Research Paper Volume 13, Issue 20 pp 23527—23544
NEOage clocks - epigenetic clocks to estimate post-menstrual and postnatal age in preterm infants
- 1 Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, GA 30322, USA
- 2 Department of Psychiatry and Human Behavior, Brown University, Providence, RI 02906, USA
- 3 Department of Pediatrics-Neonatology, Children's Mercy Hospital, Kansas City, MO 64108, USA
- 4 Department of Pediatrics, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
- 5 Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
- 6 Department of Pediatrics, Brown Alpert Medical School and Women and Infants Hospital, Providence, RI 02912, USA
- 7 Department of Pediatrics, University of Hawaii John A. Burns School of Medicine, Honolulu, HI 96813, USA
- 8 Department of Pediatrics, Spectrum Health-Helen Devos Hospital, Grand Rapids, MI 49503, USA
- 9 Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
- 10 Brown Center for the Study of Children at Risk, Brown Alpert Medical School and Women and Infants Hospital, Providence, RI 02912, USA
- 11 Department of Psychiatry and Human Behavior, Brown Alpert Medical School, Providence, RI 02906, USA
Received: May 24, 2021 Accepted: September 28, 2021 Published: October 16, 2021
https://doi.org/10.18632/aging.203637How to Cite
Copyright: © 2021 Graw et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Epigenetic clocks based on DNA methylation (DNAm) can accurately predict chronological age and are thought to capture biological aging. A variety of epigenetic clocks have been developed for different tissue types and age ranges, but none have focused on postnatal age prediction for preterm infants. Epigenetic estimators of biological age might be especially informative in epidemiologic studies of neonates since DNAm is highly dynamic during the neonatal period and this is a key developmental window. Additionally, markers of biological aging could be particularly important for those born preterm since they are at heightened risk of developmental impairments. We aimed to fill this gap by developing epigenetic clocks for neonatal aging in preterm infants.
As part of the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) study, buccal cells were collected at NICU discharge to profile DNAm levels in 542 very preterm infants. We applied elastic net regression to identify four epigenetic clocks (NEOage Clocks) predictive of post-menstrual and postnatal age, compatible with the Illumina EPIC and 450K arrays. We observed high correlations between predicted and reported ages (0.93 – 0.94) with root mean squared errors (1.28 - 1.63 weeks).
Epigenetic estimators of neonatal aging in preterm infants can be useful tools to evaluate biological maturity and associations with neonatal and long-term morbidities.
Abbreviations
450k: Infinium HumanMethylation450 BeadChip; AA: Age Acceleration; CpG: Cytosine-phosphate-guanine; EPIC: Infinium MethylationEPIC BeadChip; FDR: False Discovery Rate; GA: Gestational Age; GEO: Gene Expression Omnibus; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; LOO: Leave-One-Out; NEOage: Neonatal Epigenetic Estimator of age; NICU: Neonatal Intensive Care Unit; NOVI: Neonatal Neurobehavior and Outcomes in Very Preterm Infants; PMA: Post-Menstrual Age; PNA: Post-Natal Age; RMSE: Root Mean Squared Error; SNP: single nucleotide polymorphisms.