Association of Maternal Insecticide Levels With Autism in Offspring From a National Birth Cohort
Publication: American Journal of Psychiatry
Abstract
Objective:
Autism is a complex neurodevelopmental disorder with a largely unknown etiology. To date, few studies have investigated prenatal exposure to toxins and risk of autism by using maternal biomarkers of exposure. Persistent organic pollutants are lipophilic halogenated organic compounds and include the insecticide dichlorodiphenyltrichloroethane (DDT), as well as its metabolite p,p′-dichlorodiphenyl dichloroethylene (p,p′-DDE), and polychlorinated biphenyls (PCBs). The objective of this study was to test whether elevated maternal levels of persistent organic pollutants are associated with autism among offspring.
Method:
The investigation was derived from the Finnish Prenatal Study of Autism, a national birth cohort study based on a nested case-control design. Cases of autism among children born between 1987 and 2005 were ascertained by national registry linkages. In cases of childhood autism and matched control subjects (778 matched case-control pairs), maternal serum specimens from early pregnancy were assayed for levels of p,p′-DDE and total levels of PCBs.
Results:
The odds of autism among offspring were significantly increased with maternal p,p′-DDE levels that were in the highest 75th percentile, with adjustment for maternal age, parity, and history of psychiatric disorders (odds ratio=1.32, 95% CI=1.02, 1.71). The odds of autism with intellectual disability were increased by greater than twofold with maternal p,p′-DDE levels above this threshold (odds ratio=2.21, 95% CI=1.32, 3.69). There was no association between total levels of maternal PCBs and autism.
Conclusions:
These findings provide the first biomarker-based evidence that maternal exposure to insecticides is associated with autism among offspring. Although further research is necessary to replicate this finding, this study has implications for the prevention of autism and may provide a better understanding of its pathogenesis.
Autism is a complex neurodevelopmental disorder with a largely unknown etiology. It is characterized by impaired language, disrupted reciprocal social interactions, and stereotyped behaviors and interests (1). Both genetic and environmental factors have been associated with the disorder (2–4). To date, few studies have examined an association between prenatal exposure to toxins and autism, and among these, most have been based on ecologically, rather than serologically, documented exposures. For example, specific associations were reported for residential proximity to sites contaminated with pesticides (5, 6) and traffic-related air pollution (7). However, associations between prenatal exposure to air pollution and risk of autism spectrum disorder were not shown in a Swedish twin study (8) or in a large collaborative European study (9).
Persistent organic pollutants are lipophilic halogenated organic compounds and include the insecticide dichlorodiphenyltrichloroethane (DDT), as well as its metabolite p,p′-dichlorodiphenyl dichloroethylene (p,p′-DDE), and polychlorinated biphenyls (PCBs) (10). Before the late 1970s, these compounds were in widespread use in developed countries (mainly as insecticides [i.e., DDT] and in transformers and electrical equipment [i.e., PCBs]). Although these chemicals were widely banned in many countries more than 30 years ago, they became ubiquitous in these countries, including in the United States (11) and Finland (12). Because of their lipophilic nature and chemical half-lives of as long as several decades (13), these compounds persist in the food chain, particularly through fatty food sources, resulting in continuous exposure among populations. Persistent organic pollutants are transferred across the placenta, resulting in lipid-adjusted cord blood concentrations that range from 30% to 50% of levels found in maternal plasma (14). Thus, there is ongoing prenatal exposure potential among nearly all children because of existing maternal body burdens (11), as demonstrated in a nationally representative sample of U.S. women in 2003–2004 (11).
Maternal exposure to persistent organic pollutants has been associated with aberrant perinatal outcomes and childhood neurocognitive outcomes. Increasing maternal levels of p,p′-DDE were associated with an elevated risk of preterm birth in a study with a large sample size (15), and reductions in indices of psychomotor development and other cognitive functions (16, 17) as well as delayed processing speed (18) have been observed in exposed offspring. Furthermore, maternal PCBs have been associated with aberrant neurocognitive outcomes, although findings are inconsistent (for a review, see reference 19).
Although associations with autism-related behaviors have been reported in several studies that used interview and ecologic data on maternal exposure to persistent organic pollutants (5, 6, 20, 21), few studies have examined biomarker-based measures of maternal exposure to these pollutants and autism spectrum disorder in offspring (22, 23). In a small pilot study from the Finnish Prenatal Study of Autism, we previously reported that maternal levels of p,p′-DDE and PCBs were associated with autism in childhood, although the findings were not statistically significant (22). In the Early Markers of Autism study, Lyall et al. (23) observed increased mean levels of several PCB congeners, including PCB 138/158 and PCB 153, in mothers of children with autism spectrum disorder.
We therefore hypothesized that maternal p,p′-DDE levels and total PCB levels, each in the highest quartile of the distribution, would be related to risk of autism among offspring. Supplementary analyses were conducted to investigate whether offspring sex and comorbid intellectual disability modified the relationship between maternal exposure to persistent organic pollutants and autism.
Method
Study Population
The study is derived from a large national population-based birth cohort. The Finnish Prenatal Study of Autism is based on a nested case-control design. The sampling frame was defined such that all members of the national birth cohort were within the age of risk of autism. Toward this end, the study subjects comprised all offspring born in Finland from 1987 to 2005, and they were followed up until 2007. The study methods are described in further detail by Lampi et al. (24).
