Influence of paternal age on assisted reproductive technology cycles and perinatal outcomes

Advanced Paternal Age in Focus: Unraveling Its Influence on Assisted Reproductive Technology Outcomes

As global demographics shift toward increasing paternal age, the realm of assisted reproductive technologies (ARTs), particularly in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI), faces new challenges and opportunities. This study provides a comprehensive exploration of the implications of advanced paternal age on ART outcomes. Background research highlights the social, cultural, and economic factors driving men toward later fatherhood, with a focus on the impact of delayed paternity on reproductive outcomes. Methods involve a thorough review of existing literature, centering on changes in testicular function, semen quality, and genetic and epigenetic shifts associated with advancing age. Study results point to intricate associations between the father's age and ART outcomes, with older age being linked to diminished semen quality, potential genetic risks, and varied impacts on embryo quality, implantation rates, and birth outcomes. The conclusions drawn from the current study suggest that while advanced paternal age presents certain risks and challenges, understanding and mitigating these through strategies such as sperm cryopreservation, lifestyle modifications, and preimplantation genetic testing can optimize ART outcomes. Future research directions are identified to further comprehend the epigenetic mechanisms and long-term effects of the older father on offspring health. This study underscores the need for a comprehensive approach in navigating the intricacies of delayed fatherhood within the context of ART, aiming for the best possible outcomes for couples and their children.

Paternal age does not jeopardize the live birth rate and perinatal outcomes after in vitro fertilization: an analysis based on 56,113 frozen embryo transfer cycles

BACKGROUND

The global trend of delaying childbearing has led to an increasing number of couples seeking in vitro fertilization. The adverse effects of advanced maternal age on pregnancy and perinatal outcomes are well documented, regardless of the conception method. In addition, advanced paternal age may contribute to poor reproductive potential because of high levels of sperm DNA fragmentation. However, it remains challenging to guide older men regarding the effect of paternal age on pregnancy and birth outcomes in the field of assisted reproduction.

OBJECTIVE

This study aimed to investigate the association of paternal age with live birth and perinatal outcomes following in vitro fertilization-frozen embryo transfer.

STUDY DESIGN

A retrospective study was performed at a university-affiliated fertility center, involving women who were younger than 36 years and had undergone frozen embryo transfer from January 2011 to June 2021. Subjects were categorized into 6 groups based on paternal age: <25, 25 to 29, 30 to 34, 35 to 39, 40 to 44, and ≥45 years. A generalized estimating equation logistic regression model was used to account for the clustered nature of data and to adjust for confounders. Paternal age between 25 and 29 years served as the reference group in the logistic regression models.

RESULTS

A total of 56,113 cycles who met the inclusion criteria were included in the final analysis. On unadjusted analyses, the reproductive outcome parameters showed a considerable decline with increasing male age. The live birth rate decreased from 47.9% for men aged 25 to 29 years to 40.3% among men aged ≥40 years. Similarly, the clinical pregnancy rate decreased from 54.4% in the reference group to 47.8% in the ≥40 years age group. Conversely, the miscarriage rate increased as male age increased, from 10.2% among men aged 25 to 29 years to 13.5% among men aged ≥45 years. However, the differences in the reproductive outcomes mentioned above were no longer significant in the multivariable models. Compared with the younger controls, advanced paternal age was not associated with a lower chance of live birth (males aged 40-44 years: adjusted odds ratio, 0.94; 95% confidence interval, 0.85-1.04; males aged ≥45 years: adjusted odds ratio, 0.93; 95% confidence interval, 0.79-1.10). In addition, the rates of clinical pregnancy (males aged 40-44 years: adjusted odds ratio, 0.95; 95% confidence interval, 0.85-1.05; males aged ≥45 years: adjusted odds ratio, 0.94; 95% confidence interval, 0.79-1.12) and miscarriage (males aged 40-44 years: adjusted odds ratio, 1.05; 95% confidence interval, 0.85-1.31; males aged ≥45 years: adjusted odds ratio, 1.07; 95% confidence interval, 0.77-1.50) were comparable between the reference and advanced paternal age groups. Furthermore, men in the youngest age group (<25 years) did not have worse pregnancy outcomes than those in the reference group. Regarding perinatal outcomes, there was no difference among the study cohorts in terms of preterm birth, low birthweight, macrosomia, small for gestational age, and large for gestational age, both in the unadjusted and confounder-adjusted models.

