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www.nature.com/scientificreports Correction: Author Correction OPEN The Methylation Capacity of Arsenic and Insulin Resistance are Associated with Psychological Received: 23 November 2016 Characteristics in Children and Accepted: 24 April 2017 Published: xx xx xxxx Adolescents 1,2,3 4,5 6 5 5 Ying-Chin Lin , Chien-Tien Su , Horng-Sheng Shiue , Wei-Jen Chen , Yi-Hua Chen , 7,8 5 5 4,9 Cheuk-Sing Choy , Hung-Yi Chiou , Bor-Cheng Han & Yu-Mei Hsueh The goal of the present study was to compare the influence of the methylation capacity of arsenic, as well as insulin resistance on psychological characteristics of school students from elementary and junior high school. 296 elementary and 318 junior high school students participated in health examinations, completed questionnaires and determined their concentrations of urinary arsenic species and psychological characteristics. Insulin resistance was determined by means of the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). We found that HOMA-IR values were significantly related to increased score of the depression and anger after adjusted for age, gender, schools, father’s educational levels, mother’s educational levels, BMI, body fat, and urinary creatinine in all students. Anxiety scores and depression scores of junior high school children were significantly higher compared to elementary school children, but lower in disruptive behavior scores. HOMA-IR levels were significantly inversely related to self-concept scores in junior high school students. A greater urinary inorganic arsenic percentage (iAs%) was marginally significantly related to a higher depression score in junior high school students. This is the first study to show a relationship between HOMA-IR levels or urinary arsenic profiles and psychological distress in school students from elementary and junior high school. Arsenic is a naturally occurring metalloid, and is a known human carcinogen, promoting skin and lung cancer . Epidemiological studies have documented neurotoxic effects in children with long-term arsenic exposure from contaminated milk powder . Over the last decades, there has been an exponential increase in concern about the health risks of exposure to arsenic because of its potential neurotoxic effects . Currently, the most concerning problem from a public health point of view is exposure to low doses of arsenic in children. Recently, low arsenic concentrations have been shown to be associated with an increased susceptibility to cognitive dysfunction . In addition, a systematic review and meta-analysis study reported that arsenic exposure decreased children’s intelli- gence, measured by performing an intelligence quotient test . Another review paper also highlighted that arsenic exposure increased the risk of impaired cognition and enhanced susceptibility for mood disorders in children . Furthermore, another study provided additional evidence to support an association between arsenic exposure and impaired attention/cognitive functions, even at levels considered to be safe . 1 2 Department of Family Medicine, Shung Ho Hospital, Taipei Medical University, Taipei, Taiwan. Department of Health Examination, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan. Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan. Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan. School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan. Department of Chinese Medicine, Chang Gung Memorial Hospital, and Chang Gung University College of Medicine, Taoyuan, Taiwan. Emergency Department, Taipei Hospital, Ministry of Health and Welfare, New Taipei City, Taiwan. Department of Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan. Department of Public Health, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan. Correspondence and requests for materials should be addressed to Y.-M.H. (email: ymhsueh@tmu.edu.tw) and B.-C.H. (email: bchan@tmu.edu.tw) SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 1 www.nature.com/scientificreports/ Variables Elementary school students (N = 296) Junior high school students (N = 318) p value Age (Mean ± SE) 8.84 ± 0.09 12.69 ± 0.03 <0.01 Gender Male 155 (52.36) 174 (54.72) 0.56 Female 141 (47.64) 144 (45.28) City areas Taipei City 117 (39.53) 318 (100) New Taipei City 179 (60.47) — Schools San Xing Elementary School 41 (13.99) — Wu Xing Elementary School 50 (17.06) — Xin Yi Elementary School 23 (7.85) — Ding Xi Elementary School 40 (13.65) — Xin He Elementary School 5 (1.71) — Shuang Cheng Elementary School 24 (8.19) — Yong He Elementary School 38 (12.97) — An Keng Elementary School 72 (24.57) — Cheng De Junior High School — 63 (19.81) Yon Ji Junior High School — 255 (80.19) Father’s educational levels Illiterate 2 (0.71) 9 (3.00) <0.01 Elementary School 20 (7.07) 36 (12.00) Junior high school 101 (35.69) 131 (43.67) Senior high school 133 (47.00) 109 (36.33) College and above 27 (9.54) 15 (5.00) Mother’s educational levels Illiterate 2 (0.70) 7 (2.25) <0.01 Elementary School 13 (4.56) 39 (12.54) Junior high school 135 (47.37) 152 (48.87) Senior high school 123 (43.16) 105 (33.76) College and above 12 (4.21) 8 (2.57) Physiological characteristics BMI (kg/m ) 19.99 ± 0.26 20.56 ± 0.24 0.10 BMI group Lower than normal weight 36 (12.16) 52 (16.35) <0.01 Normal Weight 108 (36.49) 168 (52.83) Overweight/obese 152 (51.35) 98 (30.82) Body fat (%) 26.18 ± 0.56 21.87 ± 0.45 <0.01 Cholesterol (mg/dL) 173.9 ± 1.72 160.1 ± 1.54 <0.01 Triglyceride (mg/dL) 71.65 ± 2.19 75.53 ± 2.22 0.21 HDL (mg/dL) 59.31 ± 0.71 55.82 ± 0.71 <0.01 LDL (mg/dL) 100.3 ± 1.46 90.03 ± 1.30 <0.01 GOT (IU/L) 25.51 ± 0.53 21.07 ± 0.45 <0.01 GPT (IU/L) 18.82 ± 1.15 16.20 ± 0.98 0.08 Blood glucose 88.92 ± 1.11 91.76 ± 0.41 0.02 Insulin (μIU/mL) 11.91 ± 1.07 16.81 ± 0.76 <0.01 HOMA-IR value 2.80 ± 0.32 3.92 ± 0.21 <0.01 Urea 12.17 ± 0.16 11.55 ± 0.15 <0.01 Urine creatinine (mg/L) 93.10 ± 2.71 128.7 ± 3.60 <0.01 Urinary arsenic indices Urinary total arsenic (μg/L) 24.60 ± 1.24 25.96 ± 1.24 0.44 Urinary total arsenic (μg/g creatinine) 29.94 ± 1.76 23.60 ± 1.35 <0.01 iAs% 4.78 ± 0.32 7.52 ± 0.31 <0.01 MMA% 5.01 ± 0.32 5.29 ± 0.28 0.51 DMA% 90.22 ± 0.52 87.20 ± 0.44 <0.01 Table 1. Physiological characteristics and urinary arsenic proles s fi tratified by educational levels. Categorical and continuous variables are expressed as numbers (percentage) and mean ± Standard error, respectively. HDL, high-density lipoprotein; LDL, low-density lipoprotein; GOT, glutamic oxaloacetic transaminase; GPT, glutamic pyruvic transaminase. HOMA-IR, Homeostasis model assessment of insulin resistance; HOMA-IR = Fasting III V insulin (μU/mL) × Fasting glucose (mg/dL)/405; iAs%: inorganic arsenic (iAs + iAs )/total arsenic × 100; MMA%: MMA/total arsenic × 100; DMA%: DMA/total arsenic × 100. The data regarding schooling was unavailable for three children; educational levels were unavailable for 31 children’ fathers and 18 children’ mothers. SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 