Bioinformatics analysis reveals the landscape of immune cell infiltration and immune-related pathways participating in the progression of carotid atherosclerotic plaques

Multiomic integration analysis identifies atherogenic metabolites mediating between novel immune genes and cardiovascular risk

BACKGROUND

Understanding genetic-metabolite associations has translational implications for informing cardiovascular risk assessment. Interrogating functional genetic variants enhances our understanding of disease pathogenesis and the development and optimization of targeted interventions.

METHODS

In this study, a total of 187 plasma metabolite levels were profiled in 4974 individuals of European ancestry of the GCAT| Genomes for Life cohort. Results of genetic analyses were meta-analysed with additional datasets, resulting in up to approximately 40,000 European individuals. Results of meta-analyses were integrated with reference gene expression panels from 58 tissues and cell types to identify predicted gene expression associated with metabolite levels. This approach was also performed for cardiovascular outcomes in three independent large European studies (N = 700,000) to identify predicted gene expression additionally associated with cardiovascular risk. Finally, genetically informed mediation analysis was performed to infer causal mediation in the relationship between gene expression, metabolite levels and cardiovascular risk.

RESULTS

A total of 44 genetic loci were associated with 124 metabolites. Lead genetic variants included 11 non-synonymous variants. Predicted expression of 53 fine-mapped genes was associated with 108 metabolite levels; while predicted expression of 6 of these genes was also associated with cardiovascular outcomes, highlighting a new role for regulatory gene HCG27. Additionally, we found that atherogenic metabolite levels mediate the associations between gene expression and cardiovascular risk. Some of these genes showed stronger associations in immune tissues, providing further evidence of the role of immune cells in increasing cardiovascular risk.

CONCLUSIONS

These findings propose new gene targets that could be potential candidates for drug development aimed at lowering the risk of cardiovascular events through the modulation of blood atherogenic metabolite levels.

Transcriptomic profiling and risk assessment in bladder cancer: Insights from copper death-related genes

BACKGROUND

The study aimed to investigate the role of copper death-related genes (CRGs) in bladder cancer (BC) for improved prognosis assessment.

METHODS

Multi-omics techniques were utilized to analyze CRG expression in BC tissues from TCGA and GEO databases. Consensus clustering categorized patients into molecular subtypes based on clinical characteristics and immune cell infiltration.

RESULTS

An innovative risk assessment model identified eight critical genes associated with BC risk. In vitro and in vivo experiments validated LIPT1's significant impact on copper-induced cell death, proliferation, migration, and invasion in BC.

CONCLUSION

This multi-omics analysis elucidates the pivotal role of CRGs in BC progression, suggesting enhanced risk assessment through molecular subtype categorization and identification of key genes like LIPT1. Insights into these mechanisms offer the potential for improved diagnosis and treatment strategies for BC patients.

Effects of dietary selenium deficiency and supplementation on liver in grazing sheep: insights from transcriptomic and metabolomic analysis

Background

Mineral elements play a crucial role in supporting the life activities and physiological functions of animals. However, numerous studies have revealed that in some geographical areas and certain grazing situations, grazing livestock frequently suffers from mineral element deficiencies due to the loss of mineral elements from grassland forages, such as selenium (Se). To shed fresh light on this issue, this study aims to investigate the impact of dietary Se deficiency and supplementation on the liver of grazing sheep in these challenging conditions.

Method

This study involved 28 grazing Mongolian Wu Ranke sheep with an average body weight of about 32.20 ± 0.37 kg, which were divided into the Se treatment group and the control group. The Se treatment group was fed with the low-Se diet for 60 days and then continued to be fed with the high-Se diet for 41 days. The liver concentration of minerals, transcriptomic analysis, and untargeted metabolomic analysis were conducted to assess the impact of Se deficiency and supplementation on the liver of grazing sheep.

Results

Dietary Se deficiency and supplementation significantly reduced and elevated liver concentration of Se, respectively (p < 0.05). Gene functional enrichment analysis suggested that dietary Se deficiency might impair protein synthesis efficiency, while Se supplementation was found to enhance liver protein synthesis in grazing sheep. AGAP1, ERN1, MAL2, NFIC, and RERG were identified as critical genes through the weighted gene correlation network analysis, the quantitative real-time polymerase chain reaction, and the receiver operating characteristic curve validation that could potentially serve as biomarkers. Metabolomics analysis revealed that dietary Se deficiency significantly reduced the abundance of metabolites such as 5-hydroxytryptamine, while dietary Se supplementation significantly elevated the abundance of metabolites such as 5-hydroxytryptophan (p < 0.05).

