MALDI-TOF Protein Profiling Reflects Changes in Type 1 Diabetes Patients Depending on the Increased Amount of Adipose Tissue, Poor Control of Diabetes and the Presence of Chronic Complications

Non-invasive metabolic biomarkers in initial cognitive impairment in patients with diabetes: A systematic review and meta-analysis

AIM

Diabetic cognitive impairment (DCI), considered one of the most severe and commonly overlooked complications of diabetes, has shown inconsistent findings regarding the metabolic profiles in DCI patients. This systematic review and meta-analysis aimed to identify dysregulated metabolites as potential biomarkers for early DCI, providing valuable insights into the underlying pathophysiological mechanisms.

MATERIALS AND METHODS

A systematic search of four databases, namely PubMed, Embase, Web of Science and Cochrane, was conducted up to March 2024. Subsequently, a qualitative review of clinical studies was performed followed by a meta-analysis of metabolite markers. Finally, the sources of heterogeneity were explored through subgroup and sensitivity analyses.

RESULTS

A total of 774 unique publications involving 4357 participants and the identification of multiple metabolites were retrieved. Of these, 13 clinical studies reported metabolite differences between the DCI and control groups. Meta-analysis was conducted for six brain metabolites and two metabolite ratios. The results revealed a significant increase in myo-inositol (MI) concentration and decreases in glutamate (Glu), Glx (glutamate and glutamine) and N-acetylaspartate/creatine (NAA/Cr) ratios in DCI, which have been identified as the most sensitive metabolic biomarkers for evaluating DCI progression. Notably, brain metabolic changes associated with cognitive impairment are more pronounced in type 2 diabetes mellitus than in type 1 diabetes mellitus, and the hippocampus emerged as the most sensitive brain region regarding metabolic changes associated with DCI.

CONCLUSIONS

Our results suggest that MI, Glu, and Glx concentrations and NAA/Cr ratios within the hippocampus may serve as metabolic biomarkers for patients with early-stage DCI.

Exploration of quantitative site-specific serum O-glycoproteomics with isobaric labeling for the discovery of putative O-glycoprotein biomarkers

PURPOSE

Exploration study of site-specific isobaric-TMT-labeling quantitative serum O-glycoproteomics for the discovery of putative O-glycoprotein cancer biomarkers.

EXPERIMENTAL DESIGN

Sera of 10 breast cancer patients was used as the exploration cohort. More abundant N-glycosylation was first removed with PNGase F. After tryptic digestion of de-N-glycosylated serum proteome, the TMT-labeled O-glycopeptides mixture was prepared and analyzed with RPLC-MS/MS. Site-specific qualitative and quantitative database search of O-glycopeptides was carried out with pGlyco 3.0. The same raw datasets were also searched with intact N-glycopeptide search engine GPSeeker to exclude possible interference of N-glycosylation. The final IDs were checked manually with GlcNAc-containing glycosite-determining fragment ions for confirmation.

RESULTS

With the control of spectrum-level FDR ≤ 1% and manual validation, 299 O-glycopeptides corresponding to 83 O-glycosites and 66 O-glycoproteins were identified, and 13 O-glycopeptides were found differentially expressed. Most interestingly, differential O-glycosylation was observed for IgG1 and IgG3, which is an interesting putative biomarker panel.

CONCLUSION AND CLINICAL RELEVANCE

Isobaric-labeling site-specific quantitative O-glycoproteomics is currently a state-of-the-art instrumental platform for discovery of putative seral cancer biomarkers. Differential seral O-glycosylation was observed in the IgG1 and IgG3.

UPLC-HDMSE to discover serum biomarkers in adults with type 1 diabetes

Type 1 diabetes (T1D) is a complex disease with metabolic and functional changes that can alter an individual's proteome. An LC-MS/MS analytical method, in an HDMS^E system, was used to identify differentially expressed proteins in the high abundance protein-depleted serum of T1D patients and healthy controls. Samples were processed in Progenesis QI for Proteomics software. A functional enrichment of the proteins was performed with Gene Ontology and ToppGene, and the interactions were visualized by STRING 11.5. As a result, 139 proteins were identified, 14 of which were downregulated in the serum of patients with T1D compared to controls. Most of the differentially expressed proteins were shown to be involved with the immune system, inflammation, and growth hormone stimulus response, and were associated with the progression of T1D. Differential protein expression data showed for the first-time changes in CPN2 expression levels in the serum of patients with T1D. Our findings indicate that these proteins are targets of interest for future investigations and for validation of protein biomarkers in T1D.

MALDI-TOF MS: application in diagnosis, dereplication, biomolecule profiling and microbial ecology

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized scientific research over the past few decades and has provided a unique platform in ongoing technological developments. Undoubtedly, there has been a bloom chiefly in the field of biological sciences with this emerging technology, and has enabled researchers to generate critical data in the field of disease diagnoses, drug development, dereplication. It has received well acceptance in the field of microbial identification even at strain level, as well as diversified field like biomolecule profiling (proteomics and lipidomics) has evolved tremendously. Additionally, this approach has received a lot more attention over conventional technologies due to its high throughput, speed, and cost effectiveness. This review aims to provide a detailed insight regarding the application of MALDI-TOF MS in the context of medicine, biomolecule profiling, dereplication, and microbial ecology. In general, the expansion in the application of this technology and new advancements it has made in the field of science and technology has been highlighted.