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Curr Diab Rep. 2016 Jul;16(7):57. doi: 10.1007/s11892-016-0758-y.

Putting the Genome in Context: Gene-Environment Interactions in Type 2 Diabetes.

Franks PW1,2,3, Paré G4,5,6,7.

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Genetic and Molecular Epidemiology Unit, Lund University Diabetes Center, Department of Clinical Sciences, Clinical Research Center, Skåne University Hospital Malmö, Lund University, Building 91, Level 10, Jan Waldenströms gata 35, 205 02, Malmö, Sweden.
Department of Public Health and Clinical Medicine, Umeå University, 90188, Umeå, Sweden.
Department of Nutrition, Harvard School of Public Health, Boston, MA, 02115, USA.
Population Health Research Institute, McMaster University, Hamilton General Hospital Campus, DB-CVSRI, 237 Barton Street East, Room C3103, Hamilton, ON, L8L 2X2, Canada.
Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada.
Department of Clinical Epidemiology and Biostatistics, Population Genomics Program, McMaster University, Hamilton, ON, Canada.
Thrombosis and Atherosclerosis Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada.


The genome is often the conduit through which environmental exposures convey their effects on health and disease. Whilst not all diseases act by directly perturbing the genome, the phenotypic responses are often genetically determined. Hence, whilst diseases are often defined has having differing degrees of genetic determination, genetic and environmental factors are, with few exceptions, inseparable features of most diseases, not least type 2 diabetes. It follows that to optimize diabetes, prevention and treatment will require that the etiological roles of genetic and environmental risk factors be jointly considered. As we discuss here, studies focused on quantifying gene-environment and gene-treatment interactions are gathering momentum and may eventually yield data that helps guide health-related choices and medical interventions for type 2 diabetes and other complex diseases.


Cardiometabolic; Gene-lifestyle interaction; Genomic; Genotype-based recall; Obesity; Recall by genotype; Systems biology; Variance heterogeneity

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