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    Home»Pregnancy»Cell-Free DNA May Predict Pregnancy Complications
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    Cell-Free DNA May Predict Pregnancy Complications

    adminBy adminAugust 29, 2026No Comments3 Mins Read
    Cell-Free DNA May Predict Pregnancy Complications
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    CELL-FREE DNA patterns detectable during the first trimester could help identify patients at increased risk of pregnancy complications before clinical warning signs emerge, according to new research. 

    The study suggests that information already contained within prenatal blood samples could provide a new way to stratify high-risk pregnancies and potentially allow clinicians to intensify monitoring and care earlier. 

    DNA Fragmentation Reveals Pregnancy Risk 

    Researchers in Belgium analysed 1,910 first-trimester blood samples from pregnant individuals, including low-risk pregnancies and those considered at higher risk of adverse pregnancy outcomes because of twin pregnancy, pre-existing immune-mediated disease, or cytomegalovirus infection. 

    Rather than focusing only on the genetic sequence of cell-free DNA (cfDNA), the researchers examined its fragmentome: characteristics of how DNA molecules circulating in the blood have been fragmented.  

    Their analysis incorporated multiple features, including DNA fragment length profiles, frequencies of sequences found at fragment ends, and estimates of the cell types contributing cfDNA. 

    Using these features, the team developed models capable of distinguishing the high-risk pregnancy groups from low-risk controls, with the exception of diabetes. 

    Hidden Risk in Immune-Mediated Disease 

    One of the most striking findings emerged among patients with immune-mediated diseases. The researchers identified a distinct cfDNA fragmentomic profile associated with adverse pregnancy outcomes, even among patients whose disease was clinically quiescent and serologically inactive during early pregnancy. 

    At a fixed 10% false-positive rate, fragmentomic analysis correctly identified 54% of patients with systemic immune-mediated disease who subsequently experienced an adverse pregnancy outcome. Detection reached 38% for thyroid-related immune disease, 73% for Crohn’s disease, and 90% for psoriasis. 

    Importantly, the researchers validated their findings in an independent cohort of pregnant patients with immune-mediated diseases from an external centre, strengthening evidence that the observed signal was not restricted to the original study population. 

    Potential for Earlier Pregnancy Triage 

    The fragmentomic information also provided predictive value independent of, and additional to, established clinical risk factors and fetal fraction measurements, indicating that it may capture biological information that conventional assessments miss. 

    Cell-free DNA testing is already widely used during pregnancy for non-invasive prenatal screening. These findings raise the possibility that the same type of blood sample could eventually provide information not only about fetal chromosomal abnormalities, but also about the wider biological state of the pregnancy and risk of later complications. 

    Further prospective research will be needed to establish how fragmentomic testing performs across larger and more diverse populations and whether using these predictions to guide clinical management improves maternal and fetal outcomes.  

    However, the researchers suggest that cfDNA fragmentomics could ultimately provide a new tool for early triage of high-risk pregnancies, allowing enhanced surveillance and care to begin before complications become clinically apparent. 

    Reference 

    Stanley KE et al. Cell-free DNA fragmentome analysis informs pregnancy outcome in patients with immune-mediated disease. Sci Transl Med. 2026;18(863). 

    Featured image: Maria Sbytova on AdobeStock 

    Author:
    Cecilia Adamou

    CellFree Complications Predict Pregnancy
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    Balochistan Government and National AI Hub Partner on AI-Driven Healthcare

    By adminSeptember 11, 2026

    The Government of Balochistan and the National AI Hub for Maternal, Newborn and Child Health (MNCH) at LUMS have signed an MoU to advance the use of artificial intelligence (AI), digital innovation, and evidence-informed decision-making to strengthen maternal, newborn, and child health services across Balochistan

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