臺灣博碩士論文加值系統

研究背景：暴露體學已成為環境衛生學界的重要方法論，近年來更是發展出 “Public Health Exposome Approach”，探討特定地區的暴露特徵及健康影響。本論文針對台灣最大的石化工業區第六套輕油裂解廠 (簡稱六輕) 附近居民進行暴露體學研究，找出暴露程度、代謝體及早期健康效應生物指標物之間的相關性。
研究方法：本研究依住家與六輕距離、尿中暴露生物指標物濃度 (釩與多環芳香烴暴露生物指標物1－羥基芘) 將 273 位研究對象分為高暴露組 (9－15 歲小孩43 人、> 55 歲老年人 77 人)　與低暴露組 (小孩 75 人、老年人78 人)，分析其 (一) 外在暴露：對六輕主要排放源的距離、住家附近道路面積、住家空氣中釩及多環芳香烴濃度；(二) 內在暴露：尿中石化工業污染暴露生物指標物砷、鎘、鉻、鎳、汞、鉛、釩、錳、銅、鍶、鉈與1－羥基芘濃度；(三) 代謝體：利用二維氣相層析飛行時間質譜儀建立尿液代謝體，以超高壓液相層析－四極柱飛行時間質譜儀分析血液代謝體及血液脂質體；(四) 早期健康效應：尿中氧化壓力指標物與血中醯基肉鹼類濃度。本研究以「中途相遇法」找出潛在可作為連結暴露與早期健康效應的中間生物指標物，並以生物途徑分析找出多重石化工業污染物暴露可能影響的生理途徑。
研究成果：本研究結果顯示在小孩及老年人受試者中，高暴露組比低暴露組居住離六輕主要排放源較近、有較高的住家空氣中釩及多環芳香烴濃度，且高暴露組比低暴露組有較高的尿中暴露生物指標物濃度與氧化壓力生物指標物濃度。尿液代謝體在高低暴露組之間有年齡依賴性的改變可連結多重暴露與氧化壓力，在小孩中是色氨酸代謝等途徑的異常，在老年人中則是甘氨酸、絲氨酸與蘇胺酸代謝等途徑的異常，且在小孩與老年人的尿液代謝體中發現潛在暴露生物指標物癸烷、十二烷、十三烷。小孩的血液代謝體在高低暴露組之間有顯著差異，並找到十個潛在可做為中間生物指標物的代謝物質，連結多重工業致癌物暴露 (國際癌症研究機構定義一級致癌物：砷、鎘、鉻、鎳；二級致癌物：汞、鉛、釩、多環芳香烴) 與早期健康效應氧化壓力增加、血中醯基肉鹼類濃度異常。生物途徑分析結果顯示小孩暴露於多重工業致癌物質可能造成嘌呤代謝途徑異常。小孩的血液脂質體在高低暴露組之間有顯著差異，並發現有 21 個脂質與多重工業污染物暴露相關，包括溶血卵磷脂類、卵磷脂類、神經鞘磷脂類及磷脂酸肌醇類，這四種脂質皆可連結到尿中氧化壓力生物指標物或血中醯基肉鹼類。
結論：Public health exposome approach 可用於探討石化工業影響地區內的易感族群，並釐清多重工業污染暴露如何影響重要生理途徑，導致與慢性和急性疾病相關的早期健康效應。氣相層析方法分析尿液代謝體可用於辨識石化工業附近的易感族群如小孩與老年人，並發現與年齡相關的生理途徑連結多重暴露與氧化壓力。液相層析方法分析血液代謝體可用於尋找多重工業致癌汙染物暴露在小孩與青少年體內影響的生理途徑，並連結癌症相關的早期健康效應。液相層析方法分析血液脂質體可用於辨識多重工業污染暴露在小孩及青少年體內造成與肝功能異常相關的脂質變化。基於本研究的發現，我們建議顯著降低石化工業污染排放量以減少暴露程度、改善代謝異常，並持續追蹤六輕附近居民的健康狀態。本研究也證實，暴露體學可作為公共衛生研究工具，探討工業污染對附近居民既有及潛在的健康效應，未來可作為尋找新的個人化健康效應指標及暴露生物指標物質、建立個人化風險評估指標的參考。

Background: Exposomics is an important methodology in environmental health research. Recently, a branching paradigm, the Public Health Exposome Approach, focuses on the impact of exposures on the overall health of a population within a particular region. This dissertation focuses on the exposomics study of residents living near No. 6 Naphtha Cracking Complex, the largest petrochemical complex in Taiwan, and aim to clarify the association between exposure levels, metabolome, and early health effect biomarkers.
