| Application: | 8304, Genetics of human lifespan ? heritability, association and prediction |
| Title: | Genomics of 1 million parent lifespans implicates novel pathways and common diseases and distinguishes survival chances |
| Size: | 2.3 MB |
| Archived: | 27 Nov 2020 |
| Stability: | Complete |
| Personal: | No individual-level data |
Return 2898
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Notes
Timmers et al. used genetic data from UK Biobank and other European cohorts alongside information on their parents lifespans to pinpoint DNA regions that influence how long people live. They identified 12 such regions, of which five were new and had not been linked to lifespan before. Across the twelve as a whole several were known to be involved in Alzheimer s disease, smoking-related cancer or heart disease. Looking at the entire genome, Timmers et al. could then predict a lifespan score for each individual, and when they sorted participants into ten groups based on these scores, they found that top group lived five years longer than the bottom, on average.Application 8304
Genetics of human lifespan ? heritability, association and prediction
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. 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. 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. 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.
| Lead investigator: | Professor James Wilson |
| Lead institution: | University of Edinburgh |
2 related Returns
| Return ID | App ID | Description | Archive Date |
|---|---|---|---|
| 2174 | 8304 | Genetic variants linked to education predict longevity | 15 Apr 2020 |
| 263 | 8304 | Variants near CHRNA3/5 and APOE have age- and sex-related effects on human lifespan. | 14 Jun 2016 |
1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 2895 | Genomics of 1 million parent lifespans implicates novel pathways and common diseases and distinguishes survival chances | Timmers PR et al. | 2019 | Elife |
Enabling scientific discoveries that improve human health