Description of the Birth Cohort, Biobank, and National Registries
All offspring in the Finnish Prenatal Study of Autism were derived from the Finnish Maternity Cohort, which consists of more than 1 million pregnancies with archived prenatal serum specimens drawn since 1983 (24). Sera were obtained during the first trimester and early second trimester (months 2–4 of pregnancy) from more than 98% of pregnant women in Finland. One maternal serum sample was acquired for each pregnancy. After the screening, serum samples were stored as one aliquot at –25°C in a single biorepository at the National Institute for Health and Welfare in Oulu, Finland. All samples in the Finnish Maternity Cohort can be linked to offspring by a unique personal identification number, assigned to all residents of Finland since 1971.
Identification of Case and Comparison Subjects
The Finnish Hospital and Outpatient Discharge Register was used to identify all recorded diagnoses from psychiatric hospital admissions and outpatient visits for childhood autism (ICD-10 code F84.0) among individuals registered with the Finnish Maternity Cohort. Registry diagnoses of childhood autism were validated with the Autism Diagnostic Interview–Revised (24). Computerized data are available from January 1, 1987, to the present. Only singleton births were included. Cases diagnosed over the sampling frame were identified from registry linkages between the Finnish Maternity Cohort and the Finnish Hospital and Outpatient Discharge Register from January 1, 1987, to December 31, 2007. The total number of childhood autism cases in the Finnish Prenatal Study of Autism was 1,132.
Case subjects were matched 1:1 to comparison subjects (singleton births only) on date of birth, sex, birthplace, and residence in Finland. Comparison subjects were drawn from the birth cohort and were without a diagnosis of autism spectrum disorder (no ICD-10 code F84.0 diagnosis). The analytic sample comprised 778 case subjects (from the 1,132 total cases of autism spectrum disorder mentioned above) and 778 matched control subjects.
Laboratory Analyses
All assays were performed blind to case-control status. Matched case and control subjects were analyzed in the same run to minimize variation between runs. In the analysis of persistent organic pollutants, we tested the following two primary hypotheses: autism in offspring would be associated with increased maternal concentration of p,p′-DDE and autism in offspring would be associated with increased maternal concentration of total PCBs. The analytical method used is described in detail elsewhere (25). Briefly, ethanol and [13C]-labeled internal standards of each persistent organic pollutant compound were added to the serum samples. Dichloromethane-hexane was added for extraction of persistent organic pollutants, followed by activated silica to bind the sample water, ethanol, and protein precipitate. The upper dichloromethane-hexane layer was poured into a multilayer silica column for the removal of coextracted compounds that interfere with the gas chromatography-mass spectrometry quantitation. Persistent organic pollutants were eluted from the cleanup column with additional dichloromethane-hexane. The recovery standard [13C]-PCB-128 was added, and the eluate was concentrated for gas chromatography with tandem mass spectrometry analysis for quantification of persistent organic pollutants.
For each batch of samples, a control serum sample from the National Institute of Standards and Technology, Standard Reference Material 1958, was included. Recoveries of p,p′-DDE and PCB levels varied from 86% to 106% (coefficient of variation, 1.6%−6.5%) of the certified concentrations for Standard Reference Material 1589 and from 83% to 101% (coefficient of variation, 2.0%−6.6%) of the calculated concentrations for diluted Standard Reference Material 1589, respectively. The limits of quantification were 5 pg/mL for each PCB congener and 40 pg/mL for p,p′-DDE. Fresh weight serum concentrations of persistent organic pollutants, which demonstrated high correlation with lipid-based concentrations in a previous study (overall, r=0.95) (26), are reported here.
Classification of Persistent Organic Pollutant Variables
In order to limit the number of analyses of the compounds, we focused on two hypothesized primary measures of maternal exposure to persistent organic pollutants: maternal p,p′-DDE levels in the highest 75th percentile of the distribution and maternal total PCBs, quantified as the sum of concentrations of the 10 measured congeners (PCB 74, PCB 99, PCB 118, PCB 138, PCB 153, PCB 156, PCB 170, PCB 180, PCB 183, and PCB 187), in the highest 75th percentile of the distribution. These PCBs were selected because they represent approximately 85%−90% of all PCBs on a mass basis.
The study was approved by the ethical committees of the hospital district of Southwest Finland and the Finland National Institute for Health and Welfare as well as the institutional review board of the New York State Psychiatric Institute. At the time all maternal serum specimens were obtained, mothers provided informed consent after receiving a description of the nature and possible consequences of the procedure and the data derived from serum analyses.