Material and Methods: We classified 273 study subjects as high exposure group (children aged 9-15 N=43; elderly aged > 55 N=77) and low exposure group (children N=75; elderly N=78) by the distance from their homes to the complex, and urinary levels of exposure biomarkers vanadium (V) and polycyclic aromatic hydrocarbon (PAHs) metabolite 1-hydroxypyrene (1-OHP). We analyzed (1) external exposures: distance from their homes to main emission points of the complex, road area surrounding homes, and ambient levels of V and PAHs at homes using previously established models; (2) internal exposures: urinary levels of exposure biomarkers, arsenic (As), cadmium (Cd), chromium (Cr), nickel (Ni), mercury (Hg), lead (Pb), vanadium (V), manganese (Mn), copper (Cu), strontium (Sr), thallium (Tl), and 1-OHP; (3) metabolome: urine metabolomics was analyzed using two dimensional gas chromatography coupled with time-of-flight mass spectrometry (GCxGC-TOFMS), and serum metabolomics and lipidomics were analyzed using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-qTOFMS); (4) early health effects: urinary levels of oxidative stress biomarkers, and serum acylcarnitines. We applied “meet-in-the-middle” approach to identify potential intermediate biomarkers connecting exposures with early health effects, and pathway analysis to find biological mechanisms affected by exposure to multiple pollutants.
Results: In both children and elderly subjects, high exposure group lived closer to main emission points of the complex, had elevated ambient levels of V and PAHs at home locations, and increased urinary exposure biomarkers and oxidative stress biomarkers compared to low exposure group. Urine metabolomics identified age-dependent biological pathways that associated multiple pollutants exposure with increased oxidative stress, including tryptophan metabolism in children, and serine, glycine, and threonine metabolism in elderly subjects. In addition, potential exposure biomarkers decane, dodecane, and tridecane were identified in both children and elderly subjects. Serum metabolomics found 10 potential metabolites possibly linking increased exposure to IARC group 1 carcinogens (As, Cd, Cr, Ni) and group 2 carcinogens (V, Hg, PAHs) with elevated oxidative stress and deregulated serum acylcarnitines. Purine metabolism was identified as the possible mechanism affected by children’s exposure to carcinogens. Serum lipidomics results in children also showed significant difference between high and low exposure groups. We found 21 lipids associated with multiple industrial pollutants exposure, including lysophosphatidylcholines, phosphatidylcholines, sphingomyelins, and phosphatidylinositols. All four types of lipids were associated with urinary oxidative stress biomarkers and/or serum acylcarnitines.
Conclusion: Public health exposome approach could be used in a large petrochemical industry influenced region to identify vulnerable populations, and understand how multiple industrial pollutants exposure are affecting critical biological mechanisms, leading to early health effects that may be precursors to chronic and acute diseases. Urine metabolomics analyzed via GC-based method could be used to identify children and elderly as vulnerable populations in regions influenced by a large petrochemical industry, and found age-dependent pathways linking multiple exposures to increased oxidative stress. Serum metabolomics analyzed via LC-based method could be used to find biological pathways affected by multiple industrial carcinogenic pollutants exposure in children and adolescents, that could be linked to cancer-related early health effects. Serum lipidomics analyzed via LC-based method could be used to identify in children and adolescents exposed to multiple industrial pollutants, lipid profile changes that have been implicated in liver dysfunctions. Based on our findings, we suggest significant reduction of petrochemical industrial emissions from the complex to decrease multiple pollutants exposure and metabolic abnormalities, and continued follow up on of residents’ health. This dissertation also attests the application of exposomics as a public health research tool, in the investigation of current and potential health impacts of industrial pollution on nearby residents, providing information for future identification of novel personalized health indicators and exposure biomarkers, and establishment of individual risk index.

