Personalized nutrition and healthy aging.

Area of Science:

• Gerontology and Nutritional Science
• Genomics, Epigenomics, and Metabolomics
• Precision Medicine and Public Health

Background:

• Human lifespan and quality of life are influenced by genetic, environmental, and lifestyle factors.
• High-throughput 'omics' technologies have significantly advanced aging research.
• Individual aging rates can be assessed using telomere length, epigenome, and metabolome.

Purpose of the Study:

• To address the incomplete understanding of individual responses to dietary factors in precision nutrition.
• To highlight the challenges in reliable dietary assessment, particularly in elderly populations.
• To emphasize the need for big data techniques in personalized nutrition research.

Main Methods:

• Utilizing high-throughput 'omics' technologies (genomic, epigenomic, metabolomic).
• Assessing individual differences in chronological versus biological age.
• Integrating 'omics' data with objective, longitudinal nutritional and environmental information.

Main Results:

• Current understanding of individual dietary response variability remains incomplete.
• Lack of reliable dietary assessment methods poses a significant challenge.
• Big data techniques are identified as essential for analyzing integrated datasets.

Conclusions:

• Big data analytics are necessary to integrate multi-omics data with nutritional and environmental factors.
• This integration is key to developing effective, personalized dietary advice.
• Actionable, personalized health recommendations can be provided to realize the potential of precision nutrition.