State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China.
Department of Fetal Medicine & Prenatal Diagnosis Center, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China.
Mol Genet Genomic Med. 2022 Aug;10(8):e1988. doi: 10.1002/mgg3.1988. Epub 2022 May 29.
Noninvasive prenatal testing (NIPT) has been widely used clinically to detect fetal chromosomal aneuploidy with high accuracy rates, gradually replacing traditional serological screening. However, the application of NIPT for monogenic diseases is still in an immature stage of exploration. The detection of mutations in peripheral blood of pregnant women requires precise qualitative and quantitative techniques, which limits its application. The bioinformatic strategies based on the SNP (single nucleotide polymorphism) linkage analysis are more practical, which can be divided into two types depending on whether proband information is needed. Hidden Markov Mode (HMM) and Sequential probability ratio test (SPRT) are suitable for families with probands. In contrast, methods based on databases and population demographic information are suitable for families without probands.
In this study, we proposed a Spearman rank correlation analysis method to infer the fetal haplotypes based on core family information. Allele frequencies of SNPs that were used to construct parental haplotypes were calculated as sets of nonparametric variables, in contrast to their theoretical values represented by a fetal fraction (FF). The effects on the calculation of the fetal concentration of two DNA enrichment methods, multiple-PCR amplification, and targeted hybrid capture, were compared, and the heterozygosity distribution of SNPs within pedigrees was analyzed to reveal the best conditions for the model application.
Predictions of the paternal haplotype inheritance were in line with expectations for both DNA library construction methods, while for maternal haplotype inheritance prediction, the rates were 96.55% for method multiple-PCR amplification and 95.8% for method targeted hybrid capture.
Positive prediction rates showed that the maternal haplotype prediction was not as accurate as paternal one, due to the large amount of maternal noise in the mother's peripheral blood. Although this model is relatively immature, it provides a new perspective for noninvasive prenatal clinical tests of monogenic diseases.
非侵入性产前检测（NIPT）已广泛应用于临床，以高准确率检测胎儿染色体非整倍体，逐渐取代传统的血清学筛查。然而，NIPT 在单基因疾病中的应用仍处于探索的不成熟阶段。孕妇外周血中突变的检测需要精确的定性和定量技术，这限制了其应用。基于 SNP（单核苷酸多态性）连锁分析的生物信息学策略更实用，根据是否需要先证者信息可分为两类。隐马尔可夫模型（HMM）和序列概率比检验（SPRT）适用于有先证者的家庭，而基于数据库和人口统计学信息的方法则适用于没有先证者的家庭。
本研究提出了一种 Spearman 秩相关分析方法，基于核心家庭信息推断胎儿单倍型。构建父母单倍型的 SNP 等位基因频率计算为非参数变量集，与代表胎儿分数（FF）的理论值相反。比较了两种 DNA 富集方法——多重 PCR 扩增和靶向杂交捕获对胎儿浓度计算的影响，并分析了家系内 SNP 的杂合度分布，以揭示模型应用的最佳条件。
两种 DNA 文库构建方法的父系单倍型遗传预测均符合预期，而母系单倍型遗传预测的准确率分别为多重 PCR 扩增法 96.55%和靶向杂交捕获法 95.8%。
阳性预测率表明，母系单倍型预测不如父系单倍型准确，这是由于母亲外周血中存在大量的母体噪声。尽管该模型相对不成熟，但它为单基因疾病的非侵入性产前临床检测提供了一个新的视角。