1. Introduction 1
1.1 Background 1
1.2 Exposomics 10
1.3 Metabolomics 10
1.4 Lipidomics 11
1.5 Oxidative stress 12
1.6 Serum acylcarnitines 12
2. Objectives 13
3. Material and Methods 14
3.1 Study area and subjects 14
3.2 External exposure 15
3.3 Internal exposure 16
3.4 Metabolomics 16
3.4.1 Urine metabolomics 16
3.4.2 Serum metabolomics 19
3.4.3 Serum lipidomics 21
3.5 Early health effects 22
3.5.1 Oxidative stress 22
3.5.2 Serum acylcarnitines 23
3.6 Pathway analysis 24
3.7 Meet-in-the-middle 24
3.8 Association between exposure and early health effects 25
3.9 Statistical analysis 26
4. Results and Discussion 27
4.1 Part 1. Linking sources to early effects by profiling urine metabolome of residents living near oil refineries and coal-fired power plants 27
4.1.1 Results 27
4.1.2 Discussion 44
4.2 Part 2. Metabolomics of Children and Adolescents Exposed to Industrial Carcinogenic Pollutants 50
4.2.1 Results 50
4.2.2 Discussion 63
4.3 Part 3. Lipidomics of Children and Adolescents Exposed to Industrial Pollutants. 67
4.3.1 Results 67
4.3.2 Discussion 83
5. Conclusion and Recommendation 85
6. References 86
7. Appendix I
7.1 Appendix 1: Urine metabolite profiles in children and elderly participants and the association with multiple exposures and oxidative stress. I
7.2 Appendix 2: Identified potential metabolite features in serum sample of 107 subjects using metabolomics. XIV
7.3 Appendix 3: Identified potential lipid species in serum sample of 107 subjects using lipidomics. XVII

Adler T. 2003. Aging research: The future face of environmental health. Environ Health Perspect 111:A760-765.
Amelio I, Cutruzzola F, Antonov A, Agostini M, Melino G. 2014. Serine and glycine metabolism in cancer. Trends Biochem Sci 39:191-198.
Ayala A, Munoz MF, Arguelles S. 2014. Lipid peroxidation: Production, metabolism, and signaling mechanisms of malondialdehyde and 4-hydroxy-2-nonenal. Oxid Med Cell Longev 2014:360438.
Bartsch H, Nair J. 2005. Accumulation of lipid peroxidation-derived DNA lesions: Potential lead markers for chemoprevention of inflammation-driven malignancies. Mutat Res 591:34-44.
Bester AC, Roniger M, Oren YS, Im MM, Sarni D, Chaoat M, et al. 2011. Nucleotide deficiency promotes genomic instability in early stages of cancer development. Cell 145:435-446.
Blow N. 2008. Metabolomics: Biochemistry''s new look. Nature 455:697-700.
Bouatra S, Aziat F, Mandal R, Guo AC, Wilson MR, Knox C, et al. 2013. The human urine metabolome. PLoS One 8:e73076.
Bowler RP, Crapo JD. 2002. Oxidative stress in allergic respiratory diseases. The Journal of allergy and clinical immunology 110:349-356.
Cantu-Medellin N, Kelley EE. 2013. Xanthine oxidoreductase-catalyzed reactive species generation: A process in critical need of reevaluation. Redox Biology 1:353-358.
Carpenter DO, Arcaro K, Spink DC. 2002. Understanding the human health effects of chemical mixtures. Environ Health Perspect 110 Suppl 1:25-42.
Chadeau-Hyam M, Athersuch TJ, Keun HC, De Iorio M, Ebbels TM, Jenab M, et al. 2011. Meeting-in-the-middle using metabolic profiling - a strategy for the identification of intermediate biomarkers in cohort studies. Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals 16:83-88.
Chan CC, Shie RH, Chang TY, Tsai DH. 2006. Workers'' exposures and potential health risks to air toxics in a petrochemical complex assessed by improved methodology. Int Arch Occup Environ Health 79:135-142.
Chan EC, Pasikanti KK, Nicholson JK. 2011. Global urinary metabolic profiling procedures using gas chromatography-mass spectrometry. Nature protocols 6:1483-1499.
Chen C-HS, Kuo T-C, Kuo H-C, Tseng YJ, Kuo C-H, Yuan T-H, et al. 2019. Metabolomics of children and adolescents exposed to industrial carcinogenic pollutants. Environ Sci Technol.
Chen CF, Chio CP, Yuan TH, Yeh YP, Chan CC. 2018. Increased cancer incidence of changhua residents living in taisi village north to the no. 6 naphtha cracking complex. Journal of the Formosan Medical Association = Taiwan yi zhi 117:1101-1107.
Chen CS, Yuan TH, Shie RH, Wu KY, Chan CC. 2017. Linking sources to early effects by profiling urine metabolome of residents living near oil refineries and coal-fired power plants. Environ Int 102:87-96.
Chen S, Kong H, Lu X, Li Y, Yin P, Zeng Z, et al. 2013. Pseudotargeted metabolomics method and its application in serum biomarker discovery for hepatocellular carcinoma based on ultra high-performance liquid chromatography/triple quadrupole mass spectrometry. Anal Chem 85:8326-8333.
