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Genetic associations for two biological age measures point to distinct aging phenotypes
Chia-Ling Kuo; Luke C Pilling; Zuyun Liu; Janice L Atkins; Morgan Levine.
Affiliation
  • Chia-Ling Kuo; University of Connecticut Health
  • Luke C Pilling; University of Exeter
  • Zuyun Liu; Zhejiang University School of Medicine
  • Janice L Atkins; University of Exeter
  • Morgan Levine; Yale University
Preprint in English | medRxiv | ID: ppmedrxiv-20150797
ABSTRACT
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 markers1,2 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=1.50x10-72); BioAgeAccel--rs7412 (APOE e2 determinant) (p=3.16x10-60). 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 heterogenous across individuals, and the manner in which a person ages may be partly attributed to genetic predisposition.
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Type of study: Prognostic study Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Prognostic study Language: English Year: 2020 Document type: Preprint
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