[Impact of Maternal cell contamination on the accuracy of short tandem repeat-based prenatal paternity testing]

To evaluate the influence of varying degrees of maternal cell contamination (MCC) in amniotic fluid samples on the accuracy of short tandem repeat (STR) - based prenatal paternity testing.

A total of 100 cases undergoing prenatal diagnosis were enrolled in the paternity testing study at Huzhou Maternity and Child Health Care Hospital in January 2025 to June 2025. Amniotic fluid samples were collected via ultrasound-guided amniocentesis. Genomic DNA was extracted from amniotic fluid cells and peripheral blood samples of the presumed parents. A multiplex PCR system (STRtyper-21G) was used to amplify 20 autosomal STR loci and one sex-determining marker. Capillary electrophoresis and genotyping were performed using a Sanger sequencer. The incidence and degree of MCC in actual cases were recorded. To assess detection sensitivity, simulated MCC samples were prepared by mixing maternal peripheral blood DNA with fetal DNA at specific ratios to mimic contamination levels of 50.0%, 20.0%, 10.0%, 5.0%, and 2.0%. These samples were analyzed using the same STRtyper-21G system. This study was approved by Medical Ethics Committee of the Huzhou Maternity and Child Health Care Hospital (Ethics No.: 2024-R-005).

Among the 100 amniotic fluid samples, MCC was observed in the following proportions: ≥ 20.0% in 1 case (1.0%), 10.0% - 20.0% in 1 case (1.0%), and 5.0% - 10% in 3 cases (3.0%). Simulation experiments demonstrated that the signal intensity of contamination alleles in electrophoretograms corresponded closely to the proportion of maternal DNA introduced. When MCC was below 5.0%, contaminant allele signals were negligible and did not significantly affect the interpretation of major alleles or the calculation of the paternity index.

MCC is a relatively common phenomenon in STR profiling of amniotic fluid cells. In prenatal paternity testing, it is essential to rigorously analyze STR electrophoretograms, accurately identify and exclude contamination peaks derived from MCC, and precisely calculate the cumulative paternity index to ensure reliable conclusions.