- Email: [email protected]
Hyperactivity Disorder in School-Age Children
Phthalates Exposure and Attention-Deficit/Hyperactivity Disorder in School-Age Children Bung-Nyun Kim, Soo-Churl Cho, Yeni Kim, Min-Sup Shin, Hee-Jeong Yoo, Jae-Won Kim, Young Hee Yang, Hyo-Won Kim, Soo-Young Bhang, and Yun-Chul Hong Background: Very few studies have examined the association between attention-deficit/hyperactivity disorder (ADHD) and phthalate exposure in humans. The aim of this study was to investigate the impact of phthalates on symptoms of ADHD in school-age children. Methods: A cross-sectional examination of urine phthalate concentrations was performed, and scores on measures of ADHD symptoms and neuropsychological dysfunction with regard to attention and impulsivity were obtained from 261 Korean children, age 8 –11 years. Results: Mono-2-ethylheyl phthalate (MEHP) and mono-2-ethyl-5-oxohexylphthalate (MEOP) for metabolites of Di-2-ethylhexylphthalate (DEHP) and mono-n-butyl phthalate (MNBP) for metabolites of dibutyl phthalate (DBP) were measured in urine samples. The mean concentrations of MEHP, MEOP, and MNBP were 34.0 g/dL (SD ⫽ 36.3; range: 2.1–386.7), 23.4 g/dL (SD ⫽ 23.0; range: .75–244.8), and 46.7 g/L (SD ⫽ 21.4; range: 13.2–159.3), respectively. After adjustment for covariates, teacher-rated ADHD scores were significantly associated with DEHP metabolites but not with DBP metabolites. We also found significant relationships between the urine concentrations of metabolites for DBP and the number of omission and commission errors in continuous performance tests (CPT) after adjustment for covariates. Conclusion: The present study showed a strong positive association between phthalate metabolites in urine and symptoms of ADHD among school-age children. Key Words: ADHD, neuropsychology, phthalate
P
hthalates are a class of high-production-volume synthetic chemicals with widespread human exposure because of their common use in plastics and other consumer products (1). Phthalates leach from plastic products into the environment over time. Due to their high-production volume, common use, and widespread environmental contamination, these compounds reach humans through ingestion, inhalation, and dermal exposure daily (2). Although limited in number, studies in human populations suggest an association between phthalate exposure and adverse reproductive health outcomes (3). A correlation was found between urinary phthalate levels and pregnancy complications such as anemia, toxemia, and preeclampsia in women living near a plastics manufacturer (4,5). Considerable public concern about the possibility that phthalates might affect neuronal functioning has emerged on the basis of the following observations. First, previous animal studies have reported that the phthalate compound might cause hyperactivity and impulsivity in rats. Those animal behaviors are strikingly From the Division of Child & Adolescent Psychiatry (B-NK, S-CC, YK, M-SS, J-WK, YHY, H-WK), Department of Psychiatry and Institute of Human Behavioral Medicine, Seoul National University College of Medicine; Department of Psychiatry (H-JY), Seoul National University Bundang Hospital, Seong-nam; Department of Preventive Medicine (Y-CH), Seoul National University College of Medicine and Institute of Environmental Medicine, SNUMRC, Seoul; and the Department of Psychiatry (S-YB), Ulsan University Hospital, Ulsan, Republic of Korea. Address correspondence to Yun-Chul Hong, M.D., Ph.D., Department of Preventive Medicine, Seoul National University College of Medicine and Institute of Environmental Medicine, SNUMRC, 28 Yongon-dong, Chongno-gu, Seoul 110-744, Republic of Korea; E-mail: [email protected]. Received Feb 23, 2009; revised Jul 16, 2009; accepted Jul 22, 2009.
0006-3223/09/$36.00 doi:10.1016/j.biopsych.2009.07.034
similar to the clinical syndrome of attention-deficit/hyperactivity disorder (ADHD) found in children (6). Second, other environmental disrupting agents such as polychlorinated biphenyls have been known to affect cognitive function (7,8). Therefore, phthalates distributed in the environment can cause injury to the developing brain. We hypothesized that phthalates might also contribute to the incidence of neurodevelopmental disorders such as ADHD. To our knowledge, there have been no human studies examining the association of phthalate and ADHD symptoms. Thus, this study might be the first to evaluate the relationship between ADHD symptoms in children and phthalate exposure.
Methods and Materials Study Population and Recruitment The study participants were recruited from four cities in Korea: Seoul (metropolitan), Seongnam (suburban), Ulsan (industrial), and Yeoncheon (rural). Schools located in the center of each city were chosen to reflect a microcosm of each city. A letter inviting participation in the study was sent to 3rd–5th-grade children and their parents. After receiving a detailed explanation of the study, 287 children and their parents gave written consent for participation (434 children contacted; participation rate ⫽ 66%). Among these, 279 children completed both urine sampling and continuous performance test (CPT) measurements. Of these subjects, 18 children were excluded from the analyses due to low birth weight (⬍2.5 kg, n ⫽ 17) or seizure disorder (n ⫽ 1), which yielded 261 students in the final analysis. We gathered informed consent from parents and assents from children. Through the informed consent process, the explanation of study contents was precisely and adequately delivered to parents, teachers, and children. The institutional review board of the Seoul National University Hospital approved the study protocol. BIOL PSYCHIATRY 2009;66:958 –963 © 2009 Society of Biological Psychiatry
BIOL PSYCHIATRY 2009;66:958 –963 959
B.-N. Kim et al. Measurement of Attention and Hyperactivity Problems Parents completed an extensive questionnaire about demographic and other relevant factors related to their children including home environment; family structure; socioeconomic status (SES); maternal and paternal education; maternal age at birth of the child; smoking behavior by the parents; and the medical, obstetric, neurodevelopmental, and educational histories of the children. Teacher-Rated ADHD Rating Scale. Comprising 18 items, the ADHD Rating Scale (ARS) designed by DuPaul (9) uses a 4-point rating scale ranging from 0 to 3 to evaluate the severity of the symptoms of ADHD according to DSM-IV diagnostic criteria. These 18 items include 9 that reflect symptoms related to inattention and 9 that reflect symptoms related to hyperactivity and impulsivity. The Korean version of teacher-rated ARS was reported to be valid and reliable in community studies (10). Computerized Measurements of Inattention and Impulsivity. A computerized CPT (11) was used to measure inattention and impulsivity among children with ADHD. The Korean version of the CPT (ADHD Diagnostic System [ADS]) has been standardized, and its validity and reliability are well-established (12). A visual stimulus was presented for 100 msec every 2 sec, with the instruction to respond to a square containing a triangle (target) and to inhibit responses to a square containing a circle or square (nontarget). The four major variables recorded included: 1) omission errors (failures to respond to the target), which are commonly interpreted as a measure of inattention; 2) commission errors (responding inappropriately to the nontarget), which are commonly interpreted as a measure of impulsivity; 3) response times for correct responses to the target; and 4) the SD of the response times for correct responses to the target. IQ Measurement. Each child was given the abbreviated form of the Korean Educational Development Institute-Wechsler Intelligence Scales (KEDI-WISC) (13), which tests vocabulary, arithmetic, picture arrangement, and block design. Testing was conducted by trained examiners in a quiet room according to arrangements made by a specialist (SMS) before the beginning of measurement. Examiners were unaware of the phthalate level of their examinee. Scores obtained on abbreviated batteries are highly correlated with the WISC full-scale IQ (FSIQ) scores (14). The sum of the age-adjusted t scores for arithmetic and vocabulary was used to estimate the verbal IQ (VIQ), and the scores for block design and picture arrangement were used to estimate the performance IQ (PIQ). Phthalate Level Measurement We measured monoester phthalates as biomarkers for exposure to phthalates to ensure that contamination with ubiquitous diester phthalates was eliminated. The monoester phthalates were measured with high-performance liquid chromatography tandem mass spectrometry (Agilent 6410 triple Quad LCMS; Agilent, Santa Clara, California). Five hundred microliters of urine were buffered with 30 L of 2.0 mol/L sodium acetate (pH 5.0) and then spiked with a mixture of isotope phthalate monoester standards (100 ng/mL) and 10 L of -glucuronidase. The sample was incubated at 37°C for 3 hours to deconjugate the glucuronidated phthalate metabolites. After incubation, 100 L of 2 nmol/L hydrogen chloride was added to collect phthalate monoester. The extract was dried with nitrogen gas and reconstituted with 1 mL of high-performance liquid chromatography– grade water in a 2-mL glass vial. One blank and one quality control (QC) sample were included in each batch of samples. The QC sample was spiked with pooled urine and a mixture of
phthalate monoester standard (100 ng/mL). The supernatants were purified by solid phase extraction with disposable Agilent C18 1.8 m (2.1 ⫻ 50 mm). The mobile phase was .1% acetic acid water: .01% acetic acid acetonitrile (90:10, v/v) at a flow rate of .25 mL/min, and the eluates were monitored at target masses of 221, 293, and 291 and internal standard masses of 225, 297, and 295. Statistical Analysis Data Analysis. We calculated means and distribution percentiles for creatinine-corrected urinary concentrations. For concentrations below the limits of detection (LOD), a value equal to the LOD divided by two was used in the statistical analysis. Because the concentrations of the exposure were not normally distributed, we used their log-transformed values. Correlations and multiple regressions were used to evaluate the effects of environmental chemical exposure on ADHD symptom scores. Covariate Adjustment and Missing Data. For sensitivity analysis, two sets of covariates were tested. Model 1 was adjusted for children’s IQ level, age, gender, and paternal educational level. Model 2 was adjusted for children’s IQ, age, gender, paternal and maternal educational levels, maternal smoking during pregnancy, and SES. All missing data were replaced with the mode of the respective variable. Analytic Model. First, differences between the children included and excluded in the analysis and differences by area were estimated with t tests or analyses of variance for continuous variables and 2 tests for categorical variables. Next, we evaluated the linear correlation between ADHD score and concurrent urine phthalate (MEOP, MEHP, MNBP) concentration. In the regression analyses with hierarchal linear model, ADHD score and ADS score were the primary dependent variables, and concurrently measured urine phthalate concentrations were the primary independent variable. The regression analyses were performed with a set of covariates based on established predictors of children’s attentional and hyperactive problems, such as children’s gender, age, SES, and maternal and paternal educational level. Regression analyses were performed with SAS 9.1 for Windows (SAS, Cary, North Carolina). We also used generalized additive model of S-plus 8.0.4 to evaluate the linearity of relationship between the metabolite concentrations and the outcomes.