Conclusion

Integrative analysis of the transcriptome and metabolome revealed that dietary Se deficiency led to reduced hepatic antioxidant and anti-inflammatory capacity, whereas Se supplementation increased the hepatic antioxidant and anti-inflammatory capacity in grazing Wu Ranke sheep. These findings provide new insights into the effects of dietary Se deficiency and supplementation on the liver of grazing sheep, potentially leading to improved overall health and well-being of grazing livestock.

ANALYSIS AND IDENTIFICATION OF FERROPTOSIS-RELATED GENE SIGNATURE FOR ACUTE LUNG INJURY

ABSTRACT

Background: Recent studies have shown that ferroptosis is involved in the evolution of acute lung injury (ALI), a serious respiratory pathological process leading to death. However, the regulatory mechanisms underlying ferroptosis in ALI remain largely unknown. The current study analyzed and identified a ferroptosis-related gene signature for ALI. Methods: Key genes associated with ferroptosis in ALI were identified by bioinformatics analysis. GSE104214, GSE18341, and GSE17355 datasets were downloaded from the Gene Expression Omnibus database. The signature genes were screened by least absolute shrinkage and selection operator regression, and the key genes of ALI were screened by weighted correlation network analysis (WGCNA), followed by immune infiltration analysis and functional enrichment analysis. In addition, mRNA expression of key genes in the lungs of mice with hemorrhagic shock (HS) and sepsis was verified. Results: A total of 2,132 differential genes were identified by various analyses, and 9 characteristic genes were detected using Lasso regression. We intersected nine signature genes with WGCNA module genes and finally determined four key genes ( PROK2 , IL6 , TNF , SLC7A11 ). All four key genes were closely correlated with immune cells and regulatory genes of ALI, and the expression of the four genes was significantly different in the lung tissues of HS and sepsis models. Besides, the ferroptosis-related molecules GPX4 and ACSL4 showed remarkable difference in these models. Conclusion: These results indicate that PROK2 , IL6 , TNF , and SLC7A11 may be key regulatory targets of ferroptosis during ALI. This study proved that ferroptosis is a common pathophysiological process in three ALI models.

Diagnosis and therapies for patients with cerebral palsy over the past 30 years: a bibliometric analysis

Background

Currently, the incidence of cerebral palsy is high in newborns. However, the current methods for diagnosing and treating patients with cerebral palsy are complex and poorly targeted. Moreover, these studies lack the support of bibliometric analysis results.

Objective

Our study focused on a bibliometric analysis of published papers on the diagnosis and treatment of patients with cerebral palsy. This study identified the primary authors, institutions, and countries involved in analyzing the status and trends of research on the diagnosis and treatment of patients with cerebral palsy. Additionally, the study also involved screening pathways related to cerebral palsy.

Methods

The PubMed database was searched for publications on the diagnosis and treatment of patients with cerebral palsy between 1990 and 2023. R v4.2.2 and VOSviewer v1.6.18 software tools were utilized to perform bibliometric analysis and visualization.

Results

There were 1,965 publications on cerebral palsy diagnosis and 5,418 articles on the qualified treatment strategies, and the annual number of publications also increased. The United States dominated in this field of research. Gregory Y.H. Lip and Patrizio Lancellotti published the most number of papers. The Cleveland Clinic published the most number of papers in the field. According to the analysis of the co-occurrence of keywords, we found that the main research directions were age, sex, disease diagnosis, and treatment. Newly emerging research has focused mainly on heart failure, which is related to valvular heart disease.

Conclusion

The findings presented in this study offer valuable insights into ongoing research and potential future directions pertaining to cerebral palsy. These insights can assist researchers in identifying suitable collaborators and enhancing their investigations aimed at identifying the underlying molecular mechanisms associated with cerebral palsy, encompassing its etiology, preventive measures, and therapeutic interventions.

Transcriptomics and metabolomics analysis reveal the dietary copper deficiency and supplementation effects of liver gene expression and metabolite change in grazing sheep

BACKGROUND

The appropriate mineral nutrients are essential for sheep growth and reproduction. However, traditional grazing sheep often experience mineral nutrient deficiencies, especially copper (Cu), due to inadequate mineral nutrients from natural pastures.

RESULTS

The results indicated that dietary Cu deficiency and supplementation significantly reduced and elevated liver concentration of Cu, respectively (p < 0.05). FOXO3, PLIN1, ACTN2, and GHRHR were identified as critical genes using the weighted gene co-expression network analysis (WGCNA), quantitative real-time polymerase chain reaction (qRT-PCR), and receiver operating characteristic curve (ROC) validation as potential biomarkers for evaluating Cu status in grazing sheep. Combining these critical genes with gene functional enrichment analysis, it was observed that dietary Cu deficiency may impair liver regeneration and compromise ribosomal function. Conversely, dietary Cu supplementation may enhance ribosomal function, promote lipid accumulation, and stimulate growth and metabolism in grazing sheep. Metabolomics analysis indicated that dietary Cu deficiency significantly decreased the abundance of metabolites such as cholic acid (p < 0.05). On the other hand, dietary Cu supplementation significantly increased the abundance of metabolites such as palmitic acid (p < 0.05). Integrative analysis of the transcriptome and metabolome revealed that dietary Cu deficiency may reduce liver lipid metabolism while Cu supplementation may elevate it in grazing sheep.

