Transcriptome analyses in infertile men reveal germ cell-specific expression and splicing patterns

The process of spermatogenesis-when germ cells differentiate into sperm-is tightly regulated, and misregulation in gene expression is likely to be involved in the physiopathology of male infertility. The testis is one of the most transcriptionally rich tissues; nevertheless, the specific gene expression changes occurring during spermatogenesis are not fully understood. To better understand gene expression during spermatogenesis, we generated germ cell-specific whole transcriptome profiles by systematically comparing testicular transcriptomes from tissues in which spermatogenesis is arrested at successive steps of germ cell differentiation. In these comparisons, we found thousands of differentially expressed genes between successive germ cell types of infertility patients. We demonstrate our analyses' potential to identify novel highly germ cell-specific markers (TSPY4 and LUZP4 for spermatogonia; HMGB4 for round spermatids) and identified putatively misregulated genes in male infertility (RWDD2A, CCDC183, CNNM1, SERF1B). Apart from these, we found thousands of genes showing germ cell-specific isoforms (including SOX15, SPATA4, SYCP3, MKI67). Our approach and dataset can help elucidate genetic and transcriptional causes for male infertility.

O-248 Cluster Analysis of men with idiopathic and unexplained male infertility identifies FSHB Genotype as relevant diagnostic parameter

Study question

In a cohort of idiopathic and unexplained infertile men we aimed to identify subgroups with similar characteristics, and therewith underlying etiologic factors, by clustering approach.

Summary answer

We identified two distinct patient clusters. Across all diverse phenotypes of infertility, the strongest segregation markers were FSHB c.-211G>T, FSH, and bi-testicular volume.

What is known already

In about 30-75% of infertile men no major causative factors can be identified; leading to the diagnose of unexplained (normozoospermia) or idiopathic (abnormal semen parameters) male infertility. This cohort of men remains very heterogenous, albeit the detailed andrological characterization that is currently applied in infertility workup.

New analysis tools such as machine learning and cluster analysis can provide a more in-depth approach. Such explorative analyses have the potential to uncover hitherto hidden patterns in data that might be difficult to spot for andrologists but become visible by these tools.

Study design, size, duration

A Cluster analysis was retrospectively performed in a clinically well characterized cohort of 2742 men with unexplained or idiopathic male infertility. These men had visited our Centre within a 10-year period (2008-2018) for infertility workup. Due to the well curated database (Androbase®) we were able to include up to 37 andrologic parameters in the unbiased cluster analysis.

Participants/materials, setting, methods

After applying strict selection criteria 2742, of initially 7627, infertile men remained for cluster analysis (exclusion: obstructive -, genetic -, other causative factors, female factor; inclusion: azoo- to normozoospermia, FSH ≥ 1IU/l, Testosterone ≥ 8nmol/l). For subsequent analyses the following parameters were included: somatic/semen/hormone parameters, testicular sonography and testis volume, genotyping of the FSHB c.-211G>T (rs10835638) single nucleotide polymorphism. For cluster analysis, partitioning around medoids method was employed based on Gower distance between patients.

Main results and the role of chance

The applied cluster approach for the study population yielded two separate clusters (average silhouette width ∼0.12). These clusters showed significantly different distributions in bi-testicular volume, FSH and FSHB genotype. Cluster 1 contained all men homozygous for G (wildtype) in FSHB c.-211G>T (100%), while Cluster 2 contained most patients carrying a T allele (>96.6%). Even in subgroup analysis (Total sperm count (TSC) <1Mill and TSC 1³Mill) two clusters each were formed too. Again, the strongest segregation markers between the respective clusters were FSHB c.-211G>T, bitesticular volume, and FSH, supporting the notion of a contributing genetic factor.

Surprisingly, sperm parameters like TSC, motility and morphology played a minor role in cluster formation; as well as testicular maldescent, varicocele, smoking, and microlithiasis testes.

The genetic parameter of FSHB c.-211G>T in combination with the established parameters FSH and testicular volume should attract more attention in future clinical workups of infertile men with unknown etiologic factors.