Results Participant Characteristics The geographic distribution of study participants was as follows: Seoul, n ⫽ 78; Seongnam, n ⫽ 86; Ulsan, n ⫽ 64; and Yeoncheon, n ⫽ 59. No significant differences were found in the numbers of children recruited from each city [2(3) ⫽ 6.43, p ⫽ .092]. Of the 287 children, 279 had completed teacher-rated scales, ADS testing, and urine phthalate measures. Of these subjects, 18 were excluded from analyses due to low birth weight (⬍2.5 kg, n ⫽ 17) and seizure disorder (n ⫽ 1). The demographic characteristics of the subjects are summarized in Table 1. No significant differences were found in the background characteristics among children included and those excluded from analysis, except with regard to paternal educational level and birth weight (Table 1). The demographic information was provided by mothers for 85.7% of the participants, by fathers for 9.6% of the participants, and by other caretakers for 4.8% of the participants. The mean full-scale KEDI-WISC for the total sample was 104.8 (SD: 14.4, range: 49 –137), the mean verbal IQ was 20.9 (SD: 5.3, www.sobp.org/journal
960 BIOL PSYCHIATRY 2009;66:958 –963
B.-N. Kim et al.
Table 1. Demographic Characteristics of the Subjects
Characteristics Children Age at testing (yr) Female (%) Birth weight (kg) Indirect smoking (%) Mother Maternal age at delivery (yr) Smoked during pregnancy (%) Yearly income ⬎$25,000 (%) Education (yr) Father Education (yr)
All Children (n ⫽ 287)
Children Selected for Analysis (n ⫽ 261)
Children with Incomplete Data or Excludeda from Analysis (n ⫽ 26)
p
9.7 ⫾ .6 46.3 3.22 ⫾ .5 50.2
9.7 ⫾ .6 46.0 3.29 ⫾ .5 50.6
10.1 ⫾ .9 50 2.44 ⫾ .7 48.0
.052 .837 .000a .837
28.2 ⫾ 3.8 3.1 57.1 12.8 ⫾ 2.3
28.3 ⫾ 3.8 2.7 56.7 12.9 ⫾ 2.3
27.5 ⫾ 4.4 7.7 61.5 12.2 ⫾ 2.5
.332 .191 .92 .167
13.2 ⫾ 2.4
13.3 ⫾ 2.4
12.2 ⫾ 2.5
.027a
Children with low birth weight (⬍ 2.5 kg, n ⫽ 17), seizure disorder (n ⫽ 1), and children with incomplete data (n ⫽ 8, no peripheral blood measure or no IQ score) were excluded from the main analyses. a
range: 3–35), and the mean performance IQ was 22.2 (SD: 5.0, range: 6 –32). The mean total score of the teacher-rated ARS was 11.3 (SD: 14.4, range: 3–54). Association Between Urine Phthalate Concentrations and Concurrently Measured ADHD Symptom Scores Given by Teachers After adjusting for covariates, a significant association was found between urine phthalate metabolite concentrations and the inattention and hyperactivity subscale scores. Teacher-rated ADHD scores were significantly associated with DEHP metabolites but not with DBP metabolites (Table 2). The relationships between urine DEHP metabolites and teacher-rated ADHD symptom scores are shown in Figure 1. The relationships are not exactly linear but almost linear with threshold in the lower exposure levels.
Association Between Urine Phthalate Concentrations and Concurrently Measured ADS Data We also found significant relationships between the urine concentration of metabolites for DBP and the number of omission and commission errors in the ADS (Table 3). The relationships between urine DBP metabolites and omission and commission errors on the ADS are presented in Figure 2. Although the relationships are not completely linear, we can assume that urine DBP metabolites have linear relationships with scores of omission and commission errors.
Discussion In this study, we demonstrated that the concentration of urine phthalates was significantly correlated with teacher-rated ADHD symptom scores and with omission and commission errors on
Table 2. Association Between Urine Phthalate Metabolites Concentration and Teacher-Rated ARS Model 1 Teacher ARS Inattention Subscore MEHP MEOP MEHP⫹MEOP MNBP Hyperactivity Subscore MEHP MEOP MEHP⫹MEOP MNBP Total Score MEHP MEOP MEHP⫹MEOP MNBP
 (SE)
Model 2 p
 (SE)
p
2.228 (.967) 2.810 (.963) 2.513 (.974) ⫺1.893 (1.590)
.022 .003 .010 .235
2.150 (.973) 2.693 (.972) 2.417 (.981) ⫺2.085 (1.602)
.028 .006 .014 .194
2.615 (.885) 2.970 (.882) 2.806 (.891) ⫺.308 (1.468)
.003 ⬍.001 .001 .834
2.578 (.891) 2.938 (.890) 2.770 (.898) ⫺.406 (1.481)
.004 .001 .002 .784
4.844 (1.728) 5.780 (1.720) 5.320 (1.740) ⫺2.201 (2.859)
.005 ⬍.001 .002 .442
4.729 (1.741) 5.631 (1.737) 5.188 (1.754) ⫺2.492 (2.884)
.007 .001 .003 .388
Model 1: adjustment of children’s IQ, age, gender, and parental education level. Model 2: adjustment of children’s IQ, age, gender, and parental education level and socioeconomic status. ARS, attention-deficit/hyperactivity disorder Rating Scale; MNBP, mono-n-butyl phthalate, metabolite of dibutyl phthalate; MEHP, mono-2-ethylheyl phthalate, metabolite of di-2-ethylhexylphthalate (DEHP); MEOP, mono-2-ethyl5-oxohexylphthalate, metabolite of DEHP.
www.sobp.org/journal
BIOL PSYCHIATRY 2009;66:958 –963 961
B.-N. Kim et al.
Figure 1. Distribution of inattention (IA), hyperactivity (HA), and total scores of teacher-rated attention-deficit/hyperactivity disorder (ADHD-RS) according to log concentrations of urine di-2-ethylhexylphthalate (DEHP) metabolites after adjustment of children’s IQ, age, gender, and parental education level and SES. MEHP, mono-2-ethylheyl phthalate, metabolite of DEHP; MEOP, mono-2-ethyl-5-oxohexylphthalate, metabolite of DEHP.
neuropsychological tests after adjusting for variables including age, gender, IQ, parental educational level, and SES. To our knowledge, this study was the first to show an association between ADHD symptoms (inattention and hyperactivity/impulsivity) and urine phthalates in human subjects. Previous animal studies (6,15,16) have shown that phthalaterelated metabolites induce hyperactivity in rats. These studies reported that pups treated with phthalate demonstrated 1.4 times the level of hyperactivity at night compared with control subjects. Such hyperactivity was dose-dependent, which is consistent with the results of our study. Previous studies have also found that the vulnerability of the developing brain is particularly dependent on the period during which exposure to chemicals occurs (17,18). Animal studies have shown that the behaviors of young rats were more seriously affected by intracisternal administration of phthalate when such developmental processes as differentiation and synaptogenesis were less complete (18,19). These results suggest that the developing brains of children can experience greater harm from phthalates than those of adults.
