多路复用
基因分型
数字聚合酶链反应
Y染色体
多重聚合酶链反应
分子生物学
SNP公司
SNP基因分型
生物
分数(化学)
产前诊断
计算生物学
移植
实时聚合酶链反应
医学
遗传学
基因型
胎儿
医学检查
产前筛查
聚合酶链反应
SNP阵列
多中心研究
作者
Chianru Tan,Peng Dai,Zhuoyu Zhao,Xinwen Chen,Dong Wang,Xiaojing Ren,Lingxiang Zhu,Tizhen Yan,Jiwu Lou,Xiangdong Kong,Yu Guo
标识
DOI:10.1093/clinchem/hvag017
摘要
BACKGROUND: Fetal fraction (FF) quantification is critical for prenatal cell-free DNA screening. Current methods based on Y chromosome (chrY), differential methylation, or single-nucleotide polymorphisms (SNPs) face limitations including sex dependency, complex workflows, or the need for parental genotyping. An FF quantification method that integrates directly into the digital polymerase chain reaction (dPCR) workflow is needed to support the clinical implementation of dPCR-based prenatal screening. METHODS: We developed a multiplex dPCR assay quantifying 9 autosomal SNPs and 3 chrY loci across 2 reaction wells. Key innovations include: concurrent SNP and chrY detection for sex-independent estimation; a single-probe, dual-allele discrimination design with a calculation algorithm that eliminates parental genotyping; and a triplex chrY assay to enhance accuracy. The assay was analytically validated using simulated DNA mixtures and clinically evaluated using 143 maternal plasma samples against a next-generation sequencing (NGS) reference. RESULTS: Analytical validation showed strong linearity between expected and observed FF for both chrY (R2 = 0.971) and SNP (R2 = 0.924) methods. The chrY assay demonstrated superior accuracy and sensitivity at low FF levels (mean absolute error: 0.94% chrY, 1.61% SNPs). Clinical evaluation showed a 92.3% informative SNP rate, a low 2.8% no-call rate, and strong concordance with NGS-based FF estimates (r = 0.799, P < 0.0001). CONCLUSIONS: Our dPCR assay provides a practical QC tool for dPCR-based prenatal screening by enabling sex-independent FF quantification without parental genotyping or complex preanalytical steps. Future efforts will include multicenter validation and panel expansion. This methodology also shows potential for applications in transplantation medicine and obstetric monitoring.
科研通智能强力驱动
Strongly Powered by AbleSci AI