Next Generation Sequencing nell'analisi del DNA fetale da plasma materno per la diagnosi prenatale non invasiva di malattie genetiche
type: CreativeWork
description: Risk for monogenic disease and aneuploidies are the most common reasons that prompt couples to opt for prenatal diagnosis (PD). Unfortunately, current procedures of prenatal diagnosis are invasive and carry a 0.5-1% risk of fetal mortality. The discovery of fetal DNA in maternal plasma had opened new opportunities for non invasive diagnosis and to date, cffDNA( cell-free fetal DNA) is considered the ideal target to conduct a noninvasive diagnosis (NIPD). Simultaneously, the large develop of next generation technologies (NGS) has provided a robust method to detect and analyze cfDNA (cell free DNA) from maternal plasma. Our intent is develop new protocols able to carry forward a noninvasive diagnosis starting from cffDNA. In this work, we propose a protocol that allow fetal genotype detection from ccfDNA through a target amplification of several SNP and mutation sites, through analysis by Ion Torrent PGM platform technology and supported by statistical approaches useful to discriminate fetal DNA contribution into mixture of fetal/maternal DNA (RHDO/SPRT). In order to define haplotypes we propose a long-range PCR method based that can support the detection of the parental haplotypes in association to normal and mutated alleles. Using these approaches, we have analyzed 18 cfDNA samples with these results: 9 samples correctly defined; 7 samples defined at 50%; 1 sample not correctly defined; 1 sample not analyzed. To date, obtained data show that this method is effective and reliable, though will required additional data to confirm these results. Data collected suggest that this method could be inserted, in the near future, in clinical diagnostic practices removing risks of fetal loss, facilitating the diagnostic process and providing significant economic advantage in clinical procedures.
abstract: Risk for monogenic disease and aneuploidies are the most common reasons that prompt couples to opt for prenatal diagnosis (PD). Unfortunately, current procedures of prenatal diagnosis are invasive and carry a 0.5-1% risk of fetal mortality. The discovery of fetal DNA in maternal plasma had opened new opportunities for non invasive diagnosis and to date, cffDNA( cell-free fetal DNA) is considered the ideal target to conduct a noninvasive diagnosis (NIPD). Simultaneously, the large develop of next generation technologies (NGS) has provided a robust method to detect and analyze cfDNA (cell free DNA) from maternal plasma. Our intent is develop new protocols able to carry forward a noninvasive diagnosis starting from cffDNA. In this work, we propose a protocol that allow fetal genotype detection from ccfDNA through a target amplification of several SNP and mutation sites, through analysis by Ion Torrent PGM platform technology and supported by statistical approaches useful to discriminate fetal DNA contribution into mixture of fetal/maternal DNA (RHDO/SPRT). In order to define haplotypes we propose a long-range PCR method based that can support the detection of the parental haplotypes in association to normal and mutated alleles. Using these approaches, we have analyzed 18 cfDNA samples with these results: 9 samples correctly defined; 7 samples defined at 50%; 1 sample not correctly defined; 1 sample not analyzed. To date, obtained data show that this method is effective and reliable, though will required additional data to confirm these results. Data collected suggest that this method could be inserted, in the near future, in clinical diagnostic practices removing risks of fetal loss, facilitating the diagnostic process and providing significant economic advantage in clinical procedures.
author: PICCIAU, ANDREA
language: ita
keywords: Next Generation, diagnosi non invasiva, maternal plasma, non invasive diagnosis, Settore BIO/11 - Biologia Molecolare
date published: 2014-05-30
date modified: 2026-07-24T01:30:07Z
provider: Università di Cagliari
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Università degli Studi di Cagliari

PropertyValue
property ID: Handle
value: http://hdl.handle.net/11584/266531