Screening of key biomarkers and immune infiltration in Pulmonary Arterial Hypertension via integrated bioinformatics analysis

Unveiling Immune-related feature genes for Alzheimer's disease based on machine learning

The identification of diagnostic and therapeutic biomarkers for Alzheimer's Disease (AD) remains a crucial area of research. In this study, utilizing the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm, we identified RHBDF2 and TNFRSF10B as feature genes associated with AD pathogenesis. Analyzing data from the GSE33000 dataset, we revealed significant upregulation of RHBDF2 and TNFRSF10B in AD patients, with correlations to age and gender. Interestingly, their expression profile in AD differs notably from that of other neurodegenerative conditions. Functional analysis unveiled their involvement in immune response and various signaling pathways implicated in AD pathogenesis. Furthermore, our study demonstrated the potential of RHBDF2 and TNFRSF10B as diagnostic biomarkers, exhibiting high discrimination power in distinguishing AD from control samples. External validation across multiple datasets confirmed the robustness of the diagnostic model. Moreover, utilizing molecular docking analysis, we identified dinaciclib and tanespimycin as promising small molecule drugs targeting RHBDF2 and TNFRSF10B for potential AD treatment. Our findings highlight the diagnostic and therapeutic potential of RHBDF2 and TNFRSF10B in AD management, shedding light on novel strategies for precision medicine in AD.

Identification of monocyte-associated pathways participated in the pathogenesis of pulmonary arterial hypertension based on omics-data

Pulmonary arterial hypertension (PAH) is one kind of chronic and uncurable diseases that can cause heart failure. Immune microenvironment plays a significant role in PAH. The aim of this study was to assess the role of immune cell infiltration in the pathogenesis of PAH. Differentially expressed genes based on microarray data were enriched in several immune-related pathways. To evaluate the immune cell infiltration, based on the microarray data sets in the GEO database, we used both ssGSEA and the CIBERSORT algorithm. Additionally, single-cell RNA sequencing (scRNA-seq) data was used to further explicit the specific role and intercellular communications. Then receiver operating characteristic curves and least absolute shrinkage and selection operator were used to discover and test the potential diagnostic biomarkers for PAH. Both the immune cell infiltration analyses based on the microarray data sets and the cell proportion in scRNA-seq data exhibited a significant downregulation in the infiltration of monocytes in PAH. Then, the intercellular communications showed that the interaction weighs of most immune cells, including monocytes changed between the control and PAH groups, and the ITGAL-ITGB2 and ICAM signaling pathways played critical roles in this process. In addition, ITGAM and ICAM2 displayed good diagnosis values in PAH. This study implicated that the change of monocyte was one of the key immunologic features of PAH. Monocyte-associated ICAM-1 and ITGAL-ITGB2 signaling pathways might be involved in the pathogenesis of PAH.

Upregulation of the key biomarker kinesin family member 20A (KIF20A) is associated with pulmonary artery hypertension

OBJECTIVE

Pulmonary artery hypertension (PAH) is a complex, fatal disease with limited treatments. This study aimed to investigate possible key targets in PAH through bioinformatics.

METHODS

GSE144274 were obtained from Gene Expression Omnibus (GEO) database. Then, differentially expressed genes (DEGs) between idiopathic pulmonary hypertension (IPAH) and healthy subjects were identified and analyzed. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed, and a protein-protein interaction (PPI) network was constructed using STRING. The hub genes were identified by MCODE method. The expression levels of hub genes were validated in vitro and in vivo models. Finally, the ROC analysis was performed based on the level of hub genes in clinical plasma samples.

RESULTS

A total of 363 DEGs were identified. GO analysis on these DEGs were mainly enriched in cell division, inflammatory response, among others. In the KEGG pathways analysis, DEGs mainly involved in cytokine-cytokine receptor interaction, rheumatoid arthritis, and IL-17 signaling pathways were enriched. The DEGs were analyzed with the STRING for PPI network analysis, and 62 hub genes were identified by MCODE. Finally, 6 central genes, KIF18B, SPC25, DLGAP5, KIF20A, CEP55 and ANLN, were screened out due to their novelty role in PAH. The expression of KIF20A was validated to be significantly upregulated both in the lung tissue of hypoxia-induced pulmonary hypertension (HPH) mice and proliferative PASMCs. Additionally, KIF20A levels is evelated in PAH plasma and the area under the curve (AUC) to identify PAH was 0.8591 for KIF20A.