2 www.nature.com/scientificreports/ Variables Elementary school students (N = 296) Junior high school students (N = 318) p value Self-concept 50.58 ± 0.44 50.50 ± 0.46 0.91 Higher than normal 75 (25.34) 82 (25.79) 0.14 Normal 169 (57.09) 161 (50.63) Lower than normal 52 (17.57) 75 (23.58) Anxiety 46.96 ± 0.48 49.95 ± 0.58 <0.01 Normal 255 (86.15) 220 (69.18) <0.01 Mild 20 (6.76) 43 (13.52) Moderate/Severe 21 (7.09) 55 (17.30) Depression 45.42 ± 0.52 47.70 ± 0.57 <0.01 Normal 257 (86.82) 243 (76.42) <0.01 Mild 18 (6.08) 36 (11.32) Moderate/Severe 21 (7.09) 39 (12.26) Anger 46.94 ± 0.51 46.80 ± 0.57 0.86 Normal 249 (84.12) 258 (81.13) 0.57 Mild 24 (8.11) 33 (10.38) Moderate/Severe 23 (7.77) 27 (8.49) Disruptive behavior 46.82 ± 0.49 44.54 ± 0.54 <0.01 Normal 249 (84.12) 264 (83.02) 0.69 Mild 28 (9.46) 28 (8.81) Moderate/Severe 19 (6.42) 26 (8.18) Table 2. Psychological characteristics stratified by educational levels. e va Th riability of arsenic methylation in the body may differentiate between the susceptibility to arsenic toxicity. Absorbed arsenate is reduced to arsenite and undergoes methylation to form monomethylarsonic acid (MMA ) and V 8 9 dimethylarsinic acid (DMA ), which have low toxicity and are excreted by the kidneys . However, in vitro studies III have suggested that intermediate metabolites of inorganic arsenic such as monomethylarsonous acid (MMA ) and III 10,11 dimethylarsenious acid (DMA ) are more toxic than inorganic arsenic , although epidemiologic data are not V V available. Our previous prospective study found that, with age, the percentage of MMA (MMA %) increased and V V 12 the percentage of DMA (DMA %) decreased significantly , suggesting that a decrease in the methylation capacity of arsenic is associated with aging. Our recent study demonstrated that total urinary arsenic (sum of the inorganic and methylated arsenic species) is negatively associated with BMI in adolescents in Taiwan, and obese adolescents with high insulin levels had significantly higher MMA% and significantly lower DMA% compared to obese adoles- cents with low insulin . This implies that obesity and high insulin levels were associated with a reduced methylation capacity of arsenic in adolescents. In addition, we also found the homeostasis model assessment of insulin resistance (HOMA-IR) value was significantly and positively related to total urinary arsenic concentrations and the body mass index (BMI) Z score. Higher BMI values and higher total urinary arsenic concentrations were associated with higher HOMA-IR values in children and adolescents in Taiwan . Overweight and obese children have been shown to have a high risk of developing physiological abnormali- 15,16 17,18 ties , as well as being prone to psychosocial distress including depression, anxiety and social withdrawal , 19 20,21 leading to a poor quality of life , and behavioral problems . A recent study reported that children who were overweight/obese had significantly lower self-concept and less disruptive behavior . In addition, a recent study reported that a low mood/depression in healthy children was associated with high HOMA-IR levels . It remains to be determined whether urinary arsenic profiles and insulin resistance can influence psychosocial distress (depression, anger, self-concept, anxiety, and disruptive behavior) in adolescents, even with low arsenic exposure. Therefore, the goal of the present study was to explore the effect of arsenic exposure, and insulin resist- ance using the HOMA-IR index on psychosocial distress in elementary school and junior high school students in an area of Taiwan with low arsenic exposure. Results Table 1 shows the city areas and schools in which children were living and studying. Fathers and mothers of elementary school students had higher educational levels than those of junior high school students. Among ele- mentary school students, body fat percent, cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), glutamate oxaloacetate transaminase (GOT), and urea levels were significantly higher compared to junior high school students, and blood sugar, serum insulin, HOMA-IR values, and urine creatinine were significantly lower (Table 1). The total urinary arsenic concentrations (μ g/g creatinine) and DMA% were significantly higher in elementary school students compared to junior high school students, and iAs% was significantly lower. It seems that the methylation capability of arsenic in elementary school students was more efficient than that of junior school students (Table 1). Table 2 shows that anxiety scores and depression scores of junior high school children were significantly higher than those of elementary school children. In contrast, disruptive behavior scores of junior high school children were significantly lower than those of elementary school children. e Th distribution of categorized strata of anxiety scores and depression scores in junior high school was significantly different from those in elementary school children (Table 2). SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 3 www.nature.com/scientificreports/ Urinary total Urinary total arsenic HOMA-IR Variables N arsenic (μg/L) (μg/g creatinine) iAs% MMA% DMA% value Self-concept Higher than normal 75 25.87 ± 2.78 34.57 ± 4.71 5.61 ± 0.92 5.79 ± 0.83 88.60 ± 1.56 3.03 ± 0.79 Normal 169 24.30 ± 1.62 27.28 ± 1.86 4.68 ± 0.35 4.42 ± 0.35 90.80 ± 0.52 2.48 ± 0.26 Lower than normal 52 23.77 ± 2.44 31.90 ± 4.13 3.90 ± 0.38 5.45 ± 0.81 90.65 ± 0.98 3.53 ± 1.12 p value 0.83 0.19 0.20 0.21 0.20 0.44 Normal 169 24.30 ± 1.62 27.28 ± 1.86 4.68 ± 0.35 4.52 ± 0.35 90.80 ± 0.52 2.48 ± 0.26 Abnormal 127 25.01 ± 1.92 33.48 ± 3.24 4.91 ± 0.57 5.65 ± 0.59 89.44 ± 1.00 3.23 ± 0.66 p value 0.78 0.10 0.73 0.10 0.23 0.28 Anxiety Normal 255 23.82 ± 1.24 29.07 ± 1.83 5.03 ± 0.35 5.20 ± 0.36 89.77 ± 0.58 2.59 ± 0.33 Mild 20 28.20 ± 8.24 32.33 ± 9.66 2.42 ± 0.43 3.91 ± 1.40 93.67 ± 1.42 4.89 ± 1.05 Moderate/Severe 21 30.71 ± 3.94 38.25 ± 6.23 3.96 ± 0.93 3.67 ± 0.62 92.38 ± 1.24 3.31 ± 1.62 p value 0.27 0.38 0.09 0.32 0.09 0.17 Normal 255 23.82 ± 1.24 29.07 ± 1.83 5.03 ± 0.35 5.20 ± 0.36 89.77 ± 0.58 2.59 ± 0.33 Abnormal 41 29.49 ± 4.44 35.36 ± 5.64 3.21 ± 0.53 3.79 ± 0.74 93.01 ± 0.93 4.08 ± 0.97 p value 0.23 0.22 <0.01 0.13 <0.01 0.10 Depression Normal 257 23.59 ± 1.16 29.25 ± 1.72 4.95 ± 0.36 5.22 ± 0.36 89.83 ± 0.58 2.80 ± 0.36 c,d Mild 18 39.86 ± 10.54 44.01 ± 13.72 3.42 ± 0.55 4.56 ± 1.42 92.02 ± 1.49 2.96 ± 0.79 Moderate/Severe 21 23.96 ± 4.15 26.36 ± 5.50 3.84 ± 0.79 2.77 ± 0.58 93.39 ± 0.94 2.65 ± 0.65 p value <0.01 0.11 0.37 0.15 0.15 0.98 Normal 257 23.59 ± 1.16 29.25 ± 1.72 4.95 ± 0.36 5.22 ± 0.36 89.83 ± 0.58 2.80 ± 0.36 Abnormal 39 31.29 ± 5.43 34.50 ± 7.04 3.65 ± 0.49 3.60 ± 0.73 92.76 ± 0.85 2.79 ± 0.50 p value 0.04 0.47 0.03 0.09 <0.01 0.99 Anger Normal 249 23.80 ± 1.31 29.74 ± 1.86 4.83 ± 0.36 4.99 ± 0.35 90.18 ± 0.59 2.73 ± 0.30 Mild 24 26.27 ± 4.08 28.32 ± 5.10 4.81 ± 1.03 5.14 ± 1.12 90.05 ± 1.51 3.64 ± 2.41 Moderate/Severe 23 31.52 ± 5.79 