Glycosylation: A new signaling paradigm for the neurovascular diseases

Identification and Validation of Glycosylation‑Related Genes in Ischemic Stroke Based on Bioinformatics and Machine Learning

Ischemic stroke (IS) constitutes a severe neurological disorder with restricted treatment alternatives. Recent investigations have disclosed that glycosylation is closely associated with the occurrence and outcome of IS. Nevertheless, data on the transcriptomic dynamics of glycosylation in IS are lacking. The objective of this study was to undertake a comprehensive exploration of glycosylation-related genes (GRGs) in IS via bioinformatics and to assess their immune characteristics. In this study, through the intersection of genes from weighted gene co-expression network analysis, GRGs from five glycosylation pathways, and DEGs from differential expression analysis, 20 candidate GRGs were identified. Subsequently, through LASSO, Random Forest, and SVM-RFE, 3 hub GRGs (F5, PPP6C, and UBE2J1) were identified. Additional, a gene diagnostic model linked to glycosylation was developed and validated. The findings indicated that the diagnostic model could effectively distinguish between IS patients and healthy individuals in the training, validation, and merging datasets, indicating clinical relevance. Subsequently, by employing unsupervised clustering analysis, IS patients were classified into three clusters, and significant disparities were witnessed in immune cell infiltration among distinct clusters. In summary, this study successfully identified hub GRGs in IS and investigated the roles of these hub genes in the immune microenvironment, indicating potential clinical applications for IS.

A second act for spironolactone: cognitive benefits in renal dysfunction - a critical review

Renal dysfunction or Chronic kidney disease (CKD) are increasingly associated with cognitive deficit and memory impairment, suggesting a crucial kidney-brain axis. This review examines spironolactone's emerging role as a neuroprotective agent in the context of renal dysfunction-induced cognitive impairment. As a selective mineralocorticoid receptor (MR) antagonist, spironolactone demonstrates multifaceted protective mechanisms beyond its well established renoprotective effects. Evidences also suggests that spironolactone attenuates neuroinflammation, mitigates oxidative stress in brain, preserve blood-brain barrier (BBB) integrity and regulates hormonal imbalances associated with renal dysfunction. This review focuses on the reported beneficial effects of spironolactone in various neurodegenerative diseases (NDDs). These mechanisms collectively protect against the neurodegeneration in memory impairment induced by renal dysfunction. The dual action of spironolactone on both renal and cerebral tissues presents a novel therapeutic advantage in addressing this complex pathophysiology. This study elucidates multiple beneficial mechanisms by which spironolactone addresses cognitive impairment associated with renal dysfunction. Spironolactone enhances BBB protection and restores BBB integrity which is often compromised with renal dysfunction. It promotes neuroplasticity (allowing for improved neural adaptation and cognitive function), additionally mediates cerebral blood flow (CBF) ensuring adequate oxygen and nutrient delivery to brain. Spironolactone's anti-inflammatory effects by inhibiting the nuclear factor-kappa B (NF-κB) pathway and modulation of neuregulin1 (NRG1)/v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 4 (ERBB4) signaling effectively reduce neuroinflammation that contributes to memory impairment. It also mitigates oxidative stress by targeting NADPH-oxidase (NOX), a major source of reactive oxygen species (ROS) in the central nervous system (CNS). Spironolactone also maintains hormonal balance, particularly regarding aldosterone levels, which become dysregulated in renal dysfunction and negatively impact brain function. These insights provide new possibilities for developing targeted therapies against renal dysfunction-induced memory impairment.

Altered glycosylation in cancer: molecular functions and therapeutic potential

Glycosylation, a key mode of protein modification in living organisms, is critical in regulating various biological functions by influencing protein folding, transportation, and localization. Changes in glycosylation patterns are a significant feature of cancer, are associated with a range of pathological activities in cancer-related processes, and serve as critical biomarkers providing new targets for cancer diagnosis and treatment. Glycoproteins like human epidermal growth factor receptor 2 (HER2) for breast cancer, alpha-fetoprotein (AFP) for liver cancer, carcinoembryonic antigen (CEA) for colon cancer, and prostate-specific antigen (PSA) for prostate cancer are all tumor biomarkers approved for clinical use. Here, we introduce the diversity of glycosylation structures and newly discovered glycosylation substrate-glycosylated RNA (glycoRNA). This article focuses primarily on tumor metastasis, immune evasion, metabolic reprogramming, aberrant ferroptosis responses, and cellular senescence to illustrate the role of glycosylation in cancer. Additionally, we summarize the clinical applications of protein glycosylation in cancer diagnostics, treatment, and multidrug resistance. We envision a promising future for the clinical applications of protein glycosylation.

Clinical glycoproteomics: methods and diseases

Glycoproteins, representing a significant proportion of posttranslational products, play pivotal roles in various biological processes, such as signal transduction and immune response. Abnormal glycosylation may lead to structural and functional changes of glycoprotein, which is closely related to the occurrence and development of various diseases. Consequently, exploring protein glycosylation can shed light on the mechanisms behind disease manifestation and pave the way for innovative diagnostic and therapeutic strategies. Nonetheless, the study of clinical glycoproteomics is fraught with challenges due to the low abundance and intricate structures of glycosylation. Recent advancements in mass spectrometry-based clinical glycoproteomics have improved our ability to identify abnormal glycoproteins in clinical samples. In this review, we aim to provide a comprehensive overview of the foundational principles and recent advancements in clinical glycoproteomic methodologies and applications. Furthermore, we discussed the typical characteristics, underlying functions, and mechanisms of glycoproteins in various diseases, such as brain diseases, cardiovascular diseases, cancers, kidney diseases, and metabolic diseases. Additionally, we highlighted potential avenues for future development in clinical glycoproteomics. These insights provided in this review will enhance the comprehension of clinical glycoproteomic methods and diseases and promote the elucidation of pathogenesis and the discovery of novel diagnostic biomarkers and therapeutic targets.

Serum N-glycomic profiling identifies candidate biomarker panels for assessing coronary artery stenosis severity

Stenosis severity may escalate over the course of coronary artery disease (CAD), increasing the risk of death for the patient. Conventionally, the assessment of stenosis degree relies on invasive coronary angiography (ICA), an invasive examination unsuitable for patients in poor physical condition or those with contrast allergies and one that imposes a psychological burden on patients. Although abnormal serum N-glycan profiles have exhibited robust associations with various cardiovascular diseases, including CAD, their potential in diagnosing CAD stenosis remains to be determined. In this study, we performed a comprehensive analysis of serum N-glycome from 132 patients who underwent ICA and 27 healthy controls using MALDI-TOF-mass spectrometry. The patients who underwent ICA examination were categorized into four groups based on stenosis severity: no/mild/moderate/severe stenosis. Twenty-seven N-glycans were directly quantified, and 47 derived glycan traits were obtained. Notably, among these 74 glycan features, 18 exhibited variations across the study groups. Using a combination of least absolute shrinkage and selection operator and logistic regression analyses, we developed five diagnostic models for recognizing stenosis degree. Our results suggested that alterations in serum N-glycosylation modifications might be valuable for identifying stenosis degree and monitoring disease progression in individuals with CAD. It is expected to offer a noninvasive alternative for those who could not undergo ICA because of various reasons. However, the diagnostic potential of serum N-glycan panels as biomarkers requires multicenter, large cohort validation in the future.