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Updated: Jan 9, 2026

Semiconductor Sequencing for Preimplantation Genetic Testing for Aneuploidy
Published on: August 25, 2019
Incidence of aneuploidy in embryos studied using PGT-A in Mexico: a clinical retrospective experience
Eduardo Ponce-Najera1, Diana María Ojeda-López1, Rodolfo González-Holveman1
1Hospital Español de México Assisted Reproduction Clinic HISPAREP Mexico City Mexico Hospital Español de México, Assisted Reproduction Clinic HISPAREP, Mexico City.
Objective:
This study aimed to analyze the relationship between aneuploidy and maternal age based on preimplantation genetic testing for aneuploidies (PGT-A) and the distribution of aneuploidy across individual chromosomes.
Methods:
This is a single-center retrospective cohort study. The study included patients who underwent PGT-A during their in vitro fertilization (IVF) cycle between 2016 and 2024. PGT-A was performed on 1,341 embryos from 481 patients using next-generation sequencing (NGS)-based techniques. We conducted a Logistic regression analysis to determine the relationship between maternal age and the rate of aneuploidy; additionally, the most commonly affected chromosome and the characteristics of the detected alterations were evaluated. Statistical analysis was performed using STATA v17.
Results:
Among all patients, the observed aneuploidy rate was 55.85%. In patients younger than 30 years, the aneuploidy rate was 26.92%, with a progressive increase to 62% in women older than 40 years. Chromosomes 22, 21, 16, and 15 were the most frequently affected. Logistic regression indicated that age is a significant predictive factor for aneuploidy (coefficient = 0.0956; p < 0.001), with an odds ratio of 1.10 (95% CI: 1.07-1.13), meaning that the probability of aneuploidy increases by approximately 10% for each additional year of age.
Conclusion:
Our results indicate that an increase in maternal age is significantly associated with a higher incidence of aneuploidy in embryos that underwent PGT-A. These findings are significant for patient counseling and optimizing embryo selection in assisted reproduction treatments.
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