33.78 ± 8.97 4.23 ± 0.65 5.03 ± 1.36 90.74 ± 1.45 2.64 ± 0.56 p value 0.23 0.80 0.88 0.99 0.96 0.73 Normal 249 23.80 ± 1.31 29.74 ± 1.86 4.83 ± 0.36 4.99 ± 0.35 90.18 ± 0.59 2.73 ± 0.30 Abnormal 47 28.83 ± 3.50 30.99 ± 5.06 4.52 ± 0.61 5.09 ± 0.87 90.39 ± 1.04 3.15 ± 1.25 p value 0.14 0.80 0.67 0.92 0.86 0.75 Disruptive behavior Normal 249 24.35 ± 1.33 29.71 ± 1.87 4.67 ± 0.36 5.10 ± 0.37 90.23 ± 0.60 2.62 ± 0.29 Mild 28 25.37 ± 5.14 33.12 ± 7.86 5.15 ± 0.83 3.51 ± 0.58 91.34 ± 1.20 2.90 ± 0.67 Moderate/Severe 19 26.77 ± 3.74 28.29 ± 4.53 5.60 ± 0.77 5.98 ± 1.05 88.43 ± 1.27 5.04 ± 3.04 p value 0.88 0.83 0.72 0.27 0.55 0.17 Normal 249 24.35 ± 1.33 29.71 ± 1.87 4.67 ± 0.36 5.10 ± 0.37 90.23 ± 0.60 2.62 ± 0.29 Abnormal 47 25.94 ± 3.38 31.17 ± 5.00 5.33 ± 0.58 4.51 ± 0.57 90.16 ± 0.90 3.77 ± 1.28 p value 0.64 0.76 0.34 0.39 0.96 0.39 Table 3. Distribution of urinary total arsenic and HOMA-IR values according to psychological characteristics c d in elementary school students. Normal depression vs. Mild depression, p < 0.05; Mild depression vs. Moderate or Severe depression, p < 0.05. The comparison of total urinary arsenic concentrations, arsenic methylation indices and HOMA-IR values between different psychological characteristics groups in elementary school students is presented in Table 3. Total urinary arsenic concentration in students with a mild depression score was significantly higher than students with a normal and moderate/severe depression score in elementary school students. In addition, Total urinary arsenic concentration in students with a mild depression score and moderate/severe depression score was significantly higher than students with a normal depression score. Regarding arsenic methylation indices, we found that iAs% was significantly lower, and DMA% was significantly higher in students with abnormal depression score and anxiety score than in students with a normal depression score and anxiety score. e H Th OMA-IR value in students had a normal score or higher than normal score for self-concept were sig- nificantly lower than students with a lower than normal self-concept score among junior high school students. In addition, the HOMA-IR value in students with a mild depression score was significantly higher than students with a normal or moderate/severe depression score in junior high school students. On the other hand, iAs% in students with an abnormal depression score or abnormal disruptive behavior score was significantly higher than students with a normal depression score or normal disruptive behavior score in junior high school students (Table 4). SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 4 www.nature.com/scientificreports/ We explored the association between parents’ smoking status and the urinary total arsenic and arsenic meth- ylation capacity indices of children (Supplementary Table S1); we found that the fathers’ smoking status only ae ff cted the MMA% of children in elementary school. However, MMA% was not related to psychological char - acteristics in elementary school students or junior high school students in this study; therefore, family smoking status would not act as a confounding factor for analyzing the relationship between urinary total arsenic, iAs%, DMA% and psychological characteristics in elementary school students or junior high school students. In addi- tion, we compared the different status of body fat, vegetables and fruit intake, along with family history, on the HOMA-IR values in children (Supplementary Table S2). We found that body fat ae ff cted HOMA-IR values in both elementary and junior high students, and that the diabetes history of the mother only ae ff cted HOMA-IR values in junior high students. A multiple linear regression analysis between urinary arsenic profile, HOMA-IR values and psychological characteristics is shown in Table 5. The HOMA-IR values were significantly positively related to the depression and anger score adjusted for age, gender, schools, father’s educational levels, mother’s educational levels, BMI, body fat, and urinary creatinine in all students. In junior high school students, the HOMA-IR values were sig- nificantly negatively related to the self-concept score, and positively correlated with the depression and anger score. In addition, urinary total arsenic concentration was significantly positively related to the self-concept score. Moreover, a greater iAs% was associated with a higher depression score, to a marginal degree. Conversely, iAs% values were significantly positively related to the self-concept score in elementary school students. In addition, DMA% values, and HOMA-IR values were positively related to the anxiety score in elementary school students. HOMA-IR value and iAs% were correlated with psychological characteristics respectively, therefore we ana- lyzed the combined effects of HOMA-IR value and iAs% on psychological characteristics. We did not find any relationship between the combined effects of HOMA-IR values and iAs% and psychological characteristics in all students. Therefore, we found a sequential decrease in the OR of anxiety, depression and anger among those with no risk factor, one risk factor, and two risk factors (iAs% and HOMA-IR value) in a dose-dependent manner in elementary school students; inversely a sequential increase in the OR of depression among those with no risk factor, one risk factor, and two risk factors (iAs% and HOMA-IR value) in a dose-dependent manner in junior high school students (Table 6). Discussion To the best of our knowledge, this is the first study to show an association between multiple psychological char - acteristics including self-concept, anxiety, depression, anger, and disruptive behavior and HOMA-IR values and urinary arsenic profiles in children and adolescents in Taiwan. In this study, we have shown that elementary school students had a more efficient arsenic methylation capacity (higher DMA% and lower iAs%) than jun- 13,14 ior high school students; these results were similar to our previous study . One interesting finding was that high HOMA-IR values were significantly associated with an increased depression and anger score in junior high school students and all students. A high HOMA-IR value was significantly associated with a lower self-concept score in junior high school students; in contrast, total urinary arsenic concentration was significantly related to the self-concept score in junior high school students. In addition, a higher iAs% was associated with a higher self-concept score in elementary school students and with a higher depression score in junior high school stu- dents aer co ft variate adjustment. The educational system in Taiwan is quite different from that in Western society; ninth grade (age 14–15) students have to face academic tracking in early adolescence . A study reported that students taking the senior high school joint entrance examination slept less hours at night and were less alert during the daytime compared to those who were not taking