Can semen parameters predict pregnancy outcomes?

A 2-step remote TUNEL approach for sperm DNA fragmentation assessment. Analysis in donors and patients

OBJECTIVES

Infertility is a disease of the male or female reproductive systems. Male reproductive workup is based on routine semen analysis, although of limited value. The 2021 WHO Manual incorporated Sperm DNA Fragmentation (SDF) assessment, and highlighted the need for individual laboratories to define suitable thresholds. This study aimed to present an alternative to address this issue, determine an SDF cut-off value with fertile donors, and characterize SDF in a patient cohort and their relationship with semen parameters.

STUDY DESIGN

A service unit was established to remotely perform TUNEL assay in a 2 step-process. Semen samples were received at andrology laboratories, subjected to routine semen analysis (WHO, 2010), partially processed and transported to the service unit for SDF evaluation. Using this setting, studies were done in fertile donors (n = 15) to define the cut-off value, and in men undergoing infertility workup (n = 318).

RESULTS

A cut-off value of 9.17 % was determined with the fertile donor cohort. With this cut-off, a 64.46 % abnormal SDF incidence was determined in the patient cohort. SDF negatively correlated with sperm number, vitality and motility, and positively with abnormal morphology and male age (P < 0.05). TUNEL-positive cases depicted lower sperm quality and higher male age (P < 0.05). A similar abnormal SDF incidence was determined among patients with semen abnormalities. Asthenozoospermic and ≥40 years patient samples depicted higher (P < 0.05) SDF than those of the general population. SDF incidence was also high in normozoospermic patients.

CONCLUSIONS

Using a 2-step remote approach with a standardized procedure and an SDF cut-off value established with fertile donors, high SDF incidence in semen samples depicting normal and abnormal quality were identified in men consulting for infertility, highlighting the relevance of its evaluation as part of the male fertility workup.

Application of Flow Cytometry Using Advanced Chromatin Analyses for Assessing Changes in Sperm Structure and DNA Integrity in a Porcine Model

Chromatin status is critical for sperm fertility and reflects spermatogenic success. We tested a multivariate approach for studying pig sperm chromatin structure to capture its complexity with a set of quick and simple techniques, going beyond the usual assessment of DNA damage. Sperm doses from 36 boars (3 ejaculates/boar) were stored at 17 °C and analyzed on days 0 and 11. Analyses were: CASA (motility) and flow cytometry to assess sperm functionality and chromatin structure by SCSA (%DFI, DNA fragmentation; %HDS, chromatin maturity), monobromobimane (mBBr, tiol status/disulfide bridges between protamines), chromomycin A3 (CMA3, protamination), and 8-hydroxy-2'-deoxyguanosine (8-oxo-dG, DNA oxidative damage). Data were analyzed using linear models for the effects of boar and storage, correlations, and multivariate analysis as hierarchical clustering and principal component analysis (PCA). Storage reduced sperm quality parameters, mainly motility, with no critical oxidative stress increases, while chromatin status worsened slightly (%DFI and 8-oxo-dG increased while mBBr MFI-median fluorescence intensity-and disulfide bridge levels decreased). Boar significantly affected most chromatin variables except CMA3; storage also affected most variables except %HDS. At day 0, sperm chromatin variables clustered closely, except for CMA3, and %HDS and 8-oxo-dG correlated with many variables (notably, mBBr). After storage, the relation between %HDS and 8-oxo-dG remained, but correlations among other variables disappeared, and mBBr variables clustered separately. The PCA suggested a considerable influence of mBBr on sample variance, especially regarding storage, with SCSA and 8-oxo-dG affecting between-sample variability. Overall, CMA3 was the least informative, in contrast with results in other species. The combination of DNA fragmentation, DNA oxidation, chromatin compaction, and tiol status seems a good candidate for obtaining a complete picture of pig sperm nucleus status. It raises many questions for future molecular studies and deserves further research to establish its usefulness as a fertility predictor in multivariate models. The usefulness of CMA3 should be clarified.