Neurodevelopmental exposure to neurotoxic agents is more detrimental to children, because the neurotoxic agents might disrupt neurodevelopmental process (e.g., neuronal proliferation, migration, differentiation, and myelination) (20,21). Ethanol (22), nicotine (23), and lead (24) are environmental agents known to disrupt neuronal proliferation, migration, and differentiation. Some even suggest that lead might affect glutamate release, N-methyl-D-aspartate receptor function, or structural plasticity resulting in learning impairments and low IQ (25). Children are especially sensitive to lead, because a greater portion is ingested in the gastrointestinal tract and a greater portion of lead reaches the brain compared with adults (26). Studies on the effects of phthalates on brain development in humans are needed to investigate the contribution of phthalates to the epigenetic pathophysiological mechanisms leading to ADHD. Such studies should examine the mechanisms by which phthalates induce hyperactivity and inattention, the cardinal symptoms of ADHD. It is possible that the toxicity of phthalates is attributable to degeneration of dopaminergic neurons, leading to the hyperki-
Table 3. Association Between Urine Phthalate Metabolites Concentration and the Score of CPT Model 1 ADS Omission Error MEHP MEOP MEHP⫹MEOP MBP Commission Error MEHP MEOP MEHP⫹MEOP MBP Reaction Time MEHP MEOP MEHP⫹MEOP MBP Reaction Time-SD MEHP MEOP MEHP⫹MEOP MBP
Model 2
 (SE)
p
 (SE)
p
8.948 (8.840) 9.005 (4.392) 9.018 (8.179) 15.73 (7.23)
.383 .041 .343 .030
8.959 (4.967) 9.110 (10.606) 9.062 (4.803) 15.842 (7.343)
.165 .391 .146 .032
3.487 (5.717) 3.561 (5.677) 3.560 (5.782) 19.737 (8.347)
.592 .580 .588 .018
2.883 (5.848) 2.919 (5.882) 2.934 (5.945) 18.313 (8.426)
.661 .657 .660 .030
.881 (2.923) .802 (3.085) .932 (2.885) ⫺3.578 (5.315)
.780 .811 .766 .543
1.215 (2.873) .994 (3.117) 1.116 (2.997) ⫺2.915 (5.217)
.698 .771 .732 .610
7.971 (28.255) 7.793 (6.276) 7.952 (6.307) 18.403 (14.731)
.778 .215 .208 .294
7.846 (6.294) 7.371 (6.302) 7.838 (6.368) 18.122 (14.606)
.213 .243 .219 .298
Model 1: adjustment of children’s IQ, age, gender, and parental education level. Model 2: adjustment of children’s IQ, age, gender, and parental education level and SES. ADS, Attention Problem Diagnostic System; CPT, Continuous Performance Test; other abbreviations as in Table 2.
www.sobp.org/journal
962 BIOL PSYCHIATRY 2009;66:958 –963
Figure 2. Distribution of the scores of omission and commission errors of ADHD Diagnostic System (ADS) according to log concentrations of urine DBP metabolite after adjustment of children’s IQ, age, gender, and parental education level and SES. Omission Error, score of omission errors from ADS test; Commission Error, HA: score of omission errors from ADS test; MNBP, mono-n-butyl phthalate, metabolite of dibutyl phthalate; other abbreviations as in Figure 1.
netics observed in rats in cases of 6-hydroxydopamine (OHDA) procedures (27). Well-known animal models of ADHD like the OHDA rat model suggest that the dopamine neuronal damage can provoke hyperactivity and impulsivity. Many structural magnetic resonance imaging studies showed striatal volume loss suggesting the dopamine neuronal loss in ADHD patients (28). Phthalates can affect various levels of the dopamine system via expression of the dopamine transporter gene, which plays a role in one of the reliable animal models of ADHD (29). One of the major findings of phthalate animal studies was the modification of gene expression of dopamine transport gene. The molecular imaging studies of ADHD suggested that the dopamine transporter level of ADHD children and adults was higher compared with normal children and adults. The overexpression of dopamine transporter was one of the consistent findings in ADHD patients. These findings are compatible with animal studies (30,31). Indeed, animal studies have shown that phthalate metabolites significantly reduce immunoreactivity for tyrosine hydroxylase, which is a rate-limiting enzyme with regard to the production of dopamine (15). The molecular mechanism underlying the toxicity of phthalates has been explained in terms of the activation of peroxisome proliferators-activated receptor by phthalate metabolites, which www.sobp.org/journal
B.-N. Kim et al. in turn leads to disruption in the critical timing of the growth and differentiation of the targets cells (32). With DNA macroarray data, researchers have found that phthalate metabolites change the expression patterns of various genes, including both the dopamine receptor D4 (DRD4) and the dopamine transporter in the midbrain (6). The dopamine receptor D4 and dopamine transporter gene expression modulation can induce changes in extracellular dopamine and neuronal dopamine sensitivity, resulting in hyperactivity and impulsivity in rats. The DRD4 and the dopamine transporter gene are the most vigorously studied and most frequently replicated candidate genes to be associated with ADHD in humans (33–36). Recent Korean genetic studies have reported an association between certain alleles of the human D4 receptor gene and the dopamine transporter gene and the occurrence of ADHD (37,38). Dopamine transporters and dopamine receptors might be involved in the pathogenesis of ADHD. Indeed, methylphenidate, which increases the synaptic concentration of dopamine by blocking dopamine transporters, has been used for the treatment of ADHD (39,40). However, it remains unclear whether chemically mediated alterations in levels of the gene expression of the dopamine D4 receptor and the dopamine transporter might contribute to hyperactivity in rats. Although information about the environment and parents’ educations were obtained through questionnaires, there were no data about father’s and mother’s family history of ADHD (i.e., genetic heritability data in the present study). Therefore, potentially confounding effects of genetic influences could not be completely ruled out. Recent studies suggest that genetic influences might not be confounders but might function to increase the susceptibility of the brain to environmental insults such as environmental hormones (41). Therefore, overly controlling for these modifiers might mask the true effect of environmental hormones on neurodevelopment. However, it should be noted that not measuring the modifiers of the genetic effect can also influence the results of this study. There were several limitations to this study. First, this study did not rely on the diagnosis of ADHD but only on the symptoms of this disorder. Thus, we can report that phthalate metabolites were significantly associated only with symptoms of ADHD: hyperactivity, inattention, and omission errors. Second, we applied only the teacher rating form (TRF) of ARS. However, the TRF was reported to be more reliable and valid than the parental report form of ARS from a Korean epidemiological study (42). Third, because our data were cross-sectional and correlational, no inferences about causality are possible at this time. Fourth, although some covariates—such as IQ, age, gender, parental education levels, and SES—were controlled, other covariates could contaminate the results of our study. Fifth, because phthalates have short biological half-lives and do not accumulate in tissues of living organisms (43,44), the single sample/participant evaluated in this study limits estimation of the effects of long-term exposure to these chemicals. However, despite these limitations, the results of this study suggest the possibility of an association between phthalate metabolites, one of the major environmental disruptors, and the inattention and hyperactive-impulsivity phenotype of ADHD. To the best of our knowledge, this is the first study to evaluate the relationship between phthalate metabolites and the cognitive endophenotypes of ADHD. Further work is required to confirm these findings and to investigate causality and pathophysiological mechanisms with a prospective design and brain imaging.
