Elena García-Mengual1, Juan Carlos Triviño2, Alba Sáez-Cuevas3, Juan Bataller4, Miguel Ruíz-Jorro4, Xavier Vendrell3. 1. Reproductive Genetics Unit, Sistemas Genómicos S.L, Ronda G. Marconi 6, Parque Tecnológico, 46980, Paterna, Valencia, Spain. elena.garcia@sistemasgenomicos.com. 2. Bioinformatics Department, Sistemas Genómicos S.L, Ronda G. Marconi 6, Parque Tecnológico, 46980, Paterna, Valencia, Spain. 3. Reproductive Genetics Unit, Sistemas Genómicos S.L, Ronda G. Marconi 6, Parque Tecnológico, 46980, Paterna, Valencia, Spain. 4. CREA, Assisted Reproduction Medical Center, Carrer de Sant Martí 4, 46003, Valencia, Spain.
Abstract
PURPOSE: Fluorescence in situ hybridization (FISH) in spermatozoa provides an estimate of the frequency of chromosomal abnormalities, but there is not a clinical consensus on how to statistically analyze sperm FISH results. We therefore propose a statistical approach to establish sperm aneuploidy thresholds in a fertile population. METHODS: We have determined the distribution and variation of the frequency of nullisomy, disomy, and diploidy for a set of 13 chromosomes (1, 2, 9, 13, 15, 16, 17, 18, 19, 21, 22, X, and Y) in sperm nuclei from 14 fertile men by means of automatized FISH. The dispersion of data has been analyzed by the non-parametric Wilcoxon Rank Sum test. We have established the threshold values for each chromosome and aneuploidy type on the basis of the confidence interval values (99.9%). RESULTS: Nullisomy thresholds ranged from 0.49% for chromosome 19 to 3.09% for chromosome 22; disomy thresholds ranged from 0.30% for chromosome 21 to 1.47% for chromosome 15; diploidy thresholds ranged from 0.24% for the 9/19 chromosome set to 1.21% for the 13/21 chromosome set. CONCLUSIONS: Applying this approach with clinical purposes will enable us to categorize the patient as altered or normal regarding his sperm aneuploidy. Any result surpassing the cited threshold values indicates a 99.9% probability of being significantly different from fertile controls.
PURPOSE: Fluorescence in situ hybridization (FISH) in spermatozoa provides an estimate of the frequency of chromosomal abnormalities, but there is not a clinical consensus on how to statistically analyze sperm FISH results. We therefore propose a statistical approach to establish sperm aneuploidy thresholds in a fertile population. METHODS: We have determined the distribution and variation of the frequency of nullisomy, disomy, and diploidy for a set of 13 chromosomes (1, 2, 9, 13, 15, 16, 17, 18, 19, 21, 22, X, and Y) in sperm nuclei from 14 fertile men by means of automatized FISH. The dispersion of data has been analyzed by the non-parametric Wilcoxon Rank Sum test. We have established the threshold values for each chromosome and aneuploidy type on the basis of the confidence interval values (99.9%). RESULTS: Nullisomy thresholds ranged from 0.49% for chromosome 19 to 3.09% for chromosome 22; disomy thresholds ranged from 0.30% for chromosome 21 to 1.47% for chromosome 15; diploidy thresholds ranged from 0.24% for the 9/19 chromosome set to 1.21% for the 13/21 chromosome set. CONCLUSIONS: Applying this approach with clinical purposes will enable us to categorize the patient as altered or normal regarding his sperm aneuploidy. Any result surpassing the cited threshold values indicates a 99.9% probability of being significantly different from fertile controls.
Entities:
Keywords:
Aneuploidy thresholds; Automatized analysis; Diploidy; Disomy; Fertile donors; Fluorescence in situ hybridization (FISH); Human sperm aneuploidy; Nullisomy
Authors: W Vegetti; E Van Assche; A Frias; G Verheyen; M M Bianchi; M Bonduelle; I Liebaers; A Van Steirteghem Journal: Hum Reprod Date: 2000-02 Impact factor: 6.918
Authors: Santiago Munné; Muhterem Bahçe; Mireia Sandalinas; Tomás Escudero; Carmen Márquez; Esther Velilla; Pere Colls; Maria Oter; Mina Alikani; Jacques Cohen Journal: Reprod Biomed Online Date: 2004-01 Impact factor: 3.828
Authors: S Egozcue; J Blanco; J M Vendrell; F García; A Veiga; B Aran; P N Barri; F Vidal; J Egozcue Journal: Hum Reprod Update Date: 2000 Jan-Feb Impact factor: 15.610
Authors: Diana S Chu; Thomas Müller-Reichert; Gunar Fabig; Robert Kiewisz; Norbert Lindow; James A Powers; Vanessa Cota; Luis J Quintanilla; Jan Brugués; Steffen Prohaska Journal: Elife Date: 2020-03-10 Impact factor: 8.140