the examination , suggesting that the academic pressures that adolescents faced could influence their behavior. Therefore, the anxiety and depression scores were significantly higher in senior high school students than in the elementary school students of this study. By contrast, disruptive behavior scores of senior high school students were lower than those of elementary school students. A further study should be performed to verify this inconsistency. Our previous study found that HOMA-IR values were significantly increased in relation to the total urinary arsenic (μg/L) . This finding indicates that arsenic exposure may be related to β-cell dysfunction, increasing the risk of diabetes in Korean adults . A longitudinal study found that healthy children with low moods had higher HOMA-IR values than those without . This implies that neuropsychiatric syndromes alter metabolic networks such as insulin-glucose homeostasis, immuno-inflammatory processes and adipokine synthesis, and secretion is a defining pathophysiological component . Understanding how depressive symptoms are linked to metabolism during childhood and adolescence may be important for identifying risk factors for diabetes. However, in our study, children with high HOMA-IR values were associated with high anger scores and depression scores. Taken together, high total urinary arsenic may induce an increase in HOMA-IR values, and result in impaired glucose homeostasis, which could be related to depression and anger in children and adolescents in Taiwan; however, this hypothesis needs further studies to confirm the underlying mechanisms of the reported association. Insulin resistance has been shown to be negatively related to cognitive performance in adult humans , and insulin resistance at the level of the brain may be associated with the effects on glucose uptake, and could influ- ence mediators of brain function in adults . However, one study reported that HOMA-IR was significantly and negatively correlated with self-perceived scholastic competence in girls . We also found that HOMA-IR was sig- nificantly negatively associated with the self-concept score in junior high school students; the underlying reason why this relationship was age specific was beyond the scope of this study, but could be the subject of further inves- tigation. By contrast, total urinary arsenic was significantly related to the self-concept score, which is opposite to what we originally hypothesized. This cannot be explained by the present study and needs further investigation. On the other hand, urinary arsenic concentrations greater than 50 μg/L were associated with poor scores on tests SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 5 www.nature.com/scientificreports/ Urinary total Urinary total arsenic HOMA-IR Variables N arsenic (μg/L) (μg/g creatinine) iAs% MMA% DMA% value Self-concept Higher than normal 82 26.81 ± 2.23 23.66 ± 1.90 6.87 ± 0.51 5.55 ± 0.49 87.57 ± 0.82 3.54 ± 0.19 Normal 161 26.84 ± 1.99 24.41 ± 2.24 7.99 ± 0.45 5.48 ± 0.44 86.53 ± 0.63 3.67 ± 0.21 a,b Lower than normal 75 23.13 ± 1.82 21.80 ± 2.27 7.21 ± 0.67 4.58 ± 0.46 88.21 ± 0.89 4.88 ± 0.71 p value 0.45 0.74 0.27 0.37 0.27 0.03 Normal 161 26.84 ± 1.99 24.41 ± 2.24 7.99 ± 0.45 5.48 ± 0.44 86.53 ± 0.63 3.67 ± 0.21 Abnormal 157 25.05 ± 1.46 22.77 ± 1.47 7.03 ± 0.41 5.09 ± 0.34 87.88 ± 0.690 4.18 ± 0.36 p value 0.47 0.54 0.12 0.48 0.12 0.22 Anxiety Normal 220 25.25 ± 1.37 22.13 ± 1.54 7.24 ± 0.33 5.33 ± 0.33 87.43 ± 0.51 3.98 ± 0.26 Mild 43 31.29 ± 4.07 28.02 ± 4.33 8.66 ± 1.15 5.97 ± 0.80 85.37 ± 1.41 3.98 ± 0.58 Moderate/Severe 55 24.62 ± 3.28 26.03 ± 3.33 7.72 ± 0.76 4.58 ± 0.70 87.70 ± 1.01 3.64 ± 0.34 p value 0.23 0.24 0.28 0.38 0.25 0.82 Normal 220 25.25 ± 1.37 22.13 ± 1.54 7.24 ± 0.33 5.33 ± 0.33 87.43 ± 0.51 3.98 ± 0.26 Abnormal 98 27.54 ± 2.57 26.90 ± 2.65 8.13 ± 0.66 5.19 ± 0.53 86.68 ± 0.84 3.79 ± 0.32 p value 0.43 0.10 0.23 0.82 0.43 0.63 Depression c c Normal 243 25.43 ± 1.31 23.38 ± 1.53 7.04 ± 0.31 5.29 ± 0.31 87.67 ± 0.47 3.77 ± 0.21 c c,d Mild 36 33.04 ± 5.71 27.51 ± 5.08 9.44 ± 1.47 5.73 ± 1.06 84.83 ± 1.75 5.81 ± 1.06 Moderate/Severe 39 22.67 ± 2.66 21.40 ± 2.81 8.75 ± 0.67 4.84 ± 0.69 86.42 ± 1.13 3.13 ± 0.34 p value 0.09 0.52 0.01 0.74 0.10 <0.01 Normal 243 25.43 ± 1.31 23.38 ± 1.53 7.04 ± 0.31 5.29 ± 0.31 87.67 ± 0.47 3.77 ± 0.21 Abnormal 75 27.65 ± 3.11 24.34 ± 2.84 9.08 ± 0.78 5.26 ± 0.62 85.66 ± 1.02 4.42 ± 0.56 p value 0.51 0.76 0.02 0.97 0.08 0.28 Anger Normal 258 25.87 ± 1.28 23.45 ± 1.49 7.45 ± 0.35 5.47 ± 0.32 87.08 ± 0.50 3.75 ± 0.18 Mild 33 32.44 ± 5.75 29.15 ± 5.09 6.99 ± 0.62 4.57 ± 0.64 88.44 ± 1.05 5.29 ± 1.32 Moderate/Severe 27 18.82 ± 3.35 18.31 ± 3.12 8.80 ± 0.98 4.43 ± 0.89 86.77 ± 1.59 3.86 ± 0.60 p value 0.06 0.21 0.40 0.40 0.62 0.08 Normal 258 25.87 ± 1.28 23.45 ± 1.49 7.45 ± 0.35 5.47 ± 0.32 87.08 ± 0.50 3.75 ± 0.18 Abnormal 60 26.31 ± 3.59 24.27 ± 3.19 7.81 ± 0.57 4.51 ± 0.53 87.69 ± 0.92 4.65 ± 0.77 p value 0.91 0.81 0.60 0.12 0.59 0.26 Disruptive behavior Normal 264 26.35 ± 1.35 23.86 ± 1.52 7.18 ± 0.33 5.41 ± 0.32 87.41 ± 0.48 3.94 ± 0.22 Mild 28 22.34 ± 2.16 22.24 ± 3.24 9.73 ± 1.22 4.65 ± 0.70 85.63 ± 1.53 4.63 ± 0.97 Moderate/Severe 26 25.83 ± 6.03 22.45 ± 4.72 8.53 ± 0.95 4.71 ± 0.80 86.75 ± 1.49 3.02 ± 0.30 p value 0.66 0.91 0.04 0.62 0.50 0.27 Normal 264 26.35 ± 1.35 23.86 ± 1.52 7.18 ± 0.33 5.41 ± 0.32 87.41 ± 0.48 3.94 ± 0.22 Abnormal 54 24.02 ± 3.09 22.34 ± 2.80 9.15 ± 0.78 4.68 ± 0.53 86.17 ± 1.06 3.85 ± 0.53 p value 0.48 0.67 0.02 0.24 0.29 0.88 Table 4. Distribution of urinary total arsenic and HOMA-IR values according to psychological characteristics in junior high school students. aSelf-concept higher than normal vs. Self-concept lower than normal, p < 0.05; b c Normal self-concept vs. Self-concept lower than normal, p < 0.05; Normal depression vs. Mild depression, p < 0.05; Mild depression vs. Moderate or Severe depression, p < 0.05. measuring visual-spatial reasoning, language and vocabulary, memory, intelligence, and math skills , as well as a modest association with hyperactive behavior in 6–8 year-old children in Mexico. However, total urinary arsenic concentration was significantly related with the self-concept score in this study, which requires further investigation. However, an interesting result showed that iAs% was significantly related to increasing depression score in this study. This may suggest that arsenic depletes s-adenosylmethione (SAM)-methyl levels in the arsenic methylation pathway, leading to alterations in DNA methylation , and this epigenetic modification to the DNA, which may result in aberrant gene expression, even in the brain , increases the risk of impaired cognition and enhanced susceptibility for mood disorders. However, whether other arsenic methylation capacity indices can also influence psychological distress or the link between a particular gene of DNA methylation and cognition deficits has yet to be elucidated. Overall, arsenic methylation capacity leads to insulin resistance , and may then disrupt the