Chen Y, Guillemin GJ. 2009. Kynurenine pathway metabolites in humans: Disease and healthy states. Int J Tryptophan Res 2:1-19.
Chen YM, Lin WY, Chan CC. 2014. The impact of petrochemical industrialisation on life expectancy and per capita income in taiwan: An 11-year longitudinal study. BMC Public Health 14:247.
Chi L, Tu P, Liu CW, Lai Y, Xue J, Ru H, et al. 2019. Chronic arsenic exposure induces oxidative stress and perturbs serum lysolipids and fecal unsaturated fatty acid metabolism. Chem Res Toxicol.
Chiang TY, Yuan TH, Shie RH, Chen CF, Chan CC. 2016. Increased incidence of allergic rhinitis, bronchitis and asthma, in children living near a petrochemical complex with so2 pollution. Environ Int 96:1-7.
Chio CP, Yuan TH, Shie RH, Chan CC. 2014. Assessing vanadium and arsenic exposure of people living near a petrochemical complex with two-stage dispersion models. Journal of Hazardous Materials 271:98-107.
Chong J, Soufan O, Li C, Caraus I, Li S, Bourque G, et al. 2018. Metaboanalyst 4.0: Towards more transparent and integrative metabolomics analysis. Nucleic Acids Res 46:W486-W494.
Chuang HC, Shie RH, Chio CP, Yuan TH, Lee JH, Chan CC. 2018. Cluster analysis of fine particulate matter (pm2.5) emissions and its bioreactivity in the vicinity of a petrochemical complex. Environ Pollut 236:591-597.
Ciprandi G, De Amici M, Tosca M, Fuchs D. 2010. Tryptophan metabolism in allergic rhinitis: The effect of pollen allergen exposure. Human Immunology 71:911-915.
Davis AP, Grondin CJ, Johnson RJ, Sciaky D, McMorran R, Wiegers J, et al. 2019. The comparative toxicogenomics database: Update 2019. Nucleic Acids Res 47:D948-D954.
Driscoll CT, Buonocore JJ, Levy JI, Lambert KF, Burtraw D, Reid SB, et al. 2015. Us power plant carbon standards and clean air and health co-benefits. Nature Climate Change 5:535-540.
Dunn WB, Broadhurst D, Begley P, Zelena E, Francis-McIntyre S, Anderson N, et al. 2011. Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry. Nature protocols 6:1060-1083.
Dybing E, Schwarze PE, Nafstad P, Victorin K, Penning TM. 2013. Chapter 7. Polyclyclic aromatic hydrocarbons in ambient air and cancer. France: International Agency for Research on Cancer.
Ellis JK, Athersuch TJ, Thomas LD, Teichert F, Perez-Trujillo M, Svendsen C, et al. 2012. Metabolic profiling detects early effects of environmental and lifestyle exposure to cadmium in a human population. BMC Med 10:61.
EMA. 2011. Guideline on bioanalytical method validation emea/chmp/ewp/192217/2009 rev. 1.
Ferroni P, Santilli F, Cavaliere F, Simeone P, Costarelli L, Liani R, et al. 2017. Oxidant stress as a major determinant of platelet activation in invasive breast cancer. Int J Cancer 140:696-704.
Fouque D, Holt S, Guebre-Egziabher F, Nakamura K, Vianey-Saban C, Hadj-Aissa A, et al. 2006. Relationship between serum carnitine, acylcarnitines, and renal function in patients with chronic renal disease. Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation 16:125-131.
Fu PP, Xia Q, Sun X, Yu H. 2012. Phototoxicity and environmental transformation of polycyclic aromatic hydrocarbons (pahs)-light-induced reactive oxygen species, lipid peroxidation, and DNA damage. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev 30:1-41.
Gao X, Chen W, Li R, Wang M, Chen C, Zeng R, et al. 2012. Systematic variations associated with renal disease uncovered by parallel metabolomics of urine and serum. BMC Syst Biol 6 Suppl 1:S14.
George J, Masto RE, Ram LC, Das TB, Rout TK, Mohan M. 2015. Human exposure risks for metals in soil near a coal-fired power-generating plant. Archives of environmental contamination and toxicology 68:451-461.
Gostner JM, Becker K, Kofler H, Strasser B, Fuchs D. 2016. Tryptophan metabolism in allergic disorders. Int Arch Allergy Immunol 169:203-215.
Hastings J, de Matos P, Dekker A, Ennis M, Harsha B, Kale N, et al. 2013. The chebi reference database and ontology for biologically relevant chemistry: Enhancements for 2013. Nucleic Acids Res 41:D456-463.
