Non-invasive fetal genotyping for maternal alleles with droplet digital PCR: A comparative study of analytical approaches.

OBJECTIVES: 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.

METHODS: cfDNA was tested from one hundred and twenty-four 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.

RESULTS: 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.

CONCLUSIONS: 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. This article is protected by copyright. All rights reserved.