CONCLUSION

This study did not demonstrate a significant association between paternal age and live birth and perinatal outcomes after in vitro fertilization-frozen embryo transfer when the female partners were younger than 36 years. With the global trend toward delaying childbirth, our findings provide useful information for counseling patients that increasing paternal age may not adversely affect pregnancy and perinatal outcomes in assisted reproduction.

The impact of paternal age on cumulative assisted reproductive technology outcomes

Objective

To investigate the impact of paternal age on cumulative live birth rate in ART.

Design

Retrospective single-center cohort study.

Patients

All female patients aged 18-43 years and male patients aged 18-60 years, who performed their first ART cycle between January 2018 and December 2020, were included.

Main outcome measures

The primary outcome, cumulative live birth rate (cLBR), was estimated following fresh or frozen embryo transfers issued from an ART cycle. Secondary outcomes included the cumulative pregnancy rate (cPR) and miscarriage rate. Subgroup analyzes were performed as follows: men <45 and ≥ 45; female <35, 35-38, and > 38 years.

Results

A total of 2,358 couples were included in this study. The sperm quantity of male patients within both age groups was divided in two groups: normal and abnormal, which were found to be in significantly equal proportions. There were significantly fewer current smokers in the male group ≥45. The cPR was 0.5301 in the group <45 and 0.3111 in the group ≥45, with a p-value <0.001. Analysis according to the female age revealed that, in the female group >38, the cLBR rate was 0.26 for men <45 and 0.19 for men ≥45, with a p-value of 0.061. Additionally, the cPR was 0.34 in the male group <45 and 0.21 in the group ≥45, with a p-value <0.001. In the female group between 35 and 38 years of age, the cLBR was 0.44 in the male group <45 and 0.3 in the male group ≥45, with a p-value of 0.031. The cPR was 0.49 in the male group <45 and 0.34 in the group ≥45, p = 0.036. Within the female group <35, we observed non-significant results. The miscarriage rate results were not significantly different for women ≤38.

Conclusion

According to the results from our study, male age ≥ 45 has a significant impact on cumulative ART outcomes.

Age-Dependent Alterations in Semen Parameters and Human Sperm MicroRNA Profile

The trend to delay parenthood is increasing, impacting fertility and reproductive outcomes. Advanced paternal age (APA), defined as men's age above 40 years at conception, has been linked with testicular impairment, abnormal semen parameters, and poor reproductive and birth outcomes. Recently, the significance of sperm microRNA for fertilization and embryonic development has emerged. This work aimed to investigate the effects of men's age on semen parameters and sperm microRNA profiles. The ejaculates of 333 Portuguese men were collected between 2018 and 2022, analyzed according to WHO guidelines, and a density gradient sperm selection was performed. For microRNA expression analysis, 16 normozoospermic human sperm samples were selected and divided into four age groups: ≤30, 31-35, 36-40, and >40 years. microRNA target genes were retrieved from the miRDB and TargetScan databases and Gene Ontology analysis was performed using the DAVID tool. No significant correlation was found between male age and conventional semen parameters, except for volume. Fifteen differentially expressed microRNAs (DEMs) between groups were identified. Enrichment analysis suggested the involvement of DEMs in the sperm of men with advanced age in critical biological processes like embryonic development, morphogenesis, and male gonad development. Targets of DEMs were involved in signaling pathways previously associated with the ageing process, including cellular senescence, autophagy, insulin, and mTOR pathways. These results suggest that although conventional semen parameters were not affected by men's age, alterations in microRNA regulation may occur and be responsible for poor fertility and reproductive outcomes associated with APA.

Analysing medical predictors for the outcome of infertility treatment: a 5-year follow-up survey

PURPOSE

For many couples, bearing children is a common life goal; however it cannot always be fulfilled. Undergoing infertility treatment does not always guarantee pregnancies and live births. Couples experience miscarriages and even discontinue infertility treatment. Significant medical predictors for the outcome of infertility treatment have yet to be fully identified.

METHODS

To further our understanding, a cross-sectional 5-year follow-up survey was undertaken, in which 95 women and 82 men that have been treated at the Women's Hospital of Heidelberg University participated. Binary logistic regressions, parametric and non-parametric methods were used for our sample to determine the relevance of biological (infertility diagnoses, maternal and paternal age) and lifestyle factors (smoking, drinking, over- and underweight) on the outcome of infertility treatment (clinical pregnancy, live birth, miscarriage, dropout rate). In addition, chi-square tests were used to examine differences in the outcome depending on the number of risk factors being present.