Statistical Analysis
We computed descriptive statistics and correlations between levels of persistent organic pollutants. These were analyzed separately for case and control subjects. Potential confounders were selected on the basis of previous relationships with exposure to persistent organic pollutants or autism from other studies (27) and compared between the two study groups by using chi-square and t tests. Potential confounders were maternal age, number of previous births (0 or ≥1), socioeconomic status (upper white collar, lower white collar, blue collar, or other), maternal and parental history of psychiatric disorders, and gestational week of the blood draw (Table 1). Data on maternal age, maternal socioeconomic status, and previous births were acquired from the Finnish Medical Birth Register. Data on maternal and paternal history of psychiatric disorders were acquired from the Finnish Hospital and Outpatient Discharge Register. Data on paternal age were obtained from the Finnish Population Register. Data on gestational week of the blood draw were obtained from the Finnish Maternity Cohort.
| Covariate | Case Subjects (N=778) | Control Subjects (N=778) | |||
|---|---|---|---|---|---|
| N | % | N | % | pa | |
| Birth year | 1.0 | ||||
| 1987–1990 | 68 | 8.7 | 68 | 8.7 | |
| 1991–1993 | 209 | 26.9 | 209 | 26.9 | |
| 1994–1996 | 208 | 26.7 | 208 | 26.7 | |
| 1997–2005 | 293 | 37.7 | 293 | 37.7 | |
| Offspring sex | 1.0 | ||||
| Male | 606 | 77.9 | 606 | 77.9 | |
| Female | 172 | 22.1 | 172 | 22.1 | |
| Maternal age (years) | 0.01 | ||||
| ≤19 | 9 | 1.2 | 21 | 2.7 | |
| 20–24 | 107 | 13.8 | 134 | 17.2 | |
| 25–29 | 257 | 33.0 | 254 | 32.7 | |
| 30–34 | 228 | 29.3 | 233 | 30.0 | |
| 35–39 | 141 | 18.1 | 116 | 14.9 | |
| ≥40 | 36 | 4.6 | 20 | 2.6 | |
| Maternal parityb | 0.001 | ||||
| 0 | 189 | 24.3 | 254 | 32.9 | |
| 1 | 266 | 34.2 | 241 | 31.2 | |
| 2 | 177 | 22.8 | 134 | 17.3 | |
| ≥3 | 145 | 18.7 | 144 | 18.6 | |
| Maternal socioeconomic statusc | 0.46 | ||||
| Upper white collar | 89 | 13.5 | 106 | 16.6 | |
| Lower white collar | 305 | 46.3 | 284 | 44.4 | |
| Blue collar | 134 | 20.3 | 131 | 20.5 | |
| Other | 131 | 19.9 | 119 | 18.6 | |
| Maternal history of psychiatric disordersd | 0.0003 | ||||
| No | 650 | 83.6 | 699 | 89.9 | |
| Yes | 128 | 16.5 | 79 | 10.2 | |
| Parental history of psychiatric disordersd | 0.02 | ||||
| No | 586 | 75.3 | 624 | 80.2 | |
| Yes | 192 | 24.7 | 154 | 19.8 | |
| Mean | SD | Mean | SD | pe | |
| Gestational weeks at blood draw | 10.9 | 3.47 | 10.8 | 3.4 | 0.49 |
a
Determined by using chi-square test for differences in the proportion of case and control subjects across all strata of the covariate.
b
Data are missing for one case subject and five control subjects.
c
Data are missing for 119 case subjects and 138 control subjects.
d
ICD-10 codes F20–25, F28–29, F30–34, F38–39, F84, F40–45, F48, F50–53, F55, F59–66, F68–69, F99, and F10–19; ICD-9 codes 295, 296, 297, 298.8A, 298.9x, 300.4, 301.2C, 299, 300–300.3, 300.5–301.1, 301.2 excluding 301.2C, 301.3–301.9, 302, 307.1A, 307.4A, 307.4F, 307.4H, 307.5A–C and 307.5E, 307.8A, 307.9x, 309–309.1, 309.2 excluding 309.2A and 309.2B, 309.2D–309.2F, 309.3–309.9 excluding 309.3A and 309.4A, 312.0A, 312.1–312.2, 312.3 excluding 312.3D, 312.4–312.9, 291–292, 303–305; ICD-8 codes 295, 296, 297, 298.00, 298.10, 298.20, 298.30, 298.99, 299, 300.41, 308, 300.0–300.3, 300.4, 300.5–302.9, 305, 306.40, 306.50, 306.98, 307.99, 291, and 303–304.
e
Determined by using t test for differences between case and control subjects.
Appropriate to the case-control study design, point and interval estimates of odds ratios for the association of maternal levels of p,p′-DDE and total PCBs with autism were obtained by fitting conditional logistic regression models for matched sets. Statistical significance was set at a p value <0.05. Covariates were included in the adjusted models on the basis of associations with the outcome. We did not match on these covariates because of the disadvantages of overmatching (28) and because they could be controlled effectively in the multivariable analyses.
For the primary analyses of persistent organic pollutants (p,p′-DDE and total PCBs), exposures were analyzed as dichotomous variables, with cutoff points at the 75th percentile. Exploratory analyses were conducted after stratification by sex and intellectual disability of the case subjects, given well-known sex differences in autism (29) as well as extensive evidence of comorbid intellectual disability (30) (ICD-9 codes for intellectual disability: F317, F318.0, F318.1, F318.2, and F319; ICD-10 codes for intellectual disability: F70, F71, F72, F73, F78, and F79). Moreover, previous studies have indicated that some risk factors may be distinct for autism with intellectual disability (31) relative to autism without intellectual disability (32), including our previous finding that accelerated growth velocity of head circumference at 3 months of age was associated with autism with intellectual disability but not autism without intellectual disability (31). We examined effect modification of p,p′-DDE levels and total levels of PCBs by adding product terms to models for each variable by p,p′-DDE or by PCB levels higher than the 75th percentile. The evidence for heterogeneity of the odds ratios between strata for each potential effect modifier was assessed on the basis of the p values for the product terms. In order to evaluate whether maternal levels of PCB 138/158 and PCB 153 were associated with autism, we conducted supplementary analyses of these maternal PCBs and autism.