CONCLUSIONS

The Cu content in diets may have an impact on hepatic lipid metabolism in grazing sheep. These findings provide new insights into the consequences of dietary Cu deficiency and supplementation on sheep liver and can provide valuable guidance for herders to rationalize the use of mineral supplements.

Identification of key pyroptosis-related genes and microimmune environment among peripheral arterial beds in atherosclerotic arteries

Atherosclerosis is a chronic inflammatory disease characterized with innate and adaptive immunity but also involves pyroptosis. Few studies have explored the role of pyroptosis in advanced atherosclerotic plaques from different vascular beds. Here we try to identify the different underlying function of pyroptosis in the progression of atherosclerosis between carotid arteries and femoral. arteries. We extracted gene expression levels from 55 advanced carotid or femoral atherosclerotic plaques. The pyroptosis score of each sample was calculated by single-sample-gene-set enrichment analysis (ssGSEA). We then divided the samples into two clusters: high pyroptosis scores cluster (PyroptosisScoreH cluster) and low pyroptosis scores cluster (PyroptosisScoreL cluster), and assessed functional enrichment and immune cell infiltration in the two clusters. Key pyroptosis related genes were identified by the intersection between results of Cytoscape and LASSO (Least Absolute Shrinkage and Selection Operator) regression analysis. Finally, all key pyroptosis related genes were validated in vitro. We found all but one of the 29 carotid plaque samples belonged to the PyroptosisScoreH cluster and the majority (19 out of 26) of femoral plaques were part of the PyroptosisScoreL cluster. Atheromatous plaque samples in the PyroptosisScoreL cluster had higher proportions of gamma delta T cells, M2 macrophages, myeloid dendritic cells (DCs), and cytotoxic lymphocytes (CTLs), but lower proportions of endothelial cells (ECs). Immune full-activation pathways (e.g., NOD-like receptor signaling pathway and NF-kappa B signaling pathway) were highly enriched in the PyroptosisScoreH cluster. The key pyroptosis related genes GSDMD, CASP1, NLRC4, AIM2, and IL18 were upregulated in advanced carotid atherosclerotic plaques. We concluded that compared to advanced femoral atheromatous plaques, advanced carotid atheromatous plaques were of higher grade of pyroptosis. GSDMD, CASP1, NLRC4, AIM2, and IL18 were the key pyroptosis related genes, which might provide a new sight in the prevention of fatal strokes in advanced carotid atherosclerosis.

An integrative analysis of single-cell and bulk transcriptome and bidirectional mendelian randomization analysis identified C1Q as a novel stimulated risk gene for Atherosclerosis

Background

The role of complement component 1q (C1Q) related genes on human atherosclerotic plaques (HAP) is less known. Our aim is to establish C1Q associated hub genes using single-cell RNA sequencing (scRNA-seq) and bulk RNA analysis to diagnose and predict HAP patients more effectively and investigate the association between C1Q and HAP (ischemic stroke) using bidirectional Mendelian randomization (MR) analysis.

Methods

HAP scRNA-seq and bulk-RNA data were download from the Gene Expression Omnibus (GEO) database. The C1Q-related hub genes was screened using the GBM, LASSO and XGBoost algorithms. We built machine learning models to diagnose and distinguish between types of atherosclerosis using generalized linear models and receiver operating characteristics (ROC) analyses. Further, we scored the HALLMARK_COMPLEMENT signaling pathway using ssGSEA and confirmed hub gene expression through qRT-PCR in RAW264.7 macrophages and apoE-/- mice. Furthermore, the risk association between C1Q and HAP was assessed through bidirectional MR analysis, with C1Q as exposure and ischemic stroke (IS, large artery atherosclerosis) as outcomes. Inverse variance weighting (IVW) was used as the main method.

Results

We utilized scRNA-seq dataset (GSE159677) to identify 24 cell clusters and 12 cell types, and revealed seven C1Q associated DEGs in both the scRNA-seq and GEO datasets. We then used GBM, LASSO and XGBoost to select C1QA and C1QC from the seven DEGs. Our findings indicated that both training and validation cohorts had satisfactory diagnostic accuracy for identifying patients with HPAs. Additionally, we confirmed SPI1 as a potential TF responsible for regulating the two hub genes in HAP. Our analysis further revealed that the HALLMARK_COMPLEMENT signaling pathway was correlated and activated with C1QA and C1QC. We confirmed high expression levels of C1QA, C1QC and SPI1 in ox-LDL-treated RAW264.7 macrophages and apoE-/- mice using qPCR. The results of MR indicated that there was a positive association between the genetic risk of C1Q and IS, as evidenced by an odds ratio (OR) of 1.118 (95%CI: 1.013-1.234, P = 0.027).

