Future diagnostics in male infertility: genomics, epigenetics, metabolomics and proteomics

Insight into the complexity of male infertility: a multi-omics review

Male infertility is a reproductive disorder, accounting for 40-50% of infertility. Currently, in about 70% of infertile men, the cause remains unknown. With the introduction of novel omics and advancement in high-throughput technology, potential biomarkers are emerging. The main purpose of our work was to overview different aspects of omics approaches in association with idiopathic male infertility and highlight potential genes, transcripts, non-coding RNA, proteins, and metabolites worth further exploring. Using the Gene Ontology (GO) analysis, we aimed to compare enriched GO terms from each omics approach and determine their overlapping. A PubMed database screening for the literature published between February 2014 and June 2022 was performed using the keywords: male infertility in association with different omics approaches: genomics, epigenomics, transcriptomics, ncRNAomics, proteomics, and metabolomics. A GO enrichment analysis was performed using the Enrichr tool. We retrieved 281 global studies: 171 genomics (DNA level), 21 epigenomics (19 of methylation and two histone residue modifications), 15 transcriptomics, 31 non-coding RNA, 29 proteomics, two protein posttranslational modification, and 19 metabolomics studies. Gene ontology comparison showed that different omics approaches lead to the identification of different molecular factors and that the corresponding GO terms, obtained from different omics approaches, do not overlap to a larger extent. With the integration of novel omics levels into the research of idiopathic causes of male infertility, using multi-omic systems biology approaches, we will be closer to finding the potential biomarkers and consequently becoming aware of the entire spectrum of male infertility, their cause, prognosis, and potential treatment.

The Omics Revolution in Understanding Chicken Reproduction: A Comprehensive Review

Omics approaches have significantly contributed to our understanding of several aspects of chicken reproduction. This review paper gives an overview of the use of omics technologies such as genomics, transcriptomics, proteomics, and metabolomics to elucidate the mechanisms of chicken reproduction. Genomics has transformed the study of chicken reproduction by allowing the examination of the full genetic makeup of chickens, resulting in the discovery of genes associated with reproductive features and disorders. Transcriptomics has provided insights into the gene expression patterns and regulatory mechanisms involved in reproductive processes, allowing for a better knowledge of developmental stages and hormone regulation. Furthermore, proteomics has made it easier to identify and quantify the proteins involved in reproductive physiology to better understand the molecular mechanisms driving fertility, embryonic development, and egg quality. Metabolomics has emerged as a useful technique for understanding the metabolic pathways and biomarkers linked to reproductive performance, providing vital insights for enhancing breeding tactics and reproductive health. The integration of omics data has resulted in the identification of critical molecular pathways and biomarkers linked with chicken reproductive features, providing the opportunity for targeted genetic selection and improved reproductive management approaches. Furthermore, omics technologies have helped to create biomarkers for fertility and embryonic viability, providing the poultry sector with tools for effective breeding and reproductive health management. Finally, omics technologies have greatly improved our understanding of chicken reproduction by revealing the molecular complexities that underpin reproductive processes.

A comprehensive insight into the contribution of epigenetics in male infertility; focusing on immunological modifications

Numerous recent studies have examined the impact epigenetics-including DNA methylation-has on spermatogenesis and male infertility. Differential methylation of several genes has been linked to compromised spermatogenesis and/or reproductive failure. Specifically, male infertility has been frequently associated with DNA methylation abnormalities of MEST and H19 inside imprinted genes and MTHFR within non-imprinted genes. Microbial infections mainly result in male infertility because of the immune response triggered by the bacteria' accumulation of immune cells, proinflammatory cytokines, and chemokines. Thus, bacterially produced epigenetic dysregulations may impact host cell function, supporting host defense or enabling pathogen persistence. So, it is possible to think of pathogenic bacteria as potential epimutagens that can alter the epigenome. It has been demonstrated that dysregulated levels of LncRNA correlate with motility and sperm count in ejaculated spermatozoa from infertile males. Therefore, a thorough understanding of the relationship between decreased reproductive capacity and sperm DNA methylation status should aid in creating new diagnostic instruments for this condition. To fully understand the mechanisms influencing sperm methylation and how they relate to male infertility, more research is required.