CONCLUSION

The level of KIF20A elevates during the progression of PAH, which suggestes it could be a potential diagnostic and therapeutic target for the PAH.

Single Nucleotide Polymorphism rs9277336 Controls the Nuclear Alpha Actinin 4-Human Leukocyte Antigen-DPA1 Axis and Pulmonary Endothelial Pathophenotypes in Pulmonary Arterial Hypertension

Background Pulmonary arterial hypertension (PAH) is a complex, fatal disease where disease severity has been associated with the single nucleotide polymorphism (SNP) rs2856830, located near the human leukocyte antigen DPA1 (HLA-DPA1) gene. We aimed to define the genetic architecture of functional variants associated with PAH disease severity by identifying allele-specific binding transcription factors and downstream targets that control endothelial pathophenotypes and PAH. Methods and Results Electrophoretic mobility shift assays of oligonucleotides containing SNP rs2856830 and 8 SNPs in linkage disequilibrium revealed functional SNPs via allele-imbalanced binding to human pulmonary arterial endothelial cell nuclear proteins. DNA pulldown proteomics identified SNP-binding proteins. SNP genotyping and clinical correlation analysis were performed in 84 patients with PAH at University of Pittsburgh Medical Center and in 679 patients with PAH in the All of Us database. SNP rs9277336 was identified as a functional SNP in linkage disequilibrium (r2>0.8) defined by rs2856830, and the minor allele was associated with decreased hospitalizations and improved cardiac output in patients with PAH, an index of disease severity. SNP pulldown proteomics showed allele-specific binding of nuclear ACTN4 (alpha actinin 4) protein to rs9277336 minor allele. Both ACTN4 and HLA-DPA1 were downregulated in pulmonary endothelium in human patients and rodent models of PAH. Via transcriptomic and phenotypic analyses, knockdown of HLA-DPA1 phenocopied knockdown of ACTN4, both similarly controlling cell structure pathways, immune pathways, and endothelial dysfunction. Conclusions We defined the pathogenic activity of functional SNP rs9277336, entailing the allele-specific binding of ACTN4 and controlling expression of the neighboring HLA-DPA1 gene. Through inflammatory or genetic means, downregulation of this ACTN4-HLA-DPA1 regulatory axis promotes endothelial pathophenotypes, providing a mechanistic explanation for the association between this SNP and PAH outcomes.

Construction of a diagnostic signature and immune landscape of pulmonary arterial hypertension

Background

Molecular biomarkers are widely used for disease diagnosis and exploration of pathogenesis. Pulmonary arterial hypertension (PAH) is a rapidly progressive cardiopulmonary disease with delayed diagnosis. Studies were limited regarding molecular biomarkers correlated with PAH from a broad perspective.

Methods

Two independent microarray cohorts comprising 73 PAH samples and 36 normal samples were enrolled in this study. The weighted gene co-expression network analysis (WGCNA) was performed to identify the key modules associated with PAH. The LASSO algorithm was employed to fit a diagnostic model. The latent biology mechanisms and immune landscape were further revealed via bioinformatics tools.

Results

The WGCNA approach ultimately identified two key modules significantly associated with PAH. For genes within the two models, differential expression analysis between PAH and normal samples further determined nine key genes. With the expression profiles of these nine genes, we initially developed a PAH diagnostic signature (PDS) consisting of LRRN4, PI15, BICC1, PDE1A, TSHZ2, HMCN1, COL14A1, CCDC80, and ABCB1 in GSE117261 and then validated this signature in GSE113439. The ROC analysis demonstrated outstanding AUCs with 0.948 and 0.945 in two cohorts, respectively. Besides, patients with high PDS scores enriched plenty of Th17 cells and neutrophils, while patients with low PDS scores were dramatically related to mast cells and B cells.