Hiraku Y. 2010. Formation of 8-nitroguanine, a nitrative DNA lesion, in inflammation-related carcinogenesis and its significance. Environmental health and preventive medicine 15:63-72.
Ho TJ, Kuo CH, Wang SY, Chen GY, Tseng YJ. 2013. True ion pick (tipick): A denoising and peak picking algorithm to extract ion signals from liquid chromatography/mass spectrometry data. Journal of mass spectrometry : JMS 48:234-242.
Hopps E, Noto D, Caimi G, Averna MR. 2010. A novel component of the metabolic syndrome: The oxidative stress. Nutrition, metabolism, and cardiovascular diseases : NMCD 20:72-77.
Hu L, Bo L, Zhang M, Li S, Zhao X, Sun C. 2018. Metabonomics analysis of serum from rats given long-term and low-level cadmium by ultra-performance liquid chromatography-mass spectrometry. Xenobiotica; the fate of foreign compounds in biological systems 48:1079-1088.
Hu SW, Chan YJ, Hsu HT, Wu KY, ChangChien GP, Shie RH, et al. 2011. Urinary levels of 1-hydroxypyrene in children residing near a coal-fired power plant. Environ Res 111:1185-1191.
Huang PC, Liu LH, Shie RH, Tsai CH, Liang WY, Wang CW, et al. 2016. Assessment of urinary thiodiglycolic acid exposure in school-aged children in the vicinity of a petrochemical complex in central taiwan. Environ Res 150:566-572.
IARC. 1989a. Occupational exposures in petroleum refining; crude oil and major petroleum fuels. Iarc working group on the evaluation of carcinogenic risks to humans. IARC monographs on the evaluation of carcinogenic risks to humans 45:1-322.
IARC. 1989b. Cyclohexanone. IARC monographs on the evaluation of carcinogenic risks to humans 47:157-169.
Jomova K, Valko M. 2011. Advances in metal-induced oxidative stress and human disease. Toxicology 283:65-87.
Juarez PD, Matthews-Juarez P, Hood DB, Im W, Levine RS, Kilbourne BJ, et al. 2014. The public health exposome: A population-based, exposure science approach to health disparities research. Int J Environ Res Public Health 11:12866-12895.
Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. 2014. Data, information, knowledge and principle: Back to metabolism in kegg. Nucleic Acids Res 42:D199-205.
Kell DB, Brown M, Davey HM, Dunn WB, Spasic I, Oliver SG. 2005. Metabolic footprinting and systems biology: The medium is the message. Nat Rev Microbiol 3:557-565.
Klupczynska A, Derezinski P, Dyszkiewicz W, Pawlak K, Kasprzyk M, Kokot ZJ. 2016a. Evaluation of serum amino acid profiles'' utility in non-small cell lung cancer detection in polish population. Lung cancer (Amsterdam, Netherlands) 100:71-76.
Klupczynska A, Plewa S, Dyszkiewicz W, Kasprzyk M, Sytek N, Kokot ZJ. 2016b. Determination of low-molecular-weight organic acids in non-small cell lung cancer with a new liquid chromatography-tandem mass spectrometry method. Journal of pharmaceutical and biomedical analysis 129:299-309.
Klupczynska A, Derezinski P, Garrett TJ, Rubio VY, Dyszkiewicz W, Kasprzyk M, et al. 2017. Study of early stage non-small-cell lung cancer using orbitrap-based global serum metabolomics. Journal of cancer research and clinical oncology 143:649-659.
Ko JL, Cheng YJ, Liu GC, Hsin IL, Chen HL. 2017. The association of occupational metals exposure and oxidative damage, telomere shortening in fitness equipments manufacturing workers. Industrial health 55:345-353.
Krautbauer S, Eisinger K, Wiest R, Liebisch G, Buechler C. 2016. Systemic saturated lysophosphatidylcholine is associated with hepatic function in patients with liver cirrhosis. Prostaglandins & other lipid mediators 124:27-33.
Kumar A, Bachhawat AK. 2012. Pyroglutamic acid: Throwing light on a lightly studied metabolite. Current Science 102:288-297.
Lai YS, Chen WC, Kuo TC, Ho CT, Kuo CH, Tseng YJ, et al. 2015. Mass-spectrometry-based serum metabolomics of a c57bl/6j mouse model of high-fat-diet-induced non-alcoholic fatty liver disease development. J Agric Food Chem 63:7873-7884.