clearance of β-amyloid protein ; it may also increase tau dephosphorylation and microtubule bind- ing of tau by weakening the activity of phosphoinositide 3-kinase/protein kinase B and adenosine monophos- phate, resulting in neuronal degeneration related to cognitive dysfunction. Insulin resistance may be related to SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 6 www.nature.com/scientificreports/ Self-concept Anxiety Depression Anger Disruptive behavior a b a b a b a b a b Variables Model 1 β (SE) Model 2 β (SE) Model 1 β (SE) Model 2 β (SE) Model 1 β (SE) Model 2 β (SE) Model 1 β (SE) Model 2 β (SE) Model 1 β (SE) Model 2 β (SE) Overall Urinary total 0.025 (0.016) 0.024 (0.016) 0.014 (0.019) 0.015 (0.019) −0.007 (0.019) −0.003 (0.019) −0.014 (0.019) −0.011 (0.019) 0.003 (0.018) 0.005 (0.018) arsenic (μg/L) iAs% 0.029 (0.060) −0.007 (0.072) 0.075 (0.073) 0.058 (0.072) 0.062 (0.069) DMA% −0.052 (0.039) 0.057 (0.047) 0.216 (0.109) 0.031 (0.047) −0.0004 (0.046) HOMA-IR * * * + −0.108 (0.089) −0.105 (0.089) 0.170 (0.107) 0.166 (0.107) 0.219 (0.109) 0.216 (0.109) 0.211 (0.107) 0.207 (0.107) 0.076 (0.103) 0.074 (0.103) value Elementary school students Urinary total 0.006 (0.022) 0.009 (0.022) −0.009 (0.025) −0.012 (0.025) −0.007 (0.027) −0.009 (0.027) −0.011 (0.26) −0.012 (0.026) −0.004 (0.093) −0.005 (0.026) arsenic (μg/L) iAs% 0.184 (0.079) −0.134 (0.090) −0.067 (0.098) −0.009 (0.095) −0.049 (0.093) + * DMA% −0.092 (0.049) 0.127 (0.055) 0.088 (0.060) 0.054 (0.058) 0.050 (0.057) HOMA−IR * * 0.087 (0.106) 0.091 (0.106) 0.247 (0.120) 0.245 (0.120) 0.196 (0.131) 0.196 (0.131) 0.104 (0.127) 0.106 (0.126) 0.097 (0.124) 0.096 (0.124) value Junior high school students Urinary total 0.046 (0.023) 0.039 (0.022) 0.019 (0.029) 0.022 (0.029) −0.021 (0.028) −0.015 (0.028) −0.022 (0.029) −0.014 (0.028) 0.006 (0.027) 0.011 (0.027) arsenic (μg/L) iAs% −0.138 (0.088) 0.060 (0.115) 0.196 (0.111) 0.100 (0.112) 0.136 (0.104) DMA% 0.004 (0.063) 0.002 (0.081) −0.073 (0.079) 0.027 (0.079) −0.029 (0.074) HOMA-IR * * * + * * −0.373 (0.148) −0.358 (0.149) 0.091 (0.193) 0.084 (0.193) 0.368 (0.187) 0.356 (0.187) 0.459 (0.188) 0.444 (0.188) 0.128 (0.175) 0.117 (0.176) value Table 5. Multiple linear regression analyses of urinary arsenic profiles, HOMA-IR values and psychological characteristics. β, regression coefficient; SE, Standard error. Multivariable linear regression analyses were adjusted for covariates, indicated age, gender, schools, father’s educational levels, mother’s educational levels. BMI, body fat, and urinary creatinine. Model 1: Psychological scores = β + β ·(Urinary total 0 1 arsenic) + β ·(iAs%) + β ·(HOMA-IR value) + β ·(covariates). Model 2: Psychological scores = β + β ·(Urinary 2 3 i 0 1 + * total arsenic) + β ·(DMA%) + β ·(HOMA-IR value) + β ·(covariates). 0.05 ≤ p < 0.1. p < 0.05. 2 3 i hypothalamic-pituitary adrenal axis dysfunction resulting in depressive symptoms . Hippocampal neurogenesis reduction and increased advanced glycation end products were associated with depression . This study had several limitations that need to be taken into consideration when interpreting these results. Firstly, a single-spot measurement of urinary arsenic species and blood biochemical indices may not provide enough information. In addition, the methylation of arsenic and HOMA-IR values may be influenced by nutri- ents, for which information was unavailable in this study. However, the values could be reliable if all participants had no change to their lifestyle and maintained their homeostatic metabolism. Secondly, as this study had a cross-sectional design, it could not determine the causality of the observed associations. We cannot exclude the possibility that the association between high total urinary arsenic concentrations or high HOMA-IR values and psychological indices could be the result rather than the cause of a change in psychological index values. Thirdly, the measurement of psychological characteristics was self-reported using a rating scale, and may be incomplete or subject to socially desirable effects, interpretation of results should be treated with caution. Fourthly, we did not collect any information of potential factors, such as emission of exhaust gases, waste water or home decoration, which would probably ae ff ct arsenic methylation capacity. In addition, data concerning exercise was unavailable, and eating habits and family history include missing data; these variables may be related to insulin resistance in this study. The parents’ level of income, which may influence children’s psychological characteristics, was also unavailable. The fact that they cannot be adjusted is another limitation of this study. In addition, all students were sampled in Taipei city and New Taipei City (urban areas) and, therefore, our sample is a limited representation of the entire population of Taiwan. In spite of these limitations, this study represents the first attempt to address the effect of change in urinary arsenic profiles or HOMA-IR values on psychological characteristics aer ad ft justments for BMI, educational levels and anthropometric measurements. Conclusion This is the first study to show a relationship between HOMA-IR values or urinary arsenic profiles and psycholog- ical distress in children and adolescents with low arsenic exposure in Taiwan. Methods Study participants. Two cross-sectional studies were conducted. Eight elementary schools, including San Xing, Wu Xing, Xin Yi, Ding Xi, Xin He, Shuang Cheng, Yong He, and An Keng Elementary Schools in Taipei City or New Taipei City recruited 3,500 students in the first study, from September 2007 to September 2009. Ten percent of all elementary school students were randomly invited to attend Taipei Medical University Hospital for a detailed health examination. A total of 296 (84.57%) elementary school students volunteered to receive detailed health examinations, which were conducted at Taipei Medical University Hospital from September 2009 to December 2009 . Junior high school students from Cheng De and Yon Ji Junior High Schools in Taipei City SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 7 www.nature.com/scientificreports/ Self-concept Anxiety Depression Anger Disruptive behavior Normal/ Multivariate Normal/ Multivariate Normal/ Multivariate Normal/ Multivariate Normal/ Multivariate Variables Abnormal ORs (95% CI) Abnormal ORs (95% CI) Abnormal ORs (95% CI) Abnormal ORs (95% CI) Abnormal ORs (95% CI) Overall iAs% HOMA-IR value ≤5.18 ≤2.42 92/78 1.00 141/29 1.00 146/24 1.00 139/31 1.00 142/28 1.00 ≤5.18 >2.42 71/66 0.99 (0.58–1.69) 98/39 1.42 (0.75–2.71) 117/20 1.17 (0.56–2.46) 120/17 0.52 (024–1.11) 122/15 0.58 (0.26–1.28) >5.18 ≤2.42 78/59 0.81 (0.50–1.31) 107/30 0.91 (0.49–1.69) 111/26 1.25 (0.65–2.42) 110/27 0.93 (0.50–1.74) 114/23 0.92 (0.48–1.78) >5.18 >2.42 89/81 0.99 (0.58–1.69) 129/41 0.76 (0.40–1.47) 126/44 1.58 (0.79–3.17) 138/32 0.68 (0.34–1.37) 135/35 1.09 (0.54–2.21) Elementary school students iAs% HOMA-IR value § § § ≤3.72 ≤1.74 41/33 1.00 62/12 