Conclusion

The authors have effectively developed and validated a novel diagnostic signature comprising two genes for HAP, while MR analysis has provided evidence supporting a favorable association of C1Q on IS.

Identification of potential diagnostic biomarkers of atherosclerosis based on bioinformatics strategy

BACKGROUND

Atherosclerosis is the main pathological change in atherosclerotic cardiovascular disease, and its underlying mechanisms are not well understood. The aim of this study was to explore the hub genes involved in atherosclerosis and their potential mechanisms through bioinformatics analysis.

METHODS

Three microarray datasets from Gene Expression Omnibus (GEO) identified robust differentially expressed genes (DEGs) by robust rank aggregation (RRA). We performed connectivity map (CMap) analysis and functional enrichment analysis on robust DEGs and constructed a protein‒protein interaction (PPI) network using the STRING database to identify the hub gene using 12 algorithms of cytoHubba in Cytoscape. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic potency of the hub genes.The CIBERSORT algorithm was used to perform immunocyte infiltration analysis and explore the association between the identified biomarkers and infiltrating immunocytes using Spearman's rank correlation analysis in R software. Finally, we evaluated the expression of the hub gene in foam cells.

RESULTS

A total of 155 robust DEGs were screened by RRA and were revealed to be mainly associated with cytokines and chemokines by functional enrichment analysis. CD52 and IL1RN were identified as hub genes and were validated in the GSE40231 dataset. Immunocyte infiltration analysis showed that CD52 was positively correlated with gamma delta T cells, M1 macrophages and CD4 memory resting T cells, while IL1RN was positively correlated with monocytes and activated mast cells. RT-qPCR results indicate that CD52 and IL1RN were highly expressed in foam cells, in agreement with bioinformatics analysis.

CONCLUSIONS

​This study has established that CD52 and IL1RN may play a key role in the occurrence and development of atherosclerosis, which opens new lines of thought for further research on the pathogenesis of atherosclerosis.

Immune Infiltration in Atherosclerosis is Mediated by Cuproptosis-Associated Ferroptosis Genes

Aims: In this study, we aimed to identify cuproptosis-associated ferroptosis genes in the atherosclerosis microarray of the Gene Expression Omnibus (GEO) database and to explore hub gene-mediated immune infiltration in atherosclerosis.

Background: Immune infiltration plays a crucial role in atherosclerosis development. Ferroptosis is a mode of cell death caused by the iron-dependent accumulation of lipid peroxides. Cuproptosis is a recently discovered type of programmed cell death. No previous studies have examined the mechanism of cuproptosis-associated ferroptosis gene regulation in immune infiltration in atherosclerosis.

Methods: We searched the qualified atherosclerosis gene microarray in the GEO database, integrated it with ferroptosis and cuproptosis genes, and calculated the correlation coefficients. We then obtained the cuproptosis-associated ferroptosis gene matrix and screened differentially expressed genes. Subsequently, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses and protein–protein interaction network analysis of differentially expressed genes. We also screened hub genes according to the Matthews correlation coefficient (MCC) algorithm. We conducted enrichment analysis of hub genes to explore their functions and predict related microRNAs (P<0.05). We also used the single-sample gene set enrichment analysis (ssGSEA) algorithm to analyze the relationships between hub genes and immune infiltration, and used immune-associated hub genes to construct a risk model. Finally, we used the drug prediction results and molecular docking technology to explore potential therapeutic drugs targeting the hub genes.

Results: Seventy-eight cuproptosis-associated ferroptosis genes were found to be involved in the cellular response to oxidative and chemical stress, and to be enriched in multiple pathways, including ferroptosis, glutathione metabolism, and atherosclerosis. Ten hub genes were identified with the MCC algorithm; according to the ssGSEA algorithm, these genes were closely associated with immune infiltration, thus indicating that cuproptosis-associated ferroptosis genes may participate in atherosclerosis by mediating immune infiltration. The receiver operating characteristic curve indicated that the model had a good ability to predict atherosclerosis risk. The results of drug prediction (adjusted P<0.001) and molecular docking showed that glutathione may be a potential therapeutic drug that targets the hub genes.

Conclusion: Cuproptosis-associated ferroptosis genes are associated with immune infiltration in atherosclerosis.

CD8A is a Promising Biomarker Associated with Immunocytes Infiltration in Hyperoxia-Induced Bronchopulmonary Dysplasia

Background

Bronchopulmonary dysplasia (BPD) refers to a chronic lung disease which is commonly observed in preterm infants. It can usually be caused by several pathological processes that endanger the long-term lung development, such as inflammation and immune dysfunction.