Li F, Xiang B, Jin Y, Li C, Li J, Ren S, et al. 2019. Dysregulation of lipid metabolism induced by airway exposure to polycyclic aromatic hydrocarbons in c57bl/6 mice. Environ Pollut 245:986-993.
Maiuolo J, Oppedisano F, Gratteri S, Muscoli C, Mollace V. 2016. Regulation of uric acid metabolism and excretion. Int J Cardiol 213:8-14.
Makri A, Stilianakis NI. 2008. Vulnerability to air pollution health effects. International journal of hygiene and environmental health 211:326-336.
Nadal M, Schuhmacher M, Domingo JL. 2004. Metal pollution of soils and vegetation in an area with petrochemical industry. Sci Total Environ 321:59-69.
Nadal M, Mari M, Schuhmacher M, Domingo JL. 2009. Multi-compartmental environmental surveillance of a petrochemical area: Levels of micropollutants. Environ Int 35:227-235.
Ni J, Xu L, Li W, Wu L. 2016. Simultaneous determination of thirteen kinds of amino acid and eight kinds of acylcarnitine in human serum by lc-ms/ms and its application to measure the serum concentration of lung cancer patients. Biomedical chromatography : BMC 30:1796-1806.
O''Rourke D, Connolly S. 2003. Just oil? The distribution of environmental and social impacts of oil production and consumption.ANNUAL REVIEWS.
Orešič M, Hyötyläinen T, Kotronen A, Gopalacharyulu P, Nygren H, Arola J, et al. 2013. Prediction of non-alcoholic fatty-liver disease and liver fat content by serum molecular lipids. Diabetologia 56:2266-2274.
Orhan H, Vermeulen NP, Tump C, Zappey H, Meerman JH. 2004. Simultaneous determination of tyrosine, phenylalanine and deoxyguanosine oxidation products by liquid chromatography-tandem mass spectrometry as non-invasive biomarkers for oxidative damage. J Chromatogr B Analyt Technol Biomed Life Sci 799:245-254.
Pasikanti KK, Esuvaranathan K, Hong Y, Ho PC, Mahendran R, Raman Nee Mani L, et al. 2013. Urinary metabotyping of bladder cancer using two-dimensional gas chromatography time-of-flight mass spectrometry. Journal of proteome research 12:3865-3873.
Patti GJ, Yanes O, Siuzdak G. 2012. Innovation: Metabolomics: The apogee of the omics trilogy. Nat Rev Mol Cell Biol 13:263-269.
Pedley AM, Benkovic SJ. 2017. A new view into the regulation of purine metabolism: The purinosome. Trends in Biochemical Sciences 42:141-154.
Pennell K. 2016. Population screening for biological and environmental properties of the human metabolic phenotype: Implications for personalized medicine.
Penning TM, Drury JE. 2007. Human aldo-keto reductases: Function, gene regulation, and single nucleotide polymorphisms. Archives of Biochemistry and Biophysics 464:241-250.
Peter AL, Viraraghavan T. 2005. Thallium: A review of public health and environmental concerns. Environ Int 31:493-501.
Poli G. 2000. Pathogenesis of liver fibrosis: Role of oxidative stress. Molecular Aspects of Medicine 21:49-98.
Psychogios N, Hau DD, Peng J, Guo AC, Mandal R, Bouatra S, et al. 2011. The human serum metabolome. PLoS One 6:e16957.
Rappaport SM, Smith MT. 2010. Epidemiology. Environment and disease risks. Science 330:460-461.
Reuter S, Gupta SC, Chaturvedi MM, Aggarwal BB. 2010. Oxidative stress, inflammation, and cancer: How are they linked? Free Radic Biol Med 49:1603-1616.
Robertson DG, Watkins PB, Reily MD. 2011. Metabolomics in toxicology: Preclinical and clinical applications. Toxicological sciences : an official journal of the Society of Toxicology 120 Suppl 1:S146-170.
Ruiz-Canela M, Hruby A, Clish CB, Liang L, Martinez-Gonzalez MA, Hu FB. 2017. Comprehensive metabolomic profiling and incident cardiovascular disease: A systematic review. Journal of the American Heart Association 6.
Rutkowsky JM, Knotts TA, Ono-Moore KD, McCoin CS, Huang S, Schneider D, et al. 2014. Acylcarnitines activate proinflammatory signaling pathways. American journal of physiology Endocrinology and metabolism 306:E1378-1387.
Sekas G, Patton GM, Lincoln EC, Robins SJ. 1985. Origin of plasma lysophosphatidylcholine: Evidence for direct hepatic secretion in the rat. The Journal of laboratory and clinical medicine 105:190-194.