Cancer risk and male Infertility: Unravelling predictive biomarkers and prognostic indicators

In recent years, there has been a global increase in cases of male infertility. There are about 30 million cases of male infertility worldwide and male reproductive health is showing rapid decline in last few decades. It is now recognized as a potential risk factor for developing certain types of cancer, particularly genitourinary malignancies like testicular and prostate cancer. Male infertility is considered a potential indicator of overall health and an early biomarker for cancer. Cases of unexplained male factor infertility have high levels of oxidative stress and oxidative DNA damage and this induces both denovo germ line mutations and epimutations due to build up of 8-hydroxy 2 deoxygunaosine abase which is highly mutagenic and also induces hypomethylation and genomic instability. Consequently, there is growing evidence to explore the various factors contributing to an increased cancer risk. Currently, the available prognostic and predictive biomarkers associated with semen characteristics and cancer risk are limited but gaining significant attention in clinical research for the diagnosis and treatment of elevated cancer risk in the individual and in offspring. The male germ cell being transcriptionally and translationally inert has a highly truncated repair mechanism and has minimal antioxidants and thus most vulnerable to oxidative injury due to environmental factors and unhealthy lifestyle and social habits. Therefore, advancing our understanding requires a thorough evaluation of the pathophysiologic mechanisms at the DNA, RNA, protein, and metabolite levels to identify key biomarkers that may underlie the pathogenesis of male infertility and associated cancer. Advanced methodologies such as genomics, epigenetics, proteomics, transcriptomics, and metabolomics stand at the forefront of cutting-edge approaches for discovering novel biomarkers, spanning from infertility to associated cancer types. Henceforth, in this review, we aim to assess the role and potential of recently identified predictive and prognostic biomarkers, offering insights into the success of assisted reproductive technologies, causes of azoospermia and idiopathic infertility, the impact of integrated holistic approach and lifestyle modifications, and the monitoring of cancer susceptibility, initiation and progression. Comprehending these biomarkers is crucial for providing comprehensive counselling to infertile men and cancer patients, along with their families.

Oxidative Stress Biomarkers in Male Infertility: Established Methodologies and Future Perspectives

Male fertility can be affected by oxidative stress (OS), which occurs when an imbalance between the production of reactive oxygen species (ROS) and the body's ability to neutralize them arises. OS can damage cells and influence sperm production. High levels of lipid peroxidation have been linked to reduced sperm motility and decreased fertilization ability. This literature review discusses the most commonly used biomarkers to measure sperm damage caused by ROS, such as the high level of OS in seminal plasma as an indicator of imbalance in antioxidant activity. The investigated biomarkers include 8-hydroxy-2-deoxyguanosine acid (8-OHdG), a marker of DNA damage caused by ROS, and F2 isoprostanoids (8-isoprostanes) produced by lipid peroxidation. Furthermore, this review focuses on recent methodologies including the NGS polymorphisms and differentially expressed gene (DEG) analysis, as well as the epigenetic mechanisms linked to ROS during spermatogenesis along with new methodologies developed to evaluate OS biomarkers. Finally, this review addresses a valuable insight into the mechanisms of male infertility provided by these advances and how they have led to new treatment possibilities. Overall, the use of biomarkers to evaluate OS in male infertility has supplied innovative diagnostic and therapeutic approaches, enhancing our understanding of male infertility mechanisms.

Sperm epigenetics landscape: correlation with embryo quality, reproductive outcomes and offspring's health

Epigenetics refers to how gene expression and function are modulated without modifying the DNA sequence but through subtle molecular changes or interactions with it. As spermatogenesis progresses, male germ cells suffer plenty of epigenetic modifications, resulting in the definitive epigenome of spermatozoa conditioning its functionality, and this process can be altered by several internal and external factors. The paternal epigenome is crucial for sperm function, fertilization, embryo development, and offspring's health, and altered epigenetic states are associated with male infertility with or without altered semen parameters, embryo quality impairment, and worse ART outcomes together with the future offspring's health risks mainly through intergenerational transmission of epigenetic marks. Identifying epigenetic biomarkers may improve male factor diagnosis and the development of targeted therapies, not only to improve fertility but also to allow an early detection of risk and disease prevention in the progeny. While still there is much research to be done, hopefully in the near future, improvements in high-throughput technologies applied to epigenomes will permit our understanding of the underlying epigenetic mechanisms and the development of diagnostics and therapies leading to improved reproductive outcomes. In this review, we discuss the mechanisms of epigenetics in sperm and how epigenetics behave during spermatogenesis. Additionally, we elaborate on the relationship of sperm epigenetics with sperm parameters and male infertility, and highlight the impact of sperm epigenetic alterations on sperm parameters, embryo quality, ART outcomes, miscarriage rates and offspring's health. Furthermore, we provide insights into the future research of epigenetic alterations in male infertility.

