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Open Access 01-12-2021 | Research article

Variability of multi-omics profiles in a population-based child cohort

Authors: Marta Gallego-Paüls, Carles Hernández-Ferrer, Mariona Bustamante, Xavier Basagaña, Jose Barrera-Gómez, Chung-Ho E. Lau, Alexandros P. Siskos, Marta Vives-Usano, Carlos Ruiz-Arenas, John Wright, Remy Slama, Barbara Heude, Maribel Casas, Regina Grazuleviciene, Leda Chatzi, Eva Borràs, Eduard Sabidó, Ángel Carracedo, Xavier Estivill, Jose Urquiza, Muireann Coen, Hector C. Keun, Juan R. González, Martine Vrijheid, Léa Maitre

Published in: BMC Medicine | Issue 1/2021

Abstract

Background

Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood.

Methods

We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability.

Results

All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability.

Conclusions

Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both.

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Title: Variability of multi-omics profiles in a population-based child cohort
Authors: Marta Gallego-Paüls
Carles Hernández-Ferrer
Mariona Bustamante
Xavier Basagaña
Jose Barrera-Gómez
Chung-Ho E. Lau
Alexandros P. Siskos
Marta Vives-Usano
Carlos Ruiz-Arenas
John Wright
Remy Slama
Barbara Heude
Maribel Casas
Regina Grazuleviciene
Leda Chatzi
Eva Borràs
Eduard Sabidó
Ángel Carracedo
Xavier Estivill
Jose Urquiza
Muireann Coen
Hector C. Keun
Juan R. González
Martine Vrijheid
Léa Maitre
Publication date: 01-12-2021
Publisher: BioMed Central
Published in: BMC Medicine / Issue 1/2021
Electronic ISSN: 1741-7015
DOI: https://doi.org/10.1186/s12916-021-02027-z

At a glance: The STEP trials

Springer Medicine

Variability of multi-omics profiles in a population-based child cohort

Abstract

Background

Methods

Results

Conclusions

At a glance: The STEP trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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