1.00 63/11 1.00 59/15 1.00 64/10 1.00 ≤3.72 >1.74 41/33 0.89 (0.41–1.90) 57/17 1.23 (0.46–3.31) 61/13 1.06 (0.36–3.11) 63/11 0.75 (0.26–2.18) 68/6 0.53 (0.16–1.77) >3.72 ≤1.74 47/27 0.70 (0.35–1.39) 65/9 0.49 (0.18–1.38) 64/10 0.70 (0.26–1.92) 60/14 0.78 (0.32–1.91) 58/16 1.69 (0.67–4.28) * + * >3.72 >1.74 40/34 1.00 (0.47–2.14) 71/3 0.16 (0.04–0.65) 69/5 0.28 (0.08–1.02) 67/7 0.21 (0.06–0.78) 59/15 1.23 (0.43–3.51) Junior high school students iAs% HOMA-IR value ≤6.49 ≤3.02 39/39 1.00 56/22 1.00 67/11 1.00 67/11 1.00 68/10 1.00 ≤6.49 >3.02 37/44 1.43 (0.71–2.88) 51/30 1.67 (0.79-3.55) 65/16 1.89 (0.77–4.65) 68/13 1.20 (0.46–3.11) 72/9 0.87 (0.30–2.49) >6.49 ≤3.02 47/34 0.67 (0.34–1.30) 54/27 1.14 (0.55–2.34) 56/25 2.42 (1.06–5.52) 61/20 1.87 (0.80–4.37) 61/20 2.03 (0.85–4.85) >6.49 >3.02 38/40 1.41 (0.70–2.85) 59/19 0.81 (0.37–1.78) 55/23 2.29 (0.96–5.45) 62/16 1.43 (0.57–3.59) 63/15 1.41 (0.54–3.70) Table 6. e in Th teraction of iAs% and HOMA-IR value on psychological characteristics. ORs, odds ratios; CI, 95% confidence intervals. Multivariable logistic regression analyses were adjusted for covariates, indicated age, gender, schools, father’s educational levels, mother’s educational levels, BMI, body fat, and urinary creatinine. + * § 0.05 ≤ p < 0.1. p < 0.05. p < 0.05 for trend test. took part in a second study, from October 2010 to November 2011, and recruited 318 students. The Research Ethics Committee of the Taipei Medical University, Taipei, Taiwan, approved the study, which was conducted in agreement with standards specified in the World Medical Association Declaration of Helsinki. All participants came from Taipei City or New Taipei City. All study participants provided either their parents’ or their own written informed consent form before participating in questionnaire interviews, or providing biological speci- mens. Two research assistants who had received 6 hours of specialized training performed the anthropometric measurements of weight and height for all elementary school students and junior high school students according to standard guidelines. Participants removed their shoes, and wore light clothing for measurements of standing height and weight in a rigid vertical position, using a standard medical balance scale. Height was measured to the nearest 0.5 cm, and weight was measured to the nearest 100 g. Body mass index (BMI) was calculated as weight (kg)/height (m ). Categories were divided into overweight, obese, and lower than normal weight, defined according to guidelines developed by the Ministry of Health and Welfare, Executive Yuan, Taiwan based on 41 42 WHO Child Growth Standards , and a modified locally weighted method designed for use with children and adolescents, based on BMI, age, and gender. Body fat as a percentage of weight was calculated, to obtain two measurements, by a commercially available bioelectrical impedance analyzer (Maltron BioScan 920 analyzer, Maltron International Ltd). All participants lived in Taipei City and New Taipei City, which are without obvious arsenic exposure. Participants drank tap water with arsenic levels less than the standard 10 μg/L provided by the Taipei Water Department of the Taipei City Government. The average arsenic concentration of tap water in Taipei City is 0.7 µg/L, and ranged from non-detectable to 4.0 µg/L. Questionnaire interview. Well-trained interviewers carried out face-to-face interviews to collect infor- mation using a structured questionnaire. The questionnaire included information on demographics and socio- economic characteristics, lifestyle behavior of parents, such as cigarette smoking and alcohol consumption, and personal and family disease history. Biological specimen collection. About 5 to 8 mL of peripheral blood was collected from participants using vacuumed syringes at the time of recruitment. Blood samples were then separated into red blood cells and serum, and frozen at −80 °C for subsequently measuring biochemical indices. Concurrently, spot urine samples of 20 ml were collected and immediately transferred to a −20 °C freezer until required for urinary arsenic species analyses. Urinary arsenic species measurement. The analytical methods for determining urinary arsenic spe- cies have been described previously . Briefly, urine samples were thawed at room temperature, ultrasoni- cally mixed and filtered through a Sep-Pak C18 column. A 200-μ L sample of treated urine was injected into a high-performance liquid chromatography column, linked to a hydride generator and atomic absorption III V V V spectrometer (HG-AAS) to measure the concentrations of arsenite (iAs ), arsenate (iAs ), MMA and DMA . Recovery rates of the four arsenic species were calculated by (sample spiked standard solution concentration − sample concentration)/standard solution concentration × 100. e Th recovery rates ranged from 93.8% to 102.2%, SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 8 www.nature.com/scientificreports/ III V V V and the detection limits for iAs , DMA , MMA and iAs were 0.02, 0.08, 0.05 and 0.07 μg/L respectively. The certified value of standard reference material (SRM 2670) was 480 ± 100 μg/L of inorganic arsenic obtained from the National Institute of Standards and Technology (NIST). SRM 2670 was used as a quality standard and analyzed along with urine samples. The mean value of SRM 2670 determined by our system was 507 ± 17 μg/L (n = 4). Both arsenobetain and arsenocholin are ingested from seafood and are excreted without metabolic trans- formation and, therefore, arsenobetain and arsenocholin were not measured by the HG-AAS method . Serum biochemical examination. Total cholesterol, triglyceride, high density lipoprotein (HDL) cho- lesterol, low density lipoprotein (LDL) cholesterol and insulin serum levels were determined by means of an autoanalyzer (Hitachi 737, USA) with reagents obtained from Boehringer Mannheim Diagnostics. An enzymatic assay for serum homocysteine was described by Chan et al. . A close correlation (r > 0.9) was observed between the results from the enzymatic method and a high performance liquid chromatography procedure used as ref. . HOMA-IR values were calculated using the formula: fasting insulin (μU/mL) × fasting glucose (mg/dL)/405 . Measurement of psychological characteristics. We used the Beck Youth Inventories, second edition (BYI-II), to evaluate the children’s reported thoughts, feelings, and behavior related to emotional and social dys- function . A child’s experiences in the five psychological domains, namely self-concept (assessing cognitions of competence, potency, and positive self-worth), anxiety (assessing worries about school performance, the future, negative reactions of others, and fears), depression (assessing negative thoughts about the self, life, and the future, and feelings of sadness and guilt), anger (assessing thoughts of being treated unfairly by others, and feelings of anger and hatred), and disruptive behavior (assessing thoughts and behavior associated with conduct disorder