Semba RD, Trehan I, Li X, Moaddel R, Ordiz MI, Maleta KM, et al. 2017. Environmental enteric dysfunction is associated with carnitine deficiency and altered fatty acid oxidation. EBioMedicine 17:57-66.
Senghore T, Li YF, Sung FC, Tsai MH, Hua CH, Liu CS, et al. 2018. Biomarkers of oxidative stress associated with the risk of potentially malignant oral disorders. Anticancer research 38:5211-5216.
Shen S, Zhang R, Zhang J, Wei Y, Guo Y, Su L, et al. 2018. Welding fume exposure is associated with inflammation: A global metabolomics profiling study. Environmental health : a global access science source 17:68.
Shie RH, Chan CC. 2013. Tracking hazardous air pollutants from a refinery fire by applying on-line and off-line air monitoring and back trajectory modeling. J Hazard Mater 261:72-82.
Shie RH, Yuan TH, Chan CC. 2013. Using pollution roses to assess sulfur dioxide impacts in a township downwind of a petrochemical complex. J Air Waste Manag Assoc 63:702-711.
Simoni RE, Gomes LN, Scalco FB, Oliveira CP, Aquino Neto FR, de Oliveira ML. 2007. Uric acid changes in urine and plasma: An effective tool in screening for purine inborn errors of metabolism and other pathological conditions. Journal of inherited metabolic disease 30:295-309.
Sivakumar R, Babu PV, Shyamaladevi CS. 2011. Aspartate and glutamate prevents isoproterenol-induced cardiac toxicity by alleviating oxidative stress in rats. Exp Toxicol Pathol 63:137-142.
Smith MT, de la Rosa R, Daniels SI. 2015. Using exposomics to assess cumulative risks and promote health. Environ Mol Mutagen 56:715-723.
Stegemann C, Pechlaner R, Willeit P, Langley SR, Mangino M, Mayr U, et al. 2014. Lipidomics profiling and risk of cardiovascular disease in the prospective population-based bruneck study. Circulation 129:1821-1831.
Stoy N, Mackay GM, Forrest CM, Christofides J, Egerton M, Stone TW, et al. 2005. Tryptophan metabolism and oxidative stress in patients with huntington''s disease. J Neurochem 93:611-623.
Tahara D, Nakanishi T, Akazawa S, Yamaguchi Y, Yamamoto H, Akashi M, et al. 1993. Lecithin-cholesterol acyltransferase and lipid transfer protein activities in liver disease. Metabolism 42:19-23.
Toledo JB, Arnold M, Kastenmuller G, Chang R, Baillie RA, Han X, et al. 2017. Metabolic network failures in alzheimer''s disease: A biochemical road map. Alzheimer''s & dementia : the journal of the Alzheimer''s Association 13:965-984.
Valavanidis A, Vlachogianni T, Fiotakis C. 2009. 8-hydroxy-2′-deoxyguanosine (8-ohdg): A critical biomarker of oxidative stress and carcinogenesis. Journal of Environmental Science and Health, Part C 27:120-139.
Valko M, Morris H, Cronin MT. 2005. Metals, toxicity and oxidative stress. Curr Med Chem 12:1161-1208.
Vineis P, van Veldhoven K, Chadeau-Hyam M, Athersuch TJ. 2013. Advancing the application of omics-based biomarkers in environmental epidemiology. Environ Mol Mutagen 54:461-467.
Wang CW, Liao KW, Chan CC, Yu ML, Chuang HY, Chiang HC, et al. 2019. Association between urinary thiodiglycolic acid level and hepatic function or fibrosis index in school-aged children living near a petrochemical complex. Environ Pollut 244:648-656.
Wang SY, Kuo CH, Tseng YJ. 2015. Ion trace detection algorithm to extract pure ion chromatograms to improve untargeted peak detection quality for liquid chromatography/time-of-flight mass spectrometry-based metabolomics data. Anal Chem 87:3048-3055.
Wenk MR. 2005. The emerging field of lipidomics. Nature reviews Drug discovery 4:594-610.
Wild CP. 2005. Complementing the genome with an "exposome": The outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 14:1847-1850.
Wild CP. 2009. Environmental exposure measurement in cancer epidemiology. Mutagenesis 24:117-125.
Williams PR, Patterson J, Briggs DW. 2006. Vccep pilot: Progress on evaluating children''s risks and data needs. Risk Anal 26:781-801.
Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, et al. 2018. Hmdb 4.0: The human metabolome database for 2018. Nucleic Acids Res 46:D608-D617.
