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• W2912654909 abstract "It was unknown whether plasma protein levels can be estimated based on DNA methylation (DNAm) levels, and if so, how the resulting surrogates can be consolidated into a powerful predictor of lifespan. We present here, seven DNAm-based estimators of plasma proteins including those of plasminogen activator inhibitor 1 (PAI-1) and growth differentiation factor 15. The resulting predictor of lifespan, DNAm GrimAge (in units of years), is a composite biomarker based on the seven DNAm surrogates and a DNAm-based estimator of smoking pack-years. Adjusting DNAm GrimAge for chronological age generated novel measure of epigenetic age acceleration, AgeAccelGrim.Using large scale validation data from thousands of individuals, we demonstrate that DNAm GrimAge stands out among existing epigenetic clocks in terms of its predictive ability for time-to-death (Cox regression P=2.0E-75), time-to-coronary heart disease (Cox P=6.2E-24), time-to-cancer (P= 1.3E-12), its strong relationship with computed tomography data for fatty liver/excess visceral fat, and age-at-menopause (P=1.6E-12). AgeAccelGrim is strongly associated with a host of age-related conditions including comorbidity count (P=3.45E-17). Similarly, age-adjusted DNAm PAI-1 levels are associated with lifespan (P=5.4E-28), comorbidity count (P= 7.3E-56) and type 2 diabetes (P=2.0E-26). These DNAm-based biomarkers show the expected relationship with lifestyle factors including healthy diet and educational attainment.Overall, these epigenetic biomarkers are expected to find many applications including human anti-aging studies." @default.
• W2912654909 created "2019-02-21" @default.
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• W2912654909 date "2019-01-21" @default.
• W2912654909 modified "2023-10-14" @default.
• W2912654909 title "DNA methylation GrimAge strongly predicts lifespan and healthspan" @default.
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• W2912654909 doi "https://doi.org/10.18632/aging.101684" @default.
• W2912654909 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6366976" @default.
• W2912654909 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30669119" @default.
• W2912654909 hasPublicationYear "2019" @default.
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