Methods

In this study, a bioinformatics approach was applied to identify the differentially expressed immune-related genes (DEIRGs). We downloaded the transcriptional profiles (GSE32472 dataset) from the Gene Expression Omnibus (GEO) database and performed gene set enrichment analysis (GSEA). Cell type Identification By Estimating Relative Subsets of RNA Transcripts (CIBERSORT), microenvironment cell populations counter (MCPcounter), and Estimation of STromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) were used for the analysis of the immune cell infiltration landscape of BPD. A weighted co-expression network was subsequently constructed using weighted gene co-expression network analysis (WGCNA) to screen candidate differentially expressed immune related genes (DEIRGs).

Results

GSEA results indicated that immune-related pathways were mainly involved in BPD. Ten significantly different immune cell types were observed between BPD and normal groups. A total of 228 DEGs in the turquoise module were identified, and 31 DEIRGs were further identified. Cluster of the differentiation 8 alpha (CD8A) expression was down-regulated in BPD, and its expression was validated by the GSE25286, GSE25293, GSE99633 datasets and qRT-PCR. In addition, CD8A expression was closely associated with immune cells infiltration, especially T cells CD8 and neutrophil.

Conclusion

A distinct immune cell infiltration landscape was found between BPD and normal group. CD8A can be a novel candidate biomarker for BPD, which plays an essential role in the onset and progress of hyperoxia-related BPD via the disruption of immune cell functions.

Identification of core genes associated with the anti-atherosclerotic effects of Salvianolic acid B and immune cell infiltration characteristics using bioinformatics analysis

Background

Atherosclerosis (AS) is the greatest contributor to pathogenesis of atherosclerotic cardiovascular disease (ASCVD), which is associated with increased mortality and reduced quality of life. Early intervention to mitigate AS is key to prevention of ASCVD. Salvianolic acid B (Sal B) is mainly extracted from root and rhizome of Salvia Miltiorrhiza Bunge, and exerts anti-atherosclerotic effect. The purpose of this study was to screen for anti-AS targets of Sal B and to characterize immune cell infiltration in AS.

Methods

We identified targets of Sal B using SEA (http://sea.bkslab.org/) and SIB (https://www.sib.swiss/) databases. GSE28829 and GSE43292 datasets were obtained from Gene Expression Omnibus database. We identified differentially expressed genes (DEGs) and performed enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was used to determine the most relevant module associated with atherosclerotic plaque stability. Intersecting candidate genes were evaluated by generating receiver operating characteristic (ROC) curves and molecular docking. Then, immune cell types were identified using CIBERSOFT and single-sample gene set enrichment analysis (ssGSEA), the relationship between candidate genes and immune cell infiltration was evaluated. Finally, a network-based approach to explore the candidate genes relationship with microRNAs (miRNAs) and Transcription factors (TFs).

Results

MMP9 and MMP12 were been selected as candidate genes from 64 Sal B-related genes, 81 DEGs and turquoise module with 220 genes. ROC curve results showed that MMP9 (AUC = 0.815, P<0.001) and MMP12 (AUC = 0.763, P<0.001) were positively associated with advanced atherosclerotic plaques. The results of immune infiltration showed that B cells naive, B cells memory, Plasma cells, T cells CD8, T cells CD4 memory resting, T cells CD4 memory activated, T cells regulatory (Tregs), T cells gamma delta, NK cells activated, Monocytes, and Macrophages M0 may be involved in development of AS, and the candidate genes MMP9 and MMP12 were associated with these immune cells to different degrees. What’ s more, miR-34a-5p and FOXC1, JUN maybe the most important miRNA and TFs.

Conclusion

The anti-AS effects of Sal B may be related to MMP9 and MMP12 and associated with immune cell infiltration, which is expected to be used in the early intervention of AS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03670-6.

Bioinformatic analysis and experimental validation identified DNA methylation–Related biomarkers and immune-cell infiltration of atherosclerosis

Background: DNA methylation is an important form of epigenetic regulation and is closely related to atherosclerosis (AS). The purpose of this study was to identify DNA methylation–related biomarkers and explore the immune-infiltrate characteristics of AS based on methylation data.

Methods: DNA methylation data of 15 atherosclerotic and paired healthy tissues were obtained from Gene Expression Omnibus database. Differential methylation positions (DMPs) and differential methylation regions (DMRs) were screened by the ChAMP R package. The methylation levels of DMPs located on CpG islands of gene promoter regions were averaged. The limma R package was used to screen differentially methylated genes in the CpG islands of the promoter regions. The diagnostic values of the methylation levels were evaluated using the pROC R package. The EpiDISH algorithm was applied to quantify the infiltration levels of seven types of immune cells. Subsequently, three pairs of clinical specimens of coronary atherosclerosis with Stary’s pathological stage III were collected, and the methylation levels were detected by the methylation-specific PCR (MS-PCR) assay. Western blot was performed to detect the protein expression levels of monocyte markers.

