At each point on the cerebral surface is shown the statistical significance (probability values) for correlations of total prenatal polycyclic aromatic hydrocarbon levels with measures of the cerebral surface, either cortical thickness or distance from the surface of the template brain (see the eMethods in the Supplement for detailed descriptions of each of these measures). The distance at each point of the cerebral surface in each participant from the corresponding point of the surface of the template brain provides a continuous measure that, when strictly defined, assesses the degree of indentation or protrusion at that point on the surface relative to the template brain, which can be more loosely considered an index of local volume at that point. This index of local volume can derive from either the underlying cortical gray matter, white matter, or both. Both cortical thickness and distance measures were rescaled for overall brain size, and the statistical models accounted for the age and sex of all children. The color bar indicates the color coding of P values for testing of statistical significance at each point on the surface. P values were thresholded at P < .05 after correction for multiple comparisons using the false discovery rate. Warm colors (yellow, orange, and red) represent significant positive correlations, and cool colors (blue and purple) represent inverse correlations. Sea green indicates correlations that are not statistically significant. The boundaries of major gyri are outlined in white. A, Correlations are shown for total prenatal polycyclic aromatic hydrocarbon levels with distances of the cerebral surface of each participant brain from the corresponding point on the template surface. Correlations are more statistically significant and more spatially extensive in the left hemisphere than in the right hemisphere. The gyri containing statistically significant correlations are labeled. B, These images are correlations of total prenatal polycyclic aromatic hydrocarbon levels with distances of the white matter surface of each participant from the corresponding point on the surface of white matter in the template brain. Regions with statistically significant correlations are much more extensive than those in A, covering almost the entire extent of the white matter surface in the left hemisphere. Correlations with cortical thickness were not statistically significant. Together, these findings suggest that correlations detected at the cerebral surface in A derived primarily from the underlying white matter. CG indicates cingulate gyrus; Cu, cuneus; GR, gyrus rectus; IFG, inferior frontal gyrus; ITG, inferior temporal gyrus; MFG, middle frontal gyrus; MOF, medial orbitofrontal gyrus; MTG, middle temporal gyrus; PoG, postcentral gyrus; PreC, precuneus; PrG, precentral gyrus; SFG, superior frontal gyrus; SMG, supramarginal gyrus; SPG, superior parietal gyrus; and STG, superior temporal gyrus.
Scatterplots show that the significant correlations derive from the entire range of prenatal and postnatal PAH levels and are not driven by outliers. White matter measures are adjusted for age and sex of each participant. A, Maps for these correlations are as described for Figure 1. The white circles indicate where in the brain the data set was sampled to generate the scatters. The Pearson product moment correlation coefficients from left to right are −0.57 (95% CI, −0.75 to −0.30), −0.51 (95% CI, −0.71 to −0.23), −0.50 (95% CI, −0.71 to −0.22), and −0.56 (95% CI, −0.75 to −0.30). B, Maps for these correlations are as described for Figure 1 except that the regressions are for postnatal PAH exposure levels measured at age 5 years. The analyses covaried for age, sex, and prenatal PAH levels. The values for postnatal PAH metabolite levels have been natural log transformed. The Pearson product moment correlation coefficients from left to right are −0.47 (95% CI, −0.69 to −0.18) and −0.52 (95% CI, −0.72 to −0.25). In(PAH) indicates the natural logarithm of PAH levels.
A, P values that are false discovery rate–corrected for multiple comparisons are plotted for partial correlations of processing speed with distances at each point on the white matter surface from the corresponding point on the white matter surface of the template brain, while covarying for age and sex. Warm colors (yellow, orange, and red) represent significant positive correlations in which white matter reductions associate with lower indexes for processing speed. Sea green indicates correlations that are not statistically significant. B, P values are plotted for regression models that test whether white matter surface distances mediate the association of prenatal PAH levels with processing speed from the Wechsler Intelligence Scale for Children IV (WISC-IV) assessed at ages 7 to 9 years. We tested the significance of the mediation effect at each voxel on the surface of white matter using a Sobel test z score, which was large and typically exceeded 90. We then plotted the associated P values for this mediation pathway on the template brain, corrected them for multiple statistical comparisons using the false discovery rate, and color coded the corrected P values to identify voxels where partial mediation was statistically significant. These voxels were detected throughout all lobes on the white surfaces of the left hemisphere.
