Association between prenatal particulate air pollution exposure and telomere length in cord blood: Effect modification by fetal sex

Abstract

Introduction: In utero particulate matter exposure produces oxidative stress that impacts cellular processes that include telomere biology. Newborn telomere length is likely critical to an individual's telomere biology; reduction in this initial telomere setting may signal increased susceptibility to adverse outcomes later in life. We examined associations between prenatal particulate matter with diameter ≤2.5 µm (PM_2.5) and relative leukocyte telomere length (LTL) measured in cord blood using a data-driven approach to characterize sensitive windows of prenatal PM_2.5 effects and explore sex differences.

Methods: Women who were residents of Mexico City and affiliated with the Mexican Social Security System were recruited during pregnancy (n = 423 for analyses). Mothers' prenatal exposure to PM_2.5 was estimated based on residence during pregnancy using a validated satellite-based spatio-temporally resolved prediction model. Leukocyte DNA was extracted from cord blood obtained at delivery. Duplex quantitative polymerase chain reaction was used to compare the relative amplification of the telomere repeat copy number to single gene (albumin) copy number. A distributed lag model incorporating weekly averages for PM_2.5 over gestation was used in order to explore sensitive windows. Sex-specific associations were examined using Bayesian distributed lag interaction models.

Results: In models that included child's sex, mother's age at delivery, prenatal environmental tobacco smoke exposure, pre-pregnancy BMI, gestational age, birth season and assay batch, we found significant associations between higher PM_2.5 exposure during early pregnancy (4-9 weeks) and shorter LTL in cord blood. We also identified two more windows at 14-19 and 34-36 weeks in which increased PM_2.5 exposure was associated with longer LTL. In stratified analyses, the mean and cumulative associations between PM_2.5 and shortened LTL were stronger in girls when compared to boys.

Conclusions: Increased PM_2.5 during specific prenatal windows was associated with shorter LTL and longer LTL. PM_2.5 was more strongly associated with shortened LTL in girls when compared to boys. Understanding sex and temporal differences in response to air pollution may provide unique insight into mechanisms.

Keywords: Bayesian distributed lag interaction models; Distributive lag models; Leukocyte telomere length; Particulate matter; Prenatal exposure.

Figure 1.

Associations between weekly prenatal PM_2.5 and cord blood LTL in the entire sample (n=423). Adjusted for sex, maternal age at delivery, prenatal exposure to environmental tobacco smoke, pre-pregnancy BMI, gestational age, birth season and batch. The y-axis represents the change in LTL associated with a 10 μg/m³ increase in PM_2.5; the x-axis is gestational age in weeks. Solid lines show the predicted change in LTL. Gray areas indicate 95% CIs. A sensitive window is identified for the weeks where the estimated pointwise 95% CI (shaded area) does not include zero.

Figure 2.

Linear model estimates for percent change in LTL per 10 μg/m³ higher PM_2.5 concentration averaged clinically defined trimesters and the entire pregnancy. All models adjusted for sex, maternal age at delivery, prenatal exposure to environmental tobacco smoke, pre-pregnancy BMI, gestational age, birth season and batch. Trimester results are from a single model that included all three trimesters.

Figure 3.

Sex-stratified association between weekly ambient PM_2.5 over gestation and cord blood LTL. Bayesian distributed lag interaction models (BDLIM) were used to estimate week-specific effects and interaction by sex. Models were adjusted for sex, maternal age at delivery, prenatal exposure to environmental tobacco smoke, pre-pregnancy BMI, gestational age, birth season and batch. The x-axis demarcates the gestational age in weeks. The y-axis represents the percent change in LTL per 10 μg/m³ increase in PM_2.5. Solid lines represent the predicted time–varying percent change in LTL and gray areas indicates the 95% confidence intervals (CI). A sensitive window is identified when the estimated point-wise 95% CI does not include zero.

Figure 4.

Bayesian distributed lag interaction models (BDLIM) were used to estimate mean within –window effect and cumulative changes in LTL per 10 μg/m³ higher PM_2.5 by sex. All models adjusted for sex, maternal age at delivery, prenatal exposure to environmental tobacco smoke, pre-pregnancy BMI, gestational age, birth season and batch.