Limitations, reasons for caution

Categorical and numeric features contribute diversely to the calculation of patient dissimilarity. Potentially, categorical features can have a higher impact because patients are rated as completely different if they fall in different categories; for numeric features, the dissimilarity depends on the range of values.

Wider implications of the findings

The FSHB SNP was identified as an informative segregation marker; we therefore suggest introducing diagnostic genotyping into clinical routine in men with so far idiopathic or unexplained male infertility. This may reduce the high number of infertile men with so far unknown origin by nearly one-third.

Trial registration number

DFG Clinical Research Unit 326 Male Germ Cells

Machine learning based prediction models in male reproductive health: Development of a proof-of-concept model for Klinefelter Syndrome in azoospermic patients

BACKGROUND

Due to the highly variable clinical phenotype, Klinefelter Syndrome is underdiagnosed.

OBJECTIVE

Assessment of supervised machine learning based prediction models for identification of Klinefelter Syndrome among azoospermic patients, and comparison to expert clinical evaluation.

MATERIALS AND METHODS

Retrospective patient data (karyotype, age, height, weight, testis volume, follicle-stimulating hormone, luteinizing hormone, testosterone, estradiol, prolactin, semen pH and semen volume) collected between January 2005 and June 2019 were retrieved from a patient data bank of a University Centre. Models were trained, validated and benchmarked based on different supervised machine learning algorithms. Models were then tested on an independent, prospectively acquired set of patient data (between July 2019 and July 2020). Benchmarking against physicians was performed in addition.

RESULTS

Based on average performance, support vector machines and CatBoost were particularly well-suited models, with 100% sensitivity and >93% specificity on the test dataset. Compared to a group of 18 expert clinicians, the machine learning models had significantly better median sensitivity (100% vs. 87.5%, p = 0.0455) and fared comparably with regards to specificity (90% vs. 89.9%, p = 0.4795), thereby possibly improving diagnosis rate. A Klinefelter Syndrome Score Calculator based on the prediction models is available on http://klinefelter-score-calculator.uni-muenster.de.

DISCUSSION

Differentiating Klinefelter Syndrome patients from azoospermic patients with normal karyotype (46,XY) is a problem that can be solved with supervised machine learning techniques, improving patient care.

CONCLUSIONS

Machine learning could improve the diagnostic rate of Klinefelter Syndrome among azoospermic patients, even more for less-experienced physicians.

FSHB Genotype Identified as a Relevant Diagnostic Parameter Revealed by Cluster Analysis of Men With Idiopathic Infertility

Introduction and Objectives

About 30-75% of infertile men are diagnosed with idiopathic infertility, thereby lacking major causative factors to explain their impaired fertility status. In this study, we used a large cohort of idiopathic infertile men to determine whether subgroups could be identified by an unbiased clustering approach and whether underlying etiologic factors could be delineated.

Patients and Methods

From our in-house database Androbase®, we retrospectively selected patients (from 2008 to 2018) with idiopathic male infertility (azoo- to normozoospermia) who fit the following selection criteria: FSH ≥ 1 IU/l, testosterone ≥ 8 nmol/l, ejaculate volume ≥ 1.5 ml. Patients with genetic abnormalities or partners with female factors were excluded.For the identified study population (n=2742), we used common andrologic features (somatic, semen and hormonal parameters, including the FSHB c.-211G>T (rs10835638) single nucleotide polymorphism) for subsequent analyses. Cluster analyses were performed for the entire study population and for two sub-cohorts, which were separated by total sperm count (TSC) thresholds: Cohort A (TSC ≥ 1 mill/ejac; n=2422) and Cohort B (TSC < 1 mill/ejac; n=320). For clustering, the partitioning around medoids method was employed, and the quality was evaluated by average silhouette width.

Results

The applied cluster approach for the whole study population yielded two separate clusters, which showed significantly different distributions in bi-testicular volume, FSH and FSHB genotype. Cluster 1 contained all men homozygous for G (wildtype) in FSHB c.-211G>T (100%), while Cluster 2 contained most patients carrying a T allele (>96.6%). In the analyses of sub-cohorts A/B, two clusters each were formed too. Again, the strongest segregation markers between the respective clusters were bi-testicular volume, FSH and FSHB c.-211G>T.

