We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us

Download Mobile App




New Test That Accurately Measures DNA Damage in Sperm Could Improve Male Infertility Diagnosis

By LabMedica International staff writers
Posted on 25 Jan 2022

A new test that can measure the amount of DNA damage in sperm with greater accuracy than current tests could significantly improve diagnosis of male infertility, which is more important than ever now that infertility rates are mounting. More...

A team of researchers at Tongji Medical College (Wuhan, China) developed a method that detects the number of DNA breaks in sperm, which in turn enables the calculation of the mean number of DNA breaks (MDB) per sperm in a sample. Current tests only show whether or not sperm have DNA damage and do not measure the amount of damage, even though the latter is essential for a complete evaluation of sperm health. However, this information plays a crucial role in guiding fertility treatments and in selecting high-quality sperm for sperm banks.

The researchers first evaluated their new method using sperm samples from 80 patients, 34 of whom had athenospermia (low sperm motility) and 46 of whom had normal semen. The team compared the ability of MDB to differentiate between athenospermia and normal samples with that of a conventional sperm DNA test that assesses the sperm DNA fragmentation index (DFI). From this, the researchers found that the area under the curve of MDB (0.7932) was higher than that of DFI (0.7631), meaning that MDB did a better job of telling the two sample types apart.

To further evaluate MDB’s clinical utility, the team then used it and DFI to assess 49 semen samples, 22 of which were associated with pregnancy and 27 of which were linked to an inability to get pregnant. The researchers found that the difference in MDB between the pregnant and non-pregnant groups was statistically significant (P=0.0106), while the difference in DFI between the two groups was not significant (P=0.0548). Furthermore, the area under the curve of MDB in this case (0.7576) was once again higher than the area under the curve of DFI (0.6616). Taken altogether, this means that MDB identifies viable sperm that lead to pregnancy with greater accuracy than conventional sperm DNA tests.

“These data indicated that the MDB parameter had stronger clinical relevance with the pregnancy outcomes and our established method could provide a better tool to evaluate sperm quality and male fertility,” said Xianjin Xiao, PhD, of Tongji Medical College, who led the team. “Our method involves direct detection of actual DNA fragmentation, which can measure the specific degree of sperm DNA fragmentation. The method has the advantages of short time-consumption, simple operation, high analytical sensitivity, and low requirement for instruments, which are conducive to the popularization of clinical application.”

Related Links:
Tongji Medical College 


Gold Member
Blood Gas Analyzer
Stat Profile pHOx
POC Helicobacter Pylori Test Kit
Hepy Urease Test
New
Gold Member
Genetic Type 1 Diabetes Risk Test
T1D GRS Array
Gold Member
Hematology Analyzer
Medonic M32B
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Pathology

view channel
Image: AI models combined with DOCI can classify thyroid cancer subtypes (Photo courtesy of T. Vasse et al., doi 10.1117/1.BIOS.3.1.015001)

AI-Powered Label-Free Optical Imaging Accurately Identifies Thyroid Cancer During Surgery

Thyroid cancer is the most common endocrine cancer, and its rising detection rates have increased the number of patients undergoing surgery. During tumor removal, surgeons often face uncertainty in distinguishing... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.