RESULTS

In the binary logistic regression models for clinical pregnancies, live births and drop outs were statistically significant only for the maternal age, whereas the maternal and paternal BMI, smoking, infertility diagnoses and infections showed no significant predicting effect on any of the outcome variables. A correlation between the number of risk factors and the outcome of infertility treatment could not be excluded.

CONCLUSION

The results confirm that maternal age has an effect on infertility treatment, whereas the relevance of other possible medical predictors remains unclear. Further large-scale studies should be considered to increase our knowledge on their predictive power.

Reproductive outcomes after surgical sperm retrieval in couples with male factor subfertility: a 10-year retrospective national cohort

OBJECTIVE

To determine any significant differences in the reproductive outcome from intracytoplasmic sperm injection (ICSI) with surgical sperm retrieval (SSR) between cycles using fresh and cryopreserved sperm and between cycles using epididymal and testicular sperm.

DESIGN

A retrospective national cohort study using data from the UK Human Fertilisation and Embryology Authority, including all ICSI cycles performed in the United Kingdom over a 10-year period.

SETTING

Hospital.

PATIENT(S)

All nondonor ICSI cycles from 2008 to 2017 categorized by sperm source and cryopreservation status.

INTERVENTION(S)

Intracytoplasmic sperm injection with SSR using fresh or cryopreserved sperm and using ejaculated, testicular, and epididymal sperm.

MAIN OUTCOME MEASURE(S)

Live birth rate, pregnancy rate, and implantation rate.

RESULT(S)

We analyzed data from 214,649 ICSI cycles, including 199,818 cycles of ejaculated sperm, 5,646 cycles of epididymal sperm, and 9,185 cycles of testicular sperm. Live births rates per ICSI cycle were 28.5%, 30.6%, and 28.7% for ejaculated, epididymal, and testicular sperm cycles, respectively. Epididymal sperm cycles had a higher live birth rate than that of testicular sperm cycles (odds ratio [OR], 1.067; 95% confidence interval [CI], 1.014-1.123). This was despite a higher mean male age (42.5 vs. 40.6 years; 95% CI of difference, 1.81-1.85 years) and female age (34.3 vs. 34.0 years; 95% CI of difference, 0.32-0.34 years) in epididymal cycles than in testicular cycles. Implantation (61.2% vs. 58.0%; OR, 1.086; 95% CI, 1.041-1.133) and clinical pregnancy rates (34.3% vs. 31.3%; OR, 1.085; 95% CI, 1.039-1.132) were also higher in epididymal cycles than in testicular cycles. There were no statistically significant differences in outcomes between cycles using fresh sperm and those using cryopreserved sperm for SSR-ICSI.

CONCLUSION(S)

Our study indicates that reproductive outcomes of SSR-ICSI are at least comparable with those of ICSI using ejaculated sperm and does not support the preferential use of fresh sperm over cryopreserved sperm in SSR-ICSI. Births per SSR-ICSI cycle were higher for cycles using epididymal sperm than for cycles using testicular sperm; however, the differences were small, which may provide reassurance to patients undergoing these procedures. The results must be interpreted with caution because multivariable analysis was not possible because of aggregation of data.

Risk Factors of Pregnancy Failure in Infertile Patients Undergoing Assisted Reproductive Technology

Background

Infertile couples need to use assisted reproductive technology (ART) to give birth. However, pregnancy failure after ART is not uncommon. At present, the results of studies on the causes of pregnancy failure after ART are inconsistent.

Methods

A retrospective cohort study involving 715 embryo transfer cycles was conducted at the Reproductive Medicine Center of Meizhou People's Hospital, from December 2015 to June 2022. According to the pregnancy, they were divided into clinical pregnancy group and pregnancy failure group. The relationship between demographic characteristics and pregnancy status between the two groups was analyzed.

