Associations of four biological age markers with child development: A multi-omic analysis in the European HELIX cohort
Authors: Robinson Oliver , Lau ChungHo E , Joo Sungyeon , Andrusaityte Sandra , Borras Eva , de Prado-Bert Paula , Chatzi Lida , Keun Hector C , Grazuleviciene Regina , Gutzkow Kristine B , Maitre Lea , Martens Dries S , Sabido Eduard , Siroux Valérie , Urquiza Jose , Vafeiadi Marina , Wright John , Nawrot Tim S , Bustamante Mariona , Vrijheid Martine 
Published: June 2023

Background:

While biological age in adults is often understood as representing general health and resilience, the conceptual interpretation of accelerated biological age in children and its relationship to development remains unclear. We aimed to clarify the relationship of accelerated biological age, assessed through two established biological age indicators, telomere length and DNA methylation age, and two novel candidate biological age indicators, to child developmental outcomes, including growth and adiposity, cognition, behavior, lung function and the onset of puberty, among European school-age children participating in the HELIX exposome cohort.

Methods:

The study population included up to 1173 children, aged between 5 and 12 years, from study centres in the UK, France, Spain, Norway, Lithuania, and Greece. Telomere length was measured through qPCR, blood DNA methylation, and gene expression was measured using microarray, and proteins and metabolites were measured by a range of targeted assays. DNA methylation age was assessed using Horvath’s skin and blood clock, while novel blood transcriptome and ‘immunometabolic’ (based on plasma proteins and urinary and serum metabolites) clocks were derived and tested in a subset of children assessed six months after the main follow-up visit. Associations between biological age indicators with child developmental measures as well as health risk factors were estimated using linear regression, adjusted for chronological age, sex, ethnicity, and study centre. The clock derived markers were expressed as Δ age (i.e. predicted minus chronological age).

Results:

Transcriptome and immunometabolic clocks predicted chronological age well in the test set (r=0.93 and r=0.84 respectively). Generally, weak correlations were observed, after adjustment for chronological age, between the biological age indicators.

Among associations with health risk factors, higher birthweight was associated with greater immunometabolic Δ age, smoke exposure with greater DNA methylation Δ age, and high family affluence with longer telomere length.

Among associations with child developmental measures, all biological age markers were associated with greater BMI and fat mass, and all markers except telomere length were associated with greater height, at least at nominal significance (p<0.05). Immunometabolic Δ age was associated with better working memory (p=4 e–3) and reduced inattentiveness (p=4 e–4), while DNA methylation Δ age was associated with greater inattentiveness (p=0.03) and poorer externalizing behaviors (p=0.01). Shorter telomere length was also associated with poorer externalizing behaviors (p=0.03).

Conclusions:

In children, as in adults, biological aging appears to be a multi-faceted process and adiposity is an important correlate of accelerated biological aging. Patterns of associations suggested that accelerated immunometabolic age may be beneficial for some aspects of child development while accelerated DNA methylation age and telomere attrition may reflect early detrimental aspects of biological aging, apparent even in children.

Funding:

UK Research and Innovation (MR/S03532X/1); European Commission (grant agreement numbers: 308333; 874583).