Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Mini-Review: The Contribution of Intermediate Phenotypes to GxE Effects on Disorders of Body Composition in the New OMICS Era.

International journal of environmental research and public health - 17 Sept 2017

Nava-Gonzalez Edna J, Gallegos-Cabriales Esther C, Leal-Berumen Irene, Bastarrachea Raul A

Abstract excerpt

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...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Body Composition
Share to Diabetes Mellitus, Type 2

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Gene-Environment Interaction

Share to Obesity

Share to Osteoporosis

Share to Phenotype

Source

Open in PubMed Open full text

Identifiers

PMID: 28926971
DOI: 10.3390/ijerph14091079
PMCID: PMC5615616

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Mini-Review: The Contribution of Intermediate Phenotypes to GxE Effects on Disorders of Body Composition in the New OMICS Era.PMID 28926971Read ↗

Advancing translational exposomics: bridging genome, exposome and personalized medicine.Semantic proximity Read ↗

Joint modeling of genomic and exposomic data reveals a substantial GxE component in type 2 diabetes etiologySemantic proximity Read ↗

An integrative analysis of genomic and exposomic data for complex traits and phenotypic predictionSemantic proximity Read ↗

An integrative analysis of genomic and exposomic data for complex traits and phenotypic prediction.Semantic proximity Read ↗

Mapping the Analytical Landscape of Gene-Diet Interactions in Epidemiology: From Classical Models to Causal and Multi-Omics Frameworks.Semantic proximity Read ↗

Holistic Integration of Omics Tools for Precision Nutrition in Health and DiseaseSemantic proximity Read ↗

Nutrigenomics of Obesity: Integrating Genomics, Epigenetics, and Diet–Microbiome Interactions for Precision NutritionSemantic proximity Read ↗

Multi-omics architecture of childhood obesity and metabolic dysfunction uncovers biological pathways and prenatal determinantsSemantic proximity Read ↗

Unraveling phenotypic variance in metabolic syndrome through multi-omics.Semantic proximity Read ↗

Multi-omics approaches for precision obesity managementSemantic proximity Read ↗

Beyond genomics: understanding exposotypes through metabolomics.Semantic proximity Read ↗

Metabolic diseases: the environment determines the odds, even for genes.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.