Statistical analyses were performed with SAS 9.4 (SAS Institute, Cary, N.C.). Bonferroni correction was not performed given that only two primary hypothesized variables were tested (maternal p,p′-DDE levels higher than the 75th percentile and maternal total PCB levels higher than the 75th percentile), as mentioned above.
Results
Covariates
Older maternal age, increased maternal parity, and maternal and parental history of psychiatric disorders were significantly associated with odds of autism in offspring (Table 1). There were no relationships between maternal socioeconomic status and odds of autism. Earlier birth year, older maternal age, lower maternal parity, and higher maternal socioeconomic status were associated with higher maternal levels of total PCBs and of p,p′-DDE among control subjects. Offspring sex and maternal or parental history of psychiatric disorders were not associated with maternal levels of persistent organic pollutants.
Primary Findings
The mean and median levels of maternal persistent organic pollutants among the study subjects are presented in Table 2. In almost all samples, p,p′-DDE was measured above the limits of quantitation (case and control subjects, N=775/778). Each of the PCB congeners was measured above the limits of quantitation in 95%–100% of samples. The mean maternal p,p′-DDE level among case subjects was 1,032 pg/mL (SD=2,176), compared with 811 pg/mL (SD=1,660) in corresponding control subjects. Additionally, the median levels of maternal p,p′-DDE were higher among case subjects (512 pg/mL [interquartile range, 263–948]) compared with control subjects (469 pg/mL [interquartile range, 249–806]). The mean level of total maternal PCBs was 1,022 pg/mL (SD=649) among case subjects, compared with 999 pg/mL (SD=660) among control subjects, and the median levels of total maternal PCBs were 884 pg/mL (interquartile range, 583–1,282) and 865 pg/mL (interquartile range, 570–1,258) among case and control subjects, respectively. For descriptive purposes, we have reported the mean and median levels of the 10 PCB congeners.
| Case Subjects (N=778) | Control Subjects (N=778) | |||||
|---|---|---|---|---|---|---|
| Variable | Mean | SD | Median | Mean | SD | Median |
| p,p′-Dichlorodiphenyl dichloroethylene | 1,032.0 | 2,175.5 | 512.0 | 811.2 | 1659.8 | 469.4 |
| Total polychlorinated biphenyls (PCBs)a | 1022.4 | 649.4 | 883.6 | 998.6 | 659.7 | 864.8 |
| PCB congener | ||||||
| PCB 74 | 23.9 | 26.2 | 18.7 | 22.2 | 20.2 | 17.8 |
| PCB 99 | 28.1 | 21.0 | 23.4 | 28.2 | 27.1 | 22.3 |
| PCB 118 | 57.4 | 42.6 | 46.9 | 54.5 | 43.7 | 44.4 |
| PCB 138 | 198.2 | 127.4 | 174.6 | 195.8 | 134.6 | 168.8 |
| PCB 153 | 293.8 | 185.5 | 258.9 | 289.6 | 198.7 | 249.5 |
| PCB 156 | 29.8 | 20.1 | 25.5 | 29.0 | 20.6 | 24.8 |
| PCB 170 | 99.8 | 65.8 | 88.2 | 96.9 | 60.8 | 84.8 |
| PCB 180 | 211.2 | 140.5 | 181.2 | 204.2 | 132.0 | 176.6 |
| PCB 183 | 24.6 | 17.4 | 21.6 | 24.1 | 17.1 | 20.9 |
| PCB 187 | 55.7 | 41.1 | 46.4 | 53.9 | 40.1 | 45.1 |
a
Sum of the concentrations of the 10 measured PCB congeners, selected because they represent approximately 85%–90% of all PCBs on a mass basis.
The odds of autism in offspring were significantly increased (by 32%) with maternal p,p′-DDE levels that were in the top 75th percentile of the control distribution (odds ratio=1.32, 95% CI=1.02, 1.71, p=0.03), with adjustment for maternal age, parity, and maternal history of psychiatric disorders (Table 3). For total maternal levels of PCBs, there was no increase in the adjusted odds of autism among offspring for exposure above the 75th percentile (odds ratio=0.95, 95% CI=0.73, 1.24, p=0.69). Adjusting models for maternal age and parity only or for maternal age, parity, and parental history of psychiatric disorders had minimal effect on the results.
| Case Subjects | Control Subjects | Unadjusted | Adjusteda | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Persistent Organic Pollutant | N | % | N | % | Odds Ratio | 95% CI | p | Odds Ratio | 95% CI | p |
| p,p′-Dichlorodiphenyl dichloroethylene >75th percentile | 239 | 30.7 | 194 | 24.9 | 1.41 | 1.11, 1.80 | 0.01 | 1.32 | 1.02, 1.71 | 0.03 |
| Total polychlorinated biphenyls (PCBs),b >75th percentile | 202 | 26.0 | 194 | 24.9 | 1.06 | 0.84, 1.35 | 0.62 | 0.95 | 0.73, 1.24 | 0.69 |
a
Adjusted for maternal age, parity, and maternal history of psychiatric disorders (for diagnoses, see the Table 1 footnote).
b
Sum of the concentrations of 10 measured PCB congeners (PCB 74, PCB 99, PCB 118, PCB 138, PCB 153, PCB 156, PCB 170, PCB 180, PCB 183, and PCB 187), selected because they represent approximately 85%–90% of all PCBs on a mass basis.
