Abstract
Studies of gene-environment (GxE) interactions describe how genetic and environmental factors influence the risk of developing disease. Intermediate (molecular or clinical) phenotypes (IPs) are traits or metabolic biomarkers that mediate the effects of gene-environment influences on risk behaviors. Functional systems genomics discovery offers mechanistic insights into how DNA variations affect IPs in order to detect genetic causality for a given disease. Disorders of body composition include obesity (OB), Type 2 diabetes (T2D), and osteoporosis (OSTP). These pathologies are examples of how a GxE interaction contributes to their development. IPs as surrogates for inherited genotypes play a key role in models of genetic and environmental interactions in health outcomes. Such predictive models may unravel relevant genomic and molecular pathways for preventive and therapeutic interventions for OB, T2D, and OSTP. Annotation strategies for genomes, in contrast to phenomes, are well advanced. They generally do not measure specific aspects of the environment. Therefore, the concepts of deep phenotyping and the exposome generate new avenues to exploit with high-resolution technologies for analyzing this sophisticated phenome. With the successful characterization of phenomes, exposomes, and genomes, environmental and genetic determinants of chronic diseases can be united with multi-OMICS studies that better examine GxE interactions.
Highlights
In the past, disorders of body composition (OSTP, OB, and Type 2 diabetes (T2D)) were thought to be independent of one another
The results of paper this paper presented the relevance of a predictive utilizing intermediate phenotypes of bodyof composition and adipose metabolism, including model utilizing intermediate phenotypes body composition and tissue adipose tissue metabolism, metabolic metabolic biomarkers related to the insulin-glucose axis, allowing with Bone mineral density (BMD) variation in including biomarkers related to the insulin-glucose axis,correlations allowing correlations with BMD
Biological systems multi-omics can potentially be characterized at several levels: at the genomic level through single-nucleotide polymorphism (SNP), copy number variation (CNV); at the epigenome level through DNA methylation, histone modification, and micro RNA; gene expression and alternative splicing at the transcriptome level; protein expression and post-translational modification at the proteome level; and metabolite profiling at the metabolome level, and, at the phenome and exposome level [46]
Summary
Disorders of body composition (OSTP, OB, and T2D) were thought to be independent of one another. The effects of GxE interactions on molecular biomarkers or intermediate phenotypes, such as those involved in fat tissue metabolism, the insulin-glucose axis, and bone mineral turnover, have been reported in recent literature [7]. A unified definition for intermediate phenotype, endophenotype, or biomarkers is intended, these terms are mainly used to designate a connection between the genome, the environment (exposome), risk behaviors, and health outcomes. These IPs are placed at the crossroad where GxE and disease risk intersect. This paper highlights the importance of integrating the exposome and phenome with the new trend of investigating the genome through a multi-OMICS approach to better characterize GxE interactions
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