Ambient air pollution, genetic risk and telomere length in UK biobank

Telomere length (TL) is a biomarker of genomic aging. The evidence on the association between TL and air pollution was inconsistent. Besides, the modification effect of genetic susceptibility on the air pollution-TL association remains unknown.

We aimed to evaluate the association of ambient air pollution with TL and further assess the modification effect of genetic susceptibility.

433,535 participants with complete data of TL and air pollutants in UK Biobank were included. Annual average exposure of NO₂, NO_x, PM₁₀ and PM_2.5 was estimated by applying land use regression models. Genetic risk score (GRS) was constructed using reported telomere-related SNPs. Leukocyte TL was measured by quantitative polymerase chain reaction (qPCR). Multivariable linear regression models were employed to conduct associational analyses.

Categorical exposure models and RCS models both indicated U-shaped (for NO₂ and NO_x) and L-shaped (for PM₁₀ and PM_2.5) correlations between air pollution and TL. In comparison to the lowest quartile, the 2nd and 3rd quartile of NO₂ (q2: -1.3% [-2.1%, -0.4%]; q3: -1.2% [-2.0%, -0.3%], NO_x (q2: -1.3% [-2.1%, -0.5%]; q3: -1.4% [-2.2%, -0.5%]), PM_2.5 (q2: -0.8% [-1.7%, 0.0%]; q3: -1.3% [-2.2%, -0.5%]), and the third quartile of PM₁₀ (q3: -1.1% [-1.9%, -0.2%]) were inversely associated with TL. The highest quartile of NO₂ was positively correlated with TL (q4: 1.0% [0.0%, 2.0%]), whereas the negative correlation between the highest quartile of other pollutants and TL was also attenuated and no longer significant. In the genetic analyses, synergistic interactions were observed between the 4th quartile of three air pollutants (NO₂, NO_x, and PM_2.5) and genetic risk.

Our study for the first time revealed a non-linear trend for the association between air pollution and telomere length. The genetic analyses suggested synergistic interactions between air pollution and genetic risk on the air pollution-TL association. These findings may shed new light on air pollution's health effects, offer suggestions for identifying at-risk individuals, and provide hints regarding further investigation into gene-environment interactions.