Conclusion

Our study established a robust and promising signature PDS for diagnosing PAH, with key genes, novel pathways, and immune landscape offering new perspectives for exploring the molecular mechanisms and potential therapeutic targets of PAH.

FAM171B as a Novel Biomarker Mediates Tissue Immune Microenvironment in Pulmonary Arterial Hypertension

The purpose of this study was to uncover potential diagnostic indicators of pulmonary arterial hypertension (PAH), evaluate the function of immune cells in the pathogenesis of the disease, and find innovative treatment targets and medicines with the potential to enhance prognosis. Gene Expression Omnibus was utilized to acquire the PAH datasets. We recognized differentially expressed genes (DEGs) and investigated their functions utilizing R software. Weighted gene coexpression network analysis, least absolute shrinkage and selection operators, and support vector machines were used to identify biomarkers. The extent of immune cell infiltration in the normal and PAH tissues was determined using CIBERSORT. Additionally, the association between diagnostic markers and immune cells was analyzed. In this study, 258DEGs were used to analyze the disease ontology. Most DEGs were linked with atherosclerosis, arteriosclerotic cardiovascular disease, and lung disease, including obstructive lung disease. Gene set enrichment analysis revealed that compared to normal samples, results from PAH patients were mostly associated with ECM-receptor interaction, arrhythmogenic right ventricular cardiomyopathy, the Wnt signaling pathway, and focal adhesion. FAM171B was identified as a biomarker for PAH (area under the curve = 0.873). The mechanism underlying PAH may be mediated by nave CD4 T cells, resting memory CD4 T cells, resting NK cells, monocytes, activated dendritic cells, resting mast cells, and neutrophils, according to an investigation of immune cell infiltration. FAM171B expression was also associated with resting mast cells, monocytes, and CD8 T cells. The results suggest that PAH may be closely related to FAM171B with high diagnostic performance and associated with immune cell infiltration, suggesting that FAM171B may promote the progression of PAH by stimulating immune infiltration and immune response. This study provides valuable insights into the pathogenesis and treatment of PAH.

Identifying Potential Mitochondrial Proteome Signatures Associated with the Pathogenesis of Pulmonary Arterial Hypertension in the Rat Model

Pulmonary arterial hypertension (PAH) is a severe and progressive disease that affects the heart and lungs and a global health concern that impacts individuals and society. Studies have reported that some proteins related to mitochondrial metabolic functions could play an essential role in the pathogenesis of PAH, and their specific expression and biological function are still unclear. We successfully constructed a monocrotaline- (MCT-) induced PAH rat model in the present research. Then, the label-free quantification proteomic technique was used to determine mitochondrial proteins between the PAH group (n = 6) and the normal group (n = 6). Besides, we identified 1346 mitochondrial differentially expressed proteins (DEPs) between these two groups. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the mainly mitochondrial DEPs' biological functions and the signal pathways. Based on the protein-protein interaction (PPI) network construction and functional enrichment, we screened 19 upregulated mitochondrial genes (Psmd1, Psmc4, Psmd13, Psmc2, etc.) and 123 downregulated mitochondrial genes (Uqcrfs1, Uqcrc1, Atp5c1, Atp5a1, Uqcrc2, etc.) in rats with PAH. Furthermore, in an independent cohort dataset and experiments with rat lung tissue using qPCR, validation results consistently showed that 6 upregulated mitochondrial genes (Psmd2, Psmc4, Psmc3, Psmc5, Psmd13, and Psmc2) and 3 downregulated mitochondrial genes (Lipe, Cat, and Prkce) were significantly differentially expressed in the lung tissue of PAH rats. Using the RNAInter database, we predict potential miRNA target hub mitochondrial genes at the transcriptome level. We also identified bortezomib and carfilzomib as the potential drugs for treatment in PAH. Finally, this study provides us with a new perspective on critical biomarkers and treatment strategies in PAH.

Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension

Despite the multiple diagnostic and therapeutic strategies implemented in clinical practice, the mortality rate of patients with pulmonary arterial hypertension (PAH) remains high. Understanding the mechanisms and key genes involved could provide insight into the drivers of the pathogenesis of PAH. In this research, we aimed to examine the mechanisms underlying PAH and identify key genes with potential usefulness as clinical biomarkers of PAH and thereby establish therapeutic targets for PAH. The datasets GSE117261, GSE113439, and GSE53408 were downloaded from the Gene Expression Omnibus (GEOs) database. We used weighted gene coexpression network analysis (WGCNA) to identify networks and the most relevant modules in PAH. Functional enrichment analysis was performed for the selected clinically relevant modules. The least absolute shrinkage and selection operator (LASSO) was applied to identify key genes in lung samples from patients with PAH. The genes were validated in a monocrotaline-induced PAH rat model. Three clinically relevant modules were identified through average linkage hierarchical clustering. The genes in the clinically relevant modules were related to endothelial cell differentiation, inflammation, and autoimmunity. Seven genes were screened as key genes significantly associated with PAH. Interferon-induced protein 44-like (IFI44L) and signal transducer and activator of transcription 1 (STAT1) were expressed at higher levels in the lung tissues of the PAH rat model than in those of the controls. Our findings reveal the novel pathological mechanisms underlying PAH and indicate that STAT1 and IFI44L may represent potential therapeutic targets in PAH.

Monocyte-related gene biomarkers for latent and active tuberculosis

Monocytes are closely associated with tuberculosis (TB). Latent tuberculosis in some patients gradually develops into its active state. This study aimed to investigate the role of hub monocyte-associated genes in distinguishing latent TB infection (LTBI) from active TB. The gene expression profiles of 15 peripheral blood mononuclear cells (PBMCs) samples were downloaded from the gene expression omnibus (GEO) database, GSE54992. The monocyte abundance was high in active TB as evaluated by the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm. The limma test and correlation analysis documented 165 differentially expressed monocyte-related genes (DEMonRGs) between latent TB and active TB. Functional annotation and enrichment analyses of the DEMonRGs using the database for annotation, visualization, and integration discovery (DAVID) tools showed enrichment of inflammatory response mechanisms and immune-related pathways. A protein-protein interaction network was constructed with a node degree ≥10. The expression levels of these hub DEMonRGs (SERPINA1, FUCA2, and HP) were evaluated and verified using several independent datasets and clinical settings. Finally, a single sample scoring method was used to establish a gene signature for the three DEMonRGs, distinguishing active TB from latent TB. The findings of the present study provide a better understanding of monocyte-related molecular fundamentals in TB progression and contribute to the identification of new potential biomarkers for the diagnosis of active TB.

Identification of a prognostic chemoresistance-related gene signature associated with immune microenvironment in breast cancer

Breast cancer is the most common form of cancer among women globally, and chemoresistance is a major challenge to disease treatment that is associated with a poor prognosis. This study was formulated to identify a reliable prognostic biosignature capable of predicting the survival of patients with chemoresistant breast cancer (CRBC) and evaluating the associated tumor immune microenvironment. Through a series of protein-protein interaction and weighted correlation network analyses, genes that were significantly associated with breast cancer chemoresistance were identified. Moreover, univariate Cox regression and lasso-penalized Cox regression analyses were employed to generate a prognostic model, and the prognostic utility of this model was then assessed using time-dependent receiver operating characteristic (ROC) and Kaplan-Meier survival curves. Finally, The CIBERSORT and ESTIMATE algorithms were additionally leveraged to assess relationships between the tumor immune microenvironment and patient prognostic signatures. Overall, a multigenic prognostic biosignature capable of predicting CRBC patient risk was successfully developed based on bioinformatics analysis and in vitro experiments. This biosignature was able to stratify CRBC patients into high- and low-risk subgroups. ROC curves also revealed that this biosignature achieved high diagnostic efficiency, and multivariate regression analyses indicated that this risk signature was an independent risk factor linked to CRBC patient outcomes. In addition, this signature was associated with the infiltration of the tumor microenvironment by multiple immune cell types. In conclusion, the chemoresistance-associated prognostic gene signature developed herein was able to effectively evaluate the prognosis of CRBC patients and to reflect the overall composition of the tumor immune microenvironment.