Mild cognitive impairment (MCI) is an early stage of memory loss that affects cognitive abilities, such as language or virtual/spatial comprehension. This cognitive decline is mostly observed with the aging of individuals. Recently, MCI has been considered as a prodromal phase of Alzheimer’s disease (AD), with a 10–15% conversion rate. However, the existing diagnostic methods fail to provide precise and well-timed diagnoses, and the pathophysiology of MCI is not fully understood. Alterations of serum N-glycan expression could represent essential contributors to the overall pathophysiology of neurodegenerative diseases and be used as a potential marker to assess MCI diagnosis using non-invasive procedures. Herein, we undertook an LC-MS/MS glycomics approach to determine and characterize potential N-glycan markers in depleted blood serum samples from MCI patients. For the first time, we profiled the isomeric glycome of the low abundant serum glycoproteins extracted from serum samples of control and MCI patients using an LC-MS/MS analytical strategy. Additionally, the MRM validation of the identified data showed five isomeric N-glycans with the ability to discriminate between healthy and MCI patients: the sialylated N-glycans GlcNAc₅,Hex₆,Neu5Ac₃ and GlcNAc₆,Hex₇,Neu5Ac₄ with single AUCs of 0.92 and 0.87, respectively, and a combined AUC of 0.96; and the sialylated-fucosylated N-glycans GlcNAc₄,Hex₅,Fuc, Neu5Ac, GlcNAc₅,Hex₆,Fuc, Neu5Ac₂, and GlcNAc₆,Hex₇,Fuc, Neu5Ac₃ with single AUCs of 0.94, 0.67, and 0.88, respectively, and a combined AUC of 0.98. According to the ingenuity pathway analysis (IPA) and in line with recent publications, the identified N-glycans may play an important role in neuroinflammation. It is a process that plays a fundamental role in neuroinflammation, an important process in the progression of neurodegenerative diseases.

The SARS-CoV-2 virus rapidly spread worldwide, threatening public health. Since it emerged, the scientific community has been engaged in the development of effective therapeutics and vaccines. The subunit S1 in the spike protein of SARS-CoV-2 mediates the viral entry into the host and is therefore one of the major research targets. The S1 protein is extensively glycosylated, and there is compelling evidence that glycans protect the virus’ active site from the human defense system. Therefore, investigation of the S1 protein glycome alterations in the different virus variants will provide a view of the glycan evolution and its relationship with the virus pathogenesis. In this study, we explored the N-glycosylation expression of the S1 protein for eleven SARS-CoV-2 variants: five variants of concern (VOC), including alpha, beta, gamma, delta, and omicron, and six variants of interest (VOI), including epsilon, eta, iota, lambda, kappa, and mu. The results showed significant differences in the N-glycome abundance of all variants. The N-glycome of the VOC showed a large increase in the abundance of sialofucosylated glycans, with the greatest abundance in the omicron variant. In contrast, the results showed a large abundance of fucosylated glycans for most of the VOI. Two glycan compositions, GlcNAc₄,Hex₅,Fuc,NeuAc (4-5-1-1) and GlcNAc₆,Hex₈,Fuc,NeuAc (6-8-1-1), were the most abundant structures across all variants. We believe that our data will contribute to understanding the S1 protein’s structural differences between SARS-CoV-2 mutations.

Glycoproteomic analysis is always challenging because of low abundance and complex site-specific heterogeneity. Glycoproteins are involved in various biological processes such as cell signaling, adhesion, and cell–cell communication and may serve as potential biomarkers when analyzing different diseases. Here, we investigate glycoproteins in narcolepsy type 1 (NT1) disease, a form of narcolepsy characterized by cataplexy—the sudden onset of muscle paralysis that is typically triggered by intense emotions. In this study, 27 human blood serum samples were analyzed, 16 from NT1 patients and 11 from healthy individuals serving as controls. We quantified hydrophilic interaction liquid chromatography (HILIC)-enriched glycopeptides from low-abundance serum samples of controls and NT1 patients via LC-MS/MS. Twenty-eight unique N-glycopeptides showed significant changes between the two studied groups. The sialylated N-glycopeptide structures LPTQNITFQTESSVAEQEAEFQSPK HexNAc₆, Hex₃, Neu5Ac₂ (derived from the ITIH4 protein) and the structure IVLDPSGSMNIYLVLDGSDSIGASNFTGAK HexNAc₅, Hex₄, Fuc₁ (derived from the CFB protein), with p values of 0.008 and 0.01, respectively, were elevated in NT1 samples compared with controls. In addition, the N-glycopeptide protein sources Ceruloplasmin, Complement factor B, and ITH4 were observed to play an important role in the complement activation and acute-phase response signaling pathways. This may explain the possible association between the biomarkers and pathophysiological effects.

Background: Narcolepsy type 1 (NT1) is a rare neurological sleep disorder characterized by excessive daytime sleepiness and cataplexy. NT1 is thought to be caused by the loss of hypocretin-producing neurons in the hypothalamus due to autoimmunity. Since cerebrospinal fluid hypocretin testing is invasive and not always feasible in clinical practice, there is a critical need for less invasive biomarkers to improve diagnostic accuracy and accessibility. Very few studies have explored serum-based biomolecules that could serve as biomarkers for NT1. Methods: This study examines the differential abundance of serum metabolites in patients with NT1 using an LC-MS/MS-based comprehensive metabolomics approach. Results: An untargeted analysis identified a total of 1491 metabolites, 453 of which were differentially abundant compared to the control cohort. Ingenuity pathway analysis revealed that key pathways, such as the inflammatory response (p-value of 0.01, activation z-score of 0.5), generation and synthesis of reactive oxygen species (p-value of 0.0008, z-score of 1.3), and neuronal cell death (p-value of 0.04, z-score of 0.4), are predicted to be activated in NT1. A targeted analysis using parallel reaction monitoring validated 49 metabolites, including important downregulated metabolites such as uridine (fold change (FC) of 0.004), epinephrine (FC of 0.05), colchicine (FC of 0.2), corticosterone (FC of 0.3), and arginine (FC of 0.6), as well as upregulated metabolites such as p-cresol sulfate (FC of 2601.7), taurine (FC of 1315.4), inosine (FC of 429.7), and malic acid (FC of 7.9). Conclusions: Understanding the pathways identified in this study and further investigating the differentially abundant metabolites associated with them may pave the way for gaining insight into disease pathogenesis and developing novel therapeutic interventions.