Association of Air Pollution with a Urinary Biomarker of Biological Aging and Effect Modification by Vitamin K in the FLEMENGHO Prospective Population Study

Abstract

Background: A recently developed urinary peptidomics biological aging clock can be used to study accelerated human aging. From 1990 to 2019, exposure to airborne particulate matter (PM) became the leading environmental risk factor worldwide.

Objectives: This study investigated whether air pollution exposure is associated with accelerated urinary peptidomic aging, independent of calendar age, and whether this association is modified by other risk factors.

Methods: In a Flemish population, the urinary peptidomic profile (UPP) age (UPP-age) was derived from the urinary peptidomic profile measured by capillary electrophoresis coupled with mass spectrometry. UPP-age-R was calculated as the residual of the regression of UPP-age on chronological age, which reflects accelerated aging predicted by UPP-age, independent of chronological age. A high-resolution spatial-temporal interpolation method was used to assess each individual's exposure to ${\mathrm{PM}}_{10}$, ${\mathrm{PM}}_{2.5}$, black carbon (BC), and nitrogen dioxide (${\mathrm{NO}}_2$). Associations of UPP-age-R with these pollutants were investigated by mixed models, accounting for clustering by residential address and confounders. Effect modifiers of the associations between UPP-age-R and air pollutants that included 18 factors reflecting vascular function, renal function, insulin resistance, lipid metabolism, or inflammation were evaluated. Direct and indirect (via UPP-age-R) effects of air pollution on mortality were evaluated by multivariable-adjusted Cox models.

Results: Among 660 participants (50.2% women; mean age: 50.7 y), higher exposure to ${\mathrm{PM}}_{10}$, ${\mathrm{PM}}_{2.5}$, BC, and ${\mathrm{NO}}_2$ was associated with a higher UPP-age-R. Studying effect modifiers showed that higher plasma levels of desphospho-uncarboxylated matrix Gla protein (dpucMGP), signifying poorer vitamin K status, steepened the slopes of UPP-age-R on the air pollutants. In further analyses among participants with dpucMGP $\ge 4.26\mu g/L$ (median), an interquartile range (IQR) higher level in ${\mathrm{PM}}_{10}$, ${\mathrm{PM}}_{2.5}$, BC, and ${\mathrm{NO}}_2$ was associated with a higher UPP-age-R of 2.03 [95% confidence interval (CI): 0.60, 3.46], 2.22 (95% CI: 0.71, 3.74), 2.00 (95% CI: 0.56, 3.43), and 2.09 (95% CI: 0.77, 3.41) y, respectively. UPP-age-R was an indirect mediator of the associations of mortality with the air pollutants [multivariable-adjusted hazard ratios from 1.094 (95% CI: 1.000, 1.196) to 1.110 (95% CI: 1.007, 1.224)] in participants with a high dpucMGP, whereas no direct associations were observed.

Discussion: Ambient air pollution was associated with accelerated urinary peptidomics aging, and high vitamin K status showed a potential protective effect in this population. Current guidelines are insufficient to decrease the adverse health effects of airborne pollutants, including healthy aging trajectories. https://doi.org/10.1289/EHP13414.

Figure 1.

Heat maps showing the difference in UPP-age-R associated with the combined contributions of the air pollutants and dpucMGP in 660 FLEMENGHO participants. Differences in UPP-age-R were derived by mixed models, which included both the air pollutants and dpucMGP as independent variables. All models accounted for clustering between participants sharing the same residential address as random effect and for sex, age, body mass index, mean arterial pressure, plasma glucose, $\mathrm{\gamma }\text{-glutamyltransferase}$, current smoking, the total-to-high-density lipoprotein serum cholesterol ratio, glomerular filtration rate, and socioeconomic status as fixed effects. Panels (A), (C), (E), and (G) provide the percentage of study participants ($n=660$ in total) in each box of the cross-classification between dpucMGP, plotted along the horizontal axis and the air pollutant plotted along the vertical axis. Panels (B), (D), (F), and (H) show changes in UPP-age-R (in years) in association with dpucMGP and ${\mathrm{PM}}_{10}$ (B), ${\mathrm{PM}}_{2.5}$ (D), BC (F) and ${\mathrm{NO}}_2$ (H) concentrations. $p$-Values represent the significance of the linear associations between the air pollutant or dpucMGP with UPP-age-R in full adjusted models. Note: BC, black carbon; dpucMGP, desphospho-uncarboxylated matrix Gla protein; FLEMENGHO, Flemish Study on Environment, Genes, and Health Outcomes; ${\mathrm{NO}}_2$, nitrogen dioxide; ${\mathrm{PM}}_{2.5}$, particulate matter with aerodynamic diameter $\le 2.5\mathrm{\mu }\mathrm{m}$; ${\mathrm{PM}}_{10}$, particulate matter with aerodynamic diameter $\le 10\mathrm{\mu }\mathrm{m}$; UPP-age, urinary peptidomic profile age; UPP-age-R, residual of the regression of UPP-age on chronological age.