The maps were sampled at the locations indicated by white circles. The y-axis shows distances at those points for the white matter surface of each participant from the corresponding point on the white matter surface of the template brain, adjusted for age and sex of each participant. The scatterplots show that the significant findings were not driven by outliers. The Externalizing Composite Scale included only the rule-breaking behavior and aggressive behavior subscales. The Pearson product moment correlation coefficients that follow are from left to right. For processing speed, they are 0.62 (95% CI, 0.39-0.79), 0.56 (95% CI, 0.29-0.74), and 0.43 (95% CI, 0.13-0.66). For externalizing symptoms, they are −0.52 (95% CI, −0.72 to −0.24), −0.49 (95% CI, −0.70 to −0.20), and −0.50 (95% CI, −0.71 to −0.21). For DSM ADHD, they are −0.53 (95% CI, −0.72 to −0.25), −0.57 (95% CI, −0.75 to −0.31), and −0.48 (95% CI, −0.69 to −0.18). WISC-IV indicates Wechsler Intelligence Scale for Children IV.
eMethods. Supplemental Methods
eDiscussion. Supplemental Discussion
eFigure 1. Nonparametric Correlations and Scatterplots for Prenatal PAH Exposure
eFigure 2. Correlations of Postnatal PAH Levels With White Matter Surface Measures
eFigure 3. Correlations of White Matter Surface Measures With CBCL Externalizing Problems and ADHD-DSM Symptoms
eFigure 4 and eFigure 5. Correlations of White Matter Surface Measures With Additional CBCL Scores
eFigure 6. Correlation of White Matter Surface Measures With CBCL Externalizing Problems While Covarying for ADHD DSM Scores
eFigure 7. Interactions of Prenatal PAH Exposure Levels With Sex on White Matter Surface Measures
eTable. Correlation Matrix for PAH Levels and Select Behavioral Measures on the CBCL and WISC-IV
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Peterson BS, Rauh VA, Bansal R, et al. Effects of Prenatal Exposure to Air Pollutants (Polycyclic Aromatic Hydrocarbons) on the Development of Brain White Matter, Cognition, and Behavior in Later Childhood. JAMA Psychiatry. 2015;72(6):531–540. doi:10.1001/jamapsychiatry.2015.57
Copyright 2015 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.
Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous and neurotoxic environmental contaminants. Prenatal PAH exposure is associated with subsequent cognitive and behavioral disturbances in childhood.
To identify the effects of prenatal PAH exposure on brain structure and to assess the cognitive and behavioral correlates of those abnormalities in school-age children.
Design, Setting, and Participants
Cross-sectional imaging study in a representative community-based cohort followed up prospectively from the fetal period to ages 7 to 9 years. The setting was urban community residences and an academic imaging center. Participants included a sample of 40 minority urban youth born to Latina (Dominican) or African American women. They were recruited between February 2, 1998, and March 17, 2006.
Main Outcomes and Measures
Morphological measures that index local volumes of the surface of the brain and of the white matter surface after cortical gray matter was removed.
We detected a dose-response relationship between increased prenatal PAH exposure (measured in the third trimester but thought to index exposure for all of gestation) and reductions of the white matter surface in later childhood that were confined almost exclusively to the left hemisphere of the brain and that involved almost its entire surface. Reduced left hemisphere white matter was associated with slower information processing speed during intelligence testing and with more severe externalizing behavioral problems, including attention-deficit/hyperactivity disorder symptoms and conduct disorder problems. The magnitude of left hemisphere white matter disturbances mediated the significant association of PAH exposure with slower processing speed. In addition, measures of postnatal PAH exposure correlated with white matter surface measures in dorsal prefrontal regions bilaterally when controlling for prenatal PAH.