B.-N. Kim et al. Soo-Churl Cho, M.D., Ph.D., and Yun-Chul Hong, M.D., Ph.D., received a research grant from the Korea Institute of Environmental Science and Technology (Eco-Technopia 21 Project). The other authors reported no biomedical financial interests or potential conflicts of interest. 1. Wormuth M, Scheringer M, Vollenweider M, Hungerbuhler K (2006): What are the sources of exposure to eight frequently used phthalic acid esters in Europeans? Risk Anal 26:803– 824. 2. Kavlock R, Boekelheide K, Chapin R, Cunningham M, Faustman E, Foster P, et al. (2002): NTP Center for the Evaluation of Risks to Human Reproduction: Phthalates expert panel report on the reproductive and developmental toxicity of di-n-hexyl phthalate. Reprod Toxicol 16:709 –719. 3. Kavlock R, Boekelheide K, Chapin R, Cunningham M, Faustman E, Foster P, et al. (2002): NTP Center for the Evaluation of Risks to Human Reproduction: Phthalates expert panel report on the reproductive and developmental toxicity of di-n-octyl phthalate. Reprod Toxicol 16:721–734. 4. Tabacova S, Balabaeva L, Little RE (1997): Maternal exposure to exogenous nitrogen compounds and complications of pregnancy. Arch Environ Health 52:341–347. 5. Gladen BC, Tabacova S, Baird DD, Little RE, Balabaeva L (1999): Variability of lipid hydroperoxides in pregnant and nonpregnant women. Reprod Toxicol 13:41– 44. 6. Masuo Y, Morita M, Oka S, Ishido M (2004): Motor hyperactivity caused by a deficit in dopaminergic neurons and the effects of endocrine disruptors: A study inspired by the physiological roles of PACAP in the brain. Regul Pept 15:225–234. 7. Stewart PW, Reihman J, Lonky EI, Darvill TJ, Pagano J (2003): Cognitive development in preschool children prenatally exposed to PCBs and MeHg. Neurotoxicol Teratol 25:11–22. 8. Jacobson JL, Jacobson SW (2003): Prenatal exposure to polychlorinated biphenyls and attention at school age. J Pediatr 143:780 –788. 9. DuPaul GJ, Power TJ, Anastopoulos AD, Reid R (1998): ADHD Rating Scale-IV: Checklists, Norms, and Clinical Interpretation. New York: Guilford Publications. 10. So YK, Noh JS, Kim YS, Ko SG, Koh YJ (2002): The reliability and validity of Korean parent and teacher ADHD rating scale. J Korean Neuropsychiatr Assoc 41:283–289. 11. Greenberg LM, Waldman ID (1993): Developmental normative data on the test of variables of attention (TOVA). J Child Psychol Psychiatry 34: 1019 –1030. 12. Shin MS, Cho S, Chun SY, Hong KE (2000): A study of the development and standardization of ADHD diagnostic system. Korean Journal of Child and Adolescent Psychiatry 11:91–99. 13. Park KS, Yoon JY, Park HJ, Park HJ, Kwon KU (1996): Development of KEDI-WISC, Individual Intelligence Test for Korean Children. Seoul: Korean Educational Development Institute. 14. Kaufman AS (1976): A four test short form of the WISC-R. Comtemporary Educ Psychol 1:180 –196. 15. Ishido M, Masuo Y, Sayato-Suzuki J, Oka S, Niki E, Morita M (2004): Dicyclohexylphthalate causes hyperactivity in the rat concomitantly with impairment of tyrosine hydroxylase immunoreactivity. J Neurochem 91:69 –76. 16. Masuo Y, Ishido M, Morita M, Oka S (2004): Effects of neonatal treatment with 6-hydroxydopamine and endocrine disruptors on motor activity and gene expression in rats. Neural Plast 11:59 –76. 17. Rice D, Barone S Jr (2000): Critical periods of vulnerability for the developing nervous system: Evidence from humans and animal models. Environ Health Perspect 108:511–533. 18. Adams J, Barone S Jr, LaMantia A, Philen R, Rice DC, Spear L, et al. (2000): Workshop to identify critical windows of exposure for children’s health: Neurobehavioral work group summary. Environ Health Perspect 108: 535–544. 19. Vorhees CV (1994): Developmental neurotoxicity induced by therapeutic and illicit drugs. Environ Health Perspect 102:145–153. 20. Rice D, Barone S Jr (2000): Critical periods of vulnerability for the developing nervous system: Evidence from humans and animal models. Environ Health Perspect 108:511–33. 21. Mendola P, Selevan SG, Gutter S, Rice D (2002): Environmental factors associated with a spectrum of neurodevelopmental deficits. Ment Retard Dev Disabil Res Rev 8:188 –197.
BIOL PSYCHIATRY 2009;66:958 –963 963 22. Miller MW (1993): Migration of cortical neurons is altered by gestational exposure to ethanol. Alcohol Clin Exp Res 17:304 –314. 23. Levitt P (1998): Prenatal effects of drugs of abuse on brain development. Drug Alcohol Depend 51:109 –125. 24. Petit TL, Alfano DP, LeBoutillier JC (1983): Early lead exposure and the hippocampus: A review and recent advances. Neurotoxicology 4:79 –94. 25. White LD, Cory-Slechta DA, Gilbert ME, Tiffany-Castiglioni E, Zawia NH, et al. (2007): New and evolving concepts in the neurotoxicology of lead. Toxicol Appl Pharmacol 225:1–27. 26. Lidsky TI, Schneider JS (2003): Lead neurotoxicity in children: Basic mechanisms and clinical correlates. Brain 126:5–19. 27. Shaywitz BA, Yager RD, Klopper JH (1976): Selective brain dopamine depletion in developing rats: An experimental model of minimal brain dysfunction. Science 191:305–308. 28. Seidman LJ, Valera EM, Makris N (2005): Structural brain imaging of attention-deficit/hyperactivity disorder. Biol Psychiatry 57:1263–1272. 29. Adriani W, Boyer F, Gioiosa L, Macrì S, Dreyer JL, Laviola G (2009): Increased impulsive behavior and risk proneness following lentivirusmediated dopamine transporter over-expression in rats’ nucleus accumbens. Neuroscience 159:47–58. 30. Dougherty DD, Bonab AA, Spencer TJ, Rauch SL, Madras BK, Fischman AJ (1999): Dopamine transporter density in patients with attention deficit hyperactivity disorder. Lancet 354:2132–2133. 31. Cheon KA, Ryu YH, Kim YK, Namkoong K, Kim CH, Lee JD (2003): Dopamine transporter density in the basal ganglia assessed with [123I]IPT SPET in children with attention deficit hyperactivity disorder. Eur J Nucl Med Mol Imaging 30:306 –311. 32. Corton JC, Lapinskas PJ (2005): Peroxisome proliferator-activated receptors: Mediators of phthalate ester-induced effects in the male reproductive tract? Toxicol Sci 83:4 –17. 33. Cook EH Jr, Stein MA, Krasowski MD, Cox NJ, Olkon DM, Kieffer JE, et al. (1995): Association of attention-deficit disorder and the dopamine transporter gene. Am J Hum Genet 56:993–998. 34. Curran S, Mill J, Tahir E, Kent L, Richards S, Gould A, et al. (2001): Association study of a dopamine transporter polymorphism and attention deficit hyperactivity disorder in UK and Turkish samples. Mol Psychiatry 6:425– 428. 35. Barr CL, Wigg KG, Bloom S, Schachar R, Tannock R, Roberts W, et al. (2000): Further evidence from haplotype analysis for linkage of the dopamine D4 receptor gene and attention-deficit hyperactivity disorder. Am J Med Genet 96:262–267. 36. Swanson JM, Sunohara GA, Kennedy JL, Regino R, Fineberg E, Wigal T, et al. (1998): Association of the dopamine receptor D4(DRD4) gene with a refined phenotype of attention deficit hyperactivity disorder: A familybased approach. Mol Psychiatry 3:370 –372. 37. Kim JW, Kim BN, Cho SC (2006): The dopamine transporter gene and the impulsivity phenotype in attention deficit hyperactivity disorder: A case-control association study in a Korean sample. J Psychiatr Res 40: 730 –737. 38. Yang JW, Jang WS, Hong SD, Ji YI, Kim DH, Park J, et al. (2008): A case-control association study of the polymorphism at the promoter region of the DRD4 gene in Korean boys with attention deficit-hyperactivity disorder: Evidence of association with the -521 C/T SNP. Prog Neuropsychopharmacol Biol Psychiatry 32:243–248. 39. Cheon KA, Kim BN, Cho SC (2007): Association of 4-repeat allele of the dopamine D4 receptor gene exon III polymorphism and response to methylphenidate treatment in Korean ADHD children. Neuropsychopharmacology 32:1377–1383. 40. Kim YN, Shin MS, Kim JW, Yoo HJ, Cho SC, Kim BN (2009): Neurocognitive effects of switching from methylphenidate-IR to OROS-methylphenidate in children with ADHD. Hum Psychopharmacol Clin Exp 24:95–102. 41. Bellinger DC (2008): Late neurodevelopmental effects of early exposures to chemical contaminants: Reducing uncertainty in epidemiological studies. Basic Clin Pharmacol Toxicol 102:237–244. 42. Yang YH, Kim JW, Kim YN, Cho SC, Kim BN (2008): Screening of attention deficit hyperactivity disorder in Seoul. J Korean Neuropsychatr Assoc 47:292–298. 43. Koch HM, Bolt HM, Angerer J (2004): Di-2-ethylhexyl)phthalate (DEHP) metabolites in human urine and serum after a single oral dose of deuterium-labelled DEHP. Arch Toxicol 78:123–130. 44. Fennell TR, Krol WL, Sumner SC, Snyder RW (2004): Pharmacokinetics of dibutylphthalate in pregnant rats. Toxicol Sci 82:407– 418.
