Predictive value of postwashed total progressively motile sperm count using CASA estimates in 6871 non-donor intrauterine insemination cycles

The Influence of Lifestyle on Male Fertility in the Context of Insulin Resistance-Identification of Factors That Influence Semen Quality

Background: Male fertility is known to have been negatively influenced by the progress of civilization. Another condition whose incidence has been on the increase for the same reason is insulin resistance (IR). In addition, men increasingly often resign from the pursuit of active forms of leisure, preferring more sedentary ones. Considering these trends, this aim of this study was to investigate the relationships between lifestyle factors, insulin resistance, and male fertility in men with and without the condition. A further aim was to select those lifestyle factors that would make it possible to predict the level of male fertility, especially when IR is concerned. Methods: This study was performed in a group of 73 participants, divided into groups based on their insulin resistance status. Their physical activity, diet, perceived stress, sleep quality, libido level, and duration of sexual abstinence were assessed on the basis of a number of parameters, including indices proposed by the authors. In addition, relevant anthropometric measurements were taken and tests related to glucose metabolism and semen quality were carried out. On the basis of these data, statistical tests were performed to establish or disprove relationships between lifestyle choices and semen quality, as measured my sperm motility. Results: The results of this study highlighted the associations between a number of parameters, i.e., micronutrient and vitamin intake, diet quality, body composition, insulin resistance, and the duration of sexual abstinence, and semen quality, as measured by sperm motility. Significantly, the presence or absence of IR was linked to male fertility. A multivariate model was developed, incorporating parameters such as the Matsuda index, vitamin intake, and sexual abstinence duration, to predict motility scores. Conclusions: This study underscores the negative impact of modern civilization's lifestyle choices on male fertility. Notably, vitamin and mineral consumption, especially from antioxidant-rich diets like the Mediterranean diet, emerged as key modifiable factors affecting fertility. Routine diagnostics for insulin resistance in fertility-related interventions is recommended. This study also highlights the importance of considering sexual abstinence duration during semen collection for accurate diagnostic results. Future research should focus on validating the proposed multivariate model and exploring the effects of lifestyle modifications, particularly vitamin supplementation, on fertility outcomes in men, especially in the context of IR.

Can semen parameters predict pregnancy outcomes?

Semen analysis is an integral component of the evaluation and management of men with infertility. Although it is important for patient counseling and clinical decision making, a conventional semen analysis cannot reliably predict the chance of pregnancy or differentiate fertile vs. infertile men (except in the most extreme cases). Advanced, nonstandard sperm functional tests may provide additional discriminatory and prognostic power; however, further research is needed to determine how to best incorporate these tests into modern clinical practice. Therefore, the primary applications of a conventional semen analysis should be to judge the severity of infertility, estimate the effects of future therapy, and measure the response to current therapy.

Advances in non-hormonal male contraception targeting sperm motility

BACKGROUND

The high rates of unintended pregnancy and the ever-growing world population impose health, economic, social, and environmental threats to countries. Expanding contraceptive options, including male methods, are urgently needed to tackle these global challenges. Male contraception is limited to condoms and vasectomy, which are unsuitable for many couples. Thus, novel male contraceptive methods may reduce unintended pregnancies, meet the contraceptive needs of couples, and foster gender equality in carrying the contraceptive burden. In this regard, the spermatozoon emerges as a source of druggable targets for on-demand, non-hormonal male contraception based on disrupting sperm motility or fertilization.

OBJECTIVE AND RATIONALE

A better understanding of the molecules governing sperm motility can lead to innovative approaches toward safe and effective male contraceptives. This review discusses cutting-edge knowledge on sperm-specific targets for male contraception, focusing on those with crucial roles in sperm motility. We also highlight challenges and opportunities in male contraceptive drug development targeting spermatozoa.

SEARCH METHODS

We conducted a literature search in the PubMed database using the following keywords: 'spermatozoa', 'sperm motility', 'male contraception', and 'drug targets' in combination with other related terms to the field. Publications until January 2023 written in English were considered.

