Shaw Joe, Scotchman Elizabeth, Paternoster Ben, Ramos Maureen, Nesbitt Sarah, Sheppard Sophie, Snowsill Tristan, Chitty Lyn S, Chandler Natalie
North Thames Genomic Laboratory Hub, Great Ormond Street NHS Foundation Trust, London, UK.
Health Economics Group, University of Exeter, Exeter, UK.
Prenat Diagn. 2023 Apr;43(4):477-488. doi: 10.1002/pd.6333. Epub 2023 Feb 20.
To develop a flexible droplet digital PCR (ddPCR) workflow to perform non-invasive prenatal diagnosis via relative mutation dosage (RMD) for maternal pathogenic variants with a range of inheritance patterns, and to compare the accuracy of multiple analytical approaches.
Cell free DNA (cfDNA) was tested from 124 archived maternal plasma samples: 88 cases for sickle cell disease and 36 for rare Mendelian conditions. Three analytical methods were compared: sequential probability ratio testing (SPRT), Bayesian and z-score analyses.
The SPRT, Bayesian and z-score analyses performed similarly well with correct prediction rates of 96%, 97% and 98%, respectively. However, there were high rates of inconclusive results for each cohort, particularly for z-score analysis which was 31% overall. Two samples were incorrectly classified by all three analytical methods; a false negative result predicted for a fetus affected with sickle cell disease and a false positive result predicting the presence of an X-linked IDS variant in an unaffected fetus.
ddPCR can be applied to RMD for diverse conditions and inheritance patterns, but all methods carry a small risk of erroneous results. Further evaluation is required both to reduce the rate of inconclusive results and explore discordant results in more detail.
开发一种灵活的液滴数字PCR（ddPCR）工作流程，通过相对突变剂量（RMD）对具有一系列遗传模式的母体致病变异进行无创产前诊断，并比较多种分析方法的准确性。
对124份存档的母体血浆样本中的游离DNA（cfDNA）进行检测：88例镰状细胞病样本和36例罕见孟德尔疾病样本。比较了三种分析方法：序贯概率比检验（SPRT）、贝叶斯分析和z评分分析。
SPRT、贝叶斯分析和z评分分析的表现相似，正确预测率分别为96%、97%和98%。然而，每个队列的不确定结果发生率都很高，尤其是z评分分析，总体为31%。有两个样本被所有三种分析方法错误分类；一个镰状细胞病胎儿被预测为假阴性结果，一个未受影响的胎儿被预测为存在X连锁的艾杜糖醛酸硫酸酯酶（IDS）变异的假阳性结果。
ddPCR可应用于多种情况和遗传模式的RMD，但所有方法都有产生错误结果的小风险。需要进一步评估以降低不确定结果的发生率，并更详细地探讨不一致的结果。
