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Urbanization in China is associated with pronounced perturbation of plasma metabolites

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Abstract

Introduction

Urbanization is associated with major changes in environmental and lifestyle exposures that may influence metabolic signatures.

Objectives

We investigated cross-sectional urban and rural differences in plasma metabolome analyzed by liquid chromatography/mass spectrometry platform in 500 Chinese adults aged 25–68 years from two neighboring southern Chinese provinces.

Methods

We first examined the overall metabolome differences by urban and rural residential location, using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) and random forest classification. We then tested the association between urbanization status and individual metabolites using a linear regression adjusting for age, sex, and province and conducted pathway analysis (Fisher’s exact test) to identify metabolic pathways differed by urbanization status.

Results

We observed distinct overall metabolome by urbanization status in OPLS-DA and random forest classification. Using linear regression, out of a total of 1108 unique metabolite features identified in this sample, we found that 266 metabolites were differed by urbanization status (positive false discovery rate-adjusted p-value, q-value < 0.05). For example, the following metabolites were positively associated with urbanization status: caffeine metabolites from xanthine metabolism, hazardous pollutants like 4-hydroxychlorothalonil and perfluorooctanesulfonate, and metabolites implicated in cardiometabolic diseases, such as branched-chain amino acids. In pathway analysis, we found that xanthine metabolism pathways differed by urbanization status (q-value = 1.64E−04).

Conclusion

We detected profound differences in host metabolites by urbanization status. Urban residents were characterized by metabolites signaling caffeine metabolism and toxic pollutants and metabolites on known pathways to cardiometabolic disease risks, compared to their rural counterparts. Our findings highlight the importance of considering urbanization in metabolomics analysis.

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Fig. 1
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Fig. 4

source food consumption were not associated with any of the metabolites at q-value < 0.05 and thus not shown in the figure. *Metabolites at Level 2 identification according to the Metabolomics Standards Initiative (Color figure online)

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Data availability

The metadata associated to the samples, including community-, household-, and individual-level data like urbanization index, household income, education, and physical activity, is publicly available at the China Health and Nutrition Survey (CHNS) website: https://www.cpc.unc.edu/projects/china. The metabolomics data analyzed during the current study are currently not publicly available, but are pending release to a public repository with an embargo in the future. Metabolomics data are available to collaborators by permission from the corresponding author.

Code availability

The code used for the current study are available upon reasonable request.

Consent to publish

Not applicable.

References

  • Alfadda, A. A., & Sallam, R. M. (2012). Reactive oxygen species in health and disease. Journal of Biomedicine and Biotechnology, 2012, 936486.

    Google Scholar 

  • Cervantes Gracia, K., Llanas-Cornejo, D., & Husi, H. (2017). CVD and oxidative stress. Journal of Clinical Medicine, 6, 22.

    Google Scholar 

  • Chen, C., Lu, Y., Zhang, X., Geng, J., Wang, T., Shi, Y., et al. (2009). A review of spatial and temporal assessment of PFOS and PFOA contamination in China. Chemistry and Ecology, 25, 163–177.

    CAS  Google Scholar 

  • Coperchini, F., Awwad, O., Rotondi, M., Santini, F., Imbriani, M., & Chiovato, L. (2017). Thyroid disruption by perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA). Journal of Endocrinological Investigation, 40, 105–121.

    CAS  Google Scholar 

  • Ding, M., Zeleznik, O. A., Guasch-Ferre, M., Hu, J., Lasky-Su, J., Lee, I.-M., et al. (2019). Metabolome-wide association study with habitual physical activity in four prospective cohort studies. American Journal of Epidemiology. https://doi.org/10.1093/aje/kwz171.

    Article  Google Scholar 

  • Eisenberg, P. R., Sherman, L. A., Schectman, K., Perez, J., Sobel, B., & Jaffe, A. S. (1985). Fibrinopeptide A: A marker of acute coronary thrombosis. Circulation, 71, 912–918.

    CAS  Google Scholar 

  • Evans, A. M., Bridgewater, B., Liu, Q., Mitchell, M., Robinson, R., Dai, H., et al. (2014). High resolution mass spectrometry improves data quantity and quality as compared to unit mass resolution mass spectrometry in high-throughput profiling metabolomics. Metabolomics, 4(2), 1.

    Google Scholar 

  • Evans, A. M., Dehaven, C. D., Barrett, T., Mitchell, M., & Milgram, E. (2009). Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Analytical Chemistry, 81, 6656–6667.

    CAS  Google Scholar 

  • Fang, W., Peng, Y., Muir, D., Lin, J., & Zhang, X. (2019). A critical review of synthetic chemicals in surface waters of the US, the EU and China. Environment International, 131, 104994.

