ArticleFrontiers in medicine2026
A bespoke non-invasive approach to predict fetal genotype in pregnancy.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
Introduction: The fetal genome influences fetal growth; however, it is currently not used to customize fetal growth charts due to the need for invasive testing. Total cell-free-DNA (T-cfDNA) from maternal blood during pregnancy contains maternal-cfDNA and fetal-cfDNA. T-cfDNA offers the opportunity to non-invasively determine fetal single nucleotide polymorphisms (SNPs). This study aimed to determine the feasibility of genotyping fetal SNPs in pregnancy using parental genomic-DNA (gDNA) and maternal T-cfDNA, and computing fetal polygenic scores (PGS) as proxies for several health domains. Methods: Parental and cord blood gDNA, and maternal T-cfDNA were collected. Genotyping was performed using Illumina Global Screening Array. Signal intensity parameters (SIPs) were extracted for genotyped SNPs. Fetal SNPs were predicted using corresponding paired parental SNPs when both parents were homozygous, and from maternal gDNA SIP confidence intervals otherwise. Six PGSs for phenotypes including birthweight-PGS were computed using predicted fetal SNPs. Predictions were verified against genotyped cord blood. Results: The average fetal SNP prediction accuracy was 86.39% (95% CI: 85.94-86.84%). Improved performance was observed when computing PGSs with a greater number of SNPs; coefficient of variation ranged from 5.6-16.5%. Discussion: Results suggested moderate predictive performance. Improvements in the accuracy of SNP prediction are needed before clinical implementation. This may be through advanced bioinformatics methods or genotyping methodology.
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