B2815 - Comparison of polygenic risk scores across cohorts 06-01-2017 - 110415 - 20/04/2017

B number: 
B2815
Principal applicant name: 
Kate Tilling | IEU,SSCM, UoB (United Kingdom)
Co-applicants: 
Professor George Davey Smith, Marcus Munafo, Dr. Amy Taylor, Dr. Neil Davies, Dr Hannah Jones, Dr Evie Stergiakouli, Dr. Hannah Sallis, Dr. Eleanor Sanderson
Title of project: 
Comparison of polygenic risk scores across cohorts (06-01-2017 - 11:04:15)
Proposal summary: 

Members of the ALSPAC cohort (mothers, fathers and their offspring) have been followed up for almost 25 years through regular questionnaires and clinics. ALSPAC aimed to recruit all eligible mothers during their pregnancy – however, there may be some differences between participating and non-participating mothers in terms of social and lifestyle characteristics. Other studies which are used in medical research may be less representative of the general population, and this may lead to biased results. However, for each study, it is hard to identify differences between those who participate and those who don’t, as we only have information on those who participate. In this research we will use genetic variants that are associated with lifestyle factors, for example, education, body mass index and smoking, to assess whether the distributions of each of these factors differ between participants in the ALSPAC study and participants in other studies which may be less representative of the general population. We will also examine differences between participants in ALSPAC and participants in the ARIES substudy, where we know some of the lifestyle factors which differ between these two groups. Understanding whether we can identify factors related to participation from genetic data collected on participants will help researchers to obtain correct results in ALSPAC and in other cohort studies.

Date proposal received: 
Friday, 6 January, 2017
Date proposal approved: 
Monday, 9 January, 2017
Keywords: 
Statistics/methodology, Cohort studies - attrition, bias, participant engagement, ethics, Methods - e.g. cross cohort analysis, data mining, mendelian randomisation, etc., Statistical methods