    CAS  Google Scholar 

  • Genuis, S. J., Beesoon, S., & Birkholz, D. (2013). Biomonitoring and elimination of perfluorinated compounds and polychlorinated biphenyls through perspiration: Blood, urine, and sweat study. ISRN Toxicology. https://doi.org/10.1155/2013/483832.

    Article  Google Scholar 

  • Hiltunen, T. P., Rimpelä, J. M., Mohney, R. P., Stirdivant, S. M., & Kontula, K. K. (2017). Effects of four different antihypertensive drugs on plasma metabolomic profiles in patients with essential hypertension. PLoS ONE, 12, e0187729.

    Google Scholar 

  • Hou, F., Zhao, L., & Liu, F. (2016). Residues and dissipation of chlorothalonil and azoxystrobin in cabbage under field conditions. International Journal of Environmental Analytical Chemistry, 96, 1105–1116.

    CAS  Google Scholar 

  • Inoue, Y., Howard, A. G., Thompson, A. L., & Gordon-Larsen, P. (2018). Secular change in the association between urbanisation and abdominal adiposity in China (1993–2011). Journal of Epidemiology and Community Health, 72, 484–490.

    Google Scholar 

  • Jin, Y. H., Liu, W., Sato, I., Nakayama, S. F., Sasaki, K., Saito, N., et al. (2009). PFOS and PFOA in environmental and tap water in China. Chemosphere, 77, 605–611.

    CAS  Google Scholar 

  • Jones-Smith, J. C., & Popkin, B. M. (2010). Understanding community context and adult health changes in China: Development of an urbanicity scale. Social Science and Medicine, 71, 1436–1446.

    Google Scholar 

  • Khosravi, M., Poursaleh, A., Ghasempour, G., Farhad, S., & Najafi, M. (2019). The effects of oxidative stress on the development of atherosclerosis. Biological Chemistry, 400, 711–732.

    CAS  Google Scholar 

  • Künzli, N., Bridevaux, P.-O., Liu, L. S., Garcia-Esteban, R., Schindler, C., Gerbase, M., et al. (2009). Traffic-related air pollution correlates with adult-onset asthma among never-smokers. Thorax, 64, 664–670.

    Google Scholar 

  • Lai, K. P., Ng, A. H.-M., Wan, H. T., Wong, A. Y. M., Leung, C. C. T., Li, R., et al. (2018). Dietary exposure to the environmental chemical, PFOS on the diversity of gut microbiota, associated with the development of metabolic syndrome. Frontiers in Microbiology, 9, 2552.

    Google Scholar 

  • Larrosa, M., Luceri, C., Vivoli, E., Pagliuca, C., Lodovici, M., Moneti, G., et al. (2009). Polyphenol metabolites from colonic microbiota exert anti-inflammatory activity on different inflammation models. Molecular Nutrition and Food Research, 53, 1044–1054.

    CAS  Google Scholar 

  • Lin, S., Sun, J., Marinova, D., & Zhao, D. (2017). Effects of population and land urbanization on China’s environmental impact: Empirical analysis based on the extended STIRPAT model. Sustainability, 9, 825.

    Google Scholar 

  • Lotta, L. A., Scott, R. A., Sharp, S. J., Burgess, S., Luan, J. A., Tillin, T., et al. (2016). Genetic predisposition to an impaired metabolism of the branched-chain amino acids and risk of type 2 diabetes: A Mendelian randomisation analysis. PLoS Medicine, 13, e1002179.

    Google Scholar 

  • Makrecka, M., Kuka, J., Volska, K., Antone, U., Sevostjanovs, E., Cirule, H., et al. (2014). Long-chain acylcarnitine content determines the pattern of energy metabolism in cardiac mitochondria. Molecular and Cellular Biochemistry, 395, 1–10.

    CAS  Google Scholar 

  • McMahon, T. A., Halstead, N. T., Johnson, S., Raffel, T. R., Romansic, J. M., Crumrine, P. W., et al. (2011). The fungicide chlorothalonil is nonlinearly associated with corticosterone levels, immunity, and mortality in amphibians. Environmental Health Perspectives, 119, 1098–1103.

    Google Scholar 

  • Mehmood, T., Liland, K. H., Snipen, L., & Sæbø, S. (2012). A review of variable selection methods in partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 118, 62–69.

    CAS  Google Scholar 

  • Menni, C., Graham, D., Kastenmüller, G., Alharbi, N. H., Alsanosi, S. M., McBride, M., et al. (2015). Metabolomic identification of a novel pathway of blood pressure regulation involving hexadecanedioate. Hypertension, 66, 422–429.

