This review found no clear or consistent evidence that genetic risk communication alone either raises motivation or translates into actual change in dietary intake or physical activity to reduce the risk of cardiometabolic disorders in adults .
Genetic risk prediction of chronic conditions including obesity , diabetes and CVD currently has limited predictive power but its potential to engage healthy behaviour change has been of immense research interest .
We aim ed to underst and whether the latter is indeed true by conducting a systematic review and meta- analysis investigating whether genetic risk communication affects motivation and actual behaviour change towards preventative lifestyle modification .
Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study
Objectives To assess the performance of a panel of common single nucleotide polymorphisms ( genotypes ) associated with type 2 diabetes in distinguishing incident cases of future type 2 diabetes ( discrimination ) , and to examine the effect of adding genetic information to previously vali date d non-genetic ( phenotype based ) models developed to estimate the absolute risk of type 2 diabetes . Design Workplace based prospect i ve cohort study with three 5 yearly medical screenings . Participants 5535 initially healthy people ( mean age 49 years ; 33 % women ) , of whom 302 developed new onset type 2 diabetes over 10 years . Outcome measures Non-genetic variables included in two established risk models — the Cambridge type 2 diabetes risk score ( age , sex , drug treatment , family history of type 2 diabetes , body mass index , smoking status ) and the Framingham offspring study type 2 diabetes risk score ( age , sex , parental history of type 2 diabetes , body mass index , high density lipoprotein cholesterol , triglycerides , fasting glucose)— and 20 single nucleotide polymorphisms associated with susceptibility to type 2 diabetes . Cases of incident type 2 diabetes were defined on the basis of a st and ard oral glucose tolerance test , self report of a doctor ’s diagnosis , or the use of anti-diabetic drugs . Results A genetic score based on the number of risk alleles carried ( range 0 - 40 ; area under receiver operating characteristics curve 0.54 , 95 % confidence interval 0.50 to 0.58 ) and a genetic risk function in which carriage of risk alleles was weighted according to the summary odds ratios of their effect from meta-analyses of genetic studies ( area under receiver operating characteristics curve 0.55 , 0.51 to 0.59 ) did not effectively discriminate cases of diabetes . The Cambridge risk score ( area under curve 0.72 , 0.69 to 0.76 ) and the Framingham offspring risk score ( area under curve 0.78 , 0.75 to 0.82 ) led to better discrimination of cases than did genotype based tests . Adding genetic information to phenotype based risk models did not improve discrimination and provided only a small improvement in model calibration and a modest net reclassification improvement of about 5 % when added to the Cambridge risk score but not when added to the Framingham offspring risk score . Conclusion The phenotype based risk models provided greater discrimination for type 2 diabetes than did models based on 20 common independently inherited diabetes risk alleles . The addition of genotypes to phenotype based risk models produced only minimal improvement in accuracy of risk estimation assessed by recalibration and , at best , a minor net reclassification improvement . The major translational application of the currently known common , small effect genetic variants influencing susceptibility to type 2 diabetes  is likely to come from the insight they provide on causes of disease and potential therapeutic targets
This review found no clear or consistent evidence that genetic risk communication alone either raises motivation or translates into actual change in dietary intake or physical activity to reduce the risk of cardiometabolic disorders in adults .
Genetic risk prediction of chronic conditions including obesity , diabetes and CVD currently has limited predictive power but its potential to engage healthy behaviour change has been of immense research interest .
We aim ed to underst and whether the latter is indeed true by conducting a systematic review and meta- analysis investigating whether genetic risk communication affects motivation and actual behaviour change towards preventative lifestyle modification .