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. 2022 Jun 29;15(9):8185–8213. doi: 10.1007/s12274-022-4459-3

Volatolomics in healthcare and its advanced detection technology

Wenwen Hu 1,#, Weiwei Wu 2,#, Yingying Jian 2,#, Hossam Haick 3, Guangjian Zhang 4, Yun Qian 5,✉, Miaomiao Yuan 6,✉, Mingshui Yao 7,8,✉
PMCID: PMC9243817  PMID: 35789633

Abstract

Various diseases increasingly challenge the health status and life quality of human beings. Volatolome emitted from patients has been considered as a potential family of markers, volatolomics, for diagnosis/screening. There are two fundamental issues of volatolomics in healthcare. On one hand, the solid relationship between the volatolome and specific diseases needs to be clarified and verified. On the other hand, effective methods should be explored for the precise detection of volatolome. Several comprehensive review articles had been published in this field. However, a timely and systematical summary and elaboration is still desired. In this review article, the research methodology of volatolomics in healthcare is critically considered and given out, at first. Then, the sets of volatolome according to specific diseases through different body sources and the analytical instruments for their identifications are systematically summarized. Thirdly, the advanced electronic nose and photonic nose technologies for volatile organic compounds (VOCs) detection are well introduced. The existed obstacles and future perspectives are deeply thought and discussed. This article could give a good guidance to researchers in this interdisciplinary field, not only understanding the cutting-edge detection technologies for doctors (medicinal background), but also making reference to clarify the choice of aimed VOCs during the sensor research for chemists, materials scientists, electronics engineers, etc. graphic file with name 12274_2022_4459_Fig1_HTML.jpg

Keywords: volatolomics, electronic nose, disease diagnosis, sensor, artificial olfaction, volatile organic compounds

Acknowledgements

This research is supported by National Numerical Windtunnel Project (No. NNW2020ZT2-A21), Marie Sklodowska-Curie Actions: Individual Fellowship (No. H2020-MSCA-IF) [898486], Key Research and Development Program of Shaanxi (Nos. 2022ZDLSF01-04 and 2020GXLH-Y-012), the National Natural Science Foundation of China (No. 81972488), and the Shenzhen Science and Technology Program (No. JCYJ20210324115209026).

Footnotes

Wenwen Hu, Weiwei Wu, and Yingying Jian contributed equally to this work.

Contributor Information

Yun Qian, Email: qianyun1985@zju.edu.cn.

Miaomiao Yuan, Email: mingshuiyao@gmail.com.

Mingshui Yao, Email: yuanmm3@mail.sysu.edu.cn.

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