Treffer: Personalising nutrition and lifestyle recommendations: Analysis of gene-test reports by individual and geographic differences.

Title:
Personalising nutrition and lifestyle recommendations: Analysis of gene-test reports by individual and geographic differences.
Authors:
Chua S; Faculty of Engineering, Computer & Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand., Mohaghegh M; Faculty of Engineering, Computer & Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand., Paul SP; Faculty of Engineering, Computer & Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.; Faculty of Health, Medicine and Behavioural Sciences, University of Queensland, Brisbane, Australia., Miranda V; Faculty of Engineering, Computer & Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.
Source:
Nutrition and health [Nutr Health] 2026 Jan 23, pp. 2601060251415144. Date of Electronic Publication: 2026 Jan 23.
Publication Model:
Ahead of Print
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Sage Country of Publication: England NLM ID: 8306569 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2047-945X (Electronic) Linking ISSN: 02601060 NLM ISO Abbreviation: Nutr Health Subsets: MEDLINE
Imprint Name(s):
Publication: 2012- : London : Sage
Original Publication: Berkhamsted, England : Academic Publishers, 1982-
Contributed Indexing:
Keywords: Personalised nutrition; demographic variations; gene-test reports; genetic risk profiling; hierarchical clustering; nutrigenetics; nutrigenomics; precision healthcare
Entry Date(s):
Date Created: 20260123 Latest Revision: 20260123
Update Code:
20260123
DOI:
10.1177/02601060251415144
PMID:
41574831
Database:
MEDLINE

Weitere Informationen

Introduction: Advances in nutrigenomics have enabled exploration of how genetic variation may relate to nutrition and lifestyle traits. However, the extent to which demographic factors influence the distribution of such variants remains underexplored. Objective: This study examined gender- and region-specific variation in diet- and lifestyle-related genetic traits and described patterns of trait clustering within a cohort of direct-to-consumer gene-test clients. Methods: A cross-sectional analysis was conducted on 503 anonymised gene-test reports covering 41 nutrition- and lifestyle-linked genetic components. Chi-square tests assessed demographic differences in allele frequency distributions. Hierarchical clustering and principal component analysis were applied as exploratory tools to visualise trait patterns. Results: Most individuals exhibited typical genotype distributions, though some demographic differences were observed. Statistically significant gender variation was noted in omega-3/6 metabolism (p = 0.0378). Lactose intolerance showed the greatest regional disparity, disproportionately affecting Asian (p < 0.00001). Marked regional differences were also observed in vitamin-D status (p = 0.0137), omega-3 metabolism (p = 0.0215), pain tolerance (p = 0.0279), fat utilisation (p = 0.0406) and gluten sensitivity (p = 0.0411). Clustering grouped 41 components into 14 sets. Three principal clusters explained 44-80% of the variance. Predictive modelling was limited by incomplete data and class imbalance. Conclusion: This exploratory study highlights modest demographic differences in allele frequencies and demonstrates clustering of nutrition-related genetic traits within a direct-to-consumer dataset. Findings should be interpreted as descriptive signals rather than prescriptive guidance. Future research incorporating phenotypic, biomarker, and outcome data is needed to evaluate functional and clinical significance.