Dataset Information

Identification of biomarkers associated with macrophage infiltration in non-obstructive azoospermia using single-cell transcriptomic and microarray data.

ABSTRACT:

Background

Non-obstructive azoospermia (NOA) is a common clinical cause of male infertility. Research suggests that macrophages are linked to testicular function; however, their involvement in NOA remains unknown.

Methods

To evaluate the importance of macrophages infiltration in NOA and identify the macrophage-related biomarkers, the gene-expression microarray data GSE45885 and the single-cell transcriptomic data GSE149512 were utilized from the Gene Expression Omnibus (GEO). A single-sample gene set enrichment analysis (ssGSEA) was conducted to investigate immune cell proliferation. The Seurat package was used for the single-cell data analysis, and the limma package was used to identify the differentially expressed genes between the NOA and normal samples. Moreover, we conducted a weighted gene co-expression network analysis (WGCNA) to identify the macrophage-related key modules and genes, and conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses for the functional exploration. To identify the macrophage-related biomarkers, we conducted least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) analyses. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to verify the marker genes present in NOA.

Results

We confirmed that open reading frame 72 gene on chromosome 9 (C9orf72) [area under the curve (AUC) =0.861] and cartilage-associated protein (CRTAP) (AUC =0.917) were the hub genes of NOA, and the RT-qPCR analysis revealed the critical expression of both genes in NOA.

Conclusions

Through the combination of tissue transcriptomic and single-cell RNA-sequencing analyses, we concluded that macrophage infiltration is significant in different subtypes of NOA, and we hypothesized that C9orf72 and CRTAP play critical roles in NOA due to their high expression in macrophages.

SUBMITTER: Luo X

PROVIDER: S-EPMC9929779 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

Identification of biomarkers associated with macrophage infiltration in non-obstructive azoospermia using single-cell transcriptomic and microarray data.

Luo Xi X Zheng Haishan H Nai Zhen Z Li Mingying M Li Yonggang Y Lin Na N Li Yunxiu Y Wu Ze Z

Annals of translational medicine 20230101 2

<h4>Background</h4>Non-obstructive azoospermia (NOA) is a common clinical cause of male infertility. Research suggests that macrophages are linked to testicular function; however, their involvement in NOA remains unknown.<h4>Methods</h4>To evaluate the importance of macrophages infiltration in NOA and identify the macrophage-related biomarkers, the gene-expression microarray data GSE45885 and the single-cell transcriptomic data GSE149512 were utilized from the Gene Expression Omnibus (GEO). A si ...[more]

PMID: 36819497

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Project description:Background: Non-obstructive azoospermia (NOA) is the most severe form of male infertility. Currently, the molecular mechanisms underlying NOA pathology have not yet been elucidated. Hence, elucidation of the mechanisms of NOA and exploration of potential biomarkers are essential for accurate diagnosis and treatment of this disease. In the present study, we aimed to screen for biomarkers and pathways involved in NOA and reveal their potential molecular mechanisms using integrated bioinformatics. Methods: We downloaded two gene expression datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in NOA and matched the control group tissues were identified using the limma package in R software. Subsequently, Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), protein-protein interaction (PPI) network, gene-microRNAs network, and transcription factor (TF)-hub genes regulatory network analyses were performed to identify hub genes and associated pathways. Finally, we conducted immune infiltration analysis using CIBERSORT to evaluate the relationship between the hub genes and the NOA immune infiltration levels. Results: We identified 698 common DEGs, including 87 commonly upregulated and 611 commonly downregulated genes in the two datasets. GO analysis indicated that the most significantly enriched gene was protein polyglycylation, and KEGG pathway analysis revealed that the DEGs were most significantly enriched in taste transduction and pancreatic secretion signaling pathways. GSEA showed that DEGs affected the biological functions of the ribosome, focaladhesion, and protein_expor. We further identified the top 31 hub genes from the PPI network, and friends analysis of hub genes in the PPI network showed that NR4A2 had the highest score. In addition, immune infiltration analysis found that CD8+ T cells and plasma cells were significantly correlated with ODF3 expression, whereas naive B cells, plasma cells, monocytes, M2 macrophages, and resting mast cells showed significant variation in the NR4A2 gene expression group, and there were differences in T cell regulatory immune cell infiltration in the FOS gene expression groups. Conclusion: The present study successfully constructed a regulatory network of DEGs between NOA and normal controls and screened three hub genes using integrative bioinformatics analysis. In addition, our results suggest that functional changes in several immune cells in the immune microenvironment may play an important role in spermatogenesis. Our results provide a novel understanding of the molecular mechanisms of NOA and offer potential biomarkers for its diagnosis and treatment.

Project description:BackgroundNon-obstructive azoospermia (NOA) is a major contributor of male infertility. Herein, we used existing datasets to identify novel biomarkers for the diagnosis and prognosis of NOA, which could have great significance in the field of male infertility.MethodsNOA datasets were obtained from the Gene Expression Omnibus (GEO) database. CIBERSORT was utilized to analyze the distributions of 22 immune cell populations. Hub genes were identified by applying weighted gene co-expression network analysis (WGCNA), machine learning methods, and protein-protein interaction (PPI) network analysis. The expression of hub genes was verified in external datasets and was assessed by receiver operating characteristic (ROC) curve analysis. Gene set enrichment analysis (GSEA) was applied to explore the important functions and pathways of hub genes. The mRNA-microRNA (miRNA)-transcription factors (TFs) regulatory network and potential drugs were predicted based on hub genes. Single-cell RNA sequencing data from the testes of patients with NOA were applied for analyzing the distribution of hub genes in single-cell clusters. Furthermore, testis tissue samples were obtained from patients with NOA and obstructive azoospermia (OA) who underwent testicular biopsy. RT-PCR and Western blot were used to validate hub gene expression.ResultsTwo immune-related oxidative stress hub genes (SHC1 and FGFR1) were identified. Both hub genes were highly expressed in NOA samples compared to control samples. ROC curve analysis showed a remarkable prediction ability (AUCs > 0.8). GSEA revealed that hub genes were predominantly enriched in toll-like receptor and Wnt signaling pathways. A total of 24 TFs, 82 miRNAs, and 111 potential drugs were predicted based on two hub genes. Single-cell RNA sequencing data in NOA patients indicated that SHC1 and FGFR1 were highly expressed in endothelial cells and Leydig cells, respectively. RT-PCR and Western blot results showed that mRNA and protein levels of both hub genes were significantly upregulated in NOA testis tissue samples, which agree with the findings from analysis of the microarray data.ConclusionIt appears that SHC1 and FGFR1 could be significant immune-related oxidative stress biomarkers for detecting and managing patients with NOA. Our findings provide a novel viewpoint for illustrating potential pathogenesis in men suffering from infertility.

Dataset Information

Identification of biomarkers associated with macrophage infiltration in non-obstructive azoospermia using single-cell transcriptomic and microarray data.

Background

Methods

Results

Conclusions

Publications

Identification of biomarkers associated with macrophage infiltration in non-obstructive azoospermia using single-cell transcriptomic and microarray data.

Similar Datasets

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