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The early detection of asthma based on blood gene expression

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Abstract

Asthma is a complex heterogeneous disorder with hereditary tendency and the most widely used therapy is inhalation of anti-inflammatory corticosteroids. But it has systemic side effects. If the chronic inflammation can be detected in early stage, the dosage of corticosteroids will be low and the side effects can be avoided. Therefore, to discover the early stage blood biomarkers for asthma, we analyzed the gene expression profiles in the blood of 77 moderate asthma patients and 87 healthy controls. With advanced feature selection methods, minimal Redundancy Maximal Relevance and Incremental Feature Selection, we identified 31 genes, such as MYD88, ZFP36, CCR3 and CYP3A5, