Literature DB >> 31611402

The PedBE clock accurately estimates DNA methylation age in pediatric buccal cells.

Lisa M McEwen1, Kieran J O'Donnell2,3, Megan G McGill2, Rachel D Edgar1, Meaghan J Jones1, Julia L MacIsaac1, David Tse Shen Lin1, Katia Ramadori1, Alexander Morin1, Nicole Gladish1, Elika Garg2, Eva Unternaehrer2, Irina Pokhvisneva2, Neerja Karnani4,5, Michelle Z L Kee4, Torsten Klengel6, Nancy E Adler3,7,8, Ronald G Barr3,9, Nicole Letourneau10,11, Gerald F Giesbrecht10,12, James N Reynolds13, Darina Czamara14, Jeffrey M Armstrong15, Marilyn J Essex15, Carolina de Weerth16, Roseriet Beijers17, Marieke S Tollenaar18, Bekh Bradley19, Tanja Jovanovic19, Kerry J Ressler6, Meir Steiner20, Sonja Entringer21,22, Pathik D Wadhwa22,23,24,25, Claudia Buss21, Nicole R Bush7, Elisabeth B Binder3,14,19, W Thomas Boyce3,7,8, Michael J Meaney2,3,4,26, Steve Horvath27,28, Michael S Kobor29,3.   

Abstract

The development of biological markers of aging has primarily focused on adult samples. Epigenetic clocks are a promising tool for measuring biological age that show impressive accuracy across most tissues and age ranges. In adults, deviations from the DNA methylation (DNAm) age prediction are correlated with several age-related phenotypes, such as mortality and frailty. In children, however, fewer such associations have been made, possibly because DNAm changes are more dynamic in pediatric populations as compared to adults. To address this gap, we aimed to develop a highly accurate, noninvasive, biological measure of age specific to pediatric samples using buccal epithelial cell DNAm. We gathered 1,721 genome-wide DNAm profiles from 11 different cohorts of typically developing individuals aged 0 to 20 y old. Elastic net penalized regression was used to select 94 CpG sites from a training dataset (n = 1,032), with performance assessed in a separate test dataset (n = 689). DNAm at these 94 CpG sites was highly predictive of age in the test cohort (median absolute error = 0.35 y). The Pediatric-Buccal-Epigenetic (PedBE) clock was characterized in additional cohorts, showcasing the accuracy in longitudinal data, the performance in nonbuccal tissues and adult age ranges, and the association with obstetric outcomes. The PedBE tool for measuring biological age in children might help in understanding the environmental and contextual factors that shape the DNA methylome during child development, and how it, in turn, might relate to child health and disease.

Entities:  

Keywords:  DNA methylation; adolescence; age; development; epigenetic clock

Year:  2019        PMID: 31611402     DOI: 10.1073/pnas.1820843116

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  34 in total

1.  Current perspectives on the cellular and molecular features of epigenetic ageing.

Authors:  Kenneth Raj; Steve Horvath
Journal:  Exp Biol Med (Maywood)       Date:  2020-04-10

2.  Autosomal sex-associated co-methylated regions predict biological sex from DNA methylation.

Authors:  Evan Gatev; Amy M Inkster; Gian Luca Negri; Chaini Konwar; Alexandre A Lussier; Anne Skakkebaek; Marla B Sokolowski; Claus H Gravholt; Erin C Dunn; Michael S Kobor; Maria J Aristizabal
Journal:  Nucleic Acids Res       Date:  2021-09-20       Impact factor: 16.971

3.  Estimage: a webserver hub for the computation of methylation age.

Authors:  Pietro Di Lena; Claudia Sala; Christine Nardini
Journal:  Nucleic Acids Res       Date:  2021-07-02       Impact factor: 16.971

4.  Associations of DNA Methylation Mortality Risk Markers with Congenital Microcephaly from Zika Virus: A Study of Brazilian Children Less than 4 Years of Age.

Authors:  Jamaji C Nwanaji-Enwerem; Lars Van Der Laan; Elorm F Avakame; Kristan A Scott; Heather H Burris; Andres Cardenas
Journal:  J Trop Pediatr       Date:  2021-01-29       Impact factor: 1.165

Review 5.  Social epigenomics: are we at an impasse?

Authors:  Amy L Non
Journal:  Epigenomics       Date:  2021-03-22       Impact factor: 4.778

6.  Saliva cell type DNA methylation reference panel for epidemiological studies in children.

Authors:  Lauren Y M Middleton; John Dou; Jonah Fisher; Jonathan A Heiss; Vy K Nguyen; Allan C Just; Jessica Faul; Erin B Ware; Colter Mitchell; Justin A Colacino; Kelly M Bakulski
Journal:  Epigenetics       Date:  2021-02-22       Impact factor: 4.528

7.  Socioeconomic Disadvantage and the Pace of Biological Aging in Children.

Authors:  Laurel Raffington; Daniel W Belsky; Meeraj Kothari; Margherita Malanchini; Elliot M Tucker-Drob; K Paige Harden
Journal:  Pediatrics       Date:  2021-05-17       Impact factor: 9.703

Review 8.  The use of DNA methylation clock in aging research.

Authors:  Xi He; Jiaojiao Liu; Bo Liu; Jingshan Shi
Journal:  Exp Biol Med (Maywood)       Date:  2020-11-11

9.  Childhood adversity correlates with stable changes in DNA methylation trajectories in children and converges with epigenetic signatures of prenatal stress.

Authors:  Jade Martins; Darina Czamara; Susann Sauer; Monika Rex-Haffner; Katja Dittrich; Peggy Dörr; Karin de Punder; Judith Overfeld; Andrea Knop; Felix Dammering; Sonja Entringer; Sibylle M Winter; Claudia Buss; Christine Heim; Elisabeth B Binder
Journal:  Neurobiol Stress       Date:  2021-05-13

10.  Characterization of DNA Methylomic Signatures in Induced Pluripotent Stem Cells During Neuronal Differentiation.

Authors:  Jennifer Imm; Ehsan Pishva; Muhammadd Ali; Talitha L Kerrigan; Aaron Jeffries; Joe Burrage; Enrico Glaab; Emma L Cope; Kimberley M Jones; Nicholas D Allen; Katie Lunnon
Journal:  Front Cell Dev Biol       Date:  2021-07-01
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