Conclusion

With this first unbiased approach for revealing putative subgroups within a heterogenous group of idiopathic infertile men, we did indeed identify distinct patient clusters. Surprisingly, across all diverse phenotypes of infertility, the strongest segregation markers were FSHB c.-211G>T, FSH, and bi-testicular volume. Further, Cohorts A and B were significantly separated by FSHB genotype (wildtype vs. T-allele carriers), which supports the notion of a contributing genetic factor. Consequently, FSHB genotyping should be implemented as diagnostic routine in patients with idiopathic infertility.

The Male Fertility Gene Atlas: a web tool for collecting and integrating OMICS data in the context of male infertility

STUDY QUESTION

How can one design and implement a system that provides a comprehensive overview of research results in the field of epi-/genetics of male infertility and germ cells?

SUMMARY ANSWER

Working at the interface of literature search engines and raw data repositories, the newly developed Male Fertility Gene Atlas (MFGA) provides a system that can represent aggregated results from scientific publications in a standardized way and perform advanced searches, for example based on the conditions (phenotypes) and genes related to male infertility.

WHAT IS KNOWN ALREADY

PubMed and Google Scholar are established search engines for research literature. Additionally, repositories like Gene Expression Omnibus and Sequence Read Archive provide access to raw data. Selected processed data can be accessed by visualization tools like the ReproGenomics Viewer.

STUDY DESIGN, SIZE, DURATION

The MFGA was developed in a time frame of 18 months under a rapid prototyping approach.

PARTICIPANTS/MATERIALS, SETTING, METHODS

In the context of the Clinical Research Unit 'Male Germ Cells' (CRU326), a group of around 50 domain experts in the fields of male infertility and germ cells helped to develop the requirements engineering and feedback loops. They provided a set of 39 representative and heterogeneous publications to establish a basis for the system requirements.

MAIN RESULTS AND THE ROLE OF CHANCE

The MFGA is freely available online at https://mfga.uni-muenster.de. To date, it contains 115 data sets corresponding to 54 manually curated publications and provides an advanced search function based on study conditions, meta-information and genes, whereby it returns the publications' exact tables and figures that fit the search request as well as a list of the most frequently investigated genes in the result set. Currently, study data for 31 different tissue types, 32 different cell types and 20 conditions are available. Also, ∼8000 and ∼1000 distinct genes have been found to be mentioned in at least 10 and 15 of the publications, respectively.

LARGE SCALE DATA

Not applicable because no novel data were produced.

LIMITATIONS, REASONS FOR CAUTION

For the most part, the content of the system currently includes the selected publications from the development process. However, a structured process for the prospective literature search and inclusion into the MFGA has been defined and is currently implemented.

WIDER IMPLICATIONS OF THE FINDINGS

The technical implementation of the MFGA allows for accommodating a wide range of heterogeneous data from aggregated research results. This implementation can be transferred to other diseases to establish comparable systems and generally support research in the medical field.

STUDY FUNDING/COMPETING INTEREST(S)

This work was carried out within the frame of the German Research Foundation (DFG) Clinical Research Unit 'Male Germ Cells: from Genes to Function' (CRU326). The authors declare no conflicts of interest.

Bi-allelic Mutations in M1AP Are a Frequent Cause of Meiotic Arrest and Severely Impaired Spermatogenesis Leading to Male Infertility

