New test could improve diagnosis of male infertility and advance fertility treatment

News – WASHINGTON – Cutting-edge research published today in AACC clinical chemistry newspaper shows that a new test can measure the amount of DNA damage in sperm with greater accuracy than current tests. This new method could significantly improve the diagnosis of male infertility, which is more important than ever now that infertility rates are rising.

See the full study here: https://doi.org/10.1093/clinchem/hvab280

Due to a number of factors such as the widespread use of hormone-modifying chemicals, infertility has increased at an alarming rate worldwide. The overall incidence of infertility is now 10-15%, with male infertility accounting for 40% of these cases. The rise in male infertility in particular has led to a need for better ways to assess sperm DNA damage, as this information plays a crucial role in guiding fertility treatments and in the selection of high quality sperm for sperm banks. However, current tests only show whether or not sperm have DNA damage; these tests do not measure the amount of damage, although the latter is essential for a full assessment of sperm health.

To solve this problem, a team of researchers led by Xianjin Xiao, PhD, of Tongji Medical College in Wuhan, China, has developed a method that detects the number of DNA breaks in sperm, which allows its turn to calculate the average DNA count. breaks (MDB) per sperm in a sample. The researchers first evaluated this method using semen samples from 80 patients, 34 of whom had athenospermia (low sperm motility) and 46 had normal sperm. Xiao’s team compared MDB’s ability to differentiate athenospermia from normal samples with that of a conventional sperm DNA test that assesses sperm DNA fragmentation index (DFI). From this, the researchers found that the area under the curve of MDB (0.7932) was greater than that of DFI (0.7631), meaning that MDB better distinguished the two types of samples.

To further assess the clinical utility of the MDB, Xiao’s team then used it and the DFI to assess 49 semen samples, 22 of which were associated with pregnancy and 27 with an inability to conceive. 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). Moreover, the area under the curve of MDB in this case (0.7576) was again greater than the area under the curve of DFI (0.6616). Overall, this means the MDB identifies viable sperm that lead to pregnancy with greater accuracy than conventional sperm DNA testing.

“These data indicated that the MDB parameter had stronger clinical relevance with pregnancy outcomes and our established method may provide a better tool for assessing sperm quality and male fertility,” Xiao said. “Our method involves the 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, of high analytical sensitivity and low need for instruments, which is conducive to the popularization of clinical application.

About the AACC

Dedicated to improving health through laboratory medicine, AACC brings together more than 50,000 clinical laboratory professionals, physicians, researchers and business leaders from around the world focused on clinical chemistry, molecular diagnostics, mass spectrometry, translational medicine, laboratory management and other areas of laboratory science is progressing. Since 1948, the AACC has worked to advance common interests in the field, providing programs that advance scientific collaboration, knowledge, expertise, and innovation. For more information, visit www.aacc.org.

clinical chemistry (clinchem.org) is the leading international journal of laboratory medicine, presenting nearly 400 peer-reviewed studies each year that help patients obtain accurate diagnoses and essential care. This vital research advances areas of health ranging from genetic testing and drug monitoring to pediatrics and the appropriate use of testing.

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