| Title: | The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank |
| Journal: | GeroScience |
| Published: | 7 Mar 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38451433/ |
| DOI: | https://doi.org/10.1007/s11357-024-01107-1 |
Publication 8540
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Abstract
Large-scale genome-wide association studies (GWAS) strongly suggest that most traits and diseases have a polygenic component. This observation has motivated the development of disease-specific "polygenic scores (PGS)" that are weighted sums of the effects of disease-associated variants identified from GWAS that correlate with an individual's likelihood of expressing a specific phenotype. Although most GWAS have been pursued on disease traits, leading to the creation of refined "Polygenic Risk Scores" (PRS) that quantify risk to diseases, many GWAS have also been pursued on extreme human longevity, general fitness, health span, and other health-positive traits. These GWAS have discovered many genetic variants seemingly protective from disease and are often different from disease-associated variants (i.e., they are not just alternative alleles at disease-associated loci) and suggest that many health-positive traits also have a polygenic basis. This observation has led to an interest in "polygenic longevity scores (PLS)" that quantify the "risk" or genetic predisposition of an individual towards health. We derived 11 different PLS from 4 different available GWAS on lifespan and then investigated the properties of these PLS using data from the UK Biobank (UKB). Tests of association between the PLS and population structure, parental lifespan, and several cancerous and non-cancerous diseases, including death from COVID-19, were performed. Based on the results of our analyses, we argue that PLS are made up of variants not only robustly associated with parental lifespan, but that also contribute to the genetic architecture of disease susceptibility, morbidity, and mortality.</p>
15 Authors
- Janith Don
- Andrew J. Schork
- Gwênlyn Glusman
- Noa Rappaport
- Steve R. Cummings
- David Duggan
- Anish Raju
- Kajsa-Lotta Georgii Hellberg
- Sophia Gunn
- Stefano Monti
- Thomas Perls
- Jodi Lapidus
- Laura H. Goetz
- Paola Sebastiani
- Nicholas J. Schork
1 Application
| Application ID | Title |
|---|---|
| 43036 | Exploring and Accommodating Heterogeneity in Large-Scale Genetic Analyses |
Enabling scientific discoveries that improve human health