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GWAS Study

Genetic associations for two biological age measures point to distinct aging phenotypes.

Kuo CL, Pilling LC, Liu Z et al.

34038024 PubMed ID
GWAS Study Type
100228 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

KC
Kuo CL
PL
Pilling LC
LZ
Liu Z
AJ
Atkins JL
LM
Levine ME
Chapter II

Abstract

Summary of the research findings

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.

98,446 European ancestry individuals

Chapter III

Study Statistics

Key metrics and study information

100228
Total Participants
GWAS
Study Type
Yes
Replicated
1,782 European ancestry individuals
Replication Participants
European
Ancestry
U.K.
Recruitment Country
Chapter IV

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