www.sobp.org/journal
P
hthalates are a class of high-production-volume synthetic chemicals with widespread human exposure because of their common use in plastics and other consumer products (1). Phthalates leach from plastic products into the environment over time. Due to their high-production volume, common use, and widespread environmental contamination, these compounds reach humans through ingestion, inhalation, and dermal exposure daily (2). Although limited in number, studies in human populations suggest an association between phthalate exposure and adverse reproductive health outcomes (3). A correlation was found between urinary phthalate levels and pregnancy complications such as anemia, toxemia, and preeclampsia in women living near a plastics manufacturer (4,5). Considerable public concern about the possibility that phthalates might affect neuronal functioning has emerged on the basis of the following observations. First, previous animal studies have reported that the phthalate compound might cause hyperactivity and impulsivity in rats. Those animal behaviors are strikingly From the Division of Child & Adolescent Psychiatry (B-NK, S-CC, YK, M-SS, J-WK, YHY, H-WK), Department of Psychiatry and Institute of Human Behavioral Medicine, Seoul National University College of Medicine; Department of Psychiatry (H-JY), Seoul National University Bundang Hospital, Seong-nam; Department of Preventive Medicine (Y-CH), Seoul National University College of Medicine and Institute of Environmental Medicine, SNUMRC, Seoul; and the Department of Psychiatry (S-YB), Ulsan University Hospital, Ulsan, Republic of Korea. Address correspondence to Yun-Chul Hong, M.D., Ph.D., Department of Preventive Medicine, Seoul National University College of Medicine and Institute of Environmental Medicine, SNUMRC, 28 Yongon-dong, Chongno-gu, Seoul 110-744, Republic of Korea; E-mail: [email protected]. Received Feb 23, 2009; revised Jul 16, 2009; accepted Jul 22, 2009.
0006-3223/09/$36.00 doi:10.1016/j.biopsych.2009.07.034
similar to the clinical syndrome of attention-deficit/hyperactivity disorder (ADHD) found in children (6). Second, other environmental disrupting agents such as polychlorinated biphenyls have been known to affect cognitive function (7,8). Therefore, phthalates distributed in the environment can cause injury to the developing brain. We hypothesized that phthalates might also contribute to the incidence of neurodevelopmental disorders such as ADHD. To our knowledge, there have been no human studies examining the association of phthalate and ADHD symptoms. Thus, this study might be the first to evaluate the relationship between ADHD symptoms in children and phthalate exposure.
Methods and Materials Study Population and Recruitment The study participants were recruited from four cities in Korea: Seoul (metropolitan), Seongnam (suburban), Ulsan (industrial), and Yeoncheon (rural). Schools located in the center of each city were chosen to reflect a microcosm of each city. A letter inviting participation in the study was sent to 3rd–5th-grade children and their parents. After receiving a detailed explanation of the study, 287 children and their parents gave written consent for participation (434 children contacted; participation rate ⫽ 66%). Among these, 279 children completed both urine sampling and continuous performance test (CPT) measurements. Of these subjects, 18 children were excluded from the analyses due to low birth weight (⬍2.5 kg, n ⫽ 17) or seizure disorder (n ⫽ 1), which yielded 261 students in the final analysis. We gathered informed consent from parents and assents from children. Through the informed consent process, the explanation of study contents was precisely and adequately delivered to parents, teachers, and children. The institutional review board of the Seoul National University Hospital approved the study protocol. BIOL PSYCHIATRY 2009;66:958 –963 © 2009 Society of Biological Psychiatry
BIOL PSYCHIATRY 2009;66:958 –963 959
B.-N. Kim et al. Measurement of Attention and Hyperactivity Problems Parents completed an extensive questionnaire about demographic and other relevant factors related to their children including home environment; family structure; socioeconomic status (SES); maternal and paternal education; maternal age at birth of the child; smoking behavior by the parents; and the medical, obstetric, neurodevelopmental, and educational histories of the children. Teacher-Rated ADHD Rating Scale. Comprising 18 items, the ADHD Rating Scale (ARS) designed by DuPaul (9) uses a 4-point rating scale ranging from 0 to 3 to evaluate the severity of the symptoms of ADHD according to DSM-IV diagnostic criteria. These 18 items include 9 that reflect symptoms related to inattention and 9 that reflect symptoms related to hyperactivity and impulsivity. The Korean version of teacher-rated ARS was reported to be valid and reliable in community studies (10). Computerized Measurements of Inattention and Impulsivity. A computerized CPT (11) was used to measure inattention and impulsivity among children with ADHD. The Korean version of the CPT (ADHD Diagnostic System [ADS]) has been standardized, and its validity and reliability are well-established (12). A visual stimulus was presented for 100 msec every 2 sec, with the instruction to respond to a square containing a triangle (target) and to inhibit responses to a square containing a circle or square (nontarget). The four major variables recorded included: 1) omission errors (failures to respond to the target), which are commonly interpreted as a measure of inattention; 2) commission errors (responding inappropriately to the nontarget), which are commonly interpreted as a measure of impulsivity; 3) response times for correct responses to the target; and 4) the SD of the response times for correct responses to the target. IQ Measurement. Each child was given the abbreviated form of the Korean Educational Development Institute-Wechsler Intelligence Scales (KEDI-WISC) (13), which tests vocabulary, arithmetic, picture arrangement, and block design. Testing was conducted by trained examiners in a quiet room according to arrangements made by a specialist (SMS) before the beginning of measurement. Examiners were unaware of the phthalate level of their examinee. Scores obtained on abbreviated batteries are highly correlated with the WISC full-scale IQ (FSIQ) scores (14). The sum of the age-adjusted t scores for arithmetic and vocabulary was used to estimate the verbal IQ (VIQ), and the scores for block design and picture arrangement were used to estimate the performance IQ (PIQ). Phthalate Level Measurement We measured monoester phthalates as biomarkers for exposure to phthalates to ensure that contamination with ubiquitous diester phthalates was eliminated. The monoester phthalates were measured with high-performance liquid chromatography tandem mass spectrometry (Agilent 6410 triple Quad LCMS; Agilent, Santa Clara, California). Five hundred microliters of urine were buffered with 30 L of 2.0 mol/L sodium acetate (pH 5.0) and then spiked with a mixture of isotope phthalate monoester standards (100 ng/mL) and 10 L of -glucuronidase. The sample was incubated at 37°C for 3 hours to deconjugate the glucuronidated phthalate metabolites. After incubation, 100 L of 2 nmol/L hydrogen chloride was added to collect phthalate monoester. The extract was dried with nitrogen gas and reconstituted with 1 mL of high-performance liquid chromatography– grade water in a 2-mL glass vial. One blank and one quality control (QC) sample were included in each batch of samples. The QC sample was spiked with pooled urine and a mixture of
phthalate monoester standard (100 ng/mL). The supernatants were purified by solid phase extraction with disposable Agilent C18 1.8 m (2.1 ⫻ 50 mm). The mobile phase was .1% acetic acid water: .01% acetic acid acetonitrile (90:10, v/v) at a flow rate of .25 mL/min, and the eluates were monitored at target masses of 221, 293, and 291 and internal standard masses of 225, 297, and 295. Statistical Analysis Data Analysis. We calculated means and distribution percentiles for creatinine-corrected urinary concentrations. For concentrations below the limits of detection (LOD), a value equal to the LOD divided by two was used in the statistical analysis. Because the concentrations of the exposure were not normally distributed, we used their log-transformed values. Correlations and multiple regressions were used to evaluate the effects of environmental chemical exposure on ADHD symptom scores. Covariate Adjustment and Missing Data. For sensitivity analysis, two sets of covariates were tested. Model 1 was adjusted for children’s IQ level, age, gender, and paternal educational level. Model 2 was adjusted for children’s IQ, age, gender, paternal and maternal educational levels, maternal smoking during pregnancy, and SES. All missing data were replaced with the mode of the respective variable. Analytic Model. First, differences between the children included and excluded in the analysis and differences by area were estimated with t tests or analyses of variance for continuous variables and 2 tests for categorical variables. Next, we evaluated the linear correlation between ADHD score and concurrent urine phthalate (MEOP, MEHP, MNBP) concentration. In the regression analyses with hierarchal linear model, ADHD score and ADS score were the primary dependent variables, and concurrently measured urine phthalate concentrations were the primary independent variable. The regression analyses were performed with a set of covariates based on established predictors of children’s attentional and hyperactive problems, such as children’s gender, age, SES, and maternal and paternal educational level. Regression analyses were performed with SAS 9.1 for Windows (SAS, Cary, North Carolina). We also used generalized additive model of S-plus 8.0.4 to evaluate the linearity of relationship between the metabolite concentrations and the outcomes.
