Variability of multi-omics profiles in a population-based child cohort
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
Affiliations
Marta Gallego-Paüls
ISGlobal
Carles Hernández-Ferrer
ISGlobal
Mariona Bustamante
ISGlobal
Xavier Basagaña
ISGlobal
Jose Barrera-Gómez
ISGlobal
Chung-Ho E. Lau
MRC Centre for Environment and Health, School of Public Health, Imperial College London
Alexandros P. Siskos
Cancer Metabolism & Systems Toxicology Group, Division of Cancer, Department of Surgery & Cancer and Division of Systems Medicine, Department of Metabolism, Digestion & Reproduction, Imperial College London
Marta Vives-Usano
ISGlobal
Carlos Ruiz-Arenas
ISGlobal
John Wright
Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust
Remy Slama
Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Institute for Advanced Biosciences (IAB), Inserm, CNRS, Université Grenoble Alpes
Barbara Heude
Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE
Maribel Casas
ISGlobal
Regina Grazuleviciene
Department of Environmental Sciences, Vytautas Magnus University
Leda Chatzi
Department of Preventive Medicine, Keck School of Medicine, University of Southern California
Eva Borràs
Universitat Pompeu Fabra (UPF)
Eduard Sabidó
Universitat Pompeu Fabra (UPF)
Ángel Carracedo
Medicine Genomics Group, Centro de Investigación Biomédica en Red Enfermedades Raras (CIBERER), University of Santiago de Compostela, CEGEN-PRB3
Xavier Estivill
Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST)
Jose Urquiza
ISGlobal
Muireann Coen
Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London
Hector C. Keun
Cancer Metabolism & Systems Toxicology Group, Division of Cancer, Department of Surgery & Cancer and Division of Systems Medicine, Department of Metabolism, Digestion & Reproduction, Imperial College London
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.
