Abstract
Non-invasive prenatal testing (NIPT) has revolutionized prenatal diagnostics by providing a safer alternative to invasive techniques such as amniocentesis and chorionic villus sampling. NIPT detects chromosomal abnormalities through the analysis of cell-free fetal DNA (cffDNA) in maternal plasma. One of the critical factors influencing accuracy of NIPT is the fetal fraction (FF) - the proportion of fetal cell-free DNA relative to total cell-free DNA in maternal plasma. This study investigates the potential of using telomere length measurements as a novel biomarker for fetal fraction prediction in NIPT. Telomere-derived fragments, which differ between maternal and fetal DNA, may serve as a measure of FF due to the distinct telomere length. Specifically, deviations from the expected shorter telomere lengths of maternal DNA toward longer lengths could be more pronounced at higher FF levels. Various models incorporating telomere content and features selected by Ordinary Least Squares (OLS) were evaluated to enhance fetal fraction prediction. Our results showed that telomere content also works as an independent predictor (with Pearson correlation 0.23), yielding a small improvement in prediction precision when combined with traditional models.