Results: A total of 110, 695 DMPs, and 918 DMRs were screened in the whole genome. Also, six genes with significant methylation differences in the CpG islands of the promoter regions were identified, including 49 DMPs. In total, three genes (GRIK2, HOXA2, and HOXA3) had delta beta greater than 0.2. The infiltration level of monocytes was significantly upregulated in AS tissues. MS-PCR assay confirmed the methylation status of the aforementioned three genes in AS samples. The Western blot results showed that the expression levels of the monocyte marker CD14 and M1-type macrophage marker CD86 were significantly increased in AS while M2-type macrophage marker protein CD206 was significantly decreased.

Conclusion: This study identified potential DNA methylation–related biomarkers and revealed the role of monocytes in early AS.

The landscape of immune cell infiltration in the glomerulus of diabetic nephropathy: evidence based on bioinformatics

Background

Increasing evidence suggests that immune cell infiltration contributes to the pathogenesis and progression of diabetic nephropathy (DN). We aim to unveil the immune infiltration pattern in the glomerulus of DN and provide potential targets for immunotherapy.

Methods

Infiltrating percentage of 22 types of immune cell in the glomerulus tissues were estimated by the CIBERSORT algorithm based on three transcriptome datasets mined from the GEO database. Differentially expressed genes (DEGs) were identified by the “limma” package. Then immune-related DEGs were identified by intersecting DEGs with immune-related genes (downloaded from Immport database). The protein–protein interactions of Immune-related DEGs were explored using the STRING database and visualized by Cytoscape. The enrichment analyses for KEGG pathways and GO terms were carried out by the gene set enrichment analysis (GSEA) method.

Results

11 types of immune cell were revealed to be significantly altered in the glomerulus tissues of DN (Up: B cells memory, T cells gamma delta, NK cells activated, Macrophages.M1, Macrophages M2, Dendritic cells resting, Mast cells resting; Down: B cells naive, NK cells resting, Mast cells activated, Neutrophils). Several pathways related to immune, autophagy and metabolic process were significantly activated. Moreover, 6 hub genes with a medium to strong correlation with renal function (eGFR) were identified (SERPINA3, LTF, C3, PTGDS, EGF and ALB).

Conclusion

In the glomerulus of DN, the immune infiltration pattern changed significantly. A complicated and tightly regulated network of immune cells exists in the pathological of DN. The hub genes identified here will facilitate the development of immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-022-02906-4.

Association Between the Children's Dietary Inflammatory Index (C-DII) and Markers of Inflammation and Oxidative Stress Among Children and Adolescents: NHANES 2015-2018

Objectives

To explore the association of Children's Dietary Inflammatory Index (C-DII) scores with inflammation and markers of inflammatory factors in children and adolescents.

Methods

Data on dietary nutrient intake, markers of inflammation (ferritin, alkaline phosphatase, C-reactive protein (CRP), absolute neutrophil cell count and lymphocyte count) and oxidative stress (serum bilirubin, albumin, and iron) were available for participants aged 6–19 years (n = 1281). Each participant's C-DII score was calculated based on a 24-h diet and recall. Generalized linear models were applied to examine associations between C-DII and markers of inflammation and oxidative stress, while adjusting for covariates. Restricted cubic splines were used to explore the dose-response association of C-DII scores with indicators of inflammatory oxidative stress. Akaike's Information Criterionwas applied to compare the performance of linear and non-linear models.

Results

After adjusting for potential confounders, quantile regression results showed that when comparing C-DII quartile 4 (most pro-inflammatory) and quartile 1 (most anti-inflammatory), lymphocytes, ferritin, CRP were statistically significant differences in serum bilirubin, albumin and serum iron (P < 0.05). The C-DII score showed a non-linear relationship with inflammatory oxidative stress indicators. Overweight/obese children and adolescents who ate a high pro-inflammatory diet were more likely to have higher levels of inflammatory cytokines (P = 0.002).

Conclusions

The dietary inflammatory index in children is associated with markers of chronic inflammation and oxidative stress. A pro-inflammatory diet resulted in increased serum concentrations of these markers, implying that early dietary interventions have implications for reducing chronic inflammation and oxidative stress in children and adolescents.