Results

The pregnancy failure rate after ART was 49.7% (355/715). There were statistically significant distribution differences of maternal age, paternal age, COH protocols, and number of embryos transferred between clinical pregnancy and pregnancy failure groups (all P<0.01). Multiple logistic regression analysis shows that high maternal age (>35 years old vs ≤35 years old: OR 2.173, 95% CI: 1.386-3.407, P=0.001), and GnRH-a short protocol (GnRH-a short protocol vs GnRH-a long protocol: OR 2.139, 95% CI: 1.127-4.058, P=0.020) may increase risk of pregnancy failure in ART pregnancies, while two embryos transferred (two embryos transferred vs one embryo transferred: OR 0.563, 95% CI: 0.377-0.839, P=0.005) may reduce risk of pregnancy failure. In addition, high maternal age, GnRH antagonist protocol, and GnRH-a short protocol may increase risk of implantation failure, while two embryos transferred may reduce risk of implantation failure. And high maternal age may increase risk of biochemical pregnancy.

Conclusion

The risk of pregnancy failure increased in ART cycles with maternal age >35 years old and GnRH-a short protocol, while reduced with two embryos transferred.

Reproductive axis ageing and fertility in men

Compared to women, increasing male age is not accompanied by such marked changes in reproductive function but changes certainly do happen. These include alterations to the hypothalamo-pituitary-testicular axis, with resultant implications for testosterone production and bioavailability as well as spermatogenesis. There is a decline in sexual function as men age, with a dramatic increase in the prevalence of erectile dysfunction after the age of 40, which is a marker for both clinically evident as well as covert coronary artery disease. Despite a quantitative decline in spermatogenesis and reduced fecundability, the male potential for fertility persists throughout adult life, however there are also increasingly recognised alterations in sperm quality and function with significant implications for offspring health. These changes are relevant to both natural and medically assisted conception.

Age-associated epigenetic changes in mammalian sperm: implications for offspring health and development

BACKGROUND

Modern reproductive behavior in most developed countries is characterized by delayed parenthood. Older gametes are generally less fertile, accumulating and compounding the effects of varied environmental exposures that are modified by lifestyle factors. Clinicians are primarily concerned with advanced maternal age, while the influence of paternal age on fertility, early development and offspring health remains underappreciated. There is a growing trend to use assisted reproductive technologies for couples of advanced reproductive age. Thus, the number of children born from older gametes is increasing.

OBJECTIVE AND RATIONALE

We review studies reporting age-associated epigenetic changes in mammals and humans in sperm, including DNA methylation, histone modifications and non-coding RNAs. The interplay between environment, fertility, ART and age-related epigenetic signatures is explored. We focus on the association of sperm epigenetics on epigenetic and phenotype events in embryos and offspring.

SEARCH METHODS

Peer-reviewed original and review articles over the last two decades were selected using PubMed and the Web of Science for this narrative review. Searches were performed by adopting the two groups of main terms. The first group included 'advanced paternal age', 'paternal age', 'postponed fatherhood', 'late fatherhood', 'old fatherhood' and the second group included 'sperm epigenetics', 'sperm', 'semen', 'epigenetic', 'inheritance', 'DNA methylation', 'chromatin', 'non-coding RNA', 'assisted reproduction', 'epigenetic clock'.

OUTCOMES

Age is a powerful factor in humans and rodent models associated with increased de novo mutations and a modified sperm epigenome. Age affects all known epigenetic mechanisms, including DNA methylation, histone modifications and profiles of small non-coding (snc)RNA. While DNA methylation is the most investigated, there is a controversy about the direction of age-dependent changes in differentially hypo- or hypermethylated regions with advanced age. Successful development of the human sperm epigenetic clock based on cross-sectional data and four different methods for DNA methylation analysis indicates that at least some CpG exhibit a linear relationship between methylation levels and age. Rodent studies show a significant overlap between genes regulated through age-dependent differentially methylated regions and genes targeted by age-dependent sncRNA. Both age-dependent epigenetic mechanisms target gene networks enriched for embryo developmental, neurodevelopmental, growth and metabolic pathways. Thus, age-dependent changes in the sperm epigenome cannot be described as a stochastic accumulation of random epimutations and may be linked with autism spectrum disorders. Chemical and lifestyle exposures and ART techniques may affect the epigenetic aging of sperm. Although most epigenetic modifications are erased in the early mammalian embryo, there is growing evidence that an altered offspring epigenome and phenotype is linked with advanced paternal age due to the father's sperm accumulating epigenetic changes with time. It has been hypothesized that age-induced changes in the sperm epigenome are profound, physiological and dynamic over years, yet stable over days and months, and likely irreversible.

WIDER IMPLICATIONS

This review raises a concern about delayed fatherhood and age-associated changes in the sperm epigenome that may compromise reproductive health of fathers and transfer altered epigenetic information to subsequent generations. Prospective studies using healthy males that consider confounders are recommended. We suggest a broader discussion focused on regulation of the father's age in natural and ART conceptions is needed. The professional community should be informed and should raise awareness in the population and when counseling older men.

Predicting cumulative live birth for couples beginning their second complete cycle of in vitro fertilization treatment

STUDY QUESTION

Can we develop an IVF prediction model to estimate individualized chances of a live birth over multiple complete cycles of IVF in couples embarking on their second complete cycle of treatment?

SUMMARY ANSWER

Yes, our prediction model can estimate individualized chances of cumulative live birth over three additional complete cycles of IVF.

WHAT IS KNOWN ALREADY

After the completion of a first complete cycle of IVF, couples who are unsuccessful may choose to undergo further treatment to have their first child, while those who have had a live birth may decide to have more children. Existing prediction models can estimate the overall chances of success in couples before commencing IVF but are unable to revise these chances on the basis of the couple’s response to a first treatment cycle in terms of the number of eggs retrieved and pregnancy outcome. This makes it difficult for couples to plan and prepare emotionally and financially for the next step in their treatment.

STUDY DESIGN, SIZE, DURATION

For model development, a population-based cohort was used of 49 314 women who started their second cycle of IVF including ICSI in the UK from 1999 to 2008 using their own oocytes and their partners’ sperm. External validation was performed on data from 39 442 women who underwent their second cycle from 2010 to 2016.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Data about all UK IVF treatments were obtained from the Human Fertilisation and Embryology Authority (HFEA) database. Using a discrete time logistic regression model, we predicted the cumulative probability of live birth from the second up to and including the fourth complete cycles of IVF. Inverse probability weighting was used to account for treatment discontinuation. Discrimination was assessed using c-statistic and calibration was assessed using calibration-in-the-large and calibration slope.

MAIN RESULTS AND THE ROLE OF CHANCE

Following exclusions, 49 314 women with 73 053 complete cycles were included. 12 408 (25.2%) had a live birth resulting from their second complete cycle. Cumulatively, 17 394 (35.3%) had a live birth over complete cycles two to four. The model showed moderate discriminative ability (c-statistic: 0.65, 95% CI: 0.64 to 0.65) and evidence of overprediction (calibration-in-the-large = −0.08) and overfitting (calibration slope 0.85, 95% CI: 0.81 to 0.88) in the validation cohort. However, after recalibration the fit was much improved. The recalibrated model identified the following key predictors of live birth: female age (38 versus 32 years—adjusted odds ratio: 0.59, 95% CI: 0.57 to 0.62), number of eggs retrieved in the first complete cycle (12 versus 4 eggs; 1.34, 1.30 to 1.37) and outcome of the first complete cycle (live birth versus no pregnancy; 1.78, 1.66 to 1.91; live birth versus pregnancy loss; 1.29, 1.23 to 1.36). As an example, a 32-year-old with 2 years of non-tubal infertility who had 12 eggs retrieved from her first stimulation and had a live birth during her first complete cycle has a 46% chance of having a further live birth from the second complete cycle of IVF and an 81% chance over a further three cycles.

LIMITATIONS, REASONS FOR CAUTION

The developed model was updated using validation data that was 6 to 12 years old. IVF practice continues to evolve over time, which may affect the accuracy of predictions from the model. We were unable to adjust for some potentially important predictors, e.g. BMI, smoking and alcohol intake in women, as well as measures of ovarian reserve such as antral follicle count. These were not available in the linked HFEA dataset.

WIDER IMPLICATIONS OF THE FINDINGS

By appropriately adjusting for couples who discontinue treatment, our novel prediction model will provide more realistic chances of live birth in couples starting a second complete cycle of IVF. Clinicians can use these predictions to inform discussion with couples who wish to plan ahead. This prediction tool will enable couples to prepare emotionally, financially and logistically for IVF treatment.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by an Elphinstone scholarship scheme at the University of Aberdeen and Aberdeen Fertility Centre, University of Aberdeen. The authors have no conflict of interest.

TRIAL REGISTRATION NUMBER

N/A.