ESPE Abstracts

Introduction: Sex chromosome abnormalities (SCAs) are genetic conditions characterized by deviations in the number or structure of the sex chromosomes, present in 1 in 400 newborns. Despite their clinical significance, many patients with SCAs are diagnosed late in life or remain undiagnosed, leading to delayed or inadequate medical intervention. Karyotyping, the gold standard for diagnosis, is unsuitable for population-based newborn screening, as it is time-consuming, labor intensive and expensive. This study aimed to devise a rapid and cost-effective first-tier test for identifying SCAs in newborns, enabling early detection and management to enhance quality of life and reduce morbidity.

Materials and methods: Blood samples were derived from four cross-sectional studies on patients with SCAs and age-matched controls. Informed written consent was obtained for all participants and all clinical investigations were conducted according to the Declaration of Helsinki. We used Quantitative fluorescence polymerase chain reaction (QF-PCR) utilizing short tandem repeat (STR) markers and X-linked segmental duplication (SD) markers. The procedure involved DNA preparation, amplification of target DNA by multiplex SD-STR-PCR, and quantitative analysis of the PCR products. The test's performance was assessed by its accuracy in distinguishing between normal (46,XX or 46,XY) and abnormal (Non 46,XX or 46,XY) sex chromosome compositions.

Results: Combined, 367 blood samples were included (186 SCA patients, 181 healthy controls). QF-PCR accurately identified 175 out of 186 SCA samples, yielding a sensitivity of 94.1%. Among the 181 control samples, 171 were accurately identified, resulting in a specificity of 94.5%. The positive predictive value (PPV) was 94.6% and the negative predictive value (NPV) 93.9%. Primarily mosaic cases were difficult to diagnose precisely.

Conclusion: QF-PCR is a promising tool for reliably detecting SCAs, coupled with cost-effectiveness and scalability. Based on the performance of the diagnostic test in this study, conducting this analysis on 100,000 newborns would result in diagnosing 235 out of an anticipated 250 cases. Additionally, it would fail to diagnose 15 newborns with SCAs, due to false negative results. Given the current diagnostic rate of 10-30%, this approach would significantly improve the diagnostic rate. However, the rate of false positives is substantial. In a population of 100,000 newborns, there would be 5,486 false positive cases. This would cause unnecessary worry for the parents of these children and require costly verification of numerous positive test results through karyotyping. Therefore, the current methodology needs further refinement, especially to achieve a lower false positive rate.