Nutrigenomics

What This Skill Does

The Nutrigenomics skill is a specialized analytical tool designed to translate raw consumer genetic data into actionable nutritional insights. By processing files from platforms such as 23andMe, AncestryDNA, or standard VCF files, this skill interrogates a curated library of nutritionally-relevant Single Nucleotide Polymorphisms (SNPs). It bridges the gap between raw genomic code and personal health by leveraging data from the GWAS Catalog, ClinVar, and peer-reviewed nutrigenomics research. The tool calculates risk scores for various metabolic pathways, including carbohydrate sensitivity, lipid metabolism, and micronutrient processing efficiency. Outputs include a comprehensive Markdown report, radar charts illustrating nutrient risk profiles, and gene-nutrient heatmaps, all generated locally to ensure data privacy.

Installation

To integrate this skill into your OpenClaw environment, ensure you have Python 3.11+ and the necessary dependencies (pandas, numpy, matplotlib, seaborn, reportlab) installed. Use the following command in your terminal:

clawhub install openclaw/skills/skills/drdaviddelorenzo/nutrigenomics

Ensure your local environment is configured with the correct permissions to read your raw genetic data files before executing the skill.

Use Cases

This skill is intended for individuals, researchers, and health enthusiasts looking to optimize their dietary intake based on biological predispositions. Use cases include identifying potential deficiencies in vitamin absorption (e.g., Vitamin D, Folate), understanding how your body metabolizes macronutrients like fats and carbohydrates, and adjusting your intake of stimulants like caffeine based on genetic metabolic rates. It is particularly useful for those who want to move beyond generic 'one-size-fits-all' diet plans.

Example Prompts

1. "Analyze my 23andMe raw data file to identify my genetic predisposition for folate and omega-3 metabolism."
2. "Based on my uploaded ancestry DNA file, what are my risk scores for the FTO and APOA5 genes regarding fat metabolism?"
3. "Generate a personalised nutrition report focusing on carbohydrate sensitivity and my TCF7L2 variant profile."

Tips & Limitations

• Data Security: All computations are performed locally on your machine. No genetic data is transmitted to external servers.
• Evidence Disclaimer: Nutrigenomics is a developing field. While the curated SNP panel is based on reputable GWAS and clinical studies, results should be used for informational purposes only and never to replace professional medical advice.
• Input Formats: Ensure your input file is clean and in the correct format (.txt, .csv, or .vcf) as exported directly from your testing provider to avoid parsing errors.