Label-Free Liquid Chromatography-Mass Spectrometry Proteomic Analysis of Urinary Identification in Diabetic Vascular Dementia in a Han Chinese Population

Microglial AKAP8L: a key mediator in diabetes-associated cognitive impairment via autophagy inhibition and neuroinflammation triggering

BACKGROUND

Diabetes-associated cognitive impairment (DACI) poses a significant challenge to the self-management of diabetes, markedly elevating the risk of adverse complications. A burgeoning body of evidence implicates microglia as a central player in the pathogenesis of DACI.

METHODS

We utilized proteomics to identify potential biomarkers in high glucose (HG)-treated microglia, followed by gene knockdown techniques for mechanistic validation in vitro and in vivo.

RESULTS

Our proteomic analysis identified a significant upregulation of AKAP8L in HG-treated microglia, with concurrent dysregulation of autophagy and inflammation markers, making AKAP8L a novel biomarker of interest. Notably, the accumulation of AKAP8L was specific to HG-treated microglia, with no observed changes in co-cultured astrocytes or neurons, a pattern that was mirrored in streptozotocin (STZ)-induced diabetic mice. Further studies through co-immunoprecipitation and proximity ligation assay indicated that the elevated AKAP8L in HG-treated microglial cells interacts with the mTORC1. In the STZ mouse model, we demonstrated that both AKAP8L knockdown and rapamycin treatment significantly enhanced cognitive function, as evidenced by improved performance in the Morris water maze, and reduced microglial activation. Moreover, these interventions effectively suppressed mTORC1 signaling, normalized autophagic flux, mitigated neuroinflammation, and decreased pyroptosis.

CONCLUSIONS

Our findings highlight the critical role of AKAP8L in the development of DACI. By interacting with mTORC1, AKAP8L appears to obstruct autophagic processes and initiate a cascade of neuroinflammatory responses. The identification of AKAP8L as a key mediator in DACI opens up new avenues for potential therapeutic interventions.

A novel Mediterranean diet-inspired supplement ameliorates cognitive, microbial, and metabolic deficits in a mouse model of low-grade inflammation

The Mediterranean diet (MD) and its bioactive constituents have been advocated for their neuroprotective properties along with their capacity to affect gut microbiota speciation and metabolism. Mediated through the gut brain axis, this modulation of the microbiota may partly contribute to the neuroprotective properties of the MD. To explore this potential interaction, we evaluated the neuroprotective properties of a novel bioactive blend (Neurosyn240) resembling the Mediterranean diet in a rodent model of chronic low-grade inflammation. Behavioral tests of cognition, brain proteomic analysis, 16S rRNA sequencing, and 1H NMR metabolomic analyses were employed to develop an understanding of the gut-brain axis interactions involved. Recognition memory, as assessed by the novel object recognition task (NOR), decreased in response to LPS insult and was restored with Neurosyn240 supplementation. Although the open field task performance did not reach significance, it correlated with NOR performance indicating an element of anxiety related to this cognitive change. Behavioral changes associated with Neurosyn240 were accompanied by a shift in the microbiota composition which included the restoration of the Firmicutes: Bacteroidota ratio and an increase in Muribaculum, Rikenellaceae Alloprevotella, and most notably Akkermansia which significantly correlated with NOR performance. Akkermansia also correlated with the metabolites 5-aminovalerate, threonine, valine, uridine monophosphate, and adenosine monophosphate, which in turn significantly correlated with NOR performance. The proteomic profile within the brain was dramatically influenced by both interventions, with KEGG analysis highlighting oxidative phosphorylation and neurodegenerative disease-related pathways to be modulated. Intriguingly, a subset of these proteomic changes simultaneously correlated with Akkermansia abundance and predominantly related to oxidative phosphorylation, perhaps alluding to a protective gut-brain axis interaction. Collectively, our results suggest that the bioactive blend Neurosyn240 conferred cognitive and microbiota resilience in response to the deleterious effects of low-grade inflammation.

Urinary protein biomarkers based on LC-MS/MS analysis to discriminate vascular dementia from Alzheimer's disease in Han Chinese population

Objective

This study aimed to identify the potential urine biomarkers of vascular dementia (VD) and unravel the disease-associated mechanisms by applying Liquid chromatography tandem-mass spectrometry (LC-MS/MS).

Methods

LC-MS/MS proteomic analysis was applied to urine samples from 3 groups, including 14 patients with VD, 9 patients with AD, and 21 normal controls (NC). By searching the MS data by Proteome Discoverer software, analyzing the protein abundances qualitatively and quantitatively, comparing between groups, combining bioinformatics analysis using Gene Ontology (GO) and pathway crosstalk analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG), and literature searching, the differentially expressed proteins (DEPs) of VD can be comprehensively determined at last and were further quantified by receiver operating characteristic (ROC) curve methods.

Results

The proteomic findings showed quantitative changes in patients with VD compared to patients with NC and AD groups; among 4,699 identified urine proteins, 939 and 1,147 proteins displayed quantitative changes unique to VD vs. NC and AD, respectively, including 484 overlapped common DEPs. Then, 10 unique proteins named in KEGG database (including PLOD3, SDCBP, SRC, GPRC5B, TSG101/STP22/VPS23, THY1/CD90, PLCD, CDH16, NARS/asnS, AGRN) were confirmed by a ROC curve method.

Conclusion

Our results suggested that urine proteins enable detection of VD from AD and VC, which may provide an opportunity for intervention.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/

Identification of Dysregulated Mechanisms and Potential Biomarkers in Ischemic Stroke Onset

Objective

Ischemic stroke (IS) is a major cause of severe disability. This study aimed to identify potential biomarkers closely related to IS diagnosis and treatment.

Methods

Profiles of gene expression were obtained from datasets GSE16561, GSE22255, GSE112801 and GSE110993. Differentially expressed mRNAs between IS and controls were then subjected to weighted gene co-expression network analysis as well as multiscale embedded gene co-expression network analysis. The intersection of the two sets of module genes was subjected to analyses of functional enrichment and of microRNAs (miRNAs) regulation. Then, the area under receiver operating characteristic curves (AUC) was calculated to assess the ability of genes to discriminate IS patients from controls. IS diagnostic signatures were constructed using least absolute shrinkage and selection operator regression.

Results

A total of 234 common co-expression network genes were found to be potentially associated with IS. Enrichment analysis found that these genes were mainly associated with inflammation and immune response. The aberrantly expressed miRNAs (hsa-miR-651-5p, hsa-miR-138-5p, hsa-miR-9-3p and hsa-miR-374a-3p) in IS had regulatory effects on IS-related genes and were involved in brain-related diseases. We used the criterion AUC > 0.7 to screen out 23 hub genes from IS-related genes in the GSE16561 and GSE22255 datasets. We obtained an 8-gene signature (ADCY4, DUSP1, ATP5F1, DCTN5, EIF3G, ELAVL1, EXOSC7 and PPIE) from the training set of GSE16561 dataset, which we confirmed in the validation set of GSE16561 dataset and in the GSE22255 dataset. The genes in this signature were highly accurate for diagnosing IS. In addition, the 8-gene signature significantly correlated with infiltration by immune cells.

Conclusion

These findings provide new clues to molecular mechanisms and treatment targets in IS. The genes in the signature may be candidate markers and potential gene targets for treatments.