PREVENTOMICS H2020
Published May 23, 2024 | Version v1
Journal article Open

A single-blinded, randomized, parallel intervention to evaluate genetics and omics-based personalized nutrition in general population via an e-commerce tool: The PREVENTOMICS e-commerce study

Creators

  • 1. Eurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit
  • 2. Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Nutrition and Food Safety Research Institute (INSA), Facultat de Farmàcia i Ciències de l'Alimentació, Universitat de Barcelona (UB)
  • 3. Functional Nutrition, Oxidation and Cardiovascular Diseases Group (NFOC-Salut), Facultat de Medicina i Ciències de la Salut, Universitat Rovira i Virgili
  • 4. ROR icon Hospital Universitari Sant Joan de Reus
  • 5. Eurecat, Centre Tecnològic de Catalunya, Digital Health
  • 6. Laboratory of Molecular Biology, Nutrition and Biotechnology (Group of Nutrigenomics, Biomarkers and Risk Evaluation – NuBE), University of the Balearic Islands
  • 7. ROR icon Health Research Institute of the Balearic Islands
  • 8. Centro de investigación Biomédica en red de Fisiopatología de la obesidad y nutrición, Instituto de Salud Carlos III
  • 9. Alimentómica
  • 10. Eurecat Technology Centre

Description

Background

Personalized nutrition (PN) has been proposed as a strategy to increase the effectiveness of dietary recommendations and ultimately improve health status.

Objectives

We aimed to assess whether including omics-based PN in an e-commerce tool improves dietary behavior and metabolic profile in general population.

Methods

A 21-wk parallel, single-blinded, randomized intervention involved 193 adults assigned to a control group following Mediterranean diet recommendations (n = 57, completers = 36), PN (n = 70, completers = 45), or personalized plan (PP, n = 68, completers = 53) integrating a behavioral change program with PN recommendations. The intervention used metabolomics, proteomics, and genetic data to assist participants in creating personalized shopping lists in a simulated e-commerce retailer portal. The primary outcome was the Mediterranean diet adherence screener (MEDAS) score; secondary outcomes included biometric and metabolic markers and dietary habits.

Results

Volunteers were categorized with a scoring system based on biomarkers of lipid, carbohydrate metabolism, inflammation, oxidative stress, and microbiota, and dietary recommendations delivered accordingly in the PN and PP groups. The intervention significantly increased MEDAS scores in all volunteers (control—3 points; 95% confidence interval [CI]: 2.2, 3.8; PN—2.7 points; 95% CI: 2.0, 3.3; and PP—2.8 points; 95% CI: 2.1, 3.4; q < 0.001). No significant differences were observed in dietary habits or health parameters between PN and control groups after adjustment for multiple comparisons. Nevertheless, personalized recommendations significantly (false discovery rate < 0.05) and selectively enhanced the scores calculated with biomarkers of carbohydrate metabolism (β: −0.37; 95% CI: −0.56, −0.18), oxidative stress (β: −0.37; 95% CI: −0.60, −0.15), microbiota (β: −0.38; 95% CI: −0.63, −0.15), and inflammation (β: −0.78; 95% CI: −1.24, −0.31) compared with control diet.

Conclusions

Integration of personalized strategies within an e-commerce–like tool did not enhance adherence to Mediterranean diet or improved health markers compared with general recommendations. The metabotyping approach showed promising results and more research is guaranteed to further promote its application in PN.

Notes

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 818318

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