    CAS  Google Scholar 

  • Newgard, C. B., An, J., Bain, J. R., Muehlbauer, M. J., Stevens, R. D., Lien, L. F., et al. (2009). A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell Metabolism, 9, 311–326.

    CAS  Google Scholar 

  • Ng, S. W., Howard, A. G., Wang, H., Su, C., & Zhang, B. (2014). The physical activity transition among adults in China: 1991–2011. Obesity Reviews, 15, 27–36.

    Google Scholar 

  • Ng, S. W., & Popkin, B. M. (2012). Time use and physical activity: A shift away from movement across the globe. Obesity Reviews, 13, 659–680.

    CAS  Google Scholar 

  • Popkin, B. M., Adair, L. S., & Ng, S. W. (2012). Global nutrition transition and the pandemic of obesity in developing countries. Nutrition Reviews, 70, 3–21.

    Google Scholar 

  • Popkin, B. M., & Du, S. (3906S). Dynamics of the nutrition transition toward the animal foods sector in China and its implications: A worried perspective. The Journal of Nutrition, 133, 3898S–3906S.

    CAS  Google Scholar 

  • Popkin, B. M., Du, S., Zhai, F., & Zhang, B. (2009). Cohort Profile: The China Health and Nutrition Survey—Monitoring and understanding socio-economic and health change in China, 1989–2011. International Journal of Epidemiology, 39, 1435–1440.

    Google Scholar 

  • Rossi, L. A. (1999). Reregistration eligibility decision (RED) chlorothalonil. United States Environmental Protection Agency (EPA), Special Review and Reregistration Division (7508C).

  • Saikat, S., Kreis, I., Davies, B., Bridgman, S., & Kamanyire, R. (2013). The impact of PFOS on health in the general population: A review. Environmental Science: Processes and Impacts, 15, 329–335.

    CAS  Google Scholar 

  • Shahidi, F., & De Camargo, A. C. (2016). Tocopherols and tocotrienols in common and emerging dietary sources: Occurrence, applications, and health benefits. International Journal of Molecular Sciences, 17, 1745.

    Google Scholar 

  • Shin, J.-H., Jung, S., Kim, S.-A., Kang, M.-S., Kim, M.-S., Joung, H., et al. (2019). Differential effects of typical Korean versus American-style diets on gut microbial composition and metabolic profile in healthy overweight Koreans: A randomized crossover trial. Nutrients, 11, 2450.

    CAS  Google Scholar 

  • Storey, J. D. (2002). A direct approach to false discovery rates. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 64, 479–498.

    Google Scholar 

  • Storey, J. D., Taylor, J. E., & Siegmund, D. (2004). Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: A unified approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 66, 187–205.

    Google Scholar 

  • Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H., Beger, R., Daykin, C. A., et al. (2007). Proposed minimum reporting standards for chemical analysis. Metabolomics, 3, 211–221.

    CAS  Google Scholar 

  • Van Veldhoven, K., Kiss, A., Keski-Rahkonen, P., Robinot, N., Scalbert, A., Cullinan, P., et al. (2019). Impact of short-term traffic-related air pollution on the metabolome—Results from two metabolome-wide experimental studies. Environment International, 123, 124–131.

    Google Scholar 

  • Wang, T. J., Larson, M. G., Vasan, R. S., Cheng, S., Rhee, E. P., McCabe, E., et al. (2011). Metabolite profiles and the risk of developing diabetes. Nature Medicine, 17, 448.

    Google Scholar 

  • Yan, R., Li, W., Yin, L., Wang, Y., Bo, J., PC Investigators, et al. (2017). Cardiovascular diseases and risk-factor burden in urban and rural communities in high-, middle-, and low-income regions of China: A large community-based epidemiological study. Journal of the American Heart Association, 6, e004445.

    Google Scholar 

  • Yang, Y.-X. (2005). Chinese food composition table 2004. Beijing: Peking University Medical Press.

    Google Scholar 

  • Yao, M., Lichtenstein, A., Roberts, S., Ma, G., Gao, S., Tucker, K., et al. (2003). Relative influence of diet and physical activity on cardiovascular risk factors in urban Chinese adults. International Journal of Obesity, 27, 920.

    CAS  Google Scholar 

  • Yoneshiro, T., Wang, Q., Tajima, K., Matsushita, M., Maki, H., Igarashi, K., et al. (2019). BCAA catabolism in brown fat controls energy homeostasis through SLC25A44. Nature, 572, 614–619.

    CAS  Google Scholar 

  • Zhang, B., Du, W.-W., Wang, H., Su, C., Zhang, J., & Zhai, F. (2011). Tea and coffee consumption status and trend among 18 to 49 years old adults in 9 provinces of China. Food and Nutrition in China, 4.