OUTCOMES

Efforts for developing non-hormonal strategies for male contraception resulted in the identification of candidates specifically expressed or enriched in spermatozoa, including enzymes (PP1γ2, GAPDHS, and sAC), ion channels (CatSper and KSper), transmembrane transporters (sNHE, SLC26A8, and ATP1A4), and surface proteins (EPPIN). These targets are usually located in the sperm flagellum. Their indispensable roles in sperm motility and male fertility were confirmed by genetic or immunological approaches using animal models and gene mutations associated with male infertility due to sperm defects in humans. Their druggability was demonstrated by the identification of drug-like small organic ligands displaying spermiostatic activity in preclinical trials.

WIDER IMPLICATIONS

A wide range of sperm-associated proteins has arisen as key regulators of sperm motility, providing compelling druggable candidates for male contraception. Nevertheless, no pharmacological agent has reached clinical developmental stages. One reason is the slow progress in translating the preclinical and drug discovery findings into a drug-like candidate adequate for clinical development. Thus, intense collaboration among academia, private sectors, governments, and regulatory agencies will be crucial to combine expertise for the development of male contraceptives targeting sperm function by (i) improving target structural characterization and the design of highly selective ligands, (ii) conducting long-term preclinical safety, efficacy, and reversibility evaluation, and (iii) establishing rigorous guidelines and endpoints for clinical trials and regulatory evaluation, thus allowing their testing in humans.

A comprehensive evaluation of pre- and post-processing sperm parameters for predicting successful pregnancy rate following intrauterine insemination with the husband's sperms

BACKGROUND

To determine the predictive values of sperm parameters pre- and post-processing by density gradient centrifugation for clinical pregnancy rates (CPRs) following artificial insemination by husband (AIH) in infertile Chinese couples.

METHODS

A total of 3,522 AIH cycles from 1,918 couples were retrospectively analyzed. The parameters were compared between the pregnant and non-pregnant groups and further between different etiological groups (Male-factor, Both-male-and-female-factor, and Other-factor). Multivariate logistic regression analysis was performed to create models for predicting the CPRs of each etiological group.

RESULTS

The overall CPR was 13.3%. There were significant improvements for most sperm parameters after DGC. Multivariate logistic regression analysis indicated that, in overall AIH cases, the top parameters significantly influencing the CPR of AIH were pre-STR (OR = 1.037; P = 0.048) and post-VSL (OR = 1.036; P = 0.011). In the Male-factor Group, the top influencing parameters were pre-VCL (OR = 2.096; P = 0.008), pre-LIN (OR = 1.930; P = 0.002) and post-VSL (OR = 1.316; P = 0.023). In the Both-factor Group, the top influencing parameters were pre-VCL (OR = 1.451; P = 0.008) and post-motility (OR = 1.218; P = 0.049). In the Other-factor Group, the top influencing parameters were pre-VAP (OR = 1.715; P = 0.024), pre-STR (OR = 1.20; P = 0.011) and post-VSL (OR = 1.04; P = 0.017). Moreover, receiver operating characteristic analysis showed that the logistic regression models of the Male- and Both-factor Groups had greater powers for prognostic classification than those of other groups.

CONCLUSIONS

This study demonstrated that some sperm parameters have a collinearity relationship in predicting the CPR following AIH. Moreover, the predictive capacity of a multivariate logistic regression model is better than those of individual parameters, especially for the Male- and Both-factor Groups. In these cases, pre-VCL is the common top influencing factor.

Evaluation of Prognostic Factors for Clinical Pregnancy Rate Following Artificial Insemination by Husband in the Chinese Population

Background: To determine the independent prognostic factors and develop a multivariate logistic regression model for predicting successful pregnancy following artificial insemination by husband (AIH) in infertile Chinese couples.

Methods: A total of 3,015 AIH cycles with superovulation from 1,853 infertile Chinese couples were retrospectively analyzed. The clinical characteristics and sperm parameters were compared between the pregnant and non-pregnant groups. Multivariate logistic regression analysis was performed to remove the confounding factors and create an equation to predict the successful pregnancy. Receiver operating characteristic (ROC) curves were constructed for evaluating the abilities for prognostic classification of the independent predictors and the equation.

