Principal Investigator: Dr James Wilson
Department: Centre for Population Sciences
Institution: University of EdinburghTags: 8304, Association, biomarkers, lifespan, longevity, mortality, prediction
1a: The determinants of longevity are of wide interest and have been studied for over 100 years. Human lifespan is influenced by both genetic and environmental factors. We propose to study longevity in UK Biobank to better understand genetic and biological markers of lifespan, not focussed on one health condition but on overall mortality. We shall use the unprecedented scale and rich data of Biobank to investigate the degree to which lifespan is inherited, using the latest genomic methods, we shall then search for genetic variants and biomarkers which influence lifespan and estimate how well it is possible to predict lifespan.
1b: The proposed research is clearly in the public interest: individuals, health services, and the insurance and pensions industry will benefit from a better understanding of the genetic and environmental influences on lifespan and ageing. There is a clear relationship to health and illness – mortality being the ultimate end point.
1c: We propose to analyse longevity in a number of ways. (a) Assess the degree to which lifespan is genetic, using new methods designed for unrelated people. (b) Search across the genome for regions that are associated with longer or shorter survival. (c) Use the DNA sharing between individuals to try to predict lifespan in UK Biobank and compare to how this works in other populations available to us where individuals area all related and so share more DNA. (d) Assess the contribution of environmental factors and biomarkers such as albumin to lifespan.
1d: The research will focus on the ~9,000 individuals who are already deceased and recapture data towards the end of 2015 when complete genotype information is available, but will also use data for all participants.
PROJECT EXTENSION – APPROVED BY UK BIOBANK 07.10.2015
Request received to extend application 8304 to disease in the context of lifespan, and thus avoid any ambiguity.
“We wish to study the association with lifespan of diseases in offspring and parent (and the other traits we already have access to, e.g. education and height), through use of linear models and disease as a binary explanatory factor. In particular, we also wish to look at SNPs singly and collectively, previously known or discovered by us in UKB using conventional GWAS techniques, to associate with disease and their effect on longevity, akin to Mendelian randomisation. Should we discover robust disease associations with genetic variants, individually or collectively, we would report these in their own right, as well as their consequences on lifespan, using Cox models.
For genetic variants that individually or collectively are associated with longevity we wish to examine which if any diseases associate with the variant, by measuring the association between SNP and each disease, using logistic regression.
We would like to measure pleiotropy in the context of lifespan: the degree to which a variant causing one disease may increase or reduce the risk of other diseases and the resultant overall magnified or diluted effect on lifespan, using Cox models and logistic regression”.
“We are also interested in exploring whether some non-disease characteristics are related to lifespan, and have been using height and weight for this purpose”.
PROJECT EXTENSION – APPROVED BY UK BIOBANK 29.09.2015
“We wish to extend our investigations into longevity to more fully cover cognitive capacity. The broad intention is to look at similarities and differences in the genetic basis of cognition and lifespan, through GWAS of each trait and bivariate analysis. This was always our intention, and we had not realised that age at which left education would be missing for those who went to college. We therefore would specifically like field 6183 (qualifications) to complement the field we already have. On further consideration and consistent with the approach we originally envisaged, we would also like to have all the fields in category 10026 (cognitive tests).
Indeed we would like to extend our lifespan analysis further, similar to cognition to cover wider psychosocial aspects (ie all fields in category 100060). Because evolutionary theory suggests there may be pleiotropy between fertility, fecundity and longevity, we would like to also extend our analysis of common genetic bases to the male and female sex specific categories (10068 and 10069).”
Last updated Oct 15, 2015