Preliminary investigation of the function of hsa_circ_0049356 in nonobstructive azoospermia patients

A detection model of testis-derived circular RNAs in serum for predicting testicular sperm retrieval rate in non-obstructive azoospermia patients

BACKGROUND

Microdissection testicular sperm extraction is an effective method to retrieve sperm from non-obstructive azoospermia patients. However, its successful rate is less than 50%.

OBJECTIVES

To identify the predictive value of circular RNAs in serum for sperm retrieval rate in non-obstructive azoospermia patients.

MATERIALS AND METHODS

180 non-obstructive azoospermia patients were recruited in this study, including 84 individuals with successful sperm retrieval and 96 individuals with failed sperm retrieval. Our study contained two phases. First, 20 patients, selected from the 180 patients, were included in screening cohort. In this cohort, the top 20 circular RNAs from our previous testicular circRNA profiles were verified between successful and failed sperm retrieval groups using real-time polymerase chain reaction. Six circular RNAs with the most significantly different expressions were selected for further verification. Second, the 180 patients were included as discovery cohort to verify the six circular RNAs. Circular RNAs were extracted from serum in each participant. Logistic regression analysis was further performed to identify the predictive value and the area under the curve analysis was used to evaluate diagnostic efficiency, sensitivity, and specificity.

RESULTS

Six circular RNAs including hsa_circ_0058058, hsa_circ_0008045, hsa_circ_0084789, hsa_circ_0000550, hsa_circ_0007422, and hsa_circ_0004099 showed aberrant expressions between the successful and failed sperm retrieval group. In addition, both single-circular RNA panels and multi-circular RNA panels were finally verified to be significant in predicting sperm retrieval rate. Notably, multi-circular RNAs panels demonstrated better predictive abilities compared with single-circRNA panels, and the combined panel of six-circular RNAs (risk score = 1.094×hsa_circ_0058058+0.697×hsa_circ_0008045+0.718×hsa_circ_0084789-0.591×hsa_circ_0000550-0.435×hsa_circ_0007422-1.017×hsa_circ_0004099-1.561) exhibited the best predictive ability in the present study with an AUC of 0.977, a sensitivity of 91.7% and a specificity of 86.5%. A higher risk score indicated a higher risk of failure in sperm retrieval.

DISCUSSION AND CONCLUSION

Our study was the first to report that testis-derived circular RNAs in serum have the ability to predict sperm retrieval rate in non-obstructive azoospermia patients, whether it is a single-circular RNA or a combination of multi-circular RNAs.

The Role of Circular RNAs in Male Infertility and Reproductive Cancers: A Narrative Review

Infertility is a global health problem affecting about 15% of all couples, of which 50% are due to male infertility. Although the etiology of infertility is known in most infertile men, idiopathic male infertility remains a challenge. Therefore, there is a need for novel diagnostic methods to detect the underlying mechanisms and develop appropriate therapies. Recent studies have focused on the role of non-coding RNAs (ncRNAs) in male infertility. Circular RNAs (CircRNAs), a type of ncRNAs, are found to play a key role in the development of some pathological conditions, including cardiovascular diseases, diabetes, cancers, autoimmune diseases, etc. Several studies have reported the presence of CircRNAs and their target genes in the human reproductive system. In addition, their expression in testicular tissues, sperm cells, and seminal fluid has been identified. Abnormal expression of CircRNAs has been associated with azoospermia and asthenozoospermia in infertile men. The present narrative review provides a brief description of the role of CircRNAs in spermatogenic cells, male infertility, and reproductive cancers. In addition, some CircRNAs have been identified as potential biomarkers for disease detection and treatment.

Identifying potential biomarkers for non-obstructive azoospermia using WGCNA and machine learning algorithms

Objective

The cause and mechanism of non-obstructive azoospermia (NOA) is complicated; therefore, an effective therapy strategy is yet to be developed. This study aimed to analyse the pathogenesis of NOA at the molecular biological level and to identify the core regulatory genes, which could be utilised as potential biomarkers.

Methods

Three NOA microarray datasets (GSE45885, GSE108886, and GSE145467) were collected from the GEO database and merged into training sets; a further dataset (GSE45887) was then defined as the validation set. Differential gene analysis, consensus cluster analysis, and WGCNA were used to identify preliminary signature genes; then, enrichment analysis was applied to these previously screened signature genes. Next, 4 machine learning algorithms (RF, SVM, GLM, and XGB) were used to detect potential biomarkers that are most closely associated with NOA. Finally, a diagnostic model was constructed from these potential biomarkers and visualised as a nomogram. The differential expression and predictive reliability of the biomarkers were confirmed using the validation set. Furthermore, the competing endogenous RNA network was constructed to identify the regulatory mechanisms of potential biomarkers; further, the CIBERSORT algorithm was used to calculate immune infiltration status among the samples.

