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. 2022 Aug 26;6(9):e768. doi: 10.1097/HS9.0000000000000768

Table 2.

Individual-level Analysis of VAF and Age Acceleration by Linear Regression Analysis

AgeAccel Coef. (95% CI) P
Any CHIP mutation (N = 116 individuals) Horvath 5.87 (1.47 to 10.27) 0.009
IEAA 4.72 (0.57 to 8.88) 0.026
Hannum 6.38 (3.11 to 9.66) 0.00020
EEAA 7.97 (4.03 to 11.90) 0.00012
PhenoAge 4.92 (−0.44 to 10.29) 0.071
GrimAge 1.84 (−0.78 to 4.47) 0.166
TET2 mutation (N = 47 individuals) Horvath 4.11 (−1.33 to 9.54) 0.135
IEAA 2.14 (−2.52 to 6.80) 0.359
Hannum 4.85 (−0.33 to 10.03) 0.066
EEAA 6.32 (0.32 to 12.33) 0.039
PhenoAge −0.16 (−6.22 to 5.90) 0.958
GrimAge −1.35 (−4.88 to 2.19) 0.447
DNMT3A mutation (N = 52 individuals) Horvath 9.64 (1.97 to 17.31) 0.015
IEAA 9.57 (2.09 to 17.04) 0.013
Hannum 5.65 (0.51 to 10.78) 0.032
EEAA 6.45 (0.11 to 12.78) 0.046
PhenoAge 8.24 (−0.84 to 17.32) 0.074
GrimAge 2.31 (−2.40 to 7.02) 0.329

Statistically significant findings (P < 0.05) are indicated in bold.

AgeAccel = epigenetic age acceleration; CHIP = clonal hematopoiesis of indeterminate potential; Coef. = coefficient (beta value); EEAA = extrinsic epigenetic age acceleration; IEAA = intrinsic epigenetic age acceleration; VAF = variant allele frequency.