including genetic polymorphisms, physiological variables, pathophysiological conditions, and environmental factors. Examples of CYP- and UGT-mediated drug metabolism within the brain are presented at the end, illustrating the pivotal role of these enzymes in drug therapy and potential toxicity. In conclusion, this review enhances our understanding of drug metabolism's significance in the brain, with a specific focus on CYPs and UGTs. Insights into the expression, activity, and influential factors of these enzymes within the CNS have crucial implications for drug development, the design of safe drug treatment strategies, and the comprehension of drug actions within the CNS. To that end, CNS pharmacokinetic (PK) models can be improved to further advance drug development and personalized therapy.

Identification ferroptosis-related hub genes and diagnostic model in Alzheimer's disease

Background

Ferroptosis is a newly defined form of programmed cell death and plays an important role in Alzheimer's disease (AD) pathology. This study aimed to integrate bioinformatics techniques to explore biomarkers to support the correlation between ferroptosis and AD. In addition, further investigation of ferroptosis-related biomarkers was conducted on the transcriptome characteristics in the asymptomatic AD (AsymAD).

Methods

The microarray datasets GSE118553, GSE132903, GSE33000, and GSE157239 on AD were downloaded from the GEO database. The list of ferroptosis-related genes was extracted from the FerrDb website. Differentially expressed genes (DEGs) were identified by R "limma" package and used to screen ferroptosis-related hub genes. The random forest algorithm was used to construct the diagnostic model through hub genes. The immune cell infiltration was also analyzed by CIBERSORTx. The miRNet and DGIdb database were used to identify microRNAs (miRNAs) and drugs which targeting hub genes.

Results

We identified 18 ferroptosis-related hub genes anomalously expressed in AD, and consistent expression trends had been observed in both AsymAD The random forest diagnosis model had good prediction results in both training set (AUC = 0.824) and validation set (AUC = 0.734). Immune cell infiltration was analyzed and the results showed that CD4+ T cells resting memory, macrophages M2 and neutrophils were significantly higher in AD. A significant correlation of hub genes with immune infiltration was observed, such as DDIT4 showed strong positive correlation with CD4+ T cells memory resting and AKR1C2 had positive correlation with Macrophages M2. Additionally, the microRNAs (miRNAs) and drugs which targeting hub genes were screened.

Conclusion

These results suggest that ferroptosis-related hub genes we screened played a part in the pathological progression of AD. We explored the potential of these genes as diagnostic markers and their relevance to immune cells which will help in understanding the development of AD. Targeting miRNAs and drugs provides new research clues for preventing the development of AD.

Among men, androgens are associated with a decrease in Alzheimer's disease risk

INTRODUCTION

Increased levels of sex hormones have been hypothesized to decrease Alzheimer's disease (AD) risk. We assessed the association between sex steroid hormones with AD using a Mendelian randomization (MR) approach.

METHODS

An inverse-variance weighting (IVW) MR analysis was performed using effect estimates from external genome-wide association study (GWAS) summary statistics. We included independent variants (linkage disequilibrium R2  < 0.001) and a p-value threshold of 5 × 10-8 .

RESULTS

An increase in androgens was associated with a decreased AD risk among men: testosterone (odds ratio [OR]: 0.53; 95% confidence interval [CI]: 0.32-0.88; p-value: 0.01; false discovery rate [FDR] p-value: 0.03); dehydroepiandrosterone sulfate (DHEAS; OR: 0.56; 95% CI: 0.38-0.85; p-value: 0.01; FDR p-value: 0.03); and androsterone sulfate (OR: 0.69; 95% CI: 0.46-1.02; p-value: 0.06; FDR p-value: 0.10). There was no association between sex steroid hormones and AD among women, although analysis for estradiol had limited statistical power.

DISCUSSION

A higher concentration of androgens was associated with a decreased risk of AD among men of European ancestry, suggesting that androgens among men might be neuroprotective and could potentially prevent or delay an AD diagnosis.

HIGHLIGHTS

Sex hormones are hypothesized to play a role in developing Alzheimer's disease (AD). The effect of sex hormones on AD was assessed using Mendelian randomization (MR) analysis. Among women, genetically determined effects of sex hormones were limited or null. Among men, a higher concentration of androgens decreased AD risk. This study suggests a causal relationship between androgens and AD among men.

Construction of lncRNA-ceRNA Networks to Reveal the Potential Role of Lfng/Notch1 Signaling Pathway in Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) develops through a complex pathological process, in which many genes play a synergistic or antagonistic role. LncRNAs represent a kind of noncoding RNA, which can regulate gene expression at the epigenetic, transcriptional and posttranscriptional levels. Multiple lncRNAs have been found to have important regulatory functions in AD. Thus, their expression patterns, targets and functions should be explored as therapeutic targets.

METHODS

We used deep RNA-seq analysis to detect the dysregulated lncRNAs in the hippocampus of APP/PS1 mice. We performed Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to predict the biological roles and potential signaling pathways of dysregulated lncRNAs. Finally, we constructed lncRNA-miRNA-mRNA and lncRNA-mRNA co-expression networks to reveal the potential regulator roles in AD pathogenesis.

RESULTS

Our findings revealed 110 significantly dysregulated lncRNAs. GO and KEGG annotations showed the dysregulated lncRNAs to be closely related to the functions of axon and protein digestion and absorption. The lncRNA-mRNA network showed that 19 lncRNAs regulated App, Prnp, Fgf10 and Il33, while 5 lncRNAs regulated Lfng via the lncRNA-miR-3102-3p-Lfng axis. Furthermore, we preliminarily demonstrated the important regulatory role of the Lfng/Notch1 signaling pathway through lncRNA-ceRNA networks in AD.

CONCLUSION

We revealed the important regulatory roles of dysregulated lncRNAs in the etiopathogenesis of AD through lncRNA expression profiling. Our results showed that the mechanism involves the regulation of the Lfng/Notch1 signaling pathway.