Male infertility affects ∼7% of men, but its causes remain poorly understood. The most severe form is non-obstructive azoospermia (NOA), which is, in part, caused by an arrest at meiosis. So far, only a few validated disease-associated genes have been reported. To address this gap, we performed whole-exome sequencing in 58 men with unexplained meiotic arrest and identified the same homozygous frameshift variant c.676dup (p.Trp226LeufsTer4) in M1AP, encoding meiosis 1 associated protein, in three unrelated men. This variant most likely results in a truncated protein as shown in vitro by heterologous expression of mutant M1AP. Next, we screened four large cohorts of infertile men and identified three additional individuals carrying homozygous c.676dup and three carrying combinations of this and other likely causal variants in M1AP. Moreover, a homozygous missense variant, c.1166C>T (p.Pro389Leu), segregated with infertility in five men from a consanguineous Turkish family. The common phenotype between all affected men was NOA, but occasionally spermatids and rarely a few spermatozoa in the semen were observed. A similar phenotype has been described for mice with disruption of M1ap. Collectively, these findings demonstrate that mutations in M1AP are a relatively frequent cause of autosomal recessive severe spermatogenic failure and male infertility with strong clinical validity.

The Ca2+ channel CatSper is not activated by cAMP/PKA signaling but directly affected by chemicals used to probe the action of cAMP and PKA

The sperm-specific Ca²⁺ channel CatSper (cation channel of sperm) controls the influx of Ca²⁺ into the flagellum and, thereby, the swimming behavior of sperm. A hallmark of human CatSper is its polymodal activation by membrane voltage, intracellular pH, and oviductal hormones. Whether CatSper is also activated by signaling pathways involving an increase of cAMP and ensuing activation of PKA is, however, a matter of controversy. To shed light on this question, we used kinetic ion-sensitive fluorometry, patch-clamp recordings, and optochemistry to study transmembrane Ca²⁺ flux and membrane currents in human sperm from healthy donors and from patients that lack functional CatSper channels. We found that human CatSper is neither activated by intracellular cAMP directly nor indirectly by the cAMP/PKA-signaling pathway. Instead, we show that nonphysiological concentrations of cAMP and membrane-permeable cAMP analogs used to mimic the action of intracellular cAMP activate human CatSper from the outside via a hitherto-unknown extracellular binding site. Finally, we demonstrate that the effects of common PKA inhibitors on human CatSper rest predominantly, if not exclusively, on off-target drug actions on CatSper itself rather than on inhibition of PKA. We conclude that the concept of an intracellular cAMP/PKA-activation of CatSper is primarily based on unspecific effects of chemical probes used to interfere with cAMP signaling. Altogether, our findings solve several controversial issues and reveal a novel ligand-binding site controlling the activity of CatSper, which has important bearings on future studies of cAMP and Ca²⁺ signaling in sperm.

Does the FSHB c.-211G>T polymorphism impact Sertoli cell number and the spermatogenic potential in infertile patients?

BACKGROUND

A genetic variant within the FSHB gene can deviate FSH action on spermatogenesis. The c.-211G>T FSHB single nucleotide polymorphism impacts FSHB transcription and biosynthesis due to interference with the LHX3 transcription factor binding. This SNP was previously shown to be strongly associated with lowered testicular volume, reduced sperm counts, and decreased FSH levels in patients carrying one or two T-alleles.

OBJECTIVE

To determine the impact of the SNP FSHB c.-211G>T on Sertoli cell (SC) number, Sertoli cell workload (SCWL) and thereby spermatogenic potential.

MATERIAL AND METHODS

Testicular biopsies of 31 azoospermic, homozygous T patients (26 non-obstructive azoospermia (NOA), and five obstructive azoospermia (OA)) were matched to patients with GG genotype. Marker proteins for SC (SOX9), spermatogonia (MAGE A4), and round spermatids (CREM) were used for semi-automatical quantification by immunofluorescence. SCWL (number of germ cells served by one SC) was determined and an unbiased clustering on the patient groups performed.

RESULTS

Quantification of SC number in NOA patients did not yield significant differences when stratified by FSHB genotype. SC numbers are also not significantly different between FSHB genotypes for the OA patient group and between NOA and OA groups. SCWL in the NOA patient cohort is significantly reduced when compared to the OA control patients; however, in neither group an effect of the genotype could be observed. The cluster analysis of the whole study cohort yielded two groups only, namely NOA and OA, and no clustering according to the FSHB genotype.