Conclusions and Relevance
Our findings suggest that prenatal exposure to PAH air pollutants contributes to slower processing speed, attention-deficit/hyperactivity disorder symptoms, and externalizing problems in urban youth by disrupting the development of left hemisphere white matter, whereas postnatal PAH exposure contributes to additional disturbances in the development of white matter in dorsal prefrontal regions.
Polycyclic aromatic hydrocarbons (PAHs) are a class of ubiquitous and toxic environmental contaminants generated by the incomplete combustion of organic materials. Sources outdoors include diesel-powered and gasoline-powered vehicles, waste incineration, and oil and coal burning for heat and electricity, and sources indoors include cooking, tobacco smoke, and space heaters.1,2 Polycyclic aromatic hydrocarbons are neurotoxicants that readily cross the placenta and damage the fetal brain,3,4 likely by inducing inflammation, oxidative stress,5 and vascular injury.6 Animal models have shown that prenatal PAH exposure impairs subsequent development of behavior, learning, and memory, in part by disrupting glutamate signaling,4,5,7,8 activating glial cells that then become neurotoxic,9 and reducing neural plasticity.4
The frequent differential siting of outdoor pollution sources in low-income, urban, and minority communities produces disproportionate exposure of their residents to air pollutants.10-15 The substantial penetration of outdoor-generated PAH compounds into indoor residential environments16,17 also translates to disparities in exposure to pollutants indoors. In 1997, our group initiated a study of mother-newborn pairs from minority communities in New York City to evaluate the effects of prenatal exposure to ambient and indoor pollutants on birth outcomes and neurocognitive development.18 We recruited 720 nonsmoking women aged 18 to 35 years old who self-identified as African American or Latina (Dominican) and were registered at the local prenatal clinics. During the third trimester of pregnancy, 665 mothers completed questionnaires and carried personal backpack monitors for 48 hours to estimate the level of 8 common PAHs in the breathing zone.18
Our group previously reported in this cohort that exposure during gestation to airborne PAHs was associated with multiple neurodevelopmental disturbances, including developmental delay at age 3 years,19 reduced full-scale and verbal IQ at age 5 years,20 and symptoms of anxiety, depression, and inattention on the Child Behavior Checklist (CBCL) at age 7 years,21 as well as slower processing speed on the Wechsler Intelligence Scale for Children IV (WISC-IV) at age 7 years, consistent with the cognitive and behavioral effects reported in prior animal models of PAH exposure.8,22
We undertook a magnetic resonance (MR) imaging study of a representative sample (N = 40) of this urban community cohort to assess the effects of airborne PAHs on brain structure in school-age children with minimal exposure to other common environmental toxicants, including tobacco smoke, chlorpyrifos, and lead. We hypothesized that we would identify regional abnormalities in brain morphology associated with prenatal PAH exposure and that the magnitude of those brain abnormalities would mediate the effects of PAHs on information processing speed and the severity of attention-deficit/hyperactivity disorder (ADHD) symptoms.
Details of PAH exposure measures, MR imaging pulse sequences, and image processing methods are available in the supplementary material. See the eMethods in the Supplement.
African American and Dominican women residing in Washington Heights, Harlem, or the South Bronx in New York City were recruited between February 2, 1998, and March 17, 2006, through the local prenatal care clinics.19 To reduce potential confounding, enrollment was restricted to women 18 to 35 years old who were not cigarette smokers or users of other tobacco products or illicit drugs, who had initiated prenatal care by the 20th week of pregnancy, and who were free of diabetes mellitus, hypertension, and known human immunodeficiency virus. The retention rate to ages 10 to 12 years was 79.3%.