Stratum-specific estimates for associations between maternal levels of p,p′-DDE and total maternal levels of PCBs and autism are summarized in Table 4. The association between maternal p,p′-DDE levels higher than the 75th percentile and odds of autism was significant among male offspring (odds ratio=1.35, 95% CI=1.02, 1.80, p=0.04) but not female offspring (odds ratio=1.19, 95% CI=0.67, 2.13, p=0.55), although the estimates for male compared with female offspring did not differ significantly (p value for interaction, 0.70). The increase in the odds of autism associated with maternal levels of p,p′-DDE higher than the 75th percentile was greater among case subjects with intellectual disability (odds ratio=2.21, 95% CI=1.32, 3.69, p=0.002) compared with case subjects without intellectual disability (odds ratio=1.22, 95% CI=0.88, 1.69, p=0.18), and these odds ratios were significantly different from one another (p value for interaction, 0.04). There were no associations between total maternal levels of PCBs and autism among male or female offspring and among case subjects with or without intellectual disability.
| Variable | Case Subjects (N)a | Control Subjects (N)a | Odds Ratiob | 95% CI | p | p-Intc |
|---|---|---|---|---|---|---|
| p,p′-Dichlorodiphenyl dichloroethylene | ||||||
| Sex | 0.70 | |||||
| Male | 605 | 601 | 1.35 | 1.02, 1.80 | 0.04 | |
| Female | 172 | 172 | 1.19 | 0.67, 2.13 | 0.55 | |
| Intellectual disability in the case subject | 0.04 | |||||
| Yes | 218 | 216 | 2.21 | 1.32, 3.69 | 0.002 | |
| No | 559 | 557 | 1.22 | 0.88, 1.69 | 0.18 | |
| Total polychlorinated biphenyls | ||||||
| Sex | 1.00 | |||||
| Male | 605 | 601 | 0.95 | 0.70, 1.27 | 0.72 | |
| Female | 172 | 172 | 0.95 | 0.54, 1.67 | 0.85 | |
| Intellectual disability in the case subject | 0.93 | |||||
| Yes | 218 | 216 | 0.97 | 0.60, 1.56 | 0.88 | |
| No | 559 | 557 | 0.94 | 0.69, 1.28 | 0.70 |
a
Data indicate the number of subjects in each group with complete information for covariates (data on maternal parity are missing for six subjects).
b
Adjusted for maternal age, parity, and maternal history of psychiatric disorders (for diagnoses, see the Table 1 footnote).
c
The p value for the interaction between odds ratios.
We examined whether maternal levels of PCB 138 and PCB 153 were associated with autism, given the findings of Lyall et al. (23). No associations were observed for PCB 138 (odds ratio=0.90, 95% CI=0.60, 1.18, p=0.44) or PCB 153 (odds ratio=0.97, 95% CI=0.74, 1.26, p=0.80). Additionally, there were no associations between any of the other PCB congeners and autism.
Correlations Between Persistent Organic Pollutants
The correlation between maternal levels of p,p′-DDE and total PCBs was 0.4. Total PCBs were correlated with the levels of individual PCB congeners, with r values ranging from 0.74 to 0.99 (for further details, see Table S1 in the online supplement ).
Discussion
This large national birth cohort study of maternal levels of persistent organic pollutants and autism among offspring produced two principal findings. First, maternal levels of p,p′-DDE were significantly increased in mothers of case subjects with autism compared with mothers of control subjects without autism. The findings persisted after adjustment for covariates related to autism. To our knowledge, this is the first biomarker-based evidence of this association. Second, maternal levels of total PCBs, and other PCBs variously defined, were unrelated to autism risk, and thus we did not replicate the associations between maternal levels of PCBs and autism in our previous pilot study from the Finnish Prenatal Study of Autism birth cohort, despite the similar source population and method. However, the sample size in the pilot study was small, and none of the findings reached statistical significance (22).
We propose two reasons for the observation that maternal exposure to p,p′-DDE was related to autism while maternal exposure to PCB was not. First, maternal exposure to DDT and DDE is associated with both premature birth and small gestational age status. Exposures to both of these compounds have been well replicated as risk factors for autism spectrum disorder (15, 33). In contrast, maternal PCB exposure has not been related to prematurity or small gestational age status (34). Second, p,p′-DDE inhibits androgen receptor binding, androgen-induced transcriptional activity, and androgen action, including in developing rats (35). Offspring of rats injected with valproic acid, an in utero risk factor for autism (36), exhibited reduced androgen receptor expression in most cerebellar lobules, in both male and female offspring (37); cerebellar abnormalities, including Purkinje cell numbers, have been observed in the brains of individuals with autism (38) and in rat offspring exposed prenatally to valproic acid (39). In contrast, PCBs increase androgen receptor transcription (40).