Transcriptome-Based Dissection of Intracranial Aneurysms Unveils an “Immuno-Thermal” Microenvironment and Defines a Pathological Feature-Derived Gene Signature for Risk Estimation

Immune inflammation plays an essential role in the formation and rupture of intracranial aneurysm (IA). However, the current limited knowledge of alterations in the immune microenvironment of IA has hampered the mastery of pathological mechanisms and technological advances, such as molecular diagnostic and coated stent-based molecular therapy. In this study, seven IA datasets were enrolled from the GEO database to decode the immune microenvironment and relevant biometric alterations. The ssGSEA algorithm was employed for immune infiltration assessment. IAs displayed abundant immune cell infiltration, activated immune-related pathways, and high expression of immune-related genes. Several immunosuppression cells and genes were also coordinately upregulated in IAs. Five immune-related hub genes, including CXCL10, IL6, IL10, STAT1, and VEGFA, were identified from the protein-protein interaction network and further detected at the protein level. CeRNA networks and latent drugs targeting the hub genes were predicted for targeted therapy reference. Two gene modules recognized via WCGNA were functionally associated with contractile smooth muscle loss and extracellular matrix metabolism, respectively. In blood datasets, a pathological feature-derived gene signature (PFDGS) for IA diagnosis and rupture risk prediction was established using machine learning. Patients with high PFDGS scores may possess adverse biological alterations and present with a high risk of morbidity or IA rupture, requiring more vigilance or prompt intervention. Overall, we systematically unveiled an “immuno-thermal” microenvironment characterized by co-enhanced immune activation and immunosuppression in IA, which provides a novel insight into molecular pathology. The PFDGS is a promising signature for optimizing risk surveillance and clinical decision-making in IA patients.

Differential Gene Expression and Immune Cell Infiltration in Carotid Intraplaque Hemorrhage Identified Using Integrated Bioinformatics Analysis

Background

Intraplaque hemorrhage (IPH) is an important feature of unstable plaques and an independent risk factor for cardiovascular events. However, the molecular mechanisms contributing to IPH are incompletely characterized. We aimed to identify novel biomarkers and interventional targets for IPH and to characterize the role of immune cells in IPH pathogenesis.

Methods

The microarray dataset GSE163154 which contain IPH and non-IPH plaque samples was obtained from the Gene Expression Omnibus (GEO). R software was adopted for identifying differentially expressed genes (DEGs) and conducting functional investigation. The hub genes were carried by protein-protein interaction (PPI) network and were validated by the GSE120521 dataset. CIBERSORT deconvolution was used to determine differential immune cell infiltration and the relationship of immune cells and hub genes. We confirmed expression of proteins encoded by the hub genes by immunohistochemistry and western blotting in 8 human carotid endarterectomy samples with IPH and 8 samples without IPH (non-IPH).

Results

We detected a total of 438 differentially expressed genes (DEGs), of which 248 were upregulated and 190 were downregulated. DEGs were mainly involved in inflammatory related pathways, including neutrophil activation, neutrophil degranulation, neutrophil-mediated immunity, leukocyte chemotaxis, and lysosomes. The hub genes found through the method of degree in the PPI network showed that ITGB2 and ITGAM might play an important role in IPH. Receiver operating characteristic (ROC) results also showed a good performance of these two genes in the test and validation dataset. We found that the proportions of infiltrating immune cells in IPH and non-IPH samples differed, especially in terms of M0 and M2 macrophages. Immunohistochemistry and western blotting analysis showed that expression levels of ITGB2 and ITGAM increased significantly in carotid atherosclerotic plaques with IPH.

Conclusion

ITGB2 and ITGAM are key hub genes of IPH and may play an important role in the biological process of IPH. Our findings advance our understanding of the underlying mechanisms of IPH pathogenesis and provide valuable information and directions for future research into novel targets for IPH diagnosis and immunotherapy.

Immune-Associated Gene Signatures and Subtypes to Predict the Progression of Atherosclerotic Plaques Based on Machine Learning

Objective: Experimental and clinical evidence suggests that atherosclerosis is a chronic inflammatory disease. Our study was conducted for uncovering the roles of immune-associated genes during atherosclerotic plaque progression.

Methods: Gene expression profiling of GSE28829, GSE43292, GSE41571, and GSE120521 datasets was retrieved from the GEO database. Three machine learning algorithms, least absolute shrinkage, and selection operator (LASSO), random forest, and support vector machine–recursive feature elimination (SVM-RFE) were utilized for screening characteristic genes among atherosclerotic plaque progression- and immune-associated genes. ROC curves were generated for estimating the diagnostic efficacy. Immune cell infiltrations were estimated via ssGSEA, and immune checkpoints were quantified. CMap analysis was implemented to screen potential small-molecule compounds. Atherosclerotic plaque specimens were classified using a consensus clustering approach.

