Akash Singh, Banaras Hindu University
Life course approach is based on identifying early indications of health and illness trajectories during pregnancy and childhood. The most critical/sensitive phases for organ development occur during early life, making it particularly vulnerable to the impacts of external exposures. Because it takes a comprehensive picture of all cellular processes, the integration of multiple omics data—such as epigenomics, transcriptomics, proteomics, and metabolomics—is increasingly used to detect early, subtle molecular reactions to environmental exposures.
However, more research into the stability and variability of omics profiles, both between and within healthy children, is urgently needed. In order to evaluate changes in omics profiles, even if they are minor, epidemiological studies that use omics profiles to track healthy people across time must be aware of technical and biological variability. A cohort study was conducted keeping this in mind to study the variability in multi-omics profiles in healthy children.
Omics Variability:
Omics is the discipline of biology that deals with the integrated study of genomics, proteomics, metabolomics, metagenomics, and transcriptomics of the cell. The omics profile of individuals can vary heavily due to population density leading to temporal or seasonal variability. Seasonality, individual characteristics (age and BMI), stage of life (i.e. hormones may vary between pre-puberty and adulthood stages), and technical variability (due to measurement error and the limited precision of analytic tools) can all affect subtle biological changes of interest, and thus must be controlled during the design of the study.
In the study by Gallego-Paüls, M., Hernández-Ferrer, C., Bustamante, M. et al., 156 children from five European countries at two-time points with a 6-month interval were assessed for intra- and inter-individual variability in multi-omics profiles (blood-DNA methylation, gene expression, miRNA, proteins, and serum and urine metabolites) developing a cross-omics network. This network was subsequently analysed to establish clusters of mutually variable omics characteristics and to evaluate the contribution of key variables to the omics variability (even with biological characteristics and collection parameters).
Variable omics analysis:
All of the analysed omics showed a wide range of intra- and inter-individual variability, which depends on each omic feature, although they all showed the highest median intra-individual variability. The most stable profile, with median 37.6% inter-individual variability, was the methylation of DNA. They even identified 1% cross-omics between CpGs and metabolites amongst least stable characteristics (e.g. CpGs related to obesity/type 2 diabetes). Up to 9 per cent of metabolite variability was explained by the explanatory variables including age and body mass index (BMI).
Prospects:
The study confirmed that the omics-profile for individuals can vary temporarily depending upon the external stress factors. They concluded that the most reliable omics to be implemented in one-stop measurement in large cross-sectional studies were methylation and targeted serum metabolomics. The sample collection and individual features of metabolomes (e.g. BMI) constitute important parameters in the study design or analysis stage to control improved comparability.
This study led to the development of a cross-omics network which will help the epidemiologists to design and interpret epidemiological studies that would aim to link omics signatures to disease, environmental exposures, or both.
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Reference:
- Gallego-Paüls, M., Hernández-Ferrer, C., Bustamante, M. et al. Variability of multi-omics profiles in a population-based child cohort. BMC Med19, 166 (2021). https://doi.org/10.1186/s12916-021-02027-z
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Author info:
Akash Singh is a first-year master’s student of Biochemistry at Banaras Hindu University. He plans to pursue Ph.D. in the future. He aims to research and teach the young minds of the country.
Social media links: LinkedIn: https://www.linkedin.com/in/akash-singh-82b5811a2/
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