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Table 1 Overview of DNA methylation aging algorithms

From: Whole blood DNA methylation aging markers predict colorectal cancer survival: a prospective cohort study

DNAm aging algorithm Original study Tissue nCpGs Surrogate measure of biological age*
AgeAccelHorvath Horvath et al. [5] Multiple tissues# 353 Calibrated chronological age
AgeAccelHannum Hannum et al. [6] Whole blood 71 Chronological age
DNAmMRscore Zhang et al. [7] Whole blood 10(8)§ All-cause mortality
AgeAccelPheno Levine et al. [8] Whole blood 513 9 markers, chronological age
AgeAccelGrim Lu et al. [9] Whole blood 1030 7 Plasma proteins, smoking pack-years
  1. AgeAccel, age acceleration; DNAm, DNA methylation; MRscore, mortality risk score
  2. *DNAm aging algorithms are usually constructed by regressing mortality and/or a surrogate measure of biological age on a set of CpG sites
  3. #Horvath’s epigenetic clock was originally developed based on CpG sites from DNA of 51 different tissues and cell types. In our study, AgeAccelHorvath was calculated based on CpG sites from DNA of whole blood samples
  4. §DNAmMRscore was initially developed based on ten CpG sites, of which two CpG sites are not included in Illumina EPIC microarray data. An adapted formula based on the remaining eight CpG sites has been developed using the data from an external cohort, the German ESTHER cohort
  5. 9 markers include albumin, creatinine, serum glucose, C-reactive protein, lymphocyte percent, mean cell volume, red cell distribution width, alkaline phosphatase and white blood cell count
  6. 7 plasma proteins include adrenomedullin, beta-2-microglobulim, cystatin C, growth/differentiation factor 15, leptin (Leptin), plasminogen activator inhibitor-1 and tissue inhibitor metalloproteinases 1