  • Zhang, N. (2019). Urban–rural disparities in cardiovascular disease risks among middle-aged and older Chinese: Two decades of urbanisation. Ageing and Society. https://doi.org/10.1017/S0144686X18001794.

    Article  Google Scholar 

  • Zhang, Q., Ji, C., Yan, L., Lu, M., Lu, C., & Zhao, M. (2016). The identification of the metabolites of chlorothalonil in zebrafish (Danio rerio) and their embryo toxicity and endocrine effects at environmentally relevant levels. Environmental Pollution, 218, 8–15.

    CAS  Google Scholar 

  • Zhernakova, D. V., Le, T. H., Kurilshikov, A., Atanasovska, B., Bonder, M. J., Sanna, S., et al. (2018). Individual variations in cardiovascular-disease-related protein levels are driven by genetics and gut microbiome. Nature Genetics, 50, 1524–1532.

    CAS  Google Scholar 

  • Zhou, M., Jing, S., Wu, C.-Y., Shu, L., Dong, W., Liu, Y., et al. (2019). Targeting BCAA catabolism to treat obesity-associated insulin resistance. Diabetes, 68(9), 1730–1746.

    CAS  Google Scholar 

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Acknowledgements

We are grateful to the participants in the China Health and Nutrition Survey. We also want to thank Dr. Hsiao-Chuan Tien, Dr. Shufa Du, and Ms. Guifeng Jin for database assistance.

Funding

We are grateful to Research Grant funding from the National Institute for Health (NIH), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) for R01DK104371. We are also grateful to the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) for R01 HD30880 and the NIH Fogarty Grant D43 TW009077 for financial support for the CHNS data collection and analysis files from 1989 to 2015 and future surveys. We thank the National Institute for Nutrition and Health, China Center for Disease Control and Prevention. We are also grateful for funding from the NICHD to Carolina Population Center at the University of North Carolina at Chapel Hill (NIH Grant P2C HD050924). We are also grateful to the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through Grant Award Number UL1TR002489. Y.W. is grateful to the Sanofi Funding Award 29230-50347-466001 for educational support. M.C.B.T. is supported by Ruth L. Kirschstein National Research Service Awards (NRSA) Genetic Epidemiology of Heart, Lung, and Blood (HLB) Traits Training Grant (GenHLB, T32HL129982) funded by National Heart, Lung, and Blood Institute (NHLBI).

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Author notes

  1. Bing Zhang and Penny Gordon-Larsen have contributed equally to this work.

  2. Yiqing Wang and Wei Sha have contributed equally to this work.

Authors and Affiliations

  1. Department of Nutrition, Gillings School of Global Public Health & School of Medicine, University of North Carolina at Chapel Hill (UNC-Chapel Hill), Chapel Hill, NC, USA

    Yiqing Wang, Matthew C. B. Tsilimigras & Penny Gordon-Larsen

  2. Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC, USA

    Wei Sha & Anthony A. Fodor

  3. Department of Cancer Biostatistics, Levine Cancer Institute, Atrium Health, Charlotte, NC, USA

    Wei Sha

  4. Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China

    Huijun Wang, Jiguo Zhang, Chang Su, Zhihong Wang & Bing Zhang

  5. Carolina Population Center, UNC-Chapel Hill, Chapel Hill, NC, USA

    Annie Green Howard, Matthew C. B. Tsilimigras & Penny Gordon-Larsen

  6. Department of Biostatistics, Gillings School of Global Public Health, UNC-Chapel Hill, Chapel Hill, NC, USA

    Annie Green Howard

  7. Department of Epidemiology, Gillings School of Global Public Health, UNC-Chapel Hill, Chapel Hill, NC, USA

    Matthew C. B. Tsilimigras

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  1. Yiqing Wang
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Contributions

HW, JZ, CS, ZW, and BZ: performed data collection. YW and WS: designed study, analyzed data, and wrote the paper. AGH, AAF and MCBT: supervised data analysis and provided intellectual content to revise the manuscript. PG-L: designed study and provided intellectual content to revise the manuscript. All authors read and approved the manuscript.

Corresponding author

Correspondence to Penny Gordon-Larsen.

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The authors declare that they have no conflict of interest.

Ethical approval

The study met the standards for the ethical treatment of participants and was approved by the Institutional Review Boards of the University of North Carolina at Chapel Hill, Chinese Center for Disease Control and Prevention, and the National Institute for Nutrition and Health.

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Informed consent was obtained from all individual participants included in the study.

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Wang, Y., Sha, W., Wang, H. et al. Urbanization in China is associated with pronounced perturbation of plasma metabolites. Metabolomics 16, 103 (2020). https://doi.org/10.1007/s11306-020-01724-9

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