One possible reason for inconsistent findings of an association between maternal exposure to persistent organic pollutants and autism in offspring across studies is differences in the chemical mixtures and contexts of exposure between populations. A study that examined PCB 153 and p,p′-DDE levels in adults from four different geographic populations found that the correlation between the levels of these two persistent organic pollutants varied considerably, as did the associated covariates, likely reflecting differences in primary routes of exposure (41). Animal studies have demonstrated interactive effects on behavior and learning between different neurotoxicant chemicals, including PCBs and methylmercury (42). Therefore, it is possible that differences in these findings for p,p′-DDE and PCBs in studies of persistent organic pollutants and autism were due to differences between populations in the exposure profiles for other chemicals that interact with these pollutants. Moreover, Schmidt et al. (43) observed that folic acid intake during pregnancy attenuated the relationship between maternal insecticide exposure (determined on the basis of interviews and ecologically defined exposures to pesticides); conceivably, substances that may protect against developmental pathology from insecticides and other persistent organic pollutants differ between populations (43).
Our findings are not in agreement with those of Lyall et al. (23), who demonstrated that maternal levels of PCB 138/158 and 153 in the highest 75th percentile of the distribution were significantly associated with offspring with autism spectrum disorder. In another study of maternal levels of persistent organic pollutants associated with autism in offspring, based on a different cohort, a relatively small sample was utilized, and autistic behaviors rather than clinical diagnoses of autism spectrum disorder were included, and therefore the results may not be comparable with the results of the present study (44). The authors of that study found that maternal PCB 178 levels were associated with fewer autistic behaviors among offspring, and maternal levels of p,p′-DDE and dichlorodiphenyl trichloroethane did not show associations with the outcome.
In our study, the association between maternal levels of p,p′-DDE and autism in offspring was isolated to offspring with comorbid intellectual disability. This may suggest that the relationship between maternal exposure to p,p′-DDE and autism is related to intellectual disability in general and not to autism specifically. Previous studies have shown associations between maternal levels of p,p′-DDE and cognitive dysfunction, including reduced psychomotor development (16), general cognitive function, verbal and memory ability (17), and processing speed and verbal comprehension (18) among offspring; however, other studies have not shown these associations. For example, transplacental exposure to p,p′-DDE was associated with higher scores on the Bayley Scales of Infant Development at 6 months; the relationship disappeared at 12 months (45); and no associations were observed for maternal p,p′-DDE concentrations and scores on the Bayley Scales of Infant Development at age 8 months and on IQ at age 7 (46). If maternal exposure to DDT or p,p′-DDE has no effect on childhood neurocognition in general population samples, this may suggest that this exposure is related to a subgroup of autism cases characterized by comorbid intellectual disability, rather than to intellectual disability itself.
Although the association between maternal p,p′-DDE levels and autism was significant among male but not female offspring, the estimates of association did not differ significantly between males and females. It is possible that the lower number of female subjects hindered our ability to detect differences, if any were present, between the sexes.
Strengths and Limitations
Strengths of this study include a larger sample size than in some previous studies (22), high detection rates, and a national population-based sample. Our study had several limitations as well. First, we did not examine a comparison group of individuals with intellectual disability but without autism; hence, we cannot rule out the possibility that our finding of an association between maternal p,p′-DDE exposure and autism in offspring was accounted for by intellectual disability. However, in addition to the preceding discussion on maternal levels of p,p′-DDE and neurocognition in offspring, we note that Lyall et al. (23) reported similar associations in subgroup analyses of autism with and without comorbid intellectual disability. In their analysis of intellectual disability without autism spectrum disorder, they found a numerically increased risk for intellectual disability among offspring in the second and fourth quartiles of maternal levels of PCB 138/158 and in the third quartile of maternal levels of p,p′-DDE, although these associations were not statistically significant. Second, although the majority of mothers of case subjects in our birth cohort had serum samples tested, a significant proportion were not included. The included case subjects were born after 1993 (p<0.0001) and were more likely to be positive for a maternal (p=0.01) or parental (p=0.04) history of psychiatric disorders than those who were not included (for further details, see Table S2 in the online supplement ). However, this should not have biased our results given that we accounted for these characteristics in the design and analyses. Third, we presented fresh weight serum concentrations of persistent organic pollutants, rather than lipid-adjusted concentrations. However, the unadjusted measures were found to have a low degree of bias under a range of causal scenarios (47) and to be highly correlated with lipid-adjusted concentrations (r=0.95) (26). Nonetheless, we cannot entirely rule out bias due to uncontrolled confounding by serum lipids. Fourth, we did not adjust for multiple comparisons; if we had, the association of maternal levels of p,p′-DDE with autism would have narrowly missed the Bonferroni-corrected traditional threshold for statistical significance (alpha=0.025), given that two persistent organic pollutants were tested. However, the Bonferroni method focuses on situations in which multiple statistical tests are conducted without a priori hypotheses or when testing for whether all null hypotheses are true simultaneously (48). These situations did not apply to our primary statistical tests, which were restricted to a priori hypotheses, and these were evaluated separately. Finally, although potential confounders were adjusted in the analyses, there is always the possibility, as in any observational study, of residual confounding. However, given the selectivity of our finding for maternal levels of p,p′-DDE, this does not appear to be likely, unless the potential for residual confounding is greater for p,p′-DDE compared with PCBs.
Conclusions
In this study, we demonstrated an association between maternal levels of p,p′-DDE and odds of autism in offspring. To our knowledge, this is the first study to report this relationship. There was no association between maternal exposure to PCBs and autism. Further research is necessary to replicate this finding and evaluate a potential role for maternal PCBs in autism. This study has potential implications for the prevention of autism and may provide a better understanding of its pathogenesis.