Wu C, Chen ST, Peng KH, Cheng TJ, Wu KY. 2016. Concurrent quantification of multiple biomarkers indicative of oxidative stress status using liquid chromatography-tandem mass spectrometry. Anal Biochem 512:26-35.
Xu G, Luo K, Liu H, Huang T, Fang X, Tu W. 2015. The progress of inflammation and oxidative stress in patients with chronic kidney disease. Renal failure 37:45-49.
Yang L, Li M, Shan Y, Shen S, Bai Y, Liu H. 2016. Recent advances in lipidomics for disease research. J Sep Sci 39:38-50.
Yuan TH, Chio CP, Shie RH, Pien WH, Chan CC. 2015a. The distance-to-source trend in vanadium and arsenic exposures for residents living near a petrochemical complex. J Expo Sci Environ Epidemiol.
Yuan TH, Shie RH, Chin YY, Chan CC. 2015b. Assessment of the levels of urinary 1-hydroxypyrene and air polycyclic aromatic hydrocarbon in pm2.5 for adult exposure to the petrochemical complex emissions. Environ Res 136:219-226.
Yuan TH, Chung MK, Lin CY, Chen ST, Wu KY, Chan CC. 2016. Metabolites of resident exposed to vanadium and pahs in the vicinity of a petrochemical complex. In: Science of the Total Environment.
Yuan TH, Shen YC, Shie RH, Hung SH, Chen CF, Chan CC. 2018. Increased cancers among residents living in the neighborhood of a petrochemical complex: A 12-year retrospective cohort study. International journal of hygiene and environmental health 221:308-314.
Zhao Y-Y, Vaziri ND, Lin R-C. 2015. Chapter six - lipidomics: New insight into kidney disease. In: Advances in clinical chemistry, Vol. 68, (Makowski GS, ed):Elsevier, 153-175.
Zhou L, Ding L, Yin P, Lu X, Wang X, Niu J, et al. 2012a. Serum metabolic profiling study of hepatocellular carcinoma infected with hepatitis b or hepatitis c virus by using liquid chromatography-mass spectrometry. Journal of proteome research 11:5433-5442.
Zhou L, Wang Q, Yin P, Xing W, Wu Z, Chen S, et al. 2012b. Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases. Anal Bioanal Chem 403:203-213.
江姿穎. 2015. 鄰近六輕工業區孩童之空氣汙染暴露與過敏性疾病及支氣管炎相關性研究:臺灣大學.
沈育正. 2014. 六輕石化工業區附近成人癌症發生之探討:臺灣大學.
柯昀君. 2017. 重金屬暴露與六輕石化工業區附近幼兒園孩童氧化壓力之相關及飲食中抗氧化物可能的保護效果:臺灣大學.
柯登元. 2016. 六輕石化工業區周界成人居民腎功能與慢性腎臟病之探討:臺灣大學.
孫稚翔. 2017. 鄰近六輕工業區成人血清中重金屬濃度與高血脂症、慢性腎臟病相關性之研究:臺灣大學.
莊明潔. 2018. 彰化縣大城鄉居民慢性腎臟病與六輕工業區距離相關性之研究:臺灣大學.
陳其欣. 2019. 六輕石化工業區附近居民多重污染暴露與代謝體關係之暴露體學研究:臺灣大學.
陳俊霖. 2018. 六輕工業區北鄰之彰化縣大城鄉居民尿中硫代二乙酸與非侵襲性肝纖維指標的關係:臺灣大學.
詹長權. 2010. 雲林縣沿海地區空氣汙染物及環境健康世代研究計畫期末報告.
詹長權. 2011. 雲林縣沿海地區空氣汙染物及環境健康世代研究計畫期末報告.
詹長權. 2012. 雲林縣沿海地區空氣汙染物及環境健康世代研究計畫期末報告.
詹長權. 2013. 雲林縣沿海地區空氣汙染物及環境健康世代研究計畫期末報告.
劉力瑄. 2014. 以尿液中硫代二乙酸評估雲林縣麥寮鄉六輕工業區附近國小學童氯乙烯單體之暴露:臺灣大學.
謝瑞豪. 2014. 六輕石化工業區營運及意外排放對於周遭社區空氣品質的影響評估:臺灣大學.
謝億廷. 2019. 六輕工業區周圍居民無機砷暴露之研究:臺灣大學.
邊瑋緒. 2011. 六輕離島工業區周界之懸浮微粒及附近居民尿中重金屬濃度之評估研究:臺灣大學.