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A new blood based epigenetic age predictor for adolescents and young adults

Aanes Håvard.; Bleka Øyvind; Dahlberg Pål S.; Carm Kristina T.; Lehtimäki Terho; Raitakari Olli; Kähönen Mika; Hurme Mikko; Rolseth Veslemøy

A new blood based epigenetic age predictor for adolescents and young adults

Aanes Håvard.
Bleka Øyvind
Dahlberg Pål S.
Carm Kristina T.
Lehtimäki Terho
Raitakari Olli
Kähönen Mika
Hurme Mikko
Rolseth Veslemøy
Katso/Avaa
s41598-023-29381-7.pdf (1.158Mb)
Lataukset: 

Nature Research
doi:10.1038/s41598-023-29381-7
URI
https://www.nature.com/articles/s41598-023-29381-7
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2023040535092
Tiivistelmä

Children have special rights for protection compared to adults in our society. However, more than 1/4 of children globally have no documentation of their date of birth. Hence, there is a pressing need to develop biological methods for chronological age prediction, robust to differences in genetics, psychosocial events and physical living conditions. At present, DNA methylation is the most promising biological biomarker applied for age assessment. The human genome contains around 28 million DNA methylation sites, many of which change with age. Several epigenetic clocks accurately predict chronological age using methylation levels at age associated GpG-sites. However, variation in DNA methylation increases with age, and there is no epigenetic clock specifically designed for adolescents and young adults. Here we present a novel age Predictor for Adolescents and Young Adults (PAYA), using 267 CpG methylation sites to assess the chronological age of adolescents and young adults. We compared different preprocessing approaches and investigated the effect on prediction performance of the epigenetic clock. We evaluated performance using an independent validation data set consisting of 18-year-old individuals, where we obtained a median absolute deviation of just below 0.7 years. This tool may be helpful in age assessment of adolescents and young adults. However, there is a need to investigate the robustness of the age predictor across geographical and disease populations as well as environmental effects.

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