DISCUSSION AND CONCLUSION

The FSHB c.-211G>T polymorphism does not affect SC numbers or SCWL, thereby in principle maintaining the spermatogenic potential. The previously observed clinical phenotype for the FSHB genotype might therefore be caused by a hypo-stimulated spermatogenesis and not due to a decreased SC number.

De Novo Mutations in FOXJ1 Result in a Motile Ciliopathy with Hydrocephalus and Randomization of Left/Right Body Asymmetry

Hydrocephalus is one of the most prevalent form of developmental central nervous system (CNS) malformations. Cerebrospinal fluid (CSF) flow depends on both heartbeat and body movement. Furthermore, it has been shown that CSF flow within and across brain ventricles depends on cilia motility of the ependymal cells lining the brain ventricles, which play a crucial role to maintain patency of the narrow sites of CSF passage during brain formation in mice. Using whole-exome and whole-genome sequencing, we identified an autosomal-dominant cause of a distinct motile ciliopathy related to defective ciliogenesis of the ependymal cilia in six individuals. Heterozygous de novo mutations in FOXJ1, which encodes a well-known member of the forkhead transcription factors important for ciliogenesis of motile cilia, cause a motile ciliopathy that is characterized by hydrocephalus internus, chronic destructive airway disease, and randomization of left/right body asymmetry. Mutant respiratory epithelial cells are unable to generate a fluid flow and exhibit a reduced number of cilia per cell, as documented by high-speed video microscopy (HVMA), transmission electron microscopy (TEM), and immunofluorescence analysis (IF). TEM and IF demonstrate mislocalized basal bodies. In line with this finding, the focal adhesion protein PTK2 displays aberrant localization in the cytoplasm of the mutant respiratory epithelial cells.

Surface and intracardiac ECG for discriminating conduction disorders after CoreValve implantation

Background

Transcatheter aortic valve implantation (TAVI) has been developed to minimize operative morbidity and mortality in high-risk symptomatic patients unfit for open surgery. With the proximity of the aortic valve annulus to the conduction system there is, however, an unknown risk of conduction disturbances necessitating monitoring and often cardiac pacing.

Materials and methods

We enrolled 50 consecutive patients from January 2007 to 2008 in our prospective evaluation of conduction disturbances measured by surface and intracardiac ECG recordings. Baseline parameters, procedural characteristics as well as twelve-lead surface ECG and intracardiac conduction times were revealed pre-interventionally, after TAVI and at 7-day follow-up.

Results

TAVI was performed successfully in all patients. During 7 days of follow-up the rate for first-degree AV block raised from 14% at baseline to 44% at day 7 (p < 0.001), while rates for type II second- and third-degree were 0 versus 8% (p < 0.001) and 0 versus 12% (p < 0.001), respectively. Similarly, the prevalence of new left bundle branch block (LBBB) rose from 2 to 54% (p < 0.001). Intracardiac measurements revealed a prolongation of both AH and HV interval from 123.7 ± 41.6 to 136.6 ± 40.5 ms (p < 0.001) and from 54.8 ± 11.7 to 71.4 ± 20.0 ms (p < 0.001), respectively. Pacemaker implantation at a mean follow-up of 4.8 ± 1.2 days was subsequently performed in 23 patients (46%) due to complete AV block (12%) and type II second-degree AV block (8%) while another 13 patients (26%) received a pacemaker for the combination of new LBBB with marked HV prolongation. The high rate of first-degree AV block was primarily driven by an increase in HV interval.

Conclusion

Cardiac conduction disturbances were common in the early experience with CoreValve implantation necessitating close surveillance for at least 1 week.

Biofragmentable anastomosis ring for laparoscopic bowel surgery

Laparoscopic surgery is now being applied for colonic resection, and one of the key challenges is fashioning a sound anastomosis. The biofragmentable anastomosis ring, a modern version of the Murphy Button, has been utilized in a series of experiments to develop and evaluate laparoscopic anatomotic techniques. A series of purpose-built devices were used to fashion left and right simulated colectomies as well as for a variety of other anastomoses. Survival animal experiments were performed and demonstrate the feasibility of this technique.