Genome-scale models in human metabologenomics

Summary

This 2024 Nature Reviews Genetics article synthesises the application of genome-scale metabolic models as computational platforms for integrating genomic and multi-omics data in human metabologenomics. The authors propose that mechanistic computational approaches may support precision health and personalised nutrition strategies by predicting individual metabolic phenotypes, though they acknowledge that clinical validation and robust integration into routine practice remain outstanding challenges. The review suggests significant potential for advancing understanding of inter-individual metabolic variation, though practical adoption in clinical settings requires substantial further methodological and translational development.

Regional applicability

As a methodological and computational review with no specific geographic focus, the findings are theoretically applicable to precision nutrition research and clinical practice in the United Kingdom and globally. However, implementation would depend on access to appropriate cohort data, computational infrastructure, and integration into UK clinical genomics and personalised medicine pathways, which remain in early stages of development.

Key measures

Genome-scale metabolic model development, multi-omics integration, inter-individual metabolic variation prediction, clinical validation status

Outcomes reported

The article examines computational genome-scale metabolic models as tools for integrating genomic and multi-omics data to predict individual metabolic phenotypes. It synthesises evidence on potential applications to precision health and personalised nutrition, whilst identifying barriers to clinical implementation.

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