Infertility Research Today is a free monthly online journal that collates and summarizes the latest research about Infertility, including details on male and female infertility, treatment, causes, pregnancy. | ||||||||
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Low total normal motile count values are associated with increased sperm disomy and diploidy rates in infertile patients.Bernardini LM, Calogero AE, Bottazzi C, Lanteri S, Venturini PL, Burrello N, De Palma A, Conte N, Ragni N Department of Obstetrics and Gynaecology, University of Genoa, Genoa, Italy. This study was undertaken to evaluate the possibility of identifying men at increased risk of sperm aneuploidy and diploidy on the bases of specific cut-off values of the total normal motile count (TNMC). Twenty-seven consecutive, unselected male patients referred to our Unit were studied: 11 patients with normal sperm parameters (group A) suffering from unexplained infertility and 16 infertile patients with abnormal sperm parameters (group B). Disomy rates for chromosomes 1, 4, 8, 12, 18, X and Y were ascertained for each patient by means of triple and double fluorescence in situ hybridization (FISH) experiments. Both univariate and multivariate statistical analyses by principal component analysis (PCA) were performed for comparisons between sperm aneuploidy rates and semen quality (TNMC). TNMC scores in the two groups were significantly different (23.5 x 10(6) and 1.52 x 10(6), in groups A and B, respectively, p = 0.00002). In general, higher sperm disomy rates were noted for all chromosomes in group B compared with group A. Statistical significance was observed for disomy 1, total disomy rate (3.36% vs. 1.38%), and diploidy (0.49% vs. 0.19%) (p < 0.01). For disomy 4 and 8, differences resulted close to significance. PCA clearly showed how independent variables were inter-related. Infertile men with TNMC < 2 x 10(6) (male factor) were found to be at increased risk for sperm aneuploidy and diploidy. Multivariate analysis by PCA resulted as a useful method to visualize the information of the data sets on a bi-dimensional plot considering all the patients and all the variables at the same time. Published 22 November 2005 in Int J Androl, 28(6): 328-36.
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