Expression of estrogen receptors, PELP1, and SRC in human spermatozoa and their associations with semen quality

Sperm cells are target cells for both estrogens and xenoestrogens. Due to the specific structure of spermatozoa, these hormonal compounds may act on sperm in a non-genomic mechanism only. However, the ESR-mediated signaling pathways are still poorly understood. In this study, we obtained 119 samples from male participants of Caucasian descent who donated semen for standard analysis. We analyzed gene expression of estrogen receptors (ESR1 and ESR2) and their coregulators-proline-, glutamic acid-, and leucine-rich protein 1 (PELP1), and cellular kinase c-Src (SRC). RNA level was established using reverse-transcribed RNA as a template, followed by a polymerase chain reaction. Proteins' presence was confirmed by western blot and immunocytochemistry techniques. "Normal" values of semen parameters were defined as follows: > 32% sperm with progressive motility, > 4% sperm cells with normal morphology, > 15 × 10⁶ sperm per mL, > 58% live spermatozoa and leukocyte amount < 10⁶ cells per mL, according to WHO 2010 reference. Semen parameters that deviated from these "normal" values were labeled as "abnormal". Gene expression ratios revealed significant, moderate, and negative correlations for ESR1/ESR2 and weak, negative ESR2/PELP1 correlations in the subgroup of patients with abnormal values of semen parameters. In addition, SRC/PELP1 was moderately and positively correlated in the subgroup with parameters within the reference values established by WHO 2010. Our study showed that both PELP1 scaffolding protein and SRC kinase might influence semen quality via ESRs. It seems that not the expression of a single gene may affect the sperm quality, but more gene-to-gene mutual ratio. Characterization of estrogen-signaling pathway-related genes' modulated expression in sperm cells could aid in better understanding sperm biology and quality.

Bicarbonate-Triggered In Vitro Capacitation of Boar Spermatozoa Conveys an Increased Relative Abundance of the Canonical Transient Receptor Potential Cation (TRPC) Channels 3, 4, 6 and 7 and of CatSper-γ Subunit mRNA Transcripts

Simple Summary

The detection of sub-fertile boars has been a difficult task, and despite their prevalence being low, its impact is very significant because it implies economic drawbacks for artificial insemination (AI) centers and farms. Unfortunately, some crucial reproductive processes fall beyond the routine analysis performed in the porcine model, such as sperm capacitation, which is a necessary event for fertilization. A synergistic action of bicarbonate (HCO₃⁻) with calcium (Ca²⁺) is needed to achieve capacitation. The transport of Ca²⁺ is mediated by CatSper channels and Canonical Transient Potential Channels (TRPC). We quantified mRNA transcripts of different subunits of CatSper (β, γ and δ) and TRPC (1, 3, 4, 6 and 7) before and after in vitro capacitation by HCO₃⁻ ions. Our results showed that in vitro capacitation using HCO₃⁻ increases the relative abundance of mRNA transcripts of almost all subunits of Ca²⁺ channels, except CatSper-δ and TRPC1, which were significantly reduced. More studies are needed to elucidate the specific roles of the TRPC channels at a physiological and functional level.

Abstract

Sperm capacitation is a stepwise complex biochemical process towards fertilization. It includes a crucial early calcium (Ca²⁺) transport mediated by CatSper channels and Canonical Transient Potential Channels (TRPC). We studied the relative abundance of mRNA transcripts changes of the CatSper β, γ and δ subunits and TRPC-channels 1, 3, 4, 6 and 7 in pig spermatozoa, after triggering in vitro capacitation by bicarbonate ions at levels present in vivo at the fertilization site. For this purpose, we analyzedfive5 ejaculate pools (from three fertile adult boars) before (control-fresh samples) and after in vitro exposure to capacitation conditions (37 mM NaHCO₃, 2.25 mM CaCl₂, 2 mM caffeine, 0.5% bovine serum albumin and 310 mM lactose) at 38 °C, 5% CO₂ for 30 min. In vitro capacitation using bicarbonate elicits an increase in the relative abundance of mRNA transcripts of almost all studied Ca²⁺ channels, except CatSper-δ and TRPC1 (significantly reduced). These findings open new avenues of research to identify the specific role of each channel in boar sperm capacitation and elucidate the physiological meaning of the changes on sperm mRNA cargo.