Results: The overall pregnancy rate was 13.0%. The pregnancy rate of double intrauterine insemination (IUI) (18.9%) was significantly higher than that of single IUI (11.4%). The pregnancy rate of the stimulated cycle (14.4%) was significantly higher than that of the natural cycle (9.0%). The pregnancy rates of the age groups <40 years are ~3 times higher than that of the ≥40 years age group. Among sperm parameters, the influencing factors included straight-line velocity (VSL), sperm deformity index (SDI), and normal form rate (all P < 0.05). A multivariate logistic regression equation was created based on the above influencing factors. ROC analysis showed that the prognostic power of the equation is better than those of individual predictors.

Conclusion: Cycle treatment options, single/double IUI, female age, sperm VSL, SDI, and normal form rate could predict successful pregnancy following AIH in China. The multivariate logistic regression equation exhibited a greater value for prognostic classification than single predictors.

Clarifying the relationship between total motile sperm counts and intrauterine insemination pregnancy rates

OBJECTIVE

To study the relationship between postwash total motile sperm count (TMSC) and intrauterine insemination (IUI) outcomes.

DESIGN

Retrospective review SETTING: Large fertility clinic PATIENT(S): A total of 92,471 insemination cycles from 37,553 patients were included in this study.

INTERVENTION(S)

All stimulated clomiphene citrate, letrozole, and/or injectable gonadotropin IUI cycles performed at a single institution from 2002 through 2018 were reviewed. Generalized estimating equations (GEE) analysis was used to account for multiple cycles by individual patients and to adjust for female partner age, body mass index, and stimulation protocol.

MAIN OUTCOME MEASURE(S)

Successful clinical pregnancy was defined as ultrasound confirmation of an intrauterine gestational sac with fetal cardiac activity.

RESULT(S)

A total of 92,471 insemination cycles were available to evaluate the relationship between postwash TMSC and clinical pregnancy. Pregnancy rates were highest with TMSC of ≥9 × 10⁶ and declined gradually as TMSC decreased. Complete data for the adjusted GEE analysis were available for 62,758 cycles. Adjusted GEE analysis among cycles with TMSC of ≥9 × 10⁶ (n = 46,557) confirmed that TMSC in this range was unrelated to pregnancy. Conversely, TMSC was highly predictive of pregnancy (Wald χ² = 39.85) in adjusted GEE analysis among cycles with TMSC of <9 × 10⁶ (n = 16,201), with a statistically significant decline.

CONCLUSIONS

IUI pregnancy is optimized with TMSC of ≥9 × 10⁶, below which the rates gradually decline. Although rare, pregnancies were achieved with TMSC of <0.25 × 10⁶. Since the decline in pregnancy is gradual and continuous, there is no specific threshold above which IUI should be recommended. Rather, these more specific quantitative predictions can be used to provide personalized counseling and guide clinical decision making.

Comparison of two automated sperm analyzers using 2 different detection methods versus manual semen assessment

PURPOSE

The exploration of male infertility is mainly based on semen analysis, but its evaluation might be affected by the operator's competence and subjectivity. This led to the development of automated semen analyzing systems. Despite continuous improvement, the precision and correlation of these automated systems with manual sperm assessment performed strictly according to WHO guidelines remains variable in the literature, and their role in daily practice is debated.

METHODS

In this double blind prospective study, we compared the results provided by 2 automated systems based on different concepts (CASA and electro-optical signal) with manual sperm assessment. Sperm concentration, motility and morphology were performed simultaneously and independently by different operators, blinded to each other.

RESULTS

A total of 102 unselected men attending the andrology department for routine sperm analysis were included in the study. We found no significant difference between each automated method and manual assessment for all sperm parameters, except for sperm morphology assessment where the electro-optical system gave higher results and performed slightly poorer than CASA. Correlation was moderate to high between manual assessment and each automated methods for all sperm parameters, with randomly distributed differences.

CONCLUSIONS

Overall, these results show that both types of automated systems can be implemented in andrology laboratory for routine sperm analysis.

Prewash and postwash total progressively motile sperm counts have poor predictive value for clinical pregnancy after intrauterine insemination

OBJECTIVE

To evaluate the predictive value of the prewash and postwash total progressively motile sperm counts (TPMSC) on clinical pregnancy after intrauterine insemination (IUI) .