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References
1.
Fombonne E: Epidemiology of pervasive developmental disorders. Pediatr Res 2009; 65:591–598
2.
Newschaffer CJ, Croen LA, Daniels J, et al: The epidemiology of autism spectrum disorders. Annu Rev Public Health 2007; 28:235–258
3.
Ronald A, Hoekstra RA: Autism spectrum disorders and autistic traits: a decade of new twin studies. Am J Med Genet B Neuropsychiatr Genet 2011; 156B:255–274
4.
Posthuma D, Polderman TJ: What have we learned from recent twin studies about the etiology of neurodevelopmental disorders? Curr Opin Neurol 2013; 26:111–121
5.
Roberts EM, English PB, Grether JK, et al: Maternal residence near agricultural pesticide applications and autism spectrum disorders among children in the California Central Valley. Environ Health Perspect 2007; 115:1482–1489
6.
Shelton JF, Geraghty EM, Tancredi DJ, et al: Neurodevelopmental disorders and prenatal residential proximity to agricultural pesticides: the CHARGE study. Environ Health Perspect 2014; 122:1103–1109
7.
Volk HE, Lurmann F, Penfold B, et al: Traffic-related air pollution, particulate matter, and autism. JAMA Psychiatry 2013; 70:71–77
8.
Gong T, Almqvist C, Bölte S, et al: Exposure to air pollution from traffic and neurodevelopmental disorders in Swedish twins. Twin Res Hum Genet 2014; 17:553–562
9.
Guxens M, Ghassabian A, Gong T, et al: Air pollution exposure during pregnancy and childhood autistic traits in four European population-based cohort studies: The ESCAPE project. Environ Health Perspect 2016; 124:133–140
10.
Berghuis SA, Bos AF, Sauer PJ, et al: Developmental neurotoxicity of persistent organic pollutants: an update on childhood outcome. Arch Toxicol 2015; 89:687–709
11.
Woodruff TJ, Zota AR, Schwartz JM: Environmental chemicals in pregnant women in the United States: NHANES 2003–2004. Environ Health Perspect 2011; 119:878–885
12.
Kiviranta H, Tuomisto JT, Tuomisto J, et al: Polychlorinated dibenzo-p-dioxins, dibenzofurans, and biphenyls in the general population in Finland. Chemosphere 2005; 60:854–869
13.
Milbrath MO, Wenger Y, Chang CW, et al: Apparent half-lives of dioxins, furans, and polychlorinated biphenyls as a function of age, body fat, smoking status, and breast-feeding. Environ Health Perspect 2009; 117:417–425
14.
Soechitram SD, Athanasiadou M, Hovander L, et al: Fetal exposure to PCBs and their hydroxylated metabolites in a Dutch cohort. Environ Health Perspect 2004; 112:1208–1212
15.
Longnecker MP, Klebanoff MA, Zhou H, et al: Association between maternal serum concentration of the DDT metabolite DDE and preterm and small-for-gestational-age babies at birth. Lancet 2001; 358:110–114
16.
Torres-Sánchez L, Rothenberg SJ, Schnaas L, et al: In utero p,p′-DDE exposure and infant neurodevelopment: a perinatal cohort in Mexico. Environ Health Perspect 2007; 115:435–439
17.
Torres-Sánchez L, Schnaas L, Rothenberg SJ, et al: Prenatal p,p′-DDE exposure and neurodevelopment among children 3.5-5 years of age. Environ Health Perspect 2013; 121:263–268
18.
Gaspar FW, Harley KG, Kogut K, et al: Prenatal DDT and DDE exposure and child IQ in the CHAMACOS cohort. Environ Int 2015; 85:206–212
19.
Korrick SA, Sagiv SK: Polychlorinated biphenyls, organochlorine pesticides and neurodevelopment. Curr Opin Pediatr 2008; 20:198–204
20.
Keil AP, Daniels JL, Hertz-Picciotto I: Autism spectrum disorder, flea and tick medication, and adjustments for exposure misclassification: the CHARGE (CHildhood Autism Risks from Genetics and Environment) case-control study. Environ Health 2014; 13:3
21.
Roberts EM, English PB: Bayesian modeling of time-dependent vulnerability to environmental hazards: an example using autism and pesticide data. Stat Med 2013; 32:2308–2319
22.
Cheslack-Postava K, Rantakokko PV, Hinkka-Yli-Salomäki S, et al: Maternal serum persistent organic pollutants in the Finnish Prenatal Study of Autism: a pilot study. Neurotoxicol Teratol 2013; 38:1–5
23.
Lyall K, Croen LA, Sjödin A, et al: Polychlorinated biphenyl and organochlorine pesticide concentrations in maternal mid-pregnancy serum samples: association with autism spectrum disorder and intellectual disability. Environ Health Perspect 2017; 125:474–480
24.
Lampi KM, Banerjee PN, Gissler M, et al: Finnish Prenatal Study of Autism and Autism Spectrum Disorders (FIPS-A): overview and design. J Autism Dev Disord 2011; 41:1090–1096
25.
Koponen J, Rantakokko P, Airaksinen R, et al: Determination of selected perfluorinated alkyl acids and persistent organic pollutants from a small volume human serum sample relevant for epidemiological studies. J Chromatogr A 2013; 1309:48–55
26.