Effects of varicocele and microsurgical varicocelectomy on the metabolites in semen

The influence of varicocele and microsurgical varicocelectomy on semen quality remains unclear. Few studies have investigated the relationship between semen metabolism and the abnormalities in reproductive function caused by varicocele, however, there is no study on the changes of semen metabolism after microsurgical varicocelectomy. Here, we used the non-targeted and targeted metabolic analysis to investigate the different metabolites in seminal plasma within normal, varicocele, and varicocelectomy groups. We clearly showed that varicocele significantly affects semen metabolism, and microsurgical varicocelectomy can reverse this metabolic abnormality. Moreover, we characterized the landscape of three dipeptides in the seminal plasma of patients with varicocele that have not been identified previously in human tissues or biofluids. Interestingly, the levels of these three dipeptides decreased after microsurgical varicocelectomy coincident with an improvement in semen quality. Western blotting confirmed the downregulation of DPEP3 (dipeptidase 3) in the varicocele group and the upregulation of DPEP3 in the varicocelectomy group. Furthermore, we found that eight metabolites may be helpful to distinguish varicocele patients from normal subjects. Our results may be applied to earlier diagnosis or to predict the outcome of microsurgery for varicocele.

Omics and Male Infertility: Highlighting the Application of Transcriptomic Data

Male infertility is a multifaceted disorder affecting approximately 50% of male partners in infertile couples. Over the years, male infertility has been diagnosed mainly through semen analysis, hormone evaluations, medical records and physical examinations, which of course are fundamental, but yet inefficient, because 30% of male infertility cases remain idiopathic. This dilemmatic status of the unknown needs to be addressed with more sophisticated and result-driven technologies and/or techniques. Genetic alterations have been linked with male infertility, thereby unveiling the practicality of investigating this disorder from the “omics” perspective. Omics aims at analyzing the structure and functions of a whole constituent of a given biological function at different levels, including the molecular gene level (genomics), transcript level (transcriptomics), protein level (proteomics) and metabolites level (metabolomics). In the current study, an overview of the four branches of omics and their roles in male infertility are briefly discussed; the potential usefulness of assessing transcriptomic data to understand this pathology is also elucidated. After assessing the publicly obtainable transcriptomic data for datasets on male infertility, a total of 1385 datasets were retrieved, of which 10 datasets met the inclusion criteria and were used for further analysis. These datasets were classified into groups according to the disease or cause of male infertility. The groups include non-obstructive azoospermia (NOA), obstructive azoospermia (OA), non-obstructive and obstructive azoospermia (NOA and OA), spermatogenic dysfunction, sperm dysfunction, and Y chromosome microdeletion. Findings revealed that 8 genes (LDHC, PDHA2, TNP1, TNP2, ODF1, ODF2, SPINK2, PCDHB3) were commonly differentially expressed between all disease groups. Likewise, 56 genes were common between NOA versus NOA and OA (ADAD1, BANF2, BCL2L14, C12orf50, C20orf173, C22orf23, C6orf99, C9orf131, C9orf24, CABS1, CAPZA3, CCDC187, CCDC54, CDKN3, CEP170, CFAP206, CRISP2, CT83, CXorf65, FAM209A, FAM71F1, FAM81B, GALNTL5, GTSF1, H1FNT, HEMGN, HMGB4, KIF2B, LDHC, LOC441601, LYZL2, ODF1, ODF2, PCDHB3, PDHA2, PGK2, PIH1D2, PLCZ1, PROCA1, RIMBP3, ROPN1L, SHCBP1L, SMCP, SPATA16, SPATA19, SPINK2, TEX33, TKTL2, TMCO2, TMCO5A, TNP1, TNP2, TSPAN16, TSSK1B, TTLL2, UBQLN3). These genes, particularly the above-mentioned 8 genes, are involved in diverse biological processes such as germ cell development, spermatid development, spermatid differentiation, regulation of proteolysis, spermatogenesis and metabolic processes. Owing to the stage-specific expression of these genes, any mal-expression can ultimately lead to male infertility. Therefore, currently available data on all branches of omics relating to male fertility can be used to identify biomarkers for diagnosing male infertility, which can potentially help in unravelling some idiopathic cases.

