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Yuling Liu

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Review Open access Aug 2026

Genome-Wide Prenatal cfDNA Screening and the Obstetric Incidentalome: Maternal Cancer, Placental Mosaicism, and Pregnancy Risk

Abstract Prenatal cell-free DNA (cfDNA) screening was introduced as a highly accurate test for common fetal aneuploidies, but genome-wide implementation has exposed a broader and more complex clinical landscape. Maternal plasma cfDNA is a composite biological signal rather than a fetal signal in isolation. It contains predominantly maternal cfDNA, a pregnancy-derived placental fraction that serves as the practical fetal proxy in screening, and, in selected circumstances, cfDNA derived from maternal pathological processes. As a result, abnormal, complex, discordant, or nonreportable cfDNA findings may reflect fetal chromosomal disease, confined placental mosaicism (CPM), rare autosomal trisomy (RAT), maternal copy-number variation or mosaicism, benign maternal lesions, vanishing twin, technical artifact, or occult maternal malignancy. This review uses the concept of the “obstetric incidentalome” to integrate these maternal, placental, fetal, and technical findings into a single interpretive model for genome-wide prenatal cfDNA screening. Particular emphasis is placed on unusual cfDNA patterns associated with maternal cancer, rare RATs as potential markers of placental mosaicism and placenta-mediated pregnancy risk, and the diagnostic ambiguity created when placental and fetal genomes differ. We propose that the clinical value of genome-wide cfDNA screening lies less in expanding the catalogue of detectable abnormalities than in resolving the biological origin and clinical relevance of abnormal signals. A coherent clinical pathway should combine fetal diagnostic confirmation, selective maternal evaluation, genetic counseling, and risk-adapted obstetric surveillance while avoiding indiscriminate overdiagnosis. The next phase of evidence should determine whether structured management of the obstetric incidentalome improves maternal and perinatal outcomes beyond diagnostic yield alone.

Meng Xu, Yuling Liu, Meiling Gao et al. · 0 citations

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