Rylander L, Björkdahl CM, Axmon A, et al: Very high correlations between fresh weight and lipid-adjusted PCB-153 serum concentrations: irrespective of fasting status, age, body mass index, gender, or exposure distributions. Chemosphere 2012; 88:828–831
27.
Wang C, Geng H, Liu W, et al: Prenatal, perinatal, and postnatal factors associated with autism: a meta-analysis. Medicine 2017; 96:e6696
28.
Rothman KJ, Greenland S, Lash TL: Design strategies to improve study accuracy, in Modern Epidemiology, 3rd ed. Philadelphia, Lippincott Williams and Wilkins, 2008, pp 175–181
29.
Werling DM, Geschwind DH: Sex differences in autism spectrum disorders. Curr Opin Neurol 2013; 26:146–153
30.
Wingate M, Kirby RS, Pettygrove S, et al: Prevalence of autism spectrum disorder among children aged 8 years: autism and developmental disabilities monitoring network, 11 sites, United States, 2010. MMWR Surveill Summ 2014; 63:1–21
31.
McKeague IW, Brown AS, Bao Y, et al: Autism with intellectual disability related to dynamics of head circumference growth during early infancy. Biol Psychiatry 2015; 77:833–840
32.
Stessman HA, Xiong B, Coe BP, et al: Targeted sequencing identifies 91 neurodevelopmental-disorder risk genes with autism and developmental-disability biases. Nat Genet 2017; 49:515–526
33.
Lampi KM, Lehtonen L, Tran PL, et al: Risk of autism spectrum disorders in low birth weight and small for gestational age infants. J Pediatr 2012; 161:830–836
34.
Longnecker MP, Klebanoff MA, Brock JW, et al: Maternal levels of polychlorinated biphenyls in relation to preterm and small-for-gestational-age birth. Epidemiology 2005; 16:641–647
35.
Kelce WR, Stone CR, Laws SC, et al: Persistent DDT metabolite p,p′-DDE is a potent androgen receptor antagonist. Nature 1995; 375:581–585
36.
Christensen J, Grønborg TK, Sørensen MJ, et al: Prenatal valproate exposure and risk of autism spectrum disorders and childhood autism. JAMA 2013; 309:1696–1703
37.
Perez-Pouchoulen M, Miquel M, Saft P, et al: Prenatal exposure to sodium valproate alters androgen receptor expression in the developing cerebellum in a region and age specific manner in male and female rats. Int J Dev Neurosci 2016; 53:46–52
38.
Courchesne E: An MRI study of autism: the cerebellum revisited. Neurology 1999; 52:1106–1107
39.
Ingram JL, Peckham SM, Tisdale B, et al: Prenatal exposure of rats to valproic acid reproduces the cerebellar anomalies associated with autism. Neurotoxicol Teratol 2000; 22:319–324
40.
Casati L, Sendra R, Poletti A, et al: Androgen receptor activation by polychlorinated biphenyls: epigenetic effects mediated by the histone demethylase Jarid1b. Epigenetics 2013; 8:1061–1068
41.
Jönsson BA, Rylander L, Lindh C, et al: Inter-population variations in concentrations, determinants of and correlations between 2,2′,4,4′,5,5′-hexachlorobiphenyl (CB-153) and 1,1-dichloro-2,2-bis (p-chlorophenyl)-ethylene (p,p′-DDE): a cross-sectional study of 3161 men and women from Inuit and European populations. Environ Health 2005; 4:27
42.
Fischer C, Fredriksson A, Eriksson P: Neonatal co-exposure to low doses of an ortho-PCB (PCB 153) and methyl mercury exacerbate defective developmental neurobehavior in mice. Toxicology 2008; 244:157–165
43.
Schmidt RJ, Kogan V, Shelton JF, et al: Combined prenatal pesticide exposure and folic acid intake in relation to autism spectrum disorder. Environ Health Perspect 2017; 125:097007
44.
Braun JM, Kalkbrenner AE, Just AC, et al: Gestational exposure to endocrine-disrupting chemicals and reciprocal social, repetitive, and stereotypic behaviors in 4- and 5-year-old children: the HOME study. Environ Health Perspect 2014; 122:513–520
45.
Gladen BC, Rogan WJ, Hardy P, et al: Development after exposure to polychlorinated biphenyls and dichlorodiphenyl dichloroethene transplacentally and through human milk. J Pediatr 1988; 113:991–995
46.
Jusko TA, Klebanoff MA, Brock JW, et al: In-utero exposure to dichlorodiphenyltrichloroethane and cognitive development among infants and school-aged children. Epidemiology 2012; 23:689–698
47.
Gaskins AJ, Schisterman EF: The effect of lipid adjustment on the analysis of environmental contaminants and the outcome of human health risks. Methods Mol Biol 2009; 580:371–381
48.
Perneger TV: What’s wrong with Bonferroni adjustments. BMJ 1998; 316:1236–1238
Information & Authors
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History
Received: 19 October 2017
Revision received: 29 March 2018
Revision received: 7 May 2018
Accepted: 14 May 2018
Published online: 16 August 2018
Published in print: November 01, 2018
Keywords
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Competing Interests
The authors report no financial relationships with commercial interests.
Funding Information
National Institute of Environmental Health Sciences10.13039/100000066: 1R01ES019004
Supported by the National Institute of Environmental Health Sciences (grant 1R01ES019004).Metrics & Citations
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