Identification of novel biomarkers and immune infiltration characteristics of ischemic stroke based on comprehensive bioinformatic analysis and machine learning

Immunological Markers of Cardiovascular Pathology in Older Patients

Background: The aging process is accompanied by changes in the immunological status of a person. Immunosenescence is considered a significant cause of the development of cardiovascular diseases (CVD) in elderly people. However, to date, the relationship between immune/inflammatory processes and diseases associated with age is considered quite complex and is not fully understood. Immunophenotyping and the intracellular production of cytokines involved in the processes of inflammatory aging will allow us to identify biomarkers that are associated with cardiovascular diseases in the elderly. Objectives: To identify immunological markers associated with the process of inflammatory aging in older individuals with cardiovascular diseases. Methods: CD-phenotyping and intracellular cytokine analysis of peripheral blood using the flow cytometry method were conducted in 52 people over 60 years of age (group 1 had CVD and group 2 did not). Blood samples were stained with monoclonal antibodies (mAb) using Becton Dickinson (BD) reagents for the staining and binding of surface receptors CD4+, CD8+, CD14+, CD19+, CD16+, CD56+, CD59+, CD95+, and HLA DR+ and intracellular receptors TNF, IL-10, GM-CSF, VEGFR-2, IGF, and perforin. In addition, the following parameters were studied: questionnaire data (gender, age, alcohol consumption, smoking, physical activity, and marital status), clinical data (blood pressure (BP), heart rate (HR), body mass index (BMI)), comorbid conditions, and cardiovascular diseases (coronary heart disease (CHD), chronic heart failure (CHF), arterial hypertension (AH), previous myocardial infarction (PICS), diabetes mellitus (DM), atrial fibrillation (AF), and stroke). Results: The older patients with cardiovascular pathology had high levels of monocytes CD14+ (p = 0.014), low levels of CD8+ lymphocytes (p = 0.046), and low intracellular production of GM-CSF (p = 0.013) compared to the older people without CVD. Conclusions: The revealed differences in the expression of CD14+ monocytes indicate their role in the development of cardiovascular pathology associated with age-related changes. A decrease in cytotoxic CD8+ lymphocytes and intracellular GM-CSF production leads to an increased risk of developing cardiovascular diseases in older individuals. These observed changes with age will not only expand existing knowledge about the aging of the regulatory link of the immune system but also help to obtain data to predict CVD in older people. Thus, the obtained results support the use of these immunological markers to identify the risk of circulatory disease and a personalized approach in geriatric practice.

Identification of novel inflammatory response-related biomarkers in patients with ischemic stroke based on WGCNA and machine learning

BACKGROUND

Ischemic stroke (IS) is one of the most common causes of disability in adults worldwide. This study aimed to identify key genes related to the inflammatory response to provide insights into the mechanisms and management of IS.

METHODS

Transcriptomic data for IS were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were used to identify inflammation-related genes (IRGs) associated with IS. Hub IRGs were screened using Lasso, SVM-RFE, and random forest algorithms, and a nomogram diagnostic model was constructed. The diagnostic performance of the model was assessed using receiver operating characteristic (ROC) curves and calibration plots. Additionally, immune cell infiltration and potential small molecule drugs targeting IRGs were analyzed. The expression of IRG was verified by qRT-PCR in healthy controls and IS patients.

RESULTS

Nine differentially expressed IRGs were identified in IS, including NMUR1, AHR, CD68, OSM, CDKN1A, RGS1, BTG2, ATP2C1, and TLR3. Machine learning algorithms selected three hub IRGs (AHR, OSM, and NMUR1). A diagnostic model based on these three genes showed excellent diagnostic performance for IS, with an area under the curve (AUC) greater than 0.9 in both the training and validation sets. Immune infiltration analysis revealed higher levels of neutrophils and activated CD4 + T cells, and lower levels of CD8 + T cells, activated NK cells, and naive B cells in IS patients. The hub IRGs exhibited significant correlations with immune cell infiltration. Furthermore, small molecule drugs targeting hub IRGs were identified, including chrysin, piperine, genistein, and resveratrol, which have potential therapeutic effects for IS. qRT-PCR evaluation demonstrated that the levels of blood biomarkers (AHR, OSM, and NMUR1) in IS patients could serve as distinguishing indicators between IS patients and healthy controls (P < 0.05).

CONCLUSION

This study confirmed the significant impact of IRGs on the progression of IS and provided new diagnostic and therapeutic targets for personalized treatment of IS.

