| Summary: | 碩士 === 國立臺灣大學 === 職業醫學與工業衛生研究所 === 103 === Part I
Background: Phenolic compounds such as bisphenol A (BPA), nonylphenol (NP), and octylphenol (OP) are known as endocrine-disrupting compounds and commonly used in our life. Their impacts on neurodevelopment of children are inconclusive. The current study aims to investigate the association between umbilical cord blood levels of BPA, NP, OP and neurodevelopmental outcome at 2 and 7 years of age.
Methods: The study was based on Taiwan Birth Panel Study, a prospective birth cohort. We collected cord blood plasma to measure phenolic compounds levels by the ultra-performance liquid chromatography-tandem mass spectrometry. In the follow-up, 208 mother-infant pairs in their 2 years old and 148 mother-infant pairs in 7 years old were recruited in this study. We used Comprehensive Developmental Inventory for Infants and Toddlers (CDIIT) and Wechsler Intelligence Scale for Children (WISC-IV) for neurodevelopmental assessment in 2 years and 7 years of age, respectively. Multiple linear regressions were used for statistical analysis.
Results: The detection rates of BPA, NP, and OP were 55.9%, 77.6%, 68.3%, respectively. In this study, the median of BPA, NP, and OP levels in 2 years old were 3.3, 72.6, and 3.3 (ng/mL). On the other hand, the median levels of BPA, NP, and OP were 3.2, 49.3, and 6.6 (ng/mL). Levels of phenolic compounds were log10-transformed for statistical analysis. Gender stratification was further performed. In the WISC-IV analysis of neurocognitive assessment, we found that both significant negative association and trend between cord blood plasma BPA levels and full scale IQ (p for trend<0.01), verbal comprehension index (p for trend<0.01), and perceptual reasoning index (p for trend<0.01) in total study population. After stratified by sex, significant association were found in full scale IQ (p for trend=0.03) and verbal comprehension (p for trend<0.01) index in boys. In girls, the results demonstrated that prenatal BPA exposure had adverse effects on full scale IQ (p for trend=0.02), perceptual reasoning index (p for trend<0.01), and working memory index (p for trend=0.02). None of the DQs of the CDIIT analysis was significantly associated with phenolic compounds levels in cord blood based on continuous or categorical measures.
Conclusion: Prenatal exposure to BPA may affect neurocognitive development among 7 years of age, and the effects were different between boys and girls. More studies are needed to explore the relationship between NP and OP exposure in utero and childhood neurodevelopment.
Part II
Background: Cortisol was considered as stress biomarker because when we encountered a stressful event, cortisol would be secreted to meet the challenge. Hair was considered as long-term species which could evaluate the exposure in the past. In addition, moderate storing condition and explore specific timing of exposure make hair species getting notice in recent years. Therefore, cortisol levels in hair became a novel biomarker to evaluate chronic stress. The study aimed to develop an analytical method by LC-MS/MS to quantify the concentration of cortisol, cortisone, cotinine, nicotine, caffeine, and melatonin in hair, and also in serum, urine and saliva. In addition, we used structured questionnaire to evaluate stress level to investigate the correlation between concentrations of biomarkers and stress.
Methods: Study subjects recruited in this study were adult volunteers. There were 12 male and 19 female. Morning serum, urine and saliva were collected once a month within three months. Hair sample which near scalp was collected at the third month during study. We developed analytical method by liquid chromatography-tandem mass spectrometry to quantify the concentration of analytes in hair, serum, urine and saliva. Type a personality, consciously stress level, Pittsburgh Sleep Quality Index (PSQI) and Hospital Anxiety and Depression Scale (HADS) were used to evaluate the stress level of the study subjects. Pearson’s correlation coefficients were calculated between analytes concentration in different matrices, and stress-related outcomes assessment.
Results: The limit of detection and limit of quantitation were 2.57 and 7.79 (pg/mg), respectively. The detection rate which above limit of quantitation of cortisol levels in hair was 83.3%. Median of hair cortisol levels in our study population was 2.24 (pg/mg). We found that levels of cortisone but not cortisol in serum, urine, and saliva had significant correlation. We did not find significant correlation between levels of cortisol and cortisone in hair and stress-related outcomes.
Conclusions: The present results suggest that biomarker concentration and stress-related outcome may exist inconsistent. The method could be used in identify the karoshi in the future.
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