METHODS

A review of medical records of women undergoing 2064 IUI cycles in a university hospital between April 2010 and October 2018.

RESULTS

No pregnancies were seen when the prewash TPMSC was less than 9 million or the postwash TPMSC was less than 2 million. There was no correlation between TPMSC and clinical pregnancies. Further analysis was made in pregnancies after prewash TPMSC of 3-10 million and more than 10 million, and after postwash TPMSC of 10-100 million and more than 100 million. No correlation was found between TPMSC and clinical pregnancy in different strata of female age, infertility duration, type of infertility, type of IUI treatment, and the number of treatment cycles. A negative relationship was found for unstimulated IUI treatment and the number of treatment cycles. The prewash and postwash TPMSC showed no predictive value.

CONCLUSION

Prewash and postwash TPMSC have poor predictive value for clinical pregnancy in IUI. Cycles with a prewash TPMSC of 10-100 million or postwash TPMSC of 3-10 million could achieve acceptable pregnancy rates with IUI.

Current Insights and Latest Updates in Sperm Motility and Associated Applications in Assisted Reproduction

Spermatozoon is a motile cell with a special ability to travel through the woman’s reproductive tract and fertilize an oocyte. To reach and penetrate the oocyte, spermatozoa should possess progressive motility. Therefore, motility is an important parameter during both natural and assisted conception. The global trend of progressive reduction in the number and motility of healthy spermatozoa in the ejaculate is associated with increased risk of infertility. Therefore, developing approaches for maintaining or enhancing human sperm motility has been an important area of investigation. In this review we discuss the physiology of sperm, molecular pathways regulating sperm motility, risk factors affecting sperm motility, and the role of sperm motility in fertility outcomes. In addition, we discuss various pharmacological agents and biomolecules that can enhance sperm motility in vitro and in vivo conditions to improve assisted reproductive technology (ART) outcomes. This article opens dialogs to help toxicologists, clinicians, andrologists, and embryologists in understanding the mechanism of factors influencing sperm motility and various management strategies to improve treatment outcomes.

Improvement of Sperm Quality in Hyperviscous Semen following DNase I Treatment

Semen hyperviscosity impairs sperm motility and can lead to male infertility. This prospective study aimed at assessing the ability of exogenous DNase in improving sperm quality, taking into consideration that DNase has been found in the seminal plasma of several species and that neutrophils release chromatin in order to trap bacteria. A total of seventy-seven semen samples with high seminal viscosity (HSV) as the study group and sixty-two semen samples with normal seminal viscosity (NSV) as the control group were compared in this analysis. These semen samples were divided into three groups of receiving treatment (a) with DNase I at 37°C for 15 min, (b) by density gradient centrifugation, and (c) with a combination of the above two methods. Following a fifteen-minute treatment of hyperviscous semen, the motility of spermatozoa in 83% of semen samples increased to a statistically significant degree. On the contrary, DNase treatment of semen with normal viscosity had no such effects. The above treatment was also accompanied by a significant increase in the percentage of normal spermatozoa, resulting in a major decrease of the teratozoospermia index. Comparison between semen samples that underwent density gradient centrifugation following DNase I treatment, to those collected after density gradient treatment alone, showed that in the first case the results were more spectacular. The evaluation of each preparation in terms of yield (% total progressively motile sperm count after treatment in relation to the initial total sperm count) revealed that the combined approach resulted in 29.8% vs. 18.5% with density treatment alone (p=0.0121). DNase I treatment results in an improvement of sperm motility and morphology and could be beneficial to men with hyperviscous semen in assisted reproduction protocols.

The relationship between semen parameters in processed and unprocessed semen with intrauterine insemination success rates

Objective:

To evaluate the relationship between semen parameters and intrauterine insemination (IUI) success rates.

Material and Methods:

This retrospective study was conducted during a 4-year period (2011-2015) on the medical records of 350 couples admitted to the infertility center of Beast Hospital in Tehran. The participants’ data such as age, duration of infertility, semen parameters [including volume, concentration, motility, normal morphology and total motile sperm count (TMSC)] before and after sperm processing, as well as the IUI results were extracted from the patients’ records. Only the first IUI cycle of the couples was considered. The main outcome criterion for the IUI success was serum positive beta human chorionic gonadtotropin 14 days after IUI. The collected data were analyzed using the Mann-Whitney U test, chi-square, and Fisher’s exact tests.

