Getting biological about the genetics of diabetes.
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.
Newgard
Christopher B
CB
Sarah W. Stedman Nutrition and Metabolism Center and Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, USA. newga002@mc.duke.edu
Attie
Alan D
AD
D000818:Animals; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics*; D004195:Disease Models, Animal; D020022:Genetic Predisposition to Disease / Q000235:genetics; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D055432:Metabolomics; D051379:Mice; D020411:Oligonucleotide Array Sequence Analysis; D010641:Phenotype