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Approved research

Developing Methodology to Identify Genetic Factors Associated with Physical Activity

Principal Investigator: Professor Michael Swartz
Approved Research ID: 16740
Approval date: July 1st 2016

Lay summary

Physical activity is a complex behavior that is known to play an integral role in determining human health conditions. However, little is known on whether any genetic factors influence physical activity levels. The primary aim of this study is to develop a new statistical model to facilitate finding genetic markers associated with the frequency and duration of physical activity in real life conditions in healthy individuals, as part of a student's thesis development. We will use the data available from UK Biobank to assess and fine tune the method?s performance. The proposed research meets one of the UK Biobank?s objectives to improve the prevention of illnesses as well as promoting health throughout society. It is well known that physical activity levels are associated with health. This study will develop methodology to investigate genetic risk factors associated with physical activity levels. Identifying genetic factors associated with physical activity levels will offer insight into developing new personalized interventions to increase physical activity. The methods developed will be freely available for application to the UK biobank data after the UK Biobank genetic data are complete. We will use our own developed methods to process the raw accelerometer data for available individuals to obtain their levels of physical activity over the seven day measurement period. We will summarize the frequency, intensity, and duration of the physical activity of these individuals. We will compare our metrics to those derived from the UK Biobank Expert Working Group. We will also develop new statistical approaches to explore associations between multiple genetic markers and physical activity characteristics. We will report preliminary associations in the current data available from UK biobank (~30,000 individuals with both genetic and accelerometer data). We are requesting all individuals who have accelerometer data available, and the subset of the cohort who have both accelerometer data and genetic data available. As of 11/30/2015 the estimated number of participants in the UK Biobank with accelerometer data is n=100,266. In addition, we request genotype data from participants currently available. (n=30,229 with both genetic and accelerometer data available). We are also requesting the derived measures from the accelerometer data generated by the UK Biobank Physical Activity Expert Working Group.