Results Participant Characteristics The geographic distribution of study participants was as follows: Seoul, n ⫽ 78; Seongnam, n ⫽ 86; Ulsan, n ⫽ 64; and Yeoncheon, n ⫽ 59. No significant differences were found in the numbers of children recruited from each city [2(3) ⫽ 6.43, p ⫽ .092]. Of the 287 children, 279 had completed teacher-rated scales, ADS testing, and urine phthalate measures. Of these subjects, 18 were excluded from analyses due to low birth weight (⬍2.5 kg, n ⫽ 17) and seizure disorder (n ⫽ 1). The demographic characteristics of the subjects are summarized in Table 1. No significant differences were found in the background characteristics among children included and those excluded from analysis, except with regard to paternal educational level and birth weight (Table 1). The demographic information was provided by mothers for 85.7% of the participants, by fathers for 9.6% of the participants, and by other caretakers for 4.8% of the participants. The mean full-scale KEDI-WISC for the total sample was 104.8 (SD: 14.4, range: 49 –137), the mean verbal IQ was 20.9 (SD: 5.3, www.sobp.org/journal
960 BIOL PSYCHIATRY 2009;66:958 –963
B.-N. Kim et al.
Table 1. Demographic Characteristics of the Subjects
Characteristics Children Age at testing (yr) Female (%) Birth weight (kg) Indirect smoking (%) Mother Maternal age at delivery (yr) Smoked during pregnancy (%) Yearly income ⬎$25,000 (%) Education (yr) Father Education (yr)
All Children (n ⫽ 287)
Children Selected for Analysis (n ⫽ 261)
Children with Incomplete Data or Excludeda from Analysis (n ⫽ 26)
p
9.7 ⫾ .6 46.3 3.22 ⫾ .5 50.2
9.7 ⫾ .6 46.0 3.29 ⫾ .5 50.6
10.1 ⫾ .9 50 2.44 ⫾ .7 48.0
.052 .837 .000a .837
28.2 ⫾ 3.8 3.1 57.1 12.8 ⫾ 2.3
28.3 ⫾ 3.8 2.7 56.7 12.9 ⫾ 2.3
27.5 ⫾ 4.4 7.7 61.5 12.2 ⫾ 2.5
.332 .191 .92 .167
13.2 ⫾ 2.4
13.3 ⫾ 2.4
12.2 ⫾ 2.5
.027a
Children with low birth weight (⬍ 2.5 kg, n ⫽ 17), seizure disorder (n ⫽ 1), and children with incomplete data (n ⫽ 8, no peripheral blood measure or no IQ score) were excluded from the main analyses. a
range: 3–35), and the mean performance IQ was 22.2 (SD: 5.0, range: 6 –32). The mean total score of the teacher-rated ARS was 11.3 (SD: 14.4, range: 3–54). Association Between Urine Phthalate Concentrations and Concurrently Measured ADHD Symptom Scores Given by Teachers After adjusting for covariates, a significant association was found between urine phthalate metabolite concentrations and the inattention and hyperactivity subscale scores. Teacher-rated ADHD scores were significantly associated with DEHP metabolites but not with DBP metabolites (Table 2). The relationships between urine DEHP metabolites and teacher-rated ADHD symptom scores are shown in Figure 1. The relationships are not exactly linear but almost linear with threshold in the lower exposure levels.
Association Between Urine Phthalate Concentrations and Concurrently Measured ADS Data We also found significant relationships between the urine concentration of metabolites for DBP and the number of omission and commission errors in the ADS (Table 3). The relationships between urine DBP metabolites and omission and commission errors on the ADS are presented in Figure 2. Although the relationships are not completely linear, we can assume that urine DBP metabolites have linear relationships with scores of omission and commission errors.
Discussion In this study, we demonstrated that the concentration of urine phthalates was significantly correlated with teacher-rated ADHD symptom scores and with omission and commission errors on
Table 2. Association Between Urine Phthalate Metabolites Concentration and Teacher-Rated ARS Model 1 Teacher ARS Inattention Subscore MEHP MEOP MEHP⫹MEOP MNBP Hyperactivity Subscore MEHP MEOP MEHP⫹MEOP MNBP Total Score MEHP MEOP MEHP⫹MEOP MNBP
 (SE)
Model 2 p
 (SE)
p
2.228 (.967) 2.810 (.963) 2.513 (.974) ⫺1.893 (1.590)
.022 .003 .010 .235
2.150 (.973) 2.693 (.972) 2.417 (.981) ⫺2.085 (1.602)
.028 .006 .014 .194
2.615 (.885) 2.970 (.882) 2.806 (.891) ⫺.308 (1.468)
.003 ⬍.001 .001 .834
2.578 (.891) 2.938 (.890) 2.770 (.898) ⫺.406 (1.481)
.004 .001 .002 .784
4.844 (1.728) 5.780 (1.720) 5.320 (1.740) ⫺2.201 (2.859)
.005 ⬍.001 .002 .442
4.729 (1.741) 5.631 (1.737) 5.188 (1.754) ⫺2.492 (2.884)
.007 .001 .003 .388
Model 1: adjustment of children’s IQ, age, gender, and parental education level. Model 2: adjustment of children’s IQ, age, gender, and parental education level and socioeconomic status. ARS, attention-deficit/hyperactivity disorder Rating Scale; MNBP, mono-n-butyl phthalate, metabolite of dibutyl phthalate; MEHP, mono-2-ethylheyl phthalate, metabolite of di-2-ethylhexylphthalate (DEHP); MEOP, mono-2-ethyl5-oxohexylphthalate, metabolite of DEHP.
www.sobp.org/journal
BIOL PSYCHIATRY 2009;66:958 –963 961
B.-N. Kim et al.
Figure 1. Distribution of inattention (IA), hyperactivity (HA), and total scores of teacher-rated attention-deficit/hyperactivity disorder (ADHD-RS) according to log concentrations of urine di-2-ethylhexylphthalate (DEHP) metabolites after adjustment of children’s IQ, age, gender, and parental education level and SES. MEHP, mono-2-ethylheyl phthalate, metabolite of DEHP; MEOP, mono-2-ethyl-5-oxohexylphthalate, metabolite of DEHP.
neuropsychological tests after adjusting for variables including age, gender, IQ, parental educational level, and SES. To our knowledge, this study was the first to show an association between ADHD symptoms (inattention and hyperactivity/impulsivity) and urine phthalates in human subjects. Previous animal studies (6,15,16) have shown that phthalaterelated metabolites induce hyperactivity in rats. These studies reported that pups treated with phthalate demonstrated 1.4 times the level of hyperactivity at night compared with control subjects. Such hyperactivity was dose-dependent, which is consistent with the results of our study. Previous studies have also found that the vulnerability of the developing brain is particularly dependent on the period during which exposure to chemicals occurs (17,18). Animal studies have shown that the behaviors of young rats were more seriously affected by intracisternal administration of phthalate when such developmental processes as differentiation and synaptogenesis were less complete (18,19). These results suggest that the developing brains of children can experience greater harm from phthalates than those of adults.
