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Author Notes:

The authors thank J.F. Gregory, E.O. Voit, Y.-M. Go, J.R. Roede and Q.A. Soltow for helpful comments during manuscript preparation.

The authors are not aware of any affiliations, memberships, funding or financial holdings that might be perceived as affecting the objectivity of this review.

Subjects:

Research Funding:

DPJ is a Professor of Medicine supported in part by NIH Grants ES009047, ES011195, AG038746, NR012021, AA013757, ES016731, DK069322 and DK089369.

YP is an Assistant Professor of Medicine supported in part by NIH Grants AG038746, ES016731, DK089369, RR023356 and Children’s Healthcare of Atlanta Center for Developmental Lung Biology.

TRZ is a Professor of Medicine supported in part by NIH Grants DK069322, DK089369, HL110044, RR023356 and RR025008 and the Emory Global Health Institute.

Keywords:

  • Systems biology
  • microbiome
  • prevention
  • mass spectrometry
  • personalized medicine
  • exposome

Nutritional metabolomics: Progress in addressing complexity in diet and health

Tools:

Journal Title:

Annual Review of Nutrition

Volume:

Volume 32

Publisher:

, Pages 183-202

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Nutritional metabolomics is rapidly maturing to use small molecule chemical profiling to support integration of diet and nutrition in complex biosystems research. These developments are critical to facilitate transition of nutritional sciences from population-based to individual-based criteria for nutritional research, assessment and management. This review addresses progress in making these approaches manageable for nutrition research. Important concept developments concerning the exposome, predictive health and complex pathobiology, serve to emphasize the central role of diet and nutrition in integrated biosystems models of health and disease. Improved analytic tools and databases for targeted and non-targeted metabolic profiling, along with bioinformatics, pathway mapping and computational modeling, are now used for nutrition research on diet, metabolism, microbiome and health associations. These new developments enable metabolome-wide association studies (MWAS) and provide a foundation for nutritional metabolomics, along with genomics, epigenomics and health phenotyping, to support integrated models required for personalized diet and nutrition forecasting.

Copyright information:

© 2012, Annual Reviews

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