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Transcriptomics and functional genetic polymorphisms as biomarkers of micronutrient function: focus on selenium as an
John Hesketh1, Catherine Méplan
1Institute for Cell and Molecular Biosciences and Human Nutrition Research Centre, The Medical School, Newcastle University, Framlington place, Newcastle upon Tyne NE1 4HH, UK.
The Proceedings of the Nutrition Society
|May 12, 2011
Summary
Assessing micronutrient functional status is crucial. Genomic studies on selenium (Se) reveal genetic variations and gene expression changes, offering new biomarkers for health and disease risk.
Area of Science:
- Nutritional Genomics
- Biochemistry
- Molecular Biology
Background:
- Micronutrients are vital for health, but supplementation benefits are not universal, and risks exist.
- Assessing functional micronutrient status is essential for personalized nutrition.
- Genomic techniques offer new insights into micronutrient metabolism and health impacts.
Purpose of the Study:
- To explore the role of genomic research in understanding micronutrient functional status.
- To investigate selenium (Se) as a model micronutrient for studying genetic variations and gene expression.
- To identify novel biomarkers for micronutrient status and disease risk.
Main Methods:
- Gene microarray analysis to study gene expression patterns.
- Single-nucleotide polymorphism (SNP) analysis to identify genetic variations.
- In vitro and in vivo experiments on genes related to selenium metabolism.
Main Results:
- Identified functionally relevant polymorphisms in genes encoding selenoproteins (e.g., glutathione peroxidases, selenoprotein S).
- Replicated association between a selenoprotein S gene polymorphism and colorectal cancer risk.
- Gene microarray studies show Se intake affects inflammatory, stress response, and translation pathways.
Conclusions:
- Selenium (Se) intake and genetic factors interact to influence stress response, inflammation, and apoptosis.
- A systems biology approach combining genomic and nutritional data can identify biomarkers and at-risk populations.
- Further research should combine multiple genetic variants and nutritional status in disease association studies.
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