Results: Seven characteristic genes (TNFSF13B, CCL5, CCL19, ITGAL, CD14, GZMB, and BTK) were identified, which enabled the prediction of progression of atherosclerotic plaques. Higher immune cell infiltrations and immune checkpoint expressions were found in advanced-stage than in early-stage atherosclerotic plaques and were positively linked to characteristic genes. Patients could clinically benefit from the characteristic gene-based nomogram. Several small molecular compounds were predicted based on the characteristic genes. Two subtypes, namely, C1 immune subtype and C2 non-immune subtype, were classified across atherosclerotic plaques. The characteristic genes presented higher expression in C1 than in C2 subtypes.

Conclusion: Our findings provide several promising atherosclerotic plaque progression- and immune-associated genes as well as immune subtypes, which might enable to assist the design of more accurately tailored cardiovascular immunotherapy.

Identification of potential biomarkers and pathways associated with carotid atherosclerotic plaques in type 2 diabetes mellitus: A transcriptomics study

Type 2 diabetes mellitus (T2DM) affects the formation of carotid atherosclerotic plaques (CAPs) and patients are prone to plaque instability. It is crucial to clarify transcriptomics profiles and identify biomarkers related to the progression of T2DM complicated by CAPs. Ten human CAP samples were obtained, and whole transcriptome sequencing (RNA-seq) was performed. Samples were divided into two groups: diabetes mellitus (DM) versus non-DM groups and unstable versus stable groups. The Limma package in R was used to identify lncRNAs, circRNAs, and mRNAs. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, protein-protein interaction (PPI) network creation, and module generation were performed for differentially expressed mRNAs. Cytoscape was used to create a transcription factor (TF)-mRNA regulatory network, lncRNA/circRNA-mRNA co-expression network, and a competitive endogenous RNA (ceRNA) network. The GSE118481 dataset and RT-qPCR were used to verify potential mRNAs.The regulatory network was constructed based on the verified core genes and the relationships were extracted from the above network. In total, 180 differentially expressed lncRNAs, 343 circRNAs, and 1092 mRNAs were identified in the DM versus non-DM group; 240 differentially expressed lncRNAs, 390 circRNAs, and 677 mRNAs were identified in the unstable versus stable group. Five circRNAs, 14 lncRNAs, and 171 mRNAs that were common among all four groups changed in the same direction. GO/KEGG functional enrichment analysis showed that 171 mRNAs were mainly related to biological processes, such as immune responses, inflammatory responses, and cell adhesion. Five circRNAs, 14 lncRNAs, 46 miRNAs, and 54 mRNAs in the ceRNA network formed a regulatory relationship. C22orf34-hsa-miR-6785-5p-RAB37, hsacirc_013887-hsa-miR-6785-5p/hsa-miR-4763-5p/hsa-miR-30b-3p-RAB37, MIR4435-1HG-hsa-miR-30b-3p-RAB37, and GAS5-hsa-miR-30b-3p-RAB37 may be potential RNA regulatory pathways. Seven upregulated mRNAs were verified using the GSE118481 dataset and RT-qPCR. The regulatory network included seven mRNAs, five circRNAs, six lncRNAs, and 14 TFs. We propose five circRNAs (hsacirc_028744, hsacirc_037219, hsacirc_006308, hsacirc_013887, and hsacirc_045622), six lncRNAs (EPB41L4A-AS1, LINC00969, GAS5, MIR4435-1HG, MIR503HG, and SNHG16), and seven mRNAs (RAB37, CCR7, CD3D, TRAT1, VWF, ICAM2, and TMEM244) as potential biomarkers related to the progression of T2DM complicated with CAP. The constructed ceRNA network has important implications for potential RNA regulatory pathways.

Difference of immune cell infiltration between stable and unstable carotid artery atherosclerosis

Atherosclerotic plaque instability contributes to ischaemic stroke and myocardial infarction. This study is to compare the abundance and difference of immune cell subtypes within unstable atherosclerotic tissues. CIBERSORT was used to speculate the proportions of 22 immune cell types based on a microarray of atherosclerotic carotid artery samples. R software was utilized to illustrate the bar plot, heat map and vioplot. The immune cell landscape in atherosclerosis was diverse, dominated by M2 macrophages, M0 macrophages, resting CD4 memory T cells and CD8 T cells. There was a significant difference in resting CD4 memory T cells (p = 0.032), T cells follicular helper (p = 0.033), M0 (p = 0.047) and M2 macrophages (p = 0.012) between stable and unstable atherosclerotic plaques. Compared with stable atherosclerotic plaques, unstable atherosclerotic plaques had a higher percentage of M2 macrophages. Moreover, correlation analysis indicated that the percentage of naïve CD4 T cells was strongly correlated with that of gamma delta T cells (r = 0.93, p < 0.001), while memory B cells were correlated with plasma cells (r = 0.85, p < 0.001). In summary, our study explored the abundance and difference of specific immune cell subgroups at unstable plaques, which would aid new immunotherapies for atherosclerosis.

Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis

Background

Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).

Methods

“GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.

Results

A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.

Conclusion

In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.