Neurodevelopmental exposure to neurotoxic agents is more detrimental to children, because the neurotoxic agents might disrupt neurodevelopmental process (e.g., neuronal proliferation, migration, differentiation, and myelination) (20,21). Ethanol (22), nicotine (23), and lead (24) are environmental agents known to disrupt neuronal proliferation, migration, and differentiation. Some even suggest that lead might affect glutamate release, N-methyl-D-aspartate receptor function, or structural plasticity resulting in learning impairments and low IQ (25). Children are especially sensitive to lead, because a greater portion is ingested in the gastrointestinal tract and a greater portion of lead reaches the brain compared with adults (26). Studies on the effects of phthalates on brain development in humans are needed to investigate the contribution of phthalates to the epigenetic pathophysiological mechanisms leading to ADHD. Such studies should examine the mechanisms by which phthalates induce hyperactivity and inattention, the cardinal symptoms of ADHD. It is possible that the toxicity of phthalates is attributable to degeneration of dopaminergic neurons, leading to the hyperki-
Table 3. Association Between Urine Phthalate Metabolites Concentration and the Score of CPT Model 1 ADS Omission Error MEHP MEOP MEHP⫹MEOP MBP Commission Error MEHP MEOP MEHP⫹MEOP MBP Reaction Time MEHP MEOP MEHP⫹MEOP MBP Reaction Time-SD MEHP MEOP MEHP⫹MEOP MBP
Model 2
 (SE)
p
 (SE)
p
8.948 (8.840) 9.005 (4.392) 9.018 (8.179) 15.73 (7.23)
.383 .041 .343 .030
8.959 (4.967) 9.110 (10.606) 9.062 (4.803) 15.842 (7.343)
.165 .391 .146 .032
3.487 (5.717) 3.561 (5.677) 3.560 (5.782) 19.737 (8.347)
.592 .580 .588 .018
2.883 (5.848) 2.919 (5.882) 2.934 (5.945) 18.313 (8.426)
.661 .657 .660 .030
.881 (2.923) .802 (3.085) .932 (2.885) ⫺3.578 (5.315)
.780 .811 .766 .543
1.215 (2.873) .994 (3.117) 1.116 (2.997) ⫺2.915 (5.217)
.698 .771 .732 .610
7.971 (28.255) 7.793 (6.276) 7.952 (6.307) 18.403 (14.731)
.778 .215 .208 .294
7.846 (6.294) 7.371 (6.302) 7.838 (6.368) 18.122 (14.606)
.213 .243 .219 .298
Model 1: adjustment of children’s IQ, age, gender, and parental education level. Model 2: adjustment of children’s IQ, age, gender, and parental education level and SES. ADS, Attention Problem Diagnostic System; CPT, Continuous Performance Test; other abbreviations as in Table 2.
www.sobp.org/journal
962 BIOL PSYCHIATRY 2009;66:958 –963
Figure 2. Distribution of the scores of omission and commission errors of ADHD Diagnostic System (ADS) according to log concentrations of urine DBP metabolite after adjustment of children’s IQ, age, gender, and parental education level and SES. Omission Error, score of omission errors from ADS test; Commission Error, HA: score of omission errors from ADS test; MNBP, mono-n-butyl phthalate, metabolite of dibutyl phthalate; other abbreviations as in Figure 1.
netics observed in rats in cases of 6-hydroxydopamine (OHDA) procedures (27). Well-known animal models of ADHD like the OHDA rat model suggest that the dopamine neuronal damage can provoke hyperactivity and impulsivity. Many structural magnetic resonance imaging studies showed striatal volume loss suggesting the dopamine neuronal loss in ADHD patients (28). Phthalates can affect various levels of the dopamine system via expression of the dopamine transporter gene, which plays a role in one of the reliable animal models of ADHD (29). One of the major findings of phthalate animal studies was the modification of gene expression of dopamine transport gene. The molecular imaging studies of ADHD suggested that the dopamine transporter level of ADHD children and adults was higher compared with normal children and adults. The overexpression of dopamine transporter was one of the consistent findings in ADHD patients. These findings are compatible with animal studies (30,31). Indeed, animal studies have shown that phthalate metabolites significantly reduce immunoreactivity for tyrosine hydroxylase, which is a rate-limiting enzyme with regard to the production of dopamine (15). The molecular mechanism underlying the toxicity of phthalates has been explained in terms of the activation of peroxisome proliferators-activated receptor by phthalate metabolites, which www.sobp.org/journal
B.-N. Kim et al. in turn leads to disruption in the critical timing of the growth and differentiation of the targets cells (32). With DNA macroarray data, researchers have found that phthalate metabolites change the expression patterns of various genes, including both the dopamine receptor D4 (DRD4) and the dopamine transporter in the midbrain (6). The dopamine receptor D4 and dopamine transporter gene expression modulation can induce changes in extracellular dopamine and neuronal dopamine sensitivity, resulting in hyperactivity and impulsivity in rats. The DRD4 and the dopamine transporter gene are the most vigorously studied and most frequently replicated candidate genes to be associated with ADHD in humans (33–36). Recent Korean genetic studies have reported an association between certain alleles of the human D4 receptor gene and the dopamine transporter gene and the occurrence of ADHD (37,38). Dopamine transporters and dopamine receptors might be involved in the pathogenesis of ADHD. Indeed, methylphenidate, which increases the synaptic concentration of dopamine by blocking dopamine transporters, has been used for the treatment of ADHD (39,40). However, it remains unclear whether chemically mediated alterations in levels of the gene expression of the dopamine D4 receptor and the dopamine transporter might contribute to hyperactivity in rats. Although information about the environment and parents’ educations were obtained through questionnaires, there were no data about father’s and mother’s family history of ADHD (i.e., genetic heritability data in the present study). Therefore, potentially confounding effects of genetic influences could not be completely ruled out. Recent studies suggest that genetic influences might not be confounders but might function to increase the susceptibility of the brain to environmental insults such as environmental hormones (41). Therefore, overly controlling for these modifiers might mask the true effect of environmental hormones on neurodevelopment. However, it should be noted that not measuring the modifiers of the genetic effect can also influence the results of this study. There were several limitations to this study. First, this study did not rely on the diagnosis of ADHD but only on the symptoms of this disorder. Thus, we can report that phthalate metabolites were significantly associated only with symptoms of ADHD: hyperactivity, inattention, and omission errors. Second, we applied only the teacher rating form (TRF) of ARS. However, the TRF was reported to be more reliable and valid than the parental report form of ARS from a Korean epidemiological study (42). Third, because our data were cross-sectional and correlational, no inferences about causality are possible at this time. Fourth, although some covariates—such as IQ, age, gender, parental education levels, and SES—were controlled, other covariates could contaminate the results of our study. Fifth, because phthalates have short biological half-lives and do not accumulate in tissues of living organisms (43,44), the single sample/participant evaluated in this study limits estimation of the effects of long-term exposure to these chemicals. However, despite these limitations, the results of this study suggest the possibility of an association between phthalate metabolites, one of the major environmental disruptors, and the inattention and hyperactive-impulsivity phenotype of ADHD. To the best of our knowledge, this is the first study to evaluate the relationship between phthalate metabolites and the cognitive endophenotypes of ADHD. Further work is required to confirm these findings and to investigate causality and pathophysiological mechanisms with a prospective design and brain imaging.