Results:

The overall pregnancy rate for each couple was reported as 23.42% (82/350). There was no significant difference in the mean age of the couple and infertility duration between the groups who achieved pregnancy and those who failed. The two groups showed no significant differences in pre and post processing of semen parameters (including volume, concentration and TMSC). Sperm motility and normal sperm morphology before and after sperm processing were significantly different between the two groups, respectively (p=0.023 before sperm processing and p=0.032 after) (p=0.032 before sperm processing and p=0.007 after).

Conclusion:

Sperm motility and normal sperm morphology have an effect in IUI success.

CASA in the medical laboratory: CASA in diagnostic andrology and assisted conception

CASA has been used in reproductive medicine and pathology laboratories for over 25 years, yet the ‘fertility industry’ generally remains sceptical and has avoided automation, despite clear weaknesses in manual semen analysis. Early implementers had difficulty in validating CASA-Mot instruments against recommended manual methods (haemocytometer) due to the interference of seminal debris and non-sperm cells, which also affects the accuracy of grading motility. Both the inability to provide accurate sperm counts and a lack of consensus as to the value of sperm kinematic parameters appear to have continued to have a negative effect on CASA-Mot’s reputation. One positive interpretation from earlier work is that at least one or more measures of sperm velocity adds clinical value to the semen analysis, and these are clearly more objective than any manual motility analysis. Moreover, recent CASA-Mot systems offer simple solutions to earlier problems in eliminating artefacts and have been successfully validated for sperm concentration; as a result, they should be viewed with more confidence in relation to motility grading. Sperm morphology and DNA testing both require an evidence-based consensus and a well-validated (reliable, reproducible) assay to be developed before automation of either can be of real clinical benefit.

The impact of semen processing on sperm parameters and pregnancy rates after intrauterine insemination

BACKGROUND

The objective of this retrospective study was to evaluate the effect of semen processing on computer analyzed semen parameters and pregnancy rates after intrauterine insemination (IUI).

METHODS

Over a two-year period, a total of 981 couples undergoing 2231 IUI cycles were evaluated and the freshly collected non-donor semen was analyzed before and after density gradient centrifugation (DGC).

RESULTS

DGC led to significant increases in sperm concentration by 66±74 ×106/mL (P=0.0001), percentage of motile sperm by 24±22% (P=0.0001), concentration motile by 27±58 ×106/mL (P=0.0001), and forward sperm progression by 18±14 µ/s (P=0.0001). In 95% of cases, there was a decrease in the total motile sperm count (TMSC), with an average decrease of 50±124% compared to pre-processed samples (P=0.0001). Importantly, the decrease in TMSC did not negatively affect pregnancy rates (P=0.45).

CONCLUSIONS

This study proves that DGC leads to significant increases in most sperm parameters, with the exception of TMSC. Remarkably, the decrease in TMSC did not affect the pregnancy rate. This should reassure clinicians when the TMSC is negatively affected by processing.

Effect of sperm count on success of intrauterine insemination in couples diagnosed with male factor infertility

Objective:

To exam semen parameters in predicting intrauterine insemination (IUI) outcomes in couples with male factor.

Study design:

This retrospective study was performed at department of infertility and sexual medicine from September 2007 to February 2014. 307 couples with male factor infertility were included and 672 IUI cycles were analyzed.

Results:

From 672 inseminations performed on 307 couples, there are 27.36% couples get pregnancy (84 out of 307) and the overall pregnancy rate was 12.95% (87 out of 672) of IUI. With the increase of post total progressive sperm count, the clinical pregnancy rate increased. When the initial progressive sperm count was lower than 5*10⁶, there was no pregnant in the IUI cycle. At the end of the third cycle, 85 clinical pregnancies had been achieved (97.70%).

Conclusions:

The initial total progressive sperm count lower than 5*10⁶ means the poor outcome of IUI in the infertile couples with male factor. If the infertile couples with male factor don’t get pregnancy after three IUI cycles, the couples should receive re-assessment or other artificial reproductive technology.