Ultra-Performance Liquid Chromatography-Q-Exactive Orbitrap-Mass Spectrometry Analysis for Metabolic Communication between Heart and Kidney in Adriamycin-Induced Nephropathy Rats

BACKGROUND/AIMS

Although the adriamycin-induced nephropathy model is frequently employed in the study of nephrotic syndrome and focal segmental glomerulosclerosis, the accompanying myocardial damage has always been a cause for concern. Therefore, there is a great need to study cardiorenal communication in this model.

METHODS

An adriamycin-induced nephropathy model was established via tail vein injection. The levels of the biochemical indicators serum albumin, serum globulin, serum total protein, serum cholesterol, serum creatinine (SCr), urinary protein, and urinary creatinine (UCr) were measured, and histopathological changes in the heart and kidneys were assessed using hematoxylin-eosin staining. Metabolomic changes in the heart, blood, and kidneys were analyzed using the metabolomics method based on ultra-performance liquid chromatography Q-Exactive Orbitrap mass spectrometry.

RESULTS

Compared with the control group, the model group showed significant decreases in serum protein and total protein levels, albumin/globulin ratio, and creatinine clearance rate as well as significant increases in serum cholesterol, SCr, urinary protein, and UCr levels. Significant pathological changes were observed in the renal pathology sections in the model group, including diffusely merged glomerular epithelial cells, inflammatory infiltration, and vacuolated glomerular cells. Additionally, thickened myocardial fibers, swollen nuclei, inflammatory infiltration, and partial myocardial necrosis could be seen in the cardiac pathology sections in the model group. Based on multivariate statistical analysis, a total of 20 differential metabolites associated with 15 metabolic pathways were identified in the heart, 7 differential metabolites with 7 metabolic pathways were identified in the blood, and 16 differential metabolites with 21 metabolic pathways were identified in the kidney. Moreover, 6 common metabolic pathways shared by the heart and kidney were identified: arginine and proline metabolism; arginine biosynthesis; glutathione metabolism; alanine, aspartate, and glutamate metabolism; beta-alanine metabolism; and histidine metabolism. Among these metabolic pathways, alanine, aspartate, and glutamate metabolism was shared by the heart, blood, and kidney. Succinic acid was found to be the key regulatory metabolite in cardiorenal metabolic communication.

CONCLUSION

Six metabolic pathways were found to be involved in cardiorenal metabolic communication in an adriamycin-induced nephropathy model, in which alanine, aspartate, and glutamate metabolism may be the metabolic link between the heart and kidney in the development and maintenance of oxidative stress and inflammation. Succinic acid may serve as a key regulatory metabolic switch or marker of cardiac and renal co-injury, as shown in an adriamycin-induced nephropathy model.

Sperm Methylome Profiling Can Discern Fertility Levels in the Porcine Biomedical Model

A combined Genotyping By Sequencing (GBS) and methylated DNA immunoprecipitation (MeDIP) protocol was used to identify—in parallel—genetic variation (Genomic-Wide Association Studies (GWAS) and epigenetic differences of Differentially Methylated Regions (DMR) in the genome of spermatozoa from the porcine animal model. Breeding boars with good semen quality (n = 11) and specific and well-documented differences in fertility (farrowing rate, FR) and prolificacy (litter size, LS) (n = 7) in artificial insemination programs, using combined FR and LS, were categorized as High Fertile (HF, n = 4) or Low Fertile (LF, n = 3), and boars with Unknown Fertility (UF, n = 4) were tested for eventual epigenetical similarity with those fertility-proven. We identified 165,944 Single Nucleotide Polymorphisms (SNPs) that explained 14–15% of variance among selection lines. Between HF and LF individuals (n = 7, 4 HF and 3 LF), we identified 169 SNPs with p ≤ 0.00015, which explained 58% of the variance. For the epigenetic analyses, we considered fertility and period of ejaculate collection (late-summer and mid-autumn). Approximately three times more DMRs were observed in HF than in LF boars across these periods. Interestingly, UF boars were clearly clustered with one of the other HF or LF groups. The highest differences in DMRs between HF and LF experimental groups across the pig genome were located in the chr 3, 9, 13, and 16, with most DMRs being hypermethylated in LF boars. In both HF and LF boars, DMRs were mostly hypermethylated in late-summer compared to mid-autumn. Three overlaps were detected between SNPs (p ≤ 0.0005, n = 1318) and CpG sites within DMRs. In conclusion, fertility levels in breeding males including FR and LS can be discerned using methylome analyses. The findings in this biomedical animal model ought to be applied besides sire selection for andrological diagnosis of idiopathic sub/infertility.