NGS-BASED NUTRIGENOMIC BIOMARKERS FOR PERSONALIZED NUTRITION: A REVIEW OF THE CURRENT STATE OF RESEARCH
Abstract
The integration of next-generation sequencing (NGS) technology into the area of personalized nutrition provides a breakthrough approach to studying the intricate relationships between food, genetics, and health consequences. By allowing the discovery of nutrigenomic biomarkers, NGS has allowed the customization of dietary recommendations to fit with an individual’s genetic predispositions and metabolic capacity. This innovation promises to enhance the control of dietary responses, optimize nutrient metabolism, and decrease the risk factors linked with nutrition-related chronic illnesses such as obesity, type 2 diabetes, and cardiovascular problems. This review offers a complete examination of the present status of NGS-based biomarker research in personalized nutrition. It investigates the methodology applied in sequencing technology, the finding of gene-diet relationships, and the applicability of such biomarkers in clinical and public health contexts. Particular focus is given to the significance of NGS in identifying genetic variations regulating macronutrient and micronutrient metabolism, gut microbiome composition, and epigenetic changes. Despite the great advances in applying NGS to nutrition research, many hurdles exist. These include the difficulty of data interpretation, the requirement for thorough clinical validation of discovered biomarkers, and the ethical concerns connected to genetic data privacy and fairness in access to customized nutrition services. Furthermore, the integration of multi-omics data, such as transcriptomics, proteomics, and metabolomics, into NGS investigations is critical for a comprehensive understanding of nutrigenomic interactions but remains neglected. Advancing the area of NGS-based customized nutrition will need multidisciplinary cooperation among geneticists, nutritionists, bioinformaticians, and physicians. Additionally, the development of novel approaches, such as machine learning algorithms for data analysis and rigorous clinical trials for biomarker validation, will be vital. As these issues are solved, NGS offers the promise to change nutrition research and enhance public health outcomes by providing extremely accurate and tailored dietary treatments.
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