APOE-lifestyle interactions on age-related health outcomes in the UK Biobank population
Principal Investigator: Dr Raymond Noordam
Approved Research ID: 32292
Approval date: July 2nd 2018
In genome-wide association studies, the APOE gene was associated with multiple aging-related phenotypes (notably Alzheimers disease, cardiovascular disease and mortality). There is increasing evidence in literature that suggests that lifestyle factors (e.g., food intake, physical activity) interact with the variation in the APOE gene in the development of multiple age-related diseases. These interactions are potential promising strategies to prevent or delay disease onset. However, these studies were generally small in total sample size. Therefore, we aim to investigate APOE-lifestyle interactions in relation to age-related diseases in the UK Biobank. The UK Biobank aims to improve prevention, treatment and diagnosis of several life-threating illnesses throughout society. The proposed research will add to a better understanding of the interaction of variation in the APOE gene with lifestyle factors on multiple age-related diseases and mortality. This research aims to add evidence whether there is any need to specifically target APOE risk allele carriers for first-line preventive strategies. This research project may contribute to decrease and delay the development of disease in APOE-risk carriers, in order to improve quality of life and to decrease disease burden and mortality. In the present study, we aim to assess whether the association between APOE genetic variants and age-related diseases (cognition, depression, diabetes and cardiovascular disease) and mortality is modified by different lifestyle factors (notably objectively collected physical activity, nutrition, sleep, alcohol intake and smoking). For the present proposal we will use all participants of the UK Biobank with genotyped data (~500,000 participants maximum; ~100,000 participants with objectively collected physical activity data; ~211.000 participants with diet by 24-hour recall data).