Interplay of cell death pathways and immune responses in ischemic stroke: insights into novel biomarkers

Stroke is a severe neurological disease and a major worldwide issue, mostly manifesting as ischemic stroke (IS). In order to create effective treatments for IS, it is imperative to fully understand the underlying pathologies, as the existing therapeutic choices are inadequate. Recent investigations have shown the complex relationships between several programmed cell death (PCD) pathways, including necroptosis, ferroptosis, and pyroptosis, and their correlation with immune responses during IS. However, this relationship is still unclear. To address this gap, this review study explored the cellular interactions in the immune microenvironment of IS. Then, to validate prior findings and uncover biomarkers, the study investigated bioinformatics studies. Several pathways, including nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), Toll-like receptor 4 (TLR4), and receptor-interacting protein kinase (RIPK), were involved in PCD-immune interactions. The bioinformatics studies reported key biomarkers such as glutathione peroxidase 4 (GPX4), NOD-like receptor family pyrin domain containing 3 (NLRP3), gasdermin D (GSDMD), and TLR4, which have important implications in ferroptosis, cuproptosis, pyroptosis, and necroptosis respectively. These biomarkers were associated with PCD mechanisms such as oxidative stress and inflammatory reactions. The immune infiltration analysis consistently revealed a significant correlation between PCD pathways and detrimental immune cells, such as neutrophils and γδ T cells. Conversely, M2 macrophages and T helper cells showed protective effects. In conclusion, considering the intricate network of interactions between immune responses and PCD pathways, this study emphasized the necessity of a paradigm shift in therapeutic approaches to address the injuries that are related to this complex network.

Identification of ribosome biogenesis genes and subgroups in ischaemic stroke

Background

Ischaemic stroke is a leading cause of death and severe disability worldwide. Given the importance of protein synthesis in the inflammatory response and neuronal repair and regeneration after stroke, and that proteins are acquired by ribosomal translation of mRNA, it has been theorised that ribosome biogenesis may have an impact on promoting and facilitating recovery after stroke. However, the relationship between stroke and ribosome biogenesis has not been investigated.

Methods

In the present study, a ribosome biogenesis gene signature (RSG) was developed using Cox and least absolute shrinkage and selection operator (LASSO) analysis. We classified ischaemic stroke patients into high-risk and low-risk groups using the obtained relevant genes, and further elucidated the immune infiltration of the disease using ssGSEA, which clarified the close relationship between ischaemic stroke and immune subgroups. The concentration of related proteins in the serum of stroke patients was determined by ELISA, and the patients were divided into groups to evaluate the effect of the ribosome biogenesis gene on patients. Through bioinformatics analysis, we identified potential IS-RSGs and explored future therapeutic targets, thereby facilitating the development of more effective therapeutic strategies and novel drugs against potential therapeutic targets in ischaemic stroke.

Results

We obtained a set of 12 ribosome biogenesis-related genes (EXOSC5, MRPS11, MRPS7, RNASEL, RPF1, RPS28, C1QBP, GAR1, GRWD1, PELP1, UTP, ERI3), which play a key role in assessing the prognostic risk of ischaemic stroke. Importantly, risk grouping using ribosome biogenesis-related genes was also closely associated with important signaling pathways in stroke. ELISA detected the expression of C1QBP, RPS28 and RNASEL proteins in stroke patients, and the proportion of neutrophils was significantly increased in the high-risk group.

Conclusions

The present study demonstrates the involvement of ribosomal biogenesis genes in the pathogenesis of ischaemic stroke, providing novel insights into the underlying pathogenic mechanisms and potential therapeutic strategies for ischaemic stroke.

Machine learning identifies novel coagulation genes as diagnostic and immunological biomarkers in ischemic stroke

BACKGROUND

Coagulation system is currently known associated with the development of ischemic stroke (IS). Thus, the current study is designed to identify diagnostic value of coagulation genes (CGs) in IS and to explore their role in the immune microenvironment of IS.

METHODS

Aberrant expressed CGs in IS were input into unsupervised consensus clustering to classify IS subtypes. Meanwhile, key CGs involved in IS were further selected by weighted gene co-expression network analysis (WGCNA) and machine learning methods, including random forest (RF), support vector machine (SVM), generalized linear model (GLM) and extreme-gradient boosting (XGB). The diagnostic performance of key CGs were evaluated by receiver operating characteristic (ROC) curves. At last, quantitative PCR (qPCR) was performed to validate the expressions of key CGs in IS.

RESULTS

IS patients were classified into two subtypes with different immune microenvironments by aberrant expressed CGs. Further WGCNA, machine learning methods and ROC curves identified ACTN1, F5, TLN1, JMJD1C and WAS as potential diagnostic biomarkers of IS. In addition, their expressions were significantly correlated with macrophages, neutrophils and/or T cells. GSEA also revealed that those biomarkers may regulate IS via immune and inflammation. Moreover, qPCR verified the expressions of ACTN1, F5 and JMJD1C in IS.

CONCLUSIONS

The current study identified ACTN1, F5 and JMJD1C as novel coagulation-related biomarkers associated with IS immune microenvironment, which enriches our knowledge of coagulation-mediated pathogenesis of IS and sheds light on next-step in vivo and in vitro experiments to elucidate the relevant molecular mechanisms.