Of 727 enrolled mother-newborn pairs, 665 completed prenatal PAH monitoring and prenatal questionnaires. To minimize confounding by exposure to other ambient chemicals, we identified 255 of these 665 children with (1) a full range of prenatal PAH exposure levels; (2) no or very low prenatal exposure to environmental tobacco smoke, classified by maternal report validated by cotinine levels of less than 15 µg/L in umbilical cord blood; and (3) low chlorpyrifos exposure, defined as below the upper tertile of the distribution (≥4.39 pg/g) (to convert cotinine level to nanomoles per liter, multiply by 5.675). Of these 255 children, 40 were selected for neuroimaging using proportional stratified sampling, such that 20 were randomly selected from those above the median PAH level and 20 from those below the median PAH level to ensure an adequate distribution and representativeness of PAH exposure levels. By design, prenatal levels of cotinine, chlorpyrifos insecticide, and lead were low in those who underwent imaging and were significantly less than in the overall cohort from which they were drawn (Table). All participants were right handed. We obtained written informed consent from parents and signed assent from children. The institutional review boards at the New York State Psychiatric Institute and Columbia University approved the study.
We administered the CBCL and the WISC-IV, which were assessed in all study participants between the ages of 7 and 9 years.
The detailed procedures used to analyze surface morphologies, as well as related validation studies, are provided elsewhere23 and in the eMethods in the Supplement. Briefly, we flipped the images randomly in the left-right direction before processing and reversed them after processing to eliminate any possible influence of left-right human perceptual bias on morphological measures. We isolated the brains from nonbrain tissue using semiautomated methods with detailed manual editing (eMethods in the Supplement). We coregistered each brain to an appropriately selected template brain using a similarity transformation, followed by a high-dimensional, nonrigid warping algorithm based on the dynamics of fluid flow. This 2-stage coregistration transformed each brain to match the template precisely in size and shape, permitting identification of points on the surfaces of each brain in the data set that corresponded precisely with those of the template brain. We then reversed the high-dimensional nonrigid warping to bring each brain into the position of the similarity transformation with the template brain while carrying along with each brain the point correspondences established during the nonrigid high-dimensional warping.
We measured the signed euclidean distance of each point on the surface of the brain of each participant from the corresponding point on the surface of the template brain. These distances were positive for an outward deformation and negative for an inward deformation of the surface of participant brain relative to the template surface. To assess similar measures at the surface of the white matter rather than at the surface of the brain, we removed the gray matter of the cortical mantle from the images, transferring the point correspondences determined in our coregistration procedures to the nearest point on the underlying white matter surface. We then assessed the correlation of surface distances with total PAH exposure at each point. These distances from the corresponding point of the surface on the template brain provide a continuous measure that assesses the degree of indentation or protrusion at that point on the surface relative to the template brain and that can be considered an index of local volume at that point.
The associations of PAH measures with CBCL and WISC-IV scores were assessed using Pearson product moment correlation coefficients, calculated using statistical software (SPSS Statistics, version 21; IBM). For statistical analyses of imaging measures, we used general linear modeling at each point on the surface of the template brain to correlate PAH exposure, CBCL scores, or processing speed indexes with morphological measures (cortical thickness and distances of the cerebral or white matter surfaces from the corresponding surface of the template brain) while covarying for age and sex. P values for voxelwise analyses across the cerebral surface were corrected for multiple comparisons using a P < .05 false discovery rate.24 The P value for the correlation coefficient at voxels that survived false discovery rate correction was color coded and plotted at each point on the cerebral surface.
Participating children were representative of the cohort from which they were drawn (Table) except that they had significantly lower lead levels and lower levels of environmental tobacco smoke and chlorpyrifos by design. One boy had a total PAH level that was an outlier in the sample (36.5 ng/m3), which was >5 SDs from the sample mean. We report results with that child excluded, although the inclusion of his data yielded the same findings.
