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Getting biological about the genetics of diabetes

Nature Medicine volume 16, pages 388–391 (2010)Cite this article

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Abstract

New technology has provided methods for collecting large amounts of data reflecting gene expression, metabolite and protein abundance, and post-translational modification of proteins. Integration of these various data sets enable the genetic mapping of many new phenotypes and facilitates the creation of network models that link genetic variation with intermediate traits leading to human disease. The first round of genome-wide association studies has not accounted for common human diseases to the extent that was expected. New phenotyping approaches and methods of data integration should bring these studies closer to their promised goals.

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Figure 1: Constructing causal networks from genetic and molecular phenotyping data sets.

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Authors and Affiliations

  1. Christopher B. Newgard is at the Sarah W. Stedman Nutrition and Metabolism Center and Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA.,

    Christopher B Newgard

  2. Alan D. Attie is in the Department of Biochemistry, University of Wisconsin–Madison, Madison, Wisconsin, USA.,

    Alan D Attie

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  1. Christopher B Newgard
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  2. Alan D Attie
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Correspondence to Christopher B Newgard or Alan D Attie.

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The authors declare no competing financial interests.

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Newgard, C., Attie, A. Getting biological about the genetics of diabetes. Nat Med 16, 388–391 (2010). https://doi.org/10.1038/nm0410-388

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