Gaussian clustering and quantification of the sperm chromatin dispersion test using convolutional neural networks

Sperm DNA fragmentation is a sign of sperm nuclear damage. The sperm chromatin dispersion (SCD) test is a reliable and economical method for the evaluation of DNA fragmentation. However, the cut-off value for differentiation of DNA fragmented sperms is fixed at 1/3 with limited statistical justification, making the SCD test a semi-quantitative method that gives user-dependent results. We construct a collection of deep neural networks to automate the evaluation of bright-field images for SCD tests. The model can detect valid sperm nuclei and their locations from the input images captured with a 20× objective and predict the geometric parameters of the halo ring. We construct an annotated dataset consisting of N = 3120 images. The ResNet 18 based network reaches an average precision (AP50) of 91.3%, a true positive rate of 96.67%, and a true negative rate of 96.72%. The distribution of relative halo radii is fit to the multi-peak Gaussian function (p > 0.99). DNA fragmentation is regarded as those with a relative halo radius 1.6 standard deviations smaller than the mean of a normal cluster. In conclusion, we have established a deep neural network based model for the automation and quantification of the SCD test that is ready for clinical application. The DNA fragmentation index is determined using Gaussian clustering, reflecting the natural distribution of halo geometry and is more tolerable to disturbances and sample conditions, which we believe will greatly improve the clinical significance of the SCD test.

Development of a biomolecular approach to identify sperm functions and fertility using sperm RNAs

Infertility affects a significant percentage of couples worldwide, and male factors contribute significantly to this problem. Traditional assessments of male fertility rely primarily on parameters such as sperm motility, morphology, viability, and concentration. However, these metrics often do not provide a comprehensive understanding of sperm function, which is critical not only for fertilization but also for successful embryo development. Herein, we used porcine spermatozoa as a model to investigate the potential of sperm RNA markers in assessing various aspects of sperm function from motility to fertility. Using artificial insemination, we evaluated male fertility based on the litter size of sows inseminated with sperm from 20 boars. In addition, we measured parameters such as weaning rate, death births, live births, and mummy births. Sperm functional parameters, including motility and kinematics, were assessed before and after in vitro capacitation. Finally, correlations between various sperm functional parameters and sperm RNA markers were explored. Our results revealed interesting relationships between sperm functional parameters. While motility and kinematics were correlated, they were not correlated with sperm capacitation status. Surprisingly, no significant correlations were found between these parameters and male fertility. However, specific parameters of sperm capacitation status after in vitro capacitation were correlated with weaning rate and live births, highlighting their importance in predicting successful fertilization. Further analysis of sperm RNA markers identified genes related to male fertility, including IZUMO1, known for its role in sperm-egg fusion. These genes showed correlations with motility, capacitation, and fertilization parameters, shedding light on their potential roles in sperm function. In conclusion, our study demonstrates that sperm RNA markers hold promise for the diagnosis and prognosis of various aspects of sperm function, providing valuable insights into male infertility. These markers may serve as diagnostic tools to improve our understanding of male fertility problems, ultimately benefiting couples struggling with infertility.

Sperm Concentration Improvement May Be a Parameter Predicting Efficacy of FSH Therapy of Male Idiopathic Infertility

Testis stimulation with follicle-stimulating hormone (FSH) is one of the empirical treatments proposed for male idiopathic infertility, although reliable markers to predict its efficacy are still lacking. This study aimed to identify parameters able to predict FSH efficacy in terms of pregnancy achievement. A real-world study was conducted, enrolling idiopathic infertile men treated with FSH 150IU three times weekly. Patients were treated until pregnancy achievement or for a maximum of two years and two visits were considered: V0 (baseline) and V1 (end of FSH treatment). Primary endpoints were the V1-V0 percentage change in sperm concentration, total sperm count, and total motile sperm number. In total, 48 pregnancies were recorded (27.7%) among 173 men (age 37.9 ± 6.2 years). All three endpoints increased after FSH administration, and only the V1-V0 percentage of sperm concentration significantly predicted pregnancy (p = 0.007). A V1-V0 sperm concentration of 30.8% predicted pregnancy, and the sperm concentration V1-V0 percentage (Y) required to obtain a pregnancy was predicted according to its baseline values (x): Y = 9.8433x2 - 203.67x + 958.29. A higher number of pregnancies was reached in men with baseline sperm concentration below 7.3 million/mL. Thus, the percentage of sperm concentration increasing after FSH administration could predict the treatment efficacy in terms of pregnancy. At the dosage used, the efficacy was significantly higher in patients with a starting sperm concentration < 7.3 mill/mL. Mathematical analyses identified a function able to predict the sperm concentration increase required to obtain a pregnancy in relation to the baseline sperm number.