and oppositional defiant behavior) were measured, and each inventory included 20 questions. Every question was scored using a 4-point Likert scale, with 0 indicating never and 3 indicating always. Total scores were summed for each inventory. Thus, higher scores indicated a stronger display of a particular psychological domain. To enable comparison of a child’s score with those of other age-matched children, raw scores were converted (standard- ized) into T scores (with a mean of 50 and a standard deviation of 10). The internal consistency was indicated as Cronbach’s α coefficients, and ranged from 0.86 to 0.96 for all age groups on all scales, good test-retest reliability was reported to range from 0.74 to 0.93 . Validity was supported by correlations with other instruments that assess similar characteristics. Both the reliability and validity were further established using the Chinese version of the BYI-II . All Cronbach’s α coefficients were clearly greater than 0.9 for each of the five inventories, and test-retest reliability ranged from 0.64 to 0.81. Criterion-related validity was also supported for each inventory. Although continuous T scores were generally preferable in statistical modeling, providing greater variability, we wanted to identify children with psychological difficulties above or below the “warning line”, who deserved special attention. We used cutoff points suggested in the BYI-II Manual to categorize students into “lower than normal, normal” and “higher than normal” for each of the five psychological domains of depression, anxiety, anger, dis- 48,49 ruptive behavior, and self-concept . III V V Statistical analysis. e s Th um of urinary inorganic arsenic (iAs and iAs ) and methylated arsenic (MMA and DMA ) concentrations (μg/L) was defined as the total urinary arsenic. The inorganic arsenic percentages V V III V (iAs%), MMA %, and DMA % were calculated by dividing the concentration of each species [(iAs + iAs ), V V MMA and DMA ] by the total urinary arsenic concentrations. The Student’s t-test was used to compare dif- ferences in the variables of age, biochemical indices, psychological characteristics, and urinary arsenic profiles between elementary school and junior high school students. The χ test was used to test for differences in cat- egorical variables between elementary school and junior high school students. Analysis of variance (one-way ANOVA) and least significant difference test (post hoc test) with Bonferroni correction were used to compare the differences in variables of urinary arsenic profiles, and HOMA-IR levels among different psychological charac- teristics. Multiple linear regression models were used to estimate multivariate adjusted associations between the urinary arsenic profiles, HOMA-IR levels and psychological characteristics, and presented in regression coeffi- cients (β) and standard error (SE). For dose-dependent relationships, trend analysis was performed by treating ordinal-score variables as continuous variables in the regression model. For the interaction analysis, the cuto ff point for iAs% and HOMA-IR value was the median of the overall students, elementary school students and jun- ior high school students, respectively. References 1. International Agency for Research on Cancer. Overall Evaluations of Carcinogenicity: An Updating of IARC Monographs Volumes 1 to 42 (ed. Lyon: International Agency For Research On Cancer) 100–106 (Lyon, International Agency for Research on Cancer, 1987). 2. Dakeishi, M., Murata, K. & Grandjean, P. Long-term consequences of arsenic poisoning during infancy due to contaminated milk powder. Environ Health 5, 31, doi:10.1186/1476-069X-5-31 (2006). 3. Wasserman, G. A. et al. Water arsenic exposure and intellectual function in 6-year-old children in Araihazar, Bangladesh. Environ Health Perspect 115, 285–289, doi:10.1289/ehp.9501 (2007). 4. Naujokas, M. F. et al. The broad scope of health effects from chronic arsenic exposure: update on a worldwide public health problem. Environ Health Perspect 121, 295–302, doi:10.1289/ehp.1205875 (2013). 5. Rodriguez-Barranco, M. et al. Association of arsenic, cadmium and manganese exposure with neurodevelopment and behavioural disorders in children: a systematic review and meta-analysis. Sci Total Environ 454–455, 562–577, doi:10.1016/j. scitotenv.2013.03.047 (2013). 6. Tyler, C. R. & Allan, A. M. The Effects of Arsenic Exposure on Neurological and Cognitive Dysfunction in Human and Rodent Studies: A Review. Curr Environ Health Rep 1, 132–147, doi:10.1007/s40572-014-0012-1 (2014). 7. Rodriguez-Barranco, M. et al. Postnatal arsenic exposure and attention impairment in school children. Cortex 74, 370–382, doi:10.1016/j.cortex.2014.12.018 (2015). 8. Yamauchi, H. & Fowler, B. A. Toxicity and Metabolism of Inorganic and Methylated Arsenicals. Report No. BIOSIS/94/23178, Human Health and Ecosystem Effects (Yamauchi, H; Fowler, BA, 1994). 9. Vahter, M. Mechanisms of arsenic biotransformation. Toxicology 181–182, 211–217, doi:10.1016/S0300-483X(02)00285-8 (2002). SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 9 www.nature.com/scientificreports/ 10. Styblo, M. et al. Comparative toxicity of trivalent and pentavalent inorganic and methylated arsenicals in rat and human cells. Arch Toxicol 74, 289–299, doi:10.1007/s002040000134 (2000). 11. Tokar, E. J., Person, R. J., Sun, Y., Perantoni, A. O. & Waalkes, M. P. Chronic exposure of renal stem cells to inorganic arsenic induces a cancer phenotype. Chem Res Toxicol 26, 96–105, doi:10.1021/tx3004054 (2013). 12. Huang, Y. K. et al. Arsenic exposure, urinary arsenic speciation, and the incidence of urothelial carcinoma: a twelve-year follow-up study. Cancer Causes Control 19, 829–839, doi:10.1007/s10552-008-9146-5 (2008). 13. Su, C. T. et al. The relationship between obesity, insulin and arsenic methylation capability in Taiwan adolescents. Sci Total Environ 414, 152–158, doi:10.1016/j.scitotenv.2011.10.023 (2012). 14. Lin, H. C. et al. Arsenic methylation capacity and obesity are associated with insulin resistance in obese children and adolescents. Food Chem Toxicol 74C, 60–67, doi:10.1016/j.fct.2014.08.018 (2014). 15. Daniels, S. R., Jacobson, M. S., McCrindle, B. W., Eckel, R. H. & Sanner, B. M. American Heart Association Childhood Obesity Research Summit Report. Circulation 119, e489–e517, doi:10.1161/CIRCULATIONAHA.109.192216 (2009). 16. Lee, W. W. An overview of pediatric obesity. Pediatr Diabetes 8(Suppl 9), 76–87, doi:10.1111/pdi.2007.8.issue-s9 (2007). 17. Bradley, R. H. et al. The relationship between body mass index and behavior in children. J Pediatr 153, 629–634, doi:10.1016/j. jpeds.2008.05.026 (2008). 18. Warschburger, P. The unhappy obese child. Int J Obes (Lond) 29(Suppl 2), S127–S129, doi:10.1038/sj.ijo.0803097 (2005). 19. Schwimmer, J. B., Burwinkle, T. M. & Varni, J. W. Health-related quality of life of severely obese children and adolescents. JAMA 289, 1813–1819, doi:10.1001/jama.289.14.1813 (2003). 