Prenatal exposure to PAHs correlated significantly and inversely with our morphological measure (distance from the template surface, an index of local volume) at each voxel on the cerebral surface in childhood (mean [SD] age, 8.0 [1.3] years) in most of the frontal, superior temporal, and parietal lobes, as well as the entire rostrocaudal extent of the mesial surface, in the left but not the right hemisphere of the brain (Figure 1A). This index of local volume can derive from the underlying cortical gray matter, white matter, or both. Therefore, we independently explored these 2 tissue types for their associations with PAH exposure levels. Polycyclic aromatic hydrocarbon exposure did not correlate significantly with measures of cortical thickness anywhere across the cerebrum, suggesting that the surface abnormalities were likely determined primarily by abnormalities in the underlying white matter. Therefore, we removed the cortical mantle from each brain to assess the effects of prenatal PAH exposure on the underlying white matter. These analyses confirmed that the modest PAH-related effects at the cerebral surface derived from spatially much larger and statistically stronger effects of PAHs on the underlying white matter, extending throughout the entire lateral, mesial, dorsal, and ventral surfaces of the left hemisphere (Figure 1B). Much less prominent inverse correlations in the right hemisphere were localized primarily to sensorimotor white matter regions (Figure 1). These correlations were unchanged when covarying for prenatal cotinine levels, measures of postnatal PAH exposure at age 5 years, or a standard measure of handedness.25 Surface maps constructed using nonparametric Spearman rank correlation yielded the same findings as those constructed using parametric linear regression (eFigure 1 in the Supplement). Scatterplots confirmed that correlations of white matter surface measures extended across the entire range of PAH, cognitive, and behavioral values (Figure 2).
Measures of PAH exposure at age 5 years did not correlate significantly with prenatal PAH exposure or measures of the cerebral surface or cortical thickness, but they correlated significantly with white matter measures in dorsal prefrontal regions bilaterally, especially along the superior frontal gyrus, even when covarying for prenatal PAH exposure (Figure 2 and eFigure 2 in the Supplement). The inclusion of PAH exposure at age 5 years as a covariate in our original model did not change the correlation of prenatal PAH levels with white matter surface measures.
Significant behavioral correlates of PAH exposure included processing speed on the WISC-IV at age 7 years (r = −0.32, P < .05) (Table). This was similar to the correlation detected in the larger cohort from which our sample was drawn.
Processing speed on the WISC-IV and numerous CBCL measures, including externalizing problems and DSM ADHD symptoms, correlated significantly and inversely with white matter surface measures, more strongly in the left hemisphere than in the right hemisphere (Figure 3, Figure 4, and eFigures 3, 4, and 5 in the Supplement), as well as in spatial patterns almost identical to those for prenatal PAH exposure (Figure 1). The direction of correlations and the associated scatterplots indicated that progressively more prominent white matter reductions accompanied progressively greater impairments in processing speed and more severe behavioral problems (Figure 4). Because CBCL subscales were intercorrelated (eTable in the Supplement), we present findings for externalizing problems, as they subsume problems in many other subscales of the CBCL, including DSM ADHD symptoms. Based on prior findings for PAH effects on DSM ADHD symptoms in our larger cohort, we had a priori hypothesized that these symptoms would correlate with MR imaging brain measures. Correlations between white matter measures and selected CBCL scores are shown in eFigures 3, 4, and 5 in the Supplement. White matter correlations with externalizing problems persisted when controlling for DSM ADHD symptom scores on the CBCL (eFigure 6 in the Supplement).
We next applied the Sobel test26 at each point on the surface of the white matter (eMethods in the Supplement) to test our hypothesis that the effects of prenatal PAH exposure on brain structure partially mediated the effects of prenatal PAH exposure on processing speed in later childhood. Plotting the P value of the mediation pathway at each voxel on the surface of the template brain, we confirmed throughout the entire surface of the left hemisphere that white matter measures mediated the effects of prenatal PAH exposure on measures of processing speed (Figure 3B). Mediation effects were not significant for DSM ADHD symptom scores because PAH exposure in our sample did not correlate significantly with the severity of these measures, as it did in the larger cohort.
Exploratory analyses suggested that the associations of prenatal PAH exposure with white matter measures, although present in both sexes separately, may have been stronger in girls than in boys. However, scatterplots indicated that the effects were driven by only a few participants (eFigure 7 in the Supplement).