Figure 2.

Association of UPP-age-R with air pollutants in 660 FLEMENGHO participants stratified by the median ($4.26\mathrm{\mu }\mathrm{g}/\mathrm{L}$) level of dpucMGP. Red squares are unadjusted estimates with 95% CI bars. Blue circles are adjusted estimates with 95%CI bars and were derived by mixed models, which accounted for clustering between participants sharing the same residential address as random effect and for sex, age, body mass index, mean arterial pressure, plasma glucose, $\mathrm{\gamma }\text{-glutamyltransferase}$, current smoking, the total- to high-density lipoprotein serum cholesterol ratio, glomerular filtration rate, and socioeconomic status as fixed effects. Estimates provided as a difference in UPP-age-R (in years) for an IQR higher level in ${\mathrm{PM}}_{10}$ [$+3.79{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$, (A)]; ${\mathrm{PM}}_{2.5}$ [$+1.59{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$, (B)]; BC [$+0.31{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$, (C)]; and ${\mathrm{NO}}_2$ [$+5.25{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$, (D)]. Numerical estimates are provided with $\pm \text{SE}$ and $p$-value. $n=330$ for $\text{dpucMGP}<4.26\mathrm{\mu }\mathrm{g}/\mathrm{L}$ and $n=330$ for $\text{dpucMGP}\ge 4.26\mathrm{\mu }\mathrm{g}/\mathrm{L}$. Note: BC, black carbon; CI, confidence interval; dpucMGP, desphospho-uncarboxylated matrix Gla protein; FLEMENGHO, Flemish Study on Environment, Genes, and Health Outcomes; IQR, interquartile range; ${\mathrm{NO}}_2$, nitrogen dioxide; ${\mathrm{PM}}_{2.5}$, particulate matter with aerodynamic diameter $\le 2.5\mathrm{\mu }\mathrm{m}$; ${\mathrm{PM}}_{10}$, particulate matter with aerodynamic diameter $\le 10\mathrm{\mu }\mathrm{m}$; SE, standard error; UPP-age, urinary peptidomic profile age; UPP-age-R, residual of the regression of UPP-age on chronological age.

Figure 3.

Estimated direct and indirect (via UPP-age-R) effects of air pollutant exposure on total and cardiovascular mortality in 330 FLEMENGHO participants with dpucMGP of $4.26\mathrm{\mu }\mathrm{g}/\mathrm{L}$ (median) or higher. Multivariable-adjusted HRs with corresponding $p$-values were calculated by Cox proportional hazards regression. Models accounted for sex, age, body mass index, mean arterial pressure, the total-to-high-density-lipoprotein cholesterol ratio, plasma glucose, $\mathrm{\gamma }\text{-glutamyltransferase}$, current smoking, glomerular filtration rate, and socioeconomic status. HRs express the relative risk for a IQR higher level in ${\mathrm{PM}}_{10}$ [$+3.79{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$, (A)]; ${\mathrm{PM}}_{2.5}$ [$+1.59{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$, (B)], BC [$+0.31{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$, (C)]; and ${\mathrm{NO}}_2$ [$+5.25{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$, (D)]. The incidence of total and cardiovascular mortality amounted to 38/330 (11.5%) and 15/330 (4.5%), respectively. Note: BC, black carbon; dpucMGP, desphospho-uncarboxylated matrix Gla protein; FLEMENGHO, Flemish Study on Environment, Genes, and Health Outcomes; HR, hazard ratio; ${\mathrm{NO}}_2$, nitrogen dioxide; ${\mathrm{PM}}_{2.5}$, particulate matter with aerodynamic diameter $\le 2.5\mathrm{\mu }\mathrm{m}$; ${\mathrm{PM}}_{10}$, particulate matter with aerodynamic diameter $\le 10\mathrm{\mu }\mathrm{m}$; UPP-age, urinary peptidomic profile age; UPP-age-R, residual of the regression of UPP-age on chronological age.