B.-N. Kim et al. Soo-Churl Cho, M.D., Ph.D., and Yun-Chul Hong, M.D., Ph.D., received a research grant from the Korea Institute of Environmental Science and Technology (Eco-Technopia 21 Project). The other authors reported no biomedical financial interests or potential conflicts of interest. 1. Wormuth M, Scheringer M, Vollenweider M, Hungerbuhler K (2006): What are the sources of exposure to eight frequently used phthalic acid esters in Europeans? Risk Anal 26:803– 824. 2. Kavlock R, Boekelheide K, Chapin R, Cunningham M, Faustman E, Foster P, et al. (2002): NTP Center for the Evaluation of Risks to Human Reproduction: Phthalates expert panel report on the reproductive and developmental toxicity of di-n-hexyl phthalate. Reprod Toxicol 16:709 –719. 3. Kavlock R, Boekelheide K, Chapin R, Cunningham M, Faustman E, Foster P, et al. (2002): NTP Center for the Evaluation of Risks to Human Reproduction: Phthalates expert panel report on the reproductive and developmental toxicity of di-n-octyl phthalate. Reprod Toxicol 16:721–734. 4. Tabacova S, Balabaeva L, Little RE (1997): Maternal exposure to exogenous nitrogen compounds and complications of pregnancy. Arch Environ Health 52:341–347. 5. Gladen BC, Tabacova S, Baird DD, Little RE, Balabaeva L (1999): Variability of lipid hydroperoxides in pregnant and nonpregnant women. Reprod Toxicol 13:41– 44. 6. Masuo Y, Morita M, Oka S, Ishido M (2004): Motor hyperactivity caused by a deficit in dopaminergic neurons and the effects of endocrine disruptors: A study inspired by the physiological roles of PACAP in the brain. Regul Pept 15:225–234. 7. Stewart PW, Reihman J, Lonky EI, Darvill TJ, Pagano J (2003): Cognitive development in preschool children prenatally exposed to PCBs and MeHg. Neurotoxicol Teratol 25:11–22. 8. Jacobson JL, Jacobson SW (2003): Prenatal exposure to polychlorinated biphenyls and attention at school age. J Pediatr 143:780 –788. 9. DuPaul GJ, Power TJ, Anastopoulos AD, Reid R (1998): ADHD Rating Scale-IV: Checklists, Norms, and Clinical Interpretation. New York: Guilford Publications. 10. So YK, Noh JS, Kim YS, Ko SG, Koh YJ (2002): The reliability and validity of Korean parent and teacher ADHD rating scale. J Korean Neuropsychiatr Assoc 41:283–289. 11. Greenberg LM, Waldman ID (1993): Developmental normative data on the test of variables of attention (TOVA). J Child Psychol Psychiatry 34: 1019 –1030. 12. Shin MS, Cho S, Chun SY, Hong KE (2000): A study of the development and standardization of ADHD diagnostic system. Korean Journal of Child and Adolescent Psychiatry 11:91–99. 13. Park KS, Yoon JY, Park HJ, Park HJ, Kwon KU (1996): Development of KEDI-WISC, Individual Intelligence Test for Korean Children. Seoul: Korean Educational Development Institute. 14. Kaufman AS (1976): A four test short form of the WISC-R. Comtemporary Educ Psychol 1:180 –196. 15. Ishido M, Masuo Y, Sayato-Suzuki J, Oka S, Niki E, Morita M (2004): Dicyclohexylphthalate causes hyperactivity in the rat concomitantly with impairment of tyrosine hydroxylase immunoreactivity. J Neurochem 91:69 –76. 16. Masuo Y, Ishido M, Morita M, Oka S (2004): Effects of neonatal treatment with 6-hydroxydopamine and endocrine disruptors on motor activity and gene expression in rats. Neural Plast 11:59 –76. 17. Rice D, Barone S Jr (2000): Critical periods of vulnerability for the developing nervous system: Evidence from humans and animal models. Environ Health Perspect 108:511–533. 18. Adams J, Barone S Jr, LaMantia A, Philen R, Rice DC, Spear L, et al. (2000): Workshop to identify critical windows of exposure for children’s health: Neurobehavioral work group summary. Environ Health Perspect 108: 535–544. 19. Vorhees CV (1994): Developmental neurotoxicity induced by therapeutic and illicit drugs. Environ Health Perspect 102:145–153. 20. Rice D, Barone S Jr (2000): Critical periods of vulnerability for the developing nervous system: Evidence from humans and animal models. Environ Health Perspect 108:511–33. 21. Mendola P, Selevan SG, Gutter S, Rice D (2002): Environmental factors associated with a spectrum of neurodevelopmental deficits. Ment Retard Dev Disabil Res Rev 8:188 –197.
BIOL PSYCHIATRY 2009;66:958 –963 963 22. Miller MW (1993): Migration of cortical neurons is altered by gestational exposure to ethanol. Alcohol Clin Exp Res 17:304 –314. 23. Levitt P (1998): Prenatal effects of drugs of abuse on brain development. Drug Alcohol Depend 51:109 –125. 24. Petit TL, Alfano DP, LeBoutillier JC (1983): Early lead exposure and the hippocampus: A review and recent advances. Neurotoxicology 4:79 –94. 25. White LD, Cory-Slechta DA, Gilbert ME, Tiffany-Castiglioni E, Zawia NH, et al. (2007): New and evolving concepts in the neurotoxicology of lead. Toxicol Appl Pharmacol 225:1–27. 26. Lidsky TI, Schneider JS (2003): Lead neurotoxicity in children: Basic mechanisms and clinical correlates. Brain 126:5–19. 27. Shaywitz BA, Yager RD, Klopper JH (1976): Selective brain dopamine depletion in developing rats: An experimental model of minimal brain dysfunction. Science 191:305–308. 28. Seidman LJ, Valera EM, Makris N (2005): Structural brain imaging of attention-deficit/hyperactivity disorder. Biol Psychiatry 57:1263–1272. 29. Adriani W, Boyer F, Gioiosa L, Macrì S, Dreyer JL, Laviola G (2009): Increased impulsive behavior and risk proneness following lentivirusmediated dopamine transporter over-expression in rats’ nucleus accumbens. Neuroscience 159:47–58. 30. Dougherty DD, Bonab AA, Spencer TJ, Rauch SL, Madras BK, Fischman AJ (1999): Dopamine transporter density in patients with attention deficit hyperactivity disorder. Lancet 354:2132–2133. 31. Cheon KA, Ryu YH, Kim YK, Namkoong K, Kim CH, Lee JD (2003): Dopamine transporter density in the basal ganglia assessed with [123I]IPT SPET in children with attention deficit hyperactivity disorder. Eur J Nucl Med Mol Imaging 30:306 –311. 32. Corton JC, Lapinskas PJ (2005): Peroxisome proliferator-activated receptors: Mediators of phthalate ester-induced effects in the male reproductive tract? Toxicol Sci 83:4 –17. 33. Cook EH Jr, Stein MA, Krasowski MD, Cox NJ, Olkon DM, Kieffer JE, et al. (1995): Association of attention-deficit disorder and the dopamine transporter gene. Am J Hum Genet 56:993–998. 34. Curran S, Mill J, Tahir E, Kent L, Richards S, Gould A, et al. (2001): Association study of a dopamine transporter polymorphism and attention deficit hyperactivity disorder in UK and Turkish samples. Mol Psychiatry 6:425– 428. 35. Barr CL, Wigg KG, Bloom S, Schachar R, Tannock R, Roberts W, et al. (2000): Further evidence from haplotype analysis for linkage of the dopamine D4 receptor gene and attention-deficit hyperactivity disorder. Am J Med Genet 96:262–267. 36. Swanson JM, Sunohara GA, Kennedy JL, Regino R, Fineberg E, Wigal T, et al. (1998): Association of the dopamine receptor D4(DRD4) gene with a refined phenotype of attention deficit hyperactivity disorder: A familybased approach. Mol Psychiatry 3:370 –372. 37. Kim JW, Kim BN, Cho SC (2006): The dopamine transporter gene and the impulsivity phenotype in attention deficit hyperactivity disorder: A case-control association study in a Korean sample. J Psychiatr Res 40: 730 –737. 38. Yang JW, Jang WS, Hong SD, Ji YI, Kim DH, Park J, et al. (2008): A case-control association study of the polymorphism at the promoter region of the DRD4 gene in Korean boys with attention deficit-hyperactivity disorder: Evidence of association with the -521 C/T SNP. Prog Neuropsychopharmacol Biol Psychiatry 32:243–248. 39. Cheon KA, Kim BN, Cho SC (2007): Association of 4-repeat allele of the dopamine D4 receptor gene exon III polymorphism and response to methylphenidate treatment in Korean ADHD children. Neuropsychopharmacology 32:1377–1383. 40. Kim YN, Shin MS, Kim JW, Yoo HJ, Cho SC, Kim BN (2009): Neurocognitive effects of switching from methylphenidate-IR to OROS-methylphenidate in children with ADHD. Hum Psychopharmacol Clin Exp 24:95–102. 41. Bellinger DC (2008): Late neurodevelopmental effects of early exposures to chemical contaminants: Reducing uncertainty in epidemiological studies. Basic Clin Pharmacol Toxicol 102:237–244. 42. Yang YH, Kim JW, Kim YN, Cho SC, Kim BN (2008): Screening of attention deficit hyperactivity disorder in Seoul. J Korean Neuropsychatr Assoc 47:292–298. 43. Koch HM, Bolt HM, Angerer J (2004): Di-2-ethylhexyl)phthalate (DEHP) metabolites in human urine and serum after a single oral dose of deuterium-labelled DEHP. Arch Toxicol 78:123–130. 44. Fennell TR, Krol WL, Sumner SC, Snyder RW (2004): Pharmacokinetics of dibutylphthalate in pregnant rats. Toxicol Sci 82:407– 418.
www.sobp.org/journal