20. Anderson, S. E., He, X., Schoppe-Sullivan, S. & Must, A. Externalizing behavior in early childhood and body mass index from age 2 to 12 years: longitudinal analyses of a prospective cohort study. BMC Pediatr 10, 49, doi:10.1186/1471-2431-10-49 (2010). 21. Puder, J. J. & Munsch, S. Psychological correlates of childhood obesity. Int J Obes (Lond) 34(Suppl 2), S37–S43, doi:10.1038/ ijo.2010.238 (2010). 22. Chung, K. H., Chiou, H. Y. & Chen, Y. H. Psychological and physiological correlates of childhood obesity in Taiwan. Sci Rep 5, 17439, doi:10.1038/srep17439 (2015). 23. Jeffery, A. N., Hyland, M. E., Hosking, J. & Wilkin, T. J. Mood and its association with metabolic health in adolescents: a longitudinal study, EarlyBird 65. Pediatr Diabetes 15, 599–605, doi:10.1111/pedi.2014.15.issue-8 (2014). 24. Lin, W. H. & Yi, C. C. Educational Tracking and Juvenile Deviance in Taiwan: Direct Effect, Indirect Effect, or Both. Int J Oen ff der er C Th omp Criminol 60, 326–348, doi:10.1177/0306624X14549440 (2014). 25. Gau, S. F. & Soong, W. T. Sleep problems of junior high school students in Taipei. Sleep 18, 667–673, doi:10.1093/sleep/18.8.667 (1995). 26. Rhee, S. Y. et al. Arsenic exposure and prevalence of diabetes mellitus in korean adults. J Korean Med Sci 28, 861–868, doi:10.3346/ jkms.2013.28.6.861 (2013). 27. McIntyre, R. S. et al. Should Depressive Syndromes Be Reclassified as “Metabolic Syndrome Type II”. Ann Clin Psychiatry 19, 257–264, doi:10.1080/10401230701653377 (2007). 28. van den Berg, E. et al. Cognitive functioning in elderly persons with type 2 diabetes and metabolic syndrome: the Hoorn study. Dement Geriatr Cogn Disord 26, 261–268, doi:10.1159/000160959 (2008). 29. Convit, A. Links between cognitive impairment in insulin resistance: an explanatory model. Neurobiol Aging 26(Suppl 1), 31–36, doi:10.1016/j.neurobiolaging.2005.09.018 (2005). 30. Fyfe, M., Raman, A., Sharma, S., Hudes, M. L. & Fleming, S. E. Insulin resistance and self-perceived scholastic competence in inner- city, overweight and obese, African American children. Physiol Behav 102, 36–41, doi:10.1016/j.physbeh.2010.09.015 (2011). 31. Rosado, J. L. et al. Arsenic exposure and cognitive performance in Mexican schoolchildren. Environ Health Perspect 115, 1371–1375, doi:10.1289/ehp.9961 (2007). 32. Roy, A. et al. Association between arsenic exposure and behavior among first-graders from Torreon, Mexico. Environ Res 111, 670–676, doi:10.1016/j.envres.2011.03.003 (2011). 33. Bailey, K. A. et al. Arsenic and the epigenome: interindividual differences in arsenic metabolism related to distinct patterns of DNA methylation. J Biochem Mol Toxicol 27, 106–115, doi:10.1002/jbt.21462 (2013). 34. Reichard, J. F. & Puga, A. Effects of arsenic exposure on DNA methylation and epigenetic gene regulation. Epigenomics 2, 87–104, doi:10.2217/epi.09.45 (2010). 35. Lin, H. C. et al. Arsenic methylation capacity and obesity are associated with insulin resistance in obese children and adolescents. Food Chem Toxicol 74C, 60–7, doi:10.1016/j.fct.2014.08.018 (2014). 36. Ahmed, S., Mahmood, Z. & Zahid, S. Linking insulin with Alzheimer’s disease: emergence as type III diabetes. Neurol Sci 36, 1763–9, doi:10.1007/s10072-015-2352-5 (2015). 37. Banzhaf-Strathmann, J. et al. MicroRNA-125b induces tau hyperphosphorylation and cognitive deficits in Alzheimer’s disease. EMBO J 33, 1667–80, doi:10.15252/embj.201387576 (2014). 38. Rustad, J. K., Musselman, D. L. & Nemeroff, C. B. The relationship of depression and diabetes: pathophysiological and treatment implications. Psychoneuroendocrinology 36, 1276–86, doi:10.1016/j.psyneuen.2011.03.005 (2011). 39. van Dooren, F. E. et al. Depression and risk of mortality in people with diabetes mellitus: a systematic review and meta-analysis. PLoS One 8, e57058, doi:10.1371/journal.pone.0057058 (2013). 40. Ministry of Health and Welfare. e r Th ecommended value of body mass index (BMI) of child and adolescent http://obesity.hpa.gov.tw/ TC/BMIproposal.aspx (2013). 41. de, O. M., Garza, C., Onyango, A. W. & Borghi, E. Comparison of the WHO child growth standards and the CDC 2000 growth charts. J Nutr 137, 144–148 (2007). 42. Chen, J. Y., Chang, H. Y. & Pan, W. H. A modified locally weighted method for developing reference standards for height, weight, and body mass index of boys and girls aged 4 to 18 in Taiwan. Hum Biol 75, 749–770, doi:10.1353/hub.2003.0072 (2003). 43. Hsueh, Y. M. et al. Urinary levels of inorganic and organic arsenic metabolites among residents in an arseniasis-hyperendemic area in Taiwan. J Toxicol Environ Health A 54, 431–444, doi:10.1080/009841098158728 (1998). 44. Buchet, J. P., Lauwerys, R. & Roels, H. Comparison of the urinary excretion of arsenic metabolites aer a sin ft gle oral dose of sodium arsenite, monomethylarsonate, or dimethylarsinate in man. Int Arch Occup Environ Health 48, 71–79, doi:10.1007/BF00405933 (1981). 45. Chan, E. C., Chang, P. Y., Wu, T. L. & Wu, J. T. Enzymatic assay of homocysteine on microtiter plates or a TECAN analyzer using crude lysate containing recombinant methionine gamma-lyase. Ann Clin Lab Sci 35, 155–160 (2005). 46. Katz, A. et al. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 85, 2402–2410, doi:10.1210/jcem.85.7.6661 (2000). 47. Beck, A. T. Cognitive therapy and the emotional disorders Madison: International Universities Press, Inc. (1976). 48. Beck, J. S., Beck, A. T., Jolly, J. B. & Steer, R. A. Manual for the Beck Youth Inventories (2nd ed.). San Antonio, TX: Harcourt Assessment (2005). 49. Cho, S. L., Hung, L. Y., Su, C. L. & Chen, H. C. A Research of the Chinese Version Beck Youth Inventories. Psychol Testing 639–669 (2009) SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 10 www.nature.com/scientificreports/ Acknowledgements This study was supported by grants from the Taipei Medical University Hospital (99TMU-TMUH-02-3), the National Science Council (NSC 101-2314-B-038 -051-MY3 (3-3)), and the Ministry of Science and Technology, ROC (MOST103-2314-B-038-021-MY2 (1-2), and MOST103-2314-B-038-021-MY2 (2-2)). Author Contributions Chien-Tien Su, Horng-Sheng Shiue, Cheuk-Sing Choy and Hung-Yi Chiou partly contributed to the conception and design of the work, and recruited the study subjects; Yi-Hua Chen conducted the measurement of psychological characteristics; Wei-Jen Chen have done the experiment; Wei-Jen Chen contributed to the analyzed the data and Ying-Chin Lin wrote the manuscript; Yu-Mei Hsueh and Bor-Cheng Han performed the study design and executed the whole research plan. Additional Information Supplementary information accompanies this paper at doi:10.1038/s41598-017-03084-2 Competing Interests: The authors declare that they have no competing interests. Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Cre- ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per- mitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2017 SCiENTiFiC RePo R TS | 7: 3094 | DOI:10.1038/s41598-017-03084-2 11
Scientific Reports – Springer Journals
Published: Jun 8, 2017
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