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Genetic associations for two biological age measures point to distinct aging phenotypes
Biological age measures outperform chronological age in predicting various aging outcomes, yet little is known regarding genetic predisposition. We performed genome‐wide association scans of two age‐adjusted biological age measures (PhenoAgeAcceleration and BioAgeAcceleration), estimated from clinic...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208797/ https://www.ncbi.nlm.nih.gov/pubmed/34038024 http://dx.doi.org/10.1111/acel.13376 |
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author | Kuo, Chia‐Ling Pilling, Luke C. Liu, Zuyun Atkins, Janice L. Levine, Morgan E. |
author_facet | Kuo, Chia‐Ling Pilling, Luke C. Liu, Zuyun Atkins, Janice L. Levine, Morgan E. |
author_sort | Kuo, Chia‐Ling |
collection | PubMed |
description | Biological age measures outperform chronological age in predicting various aging outcomes, yet little is known regarding genetic predisposition. We performed genome‐wide association scans of two age‐adjusted biological age measures (PhenoAgeAcceleration and BioAgeAcceleration), estimated from clinical biochemistry markers (Levine et al., 2018; Levine, 2013) in European‐descent participants from UK Biobank. The strongest signals were found in the APOE gene, tagged by the two major protein‐coding SNPs, PhenoAgeAccel—rs429358 (APOE e4 determinant) (p = 1.50 × 10(−72)); BioAgeAccel—rs7412 (APOE e2 determinant) (p = 3.16 × 10(−60)). Interestingly, we observed inverse APOE e2 and e4 associations and unique pathway enrichments when comparing the two biological age measures. Genes associated with BioAgeAccel were enriched in lipid related pathways, while genes associated with PhenoAgeAccel showed enrichment for immune system, cell function, and carbohydrate homeostasis pathways, suggesting the two measures capture different aging domains. Our study reaffirms that aging patterns are heterogeneous across individuals, and the manner in which a person ages may be partly attributed to genetic predisposition. |
format | Online Article Text |
id | pubmed-8208797 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82087972021-06-25 Genetic associations for two biological age measures point to distinct aging phenotypes Kuo, Chia‐Ling Pilling, Luke C. Liu, Zuyun Atkins, Janice L. Levine, Morgan E. Aging Cell Original Articles Biological age measures outperform chronological age in predicting various aging outcomes, yet little is known regarding genetic predisposition. We performed genome‐wide association scans of two age‐adjusted biological age measures (PhenoAgeAcceleration and BioAgeAcceleration), estimated from clinical biochemistry markers (Levine et al., 2018; Levine, 2013) in European‐descent participants from UK Biobank. The strongest signals were found in the APOE gene, tagged by the two major protein‐coding SNPs, PhenoAgeAccel—rs429358 (APOE e4 determinant) (p = 1.50 × 10(−72)); BioAgeAccel—rs7412 (APOE e2 determinant) (p = 3.16 × 10(−60)). Interestingly, we observed inverse APOE e2 and e4 associations and unique pathway enrichments when comparing the two biological age measures. Genes associated with BioAgeAccel were enriched in lipid related pathways, while genes associated with PhenoAgeAccel showed enrichment for immune system, cell function, and carbohydrate homeostasis pathways, suggesting the two measures capture different aging domains. Our study reaffirms that aging patterns are heterogeneous across individuals, and the manner in which a person ages may be partly attributed to genetic predisposition. John Wiley and Sons Inc. 2021-05-26 2021-06 /pmc/articles/PMC8208797/ /pubmed/34038024 http://dx.doi.org/10.1111/acel.13376 Text en © 2021 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Kuo, Chia‐Ling Pilling, Luke C. Liu, Zuyun Atkins, Janice L. Levine, Morgan E. Genetic associations for two biological age measures point to distinct aging phenotypes |
title | Genetic associations for two biological age measures point to distinct aging phenotypes |
title_full | Genetic associations for two biological age measures point to distinct aging phenotypes |
title_fullStr | Genetic associations for two biological age measures point to distinct aging phenotypes |
title_full_unstemmed | Genetic associations for two biological age measures point to distinct aging phenotypes |
title_short | Genetic associations for two biological age measures point to distinct aging phenotypes |
title_sort | genetic associations for two biological age measures point to distinct aging phenotypes |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208797/ https://www.ncbi.nlm.nih.gov/pubmed/34038024 http://dx.doi.org/10.1111/acel.13376 |
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