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Geographical origin differentiation of Chinese Angelica by specific metal element fingerprinting and risk assessment

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Abstract

Traceability offers significant information about the quality and safety of Chinese Angelica, a medicine and food homologous substance. In this study, a systematic four-step strategy, including sample collection, specific metal element fingerprinting, multivariate statistical analysis, and benefit-risk assessment, was developed for the first time to identify Chinese Angelica based on geographical origins. Fifteen metals in fifty-six Chinese Angelica samples originated from three provinces were analyzed. The multivariate statistical analysis model established, involving hierarchical cluster analysis (HCA), principal component analysis (PCA), and self-organizing map clustering analysis was able to identify the origins of samples. Furthermore, benefit-risk assessment models were created by combinational calculation of chemical daily intake (CDI), hazard index (HI), and cancer risk (CR) levels to evaluate the potential risks of Chinese Angelica using as traditional Chinese medicine (TCM) and food, respectively. Our systematic strategy was well convinced to accurately and effectively differentiate Chinese Angelica based on geographical origins.

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Abbreviations

TCMs:

Traditional Chinese medicines

MFHS:

Medicine and food homologous substance

ICP-MS:

Inductively coupled plasma mass spectrometry

PPRC:

Pharmacopoeia of the People’s Republic of China

SMEF:

Specific metal element fingerprinting

HCA:

Hierarchical cluster analysis (HCA)

PCA:

Principal component analysis

CDI:

Chemical daily intake

HI:

Hazard index

CR:

Lifetime cancer risk

CSF:

Cancer slope factor

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Acknowledgments

This study was supported by the National Major Scientific and Technological Special Project for “Significant New Drugs Development” (2018ZX09735006).

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Author notes

  1. Lei Sun and Xiao Ma contributed equally to this work.

Authors and Affiliations

  1. School of Pharmacy, Xi’an Jiaotong University, Xi’an, 710061, China

    Lei Sun, Hong-Yu Jin, Tian-Tian Zuo & Sicen Wang

  2. National Institutes for Food and Drug Control, No. 2 Tiantan Xili, Dongcheng District, Beijing, 100050, China

    Lei Sun, Tian-Tian Zuo & Shuang-Cheng Ma

  3. Gansu Institute for Drug Control, Lanzhou, 730070, China

    Xiao Ma

  4. Shimadzu China Innovation Center, Shimadzu (China) Co. LTD, Beijing, 100020, China

    Chang-jun Fan & Xiao-dong Li

Authors
  1. Lei Sun
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  2. Xiao Ma
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  4. Chang-jun Fan
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  5. Xiao-dong Li
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  6. Tian-Tian Zuo
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  8. Sicen Wang
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Contributions

SCM and LS designed the study. LS, TTZ, CJF, and XDL conducted the experiments. TTZ analyzed the data. LS wrote the manuscript. XM, TTZ, SCW, SCM, HYJ, LS revised the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Tian-Tian Zuo, Shuang-Cheng Ma or Sicen Wang.

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Responsible editor: Philippe Garrigues

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Highlights

• A systematic four-step strategy discriminating Chinese Angelica origins was developed.

• The multivariate statistical analysis model was able to identify the geographical origins.

• Risk assessment models evaluated the potential risks of Chinese Angelica used as both TCM and food.

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Sun, L., Ma, X., Jin, HY. et al. Geographical origin differentiation of Chinese Angelica by specific metal element fingerprinting and risk assessment. Environ Sci Pollut Res 27, 45018–45030 (2020). https://doi.org/10.1007/s11356-020-10309-x

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  • DOI: https://doi.org/10.1007/s11356-020-10309-x

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