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. 2015 May 7;14(4):669–677. doi: 10.1111/acel.12347

Table 1.

Comparison of paternal effect models shows that PBY can influence telomere length distinctly from FAB

Model Study Paternal effect (95% CI) (bp/year) Age effect (95% CI) (bp/year) Paternal effect partial R2 Age effect partial R2 Model R2
Paternal birth year (PBY) UK Twins −19.48 (−23.03 to −15.93) −40.94 (−45.04 to −36.82) 0.0681 0.1144 0.1825
NHLBI-FHS −14.66 (−18.18 to −11.14) −36.42 (−40.54 to −32.31) 0.0847 0.1114 0.1962
Asklepios −17.73 (−21.97 to −13.49) −46.05 (−52.76 to −39.33) 0.0257 0.0450 0.0708
Combined −17.22 (−19.40 to −15.04) −39.44 (−42.08 to −36.80) 0.1058 0.0581 0.3967
Father’s age at birth (FAB) UK Twins 13.39 (9.63 to 17.14) −21.38 (−23.25 to −19.51) 0.0067 0.1560 0.1627
NHLBI-FHS 14.56 (11.04 to 18.08) −21.69 (−23.63 to −19.75) 0.0184 0.1774 0.1958
Asklepios 17.17 (12.90 to 21.43) −28.30 (−33.03 to −23.57) 0.0238 0.0450 0.0689
Combined 14.85 (12.63 to 17.08) −22.18 (−23.53 to −20.84) 0.0116 0.1629 0.3911

Multiple linear regression models using paternal birth year (PBY) in addition to the age, top panel, produce age-associated telomere shortening rates more consistent with longitudinal measurements of telomere shortening than models that utilize father’s age at birth (FAB), bottom panel, in all three datasets individually and combined. Further, models using PBY instead of age produce higher R2 values and have a lower fractional contribution from age.