Determining a newborn’s due date traditionally relies on maternal reports of the last menstrual period and ultrasound scans.
These conventional approaches can lead to uncertainties, especially when it comes to identifying deviations from normal fetal development that could impact research into the effects of preterm or post-term births on newborns.
However, researchers, including Kristine Løkås Haftorn, have now developed a more precise method to ascertain newborns’ gestational age through analyzing DNA methylation patterns in blood samples, utilizing machine learning.
This is crucial because accurate knowledge of gestational age is fundamental for understanding the risks and implications of preterm and post-term births on infant health.
Moreover, the ability to accurately determine gestational age in utero could revolutionize prenatal care by providing deeper insights into fetal development, potentially allowing for earlier identification of developmental issues and more tailored interventions to support healthy pregnancies.
This breakthrough, driven by machine learning’s ability to sift through and interpret complex epigenetic information, underscores the potential of combining technology with biology to enhance our understanding of human development.
In this week’s Everything Epigenetics podcast, I speak with Kristine about epigenetic gestational age prediction, how we can use gestational age clocks to look at developmental timing and how this can improve pregnancies, assisted reproductive technology (ART), and more.
Kristine is particularly interested in epigenetic patterns in newborns, how these patterns are linked to development in the fetus and child, and how they can be affected by various exposures during pregnancy.
In this podcast you’ll learn about:
– DNA methylation’s role in fetal development
– Gestational age and how is it linked to fetal development
– Predicting gestational age using epigenetics
– Why determining specific cell types responsible for an association between DNA methylation and a given phenotype important
– How Kristine is adjusting for cell type composition in her work
– What cell-type specific DNA methylation patterns are associated with gestational age
– Nucleated red blood cells
– Why Kristine believes nucleated red blood cells are the main cell type driving the DNAm-GA association
– The poor correlation observed between epigenetic age clocks for newborns and those for adults
– How we can use gestational age clocks to look at developmental timing and how this can improve pregnancies
– Assisted reproductive technology (ART)
– Differences in disease in ART babies and traditional birth babies
– Epigenome-wide association studies of ART
– Investigating CpGs on the X chromosome
– How Kristine’s research will affect ART protocols in the future
Kristine obtained her bachelor’s degree in molecular biology and biochemistry and then a master’s degree in molecular bioscience at the University of Oslo. For her master’s thesis, she worked in Vegard Wyllers group at Akershus University Hospital on regulation of gene expression in adolescents with chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME), focusing on microRNA and DNA methylation. After finishing her masters, Kristine worked as an advisor at the Norwegian Institute of Public Health (NIPH) where her main tasks were to arrange a Norwegian research conference on CFS/ME. After that, she got a PhD position at the Centre for Fertility and Health at NIPH. During her PhD, she has been working on the relationship between gestational age and DNA methylation in cord blood, focusing on prediction models and underlying biological mechanisms using data from the Norwegian Mother, Father and Child Survey (MoBa).