Results

A total of 215 differentially expressed genes (DEGs) were identified between NOA and control groups (27 upregulated and 188 downregulated genes). The WGCNA results identified 1123 genes in the MEblue module as target genes that are highly correlated with NOA positivity. The NOA samples were divided into 2 clusters using consensus clustering; further, 1027 genes in the MEblue module, which were screened by WGCNA, were considered to be target genes that are highly correlated with NOA classification. The 129 overlapping genes were then established as signature genes. The XGB algorithm that had the maximum AUC value (AUC=0.946) and the minimum residual value was used to further screen the signature genes. IL20RB, C9orf117, HILS1, PAOX, and DZIP1 were identified as potential NOA biomarkers. This 5 biomarker model had the highest AUC value, of up to 0.982, compared to other single biomarker models; additionally, the results of this biomarker model were verified in the validation set.

Conclusions

As IL20RB, C9orf117, HILS1, PAOX, and DZIP1 have been determined to possess the strongest association with NOA, these five genes could be used as potential therapeutic targets for NOA patients. Furthermore, the model constructed using these five genes, which possessed the highest diagnostic accuracy, may be an effective biomarker model that warrants further experimental validation.

Circular RNAs and Their Role in Male Infertility: A Systematic Review

Male infertility is a global health problem that is on the rise. Today, many noncoding RNAs (ncRNAs) are associated with male infertility. Circular RNAs (circRNAs) have recently drawn attention, but a comprehensive understanding of the role of circRNAs in male infertility is limited. This systematic review investigates the differential expression of circRNAs in male infertility or circRNAs that could serve as candidate biomarkers. The PRISMA guidelines were used to search PubMed and Web of Science on 11 January 2023. Inclusion criteria were human participants, experimental studies aiming to associate circRNAs with male infertility reporting differentially expressed circRNAs, and the English language. A total of 156 articles were found, and after the screening and eligibility stages, 13 studies were included in the final sample. Many circRNAs are deregulated in male infertility, and their interactions with miRNAs play an important role in affecting cellular processes and pathways. CircRNAs could also be used as biomarkers to screen patients before sperm retrieval. However, most studies focus on the role of circRNAs in azoospermia, and there is a knowledge gap regarding other subtypes of male infertility. Future research is needed to explore the exact mechanism of action of circRNAs and investigate their use as biomarkers.

Circular RNAs: Novel Biomarkers in Spermatogenesis Defects and Male Infertility

Circular RNAs (circRNAs) are a new class of endogenous non-coding RNAs involved in several cellular and biological processes, including gene expression regulation, microRNA function, transcription regulation, and translation modification. Therefore, these non-coding RNAs have important roles in the pathogenesis of various diseases. Male infertility is mainly due to abnormal sperm parameters such as motility, morphology, and concentration. Recent studies have confirmed the role of circRNAs in spermatogenesis, and the expression of several circRNAs is confirmed in seminal plasma, spermatozoa, and testicular tissue. It is suggested that deregulation of circRNAs is involved in different types of male infertility, including azoospermia, oligozoospermia, and asthenozoospermia. In the present review, we aimed to discuss the potential roles of circRNAs in spermatogenesis failure, sperm defects, and male infertility. Due to their conserved and special structure and tissue-specific expression pattern, circRNAs can be applied as reliable noninvasive molecular biomarkers, therapeutic and pharmaceutical targets in male infertility.

The gene regulatory role of non-coding RNAs in non-obstructive azoospermia

Non-coding RNAs are classified as small non-coding RNAs, long non-coding RNAs and circular RNAs, which are involved in a variety of biological processes, including cell differentiation, proliferation, apoptosis and pathological conditions of various diseases. Many studies have shown that non-coding RNAs are related to spermatogenesis, maturation, apoptosis, function, etc. In addition, the expression of non-coding RNAs in testicular tissue and semen of patients with non-obstructive azoospermia was different. However, the role of non-coding RNAs in the pathogenesis of non-obstructive azoospermia has not been fully elucidated, and the role of non-coding RNAs in non-obstructive azoospermia is rarely reviewed. Here we summarize the research progress of non-coding RNAs in the pathogenesis of non-obstructive azoospermia.