To our knowledge, this is the largest MR imaging study of the brain effects of exposure to PAH air pollutants and the first to report effects from prenatal exposure. In our community-based sample of minority urban youth followed up from gestation to school age, we detected a powerful dose-response relationship between prenatal PAH exposure and subsequent reductions of the white matter surface in childhood. The effects of PAH exposure on white matter were confined almost exclusively to the left hemisphere of the brain and involved almost its entire surface, including the frontal, parietal, temporal, and occipital lobes. Reduced white matter measures of the left hemisphere were associated significantly with higher scores for the externalizing problems subscale of the CBCL, as well as with externalizing symptoms that included ADHD symptoms and conduct disorder problems. Higher prenatal PAH exposure was associated significantly with reduced processing speed during intelligence testing, consistent with the association detected in the larger study population from which our sample was drawn. The magnitude of white matter disturbances in the left hemisphere mediated the association of processing speed with PAH exposure. These findings suggest that PAH air pollutants are important contributors to slower processing speed, ADHD symptoms, and externalizing problems in urban youth via the disruptive effects of prenatal PAH exposure on the development of left hemisphere white matter, particularly in the frontal, parietal, and temporal lobes, which subserve attention and impulse control.
Additional effects of postnatal PAH exposure, measured at age 5 years, were detected bilaterally in dorsal prefrontal white matter when covarying for prenatal PAH exposure. These effects of postnatal PAH exposure were spatially distinct from and statistically independent of those for prenatal PAH exposure. Their locations in the dorsal prefrontal cortices are consistent with the timing of exposure and the protracted postnatal development of the prefrontal cortex in humans, which continues through late childhood and adolescence. Although our data do not indicate what consequences these postnatal effects on prefrontal white matter may have on cognition or behavior, the location of the effects would be expected to exacerbate difficulties with processing speed, attention, and impulse control—functions supported by the prefrontal cortices.27
Our imaging findings are consistent with those of a prior pilot study28 that reported a higher rate of white matter hyperintensities in children living in a highly polluted urban environment (13 of 23 [56.5%]) compared with a rate in children living in a less polluted urban environment (1 of 13 [7.7%]). In addition, reduced white matter volumes measured using automated computer algorithms were detected bilaterally in a subset of 20 children from the highly polluted environment compared with a subset of 10 children from the less polluted environment.29 However, levels of exposure to specific air pollutants, such as PAHs, were not measured.
Previous anatomical imaging studies of youth with ADHD using deformation-based measures of the cerebral surface, similar to measures used herein, reported bilaterally reduced volumes of inferior frontal and anterior temporal lobes,30 likely as a consequence of delayed maturation relative to healthy comparison youth.31 The morphological features associated with ADHD symptoms detected in our community sample differed from those reported previously among youth with ADHD in clinical samples, suggesting that exposure to high levels of air pollutants (PAHs) may produce a specific morphological subtype of ADHD (eDiscussion in the Supplement).
Our findings that left hemisphere white matter reductions mediated the effects of PAH exposure on processing speed, as well as that white matter reductions were also associated with attention problems and ADHD, are consistent with reports from animal studies that prenatal exposure to high PAH levels reduces long-term potentiation7 and impairs various cognitive abilities, including spatial learning, short-term memory,32-34 and novel object discrimination.35,36 Animal studies of PAH-induced neurotoxicity have focused primarily on brain gray matter, but our findings suggest that PAH effects on white matter should be investigated as well.
Our results indicate that the left hemisphere compared with the right hemisphere is more susceptible to the effects of PAHs in the low exposure range experienced by our study population. Higher exposure levels might have produced more prominent right hemisphere effects. A greater left hemisphere susceptibility could derive from several possible sources, including a greater sensitivity to PAHs in the molecular pathways that control prenatal development of hemispheric asymmetries in brain structure, which are present by week 10 of gestation.37 The genetic and molecular determinants of anatomical asymmetries in humans are still unknown, although several have been identified in other species, including nodal, FGF8, and ion channel–related gene products,38 at least some of which regulate the development of white matter pathways.39-41 Polycyclic aromatic hydrocarbons could also influence expression of regulatory genes that have been reported to differ across the left and right hemispheres during early fetal development.42 They could also alter levels of monoaminergic neurotransmitters33,43 or their receptors44 that regulate early brain development and lateralization. For example, serotonin regulates early patterning of the left-right body axis in animals via its effects on asymmetrically expressed genes that control brain development, such as sonic hedgehog.45,46 Our findings could also derive from the known cytotoxic effects of PAHs, but these effects would have to operate unilaterally on white matter at some time during development if they were to explain our lateralized findings. The neurotoxic effects of PAHs are thought to occur indirectly via microglial activation. The PAH benzo[a]pyrene increases reactive oxygen species within microglia, thereby reducing levels of antioxidant proteins and increasing expression of nitric oxide synthase. These reactions in turn increase production of nitric oxide and proinflammatory cytokines in microglia, leading to both the bystander death of neurons and astrogliosis.9 Finally, the effects of PAHs on microglia could also in some way alter their production of myelin,47 specifically in the left hemisphere, to reduce white matter in direct proportion to the degree of PAH exposure.
Our study has some limitations. First, we assessed the effects of PAHs only at the cerebral and white matter surfaces and not deep within the brain’s parenchyma. Second, our sample size was limited. We are performing imaging in many more children in our study population to confirm these findings and to assess the interactive effects of PAHs with other environmental contaminants on brain structure and function. Third, prenatal PAH monitoring was limited to a short window during the third trimester, and the earlier stages of pregnancy may be more vulnerable to its effects. Nevertheless, estimates of prenatal PAH exposure based on individual 48-hour personal air monitoring correlated significantly with estimates based on the mean of consecutive 2-week integrated indoor air monitoring periods, indicating that PAH exposure is chronic and constant.48 Fourth, the urinary metabolite concentrations measured at age 5 years represent different sources of PAH exposure besides air, including dietary and dermal and also represent metabolites of different parent PAH compounds. Fifth, we cannot entirely exclude the possibility that our findings could have been caused by other co-occurring exposures,49 including non-PAH air pollutants, that we did not measure. Nevertheless, we were careful to select children for MR imaging from our overall cohort who had minimal prenatal exposure to environmental tobacco smoke, the insecticide chlorpyrifos, and lead. Sixth, our findings were identified in a minority population with a high level of poverty, low educational attainment, reduced English-language proficiency, and below-average maternal IQ, within a specific population of New York City. Therefore, our results do not necessarily generalize to other populations.
Despite these limitations, our findings raise important concerns about the deleterious effects of air pollutants, and PAHs in particular, on brain development in children, as well as the consequences of those brain effects on cognition and behavior. The linear dose-response relationship for the effects of PAH exposure on brain morphology suggests that every unit reduction in exposure to PAHs during gestation and early postnatal life should yield a proportionate reduction in white matter disturbance and its associated cognitive and behavioral effects. If confirmed, our findings have important public health implications given the ubiquity of PAHs in air pollutants among the general population.
Submitted for Publication: October 1, 2014; final revision received January 5, 2015; accepted January 19, 2015.
Corresponding Author: Bradley S. Peterson, MD, Institute for the Developing Mind, Children’s Hospital Los Angeles, 4650 Sunset Blvd, Mail Stop 135, Los Angeles, CA 90027 (firstname.lastname@example.org).
Published Online: March 25, 2015. doi:10.1001/jamapsychiatry.2015.57.
Author Contributions: Drs Peterson and Rauh had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Peterson, Rauh, Miller, Perera.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Peterson, Rauh, Perera.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Peterson, Rauh, Bansal, Hao.
Obtained funding: Peterson, Rauh, Miller, Perera.
Administrative, technical, or material support: All authors.
Study supervision: Peterson, Perera.
Conflict of Interest Disclosures: None reported.
Funding/Support: This study was supported by grants 5P01ES09600, P50ES015905, and 5R01ES08977 from the National Institute of Environmental Health Sciences; by grants R827027, RD832141, RD834509, 8260901, RD832096, and RR00645 from the US Environmental Protection Agency; and by grants MH068318 and K02-74677 from the National Institute of Mental Health.
Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: We are grateful to the families of northern Manhattan who have generously contributed their time and effort to this study.
Correction: This article was corrected on April 20, 2015, to fix an error in the byline.