Kim M Cecil1, Travis Beckwith1, Mekibib Altaye2, Rachel Severs2, Christopher Wolfe2, Zana Percy3, Thomas Maloney1, Kimberly Yolton2, Grace LeMasters3, and Patrick Ryan2
1Radiology/Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, 2Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, 3University of Cincinnati College of Medicine, Cincinnati, OH, United States
Synopsis
Traffic-related air pollution (TRAP) is strongly associated with adverse
cardiopulmonary health effects. Evidence suggests the developing brain may also
be a target organ for particulate matter due to translocation either from the
respiratory system or through the olfactory nerve. Using a pediatric cohort, we
tested the hypothesis that exposure to TRAP during critical windows of brain
development is significantly associated with changes in brain structure and
organization. Children with high exposure levels at time of birth were
associated with reductions in brain volume, cortical thickness, and diffusion
abnormalities in white matter at 12 years compared with children at low exposure.
Purpose
Traffic-related
air pollution (TRAP), a complex mixture of particulate matter (PM), metals,
elemental and organic carbon, polycyclic aromatic hydrocarbons (PAH), and other
constituents, is strongly associated with cardiopulmonary health effects [1]. Evidence suggests the developing
brain may also be a target organ for these particles due to translocation
either from the respiratory system or through the olfactory nerve [2]. Using an
established pediatric epidemiological cohort with extensive longitudinal
exposure assessment since infancy, we tested the hypothesis that exposure to
TRAP during critical windows of brain development is significantly associated
with changes in brain structure and organization. Our imaging study design
targeted recruitment of participants from the cohort with the highest and
lowest quartiles of exposure at time of birth.Methods
One hundred forty six participants (mean age 12.1 + 0.7 years,
57% male, 73% white, 55% high TRAP exposure) from the Cincinnati Childhood
Allergy and Air Pollution Study (CCAAPS) completed a high-resolution (1 mm3)
anatomical imaging protocol with a 32-channel head coil at 3 Tesla. We
evaluated brain volume and cortical thickness using the Computational Anatomy
Toolbox for SPM 12 software running in Matlab. We derived diffusion metrics
(fractional anisotropy (FA), mean (MD), axial (AD) and radial (RD) diffusivity)
by employing a 32-direction, diffusion tensor imaging sequence (b values 0, 800
s/mm2). Analyses were performed using DTI Studio and custom
software. Exposure to TRAP at birth was estimated using a previously developed
land use regression model [3]. One-way ANOVA and multiple linear regression analyses
were used to investigate the relationship between brain volume, cortical
thickness, and diffusion metrics with TRAP exposure, respectively. Potential
confounders and covariates were included in the analytical models.Results
Children with high TRAP exposure levels at time of birth were associated
with regionally specific reductions in brain volume, and cortical thickness,
particularly within the posterior frontal lobe, at 12 years of age compared
with children with low TRAP exposure (Figure 1). Higher exposed participants at
birth demonstrated regions with diminished FA, increased MD, and RD within the right
frontal lobe (Figure 2). In addition, higher exposed participants showed within
the posterior left frontal lobe increased FA, AD and decreased RD (Figure 3).Conclusions
Children with higher exposure to TRAP demonstrate differences in brain
structure and organization compared with their lower exposed peers. Different
regional patterns may reflect variability in TRAP effects at time birth on the
development of the brain cortex and white matter, especially with axonal
structure and myelination.Acknowledgements
Funding for this project came from the National Institutes of
Environmental Health Sciences (NIEHS) R01 ES019890.References
[1] Dockery
DW, Ann Epidemiol 2009, 19:257-263
[2] Elder
A, et al. Environ Health Perspect 2006, 114:1172-8
[3] Ryan PH,
et al. Sci Total Environ 2008, 404:139-147