| Title: | The precision nutrition recommendations based on genomic information |
| Journal: | Precision Nutrition |
| Published: | 25 Mar 2026 |
| DOI: | https://doi.org/10.1097/pn9.0000000000000131 |
Publication 18208
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Abstract
With the increasing prevalence of chronic diseases, contemporary healthcare strategies rooted in life sciences emphasize early prevention over treatment. Conventional diet-based approaches often overlook individual genetic variability in nutritional responses. Here, we propose a precision nutrition framework based on the traditional Chinese medical concept of "Zhi Wei Bing" (Treating without illness). By integrating gene, molecular, and nutrient associations through polygenic risk scores (PRS) and gene annotation, we identify individual risk profiles to enable genome-informed personalized nutrition. To operationalize this framework, we developed multi-threshold PRS models for 55 diseases using genome-wide association studies (GWAS) summary statistics and genomic data from 8293 Asian participants in the UK Biobank. High-risk conditions were identified based on PRS distributions, and associated loci were annotated to determine potential risk genes. A nutrient interaction network was constructed using 1.5 million compound-protein interactions, 1.8 million protein-protein interactions, and 6500 nutritional compounds from STITCH, STRING, and FooDB. Nutrient prioritization was performed using the GeneRank algorithm. The PRS models demonstrated strong predictive accuracy, notably for gallbladder cancer (area under the curve [AUC] = 0.80) and autoimmune hepatitis (AUC = 0.71). For autoimmune hepatitis and periodontitis, eight and nine of the top 10 ranked nutrients, respectively, were supported by existing literature for preventive relevance. At the individual level, personalized recommendations for 20 participants yielded Jaccard similarities between 0.5 and 1.0, demonstrating high personalization. Among the top 20 nutrients for two representative individuals from the "Zhi Wei Bing" cohort, 18 and 17, respectively, were supported by prior studies for disease relevance. These findings highlight the potential of a personalized, genomics-based nutrition strategy. Through tailored dietary recommendations, this approach optimizes the "Zhi Wei Bing" state and reduces disease risk, thereby contributing to effective precision health management. </p>
10 Authors
- Jiaxin He
- Jing Feng
- Ke Yu
- Ziyang Dong
- Lu Shi
- Xiujuan Shi
- Anjiang Jin
- Qifa Zhang
- Jing Gong
- Xiaohui Niu
1 Application
| Application ID | Title |
|---|---|
| 97563 | Facilitating combinatorial drug discovery by targeting epistatic disease genes. |
Enabling scientific discoveries that improve human health