Sperm DNA Damage May Be Major Cause of Unexplained Infertility

About one‐third of infertile couples are diagnosed with unexplained infertility, meaning that routine Sperm DNA Damageinfertility testing has not found the cause of their difficulty conceiving a baby. A recent study from Queen’s University in Belfast has found the cause of many cases of unexplained infertility — small breaks in the DNA of the man’s sperm. Sperm quality is generally tested by measuring sperm concentration, motility and morphology. While conventional semen‐analysis can be useful as initial test of a man’s fertility status, there is growing evidence that it has limited value in diagnosing male infertility or predicting success of assisted reproduction. Researchers continue to search for better tests of male fertility.

 

In this large study of 239 couples, a detectable abnormality known as “high sperm DNA damage” was found in 80 percent of couples with unexplained infertility. The investigators used a test called SpermComet to detect faulty DNA in sperm. DNA damage can be caused by a number of factors including poor diet and smoking, and may contribute to impaired embryo development, miscarriage, and birth defects. The study also found the amount of sperm damage is related to the chances of having a baby following IVF. It is thought that a small amount of sperm DNA damage is normal (under 15 per cent DNA damage), and as is commonly seen in the sperm of fertile men. In the study, men were divided into groups according to degree of sperm DNA damage. Following IVF, couples with < 25% sperm DNA fragmentation had a live birth rate of 33%; in contrast, couples with > 50% sperm DNA fragmentation had a much lower live birth rate of 13%.

 

Sperm DNA damage assessed by the Comet assay has a close inverse relationship with live‐birth rates after IVF. Couples with unexplained infertility, where the husband has high DNA damage, may be better treated by going directly to IVF and ICSI, rather than using less effective treatments. This new test can predict the success of infertility treatments and fast‐track couples to the treatment most likely to succeed, leading to reduced waiting times and improved chances of having a baby.