An age-based sperm nomogram: the McGill reference guide.

Abstract

How does age affect various semen parameters? For most semen parameters, the nomogram of the entire population was biphasic, peaking around the fourth decade of life. In clinical practice, semen quality is examined by using the WHO 2010 reference limits but these limits do not account for male age. A percentile-based, large-scale nomogram describing how different semen parameters change throughout reproductive life has been lacking. A retrospective study was conducted with 12 188 sperm samples, obtained from individuals who attended the McGill University Health Centre reproductive clinic between 2009 and 2018. One sample from each individual who attended the clinic during the study period was analysed by using computer-assisted sperm analysis (CASA). The analysed parameters were human-verified and included sperm concentration, motility, progressive motility, total count, morphology and semen volume. Based on this analysis, the entire dataset (n = 12 188) was further divided into two groups of samples: samples that surpassed the WHO 2010 lower reference limits ('above reference limits' group, ARL; n = 6305), and samples that did not ('below reference limit' group, BRL; n = 5883). Regression quantiles were fitted as a function of age to generate age-dependent nomograms, and these quantiles were divided into 5th, 25th, 50th, 75th and 95th percentiles. In the entire dataset, age had a significant influence (P < 0.001) on all parameters (except morphology) which demonstrated a biphasic trend peaking in the fourth decade of life. In the ARL group, age had a significant influence (P < 0.01) on all semen parameters except sperm concentration and morphology. However, unlike in the entire dataset, only semen volume demonstrated a biphasic trend in the ARL group (peaking in the fourth decade of life), whereas other parameters either remained unchanged (concentration and morphology) or consistently declined with age (sperm motility, progressive motility and total sperm count). Percentile-based nomograms were generated for individuals between the ages of 20 and 60 years in the entire dataset and in the ARL group. First, the semen samples were obtained from individuals who were referred to a fertility clinic, such that the entire dataset does not necessarily represent the general population. Second, the cross-sectional sampling design increases variance, and the nomograms are less accurate in the 5th and 95th percentiles and at the extremes of the age distributions. Third, the observed age-dependent changes in semen parameters do not necessarily indicate changes in fertility, as not all factors that affect male fertility were analysed. Fourth, some of our semen analyses employed CASA, which can have variability issues. Finally, our models did not incorporate possible secular trends. We provide the first nomogram that correlates age with semen quality parameters in different population percentiles, thus complementing the current reference limits set by the WHO in 2010. Most examined semen parameters in our study changed non-linearly with age; therefore, age should be regularly employed as a factor in the clinical analysis of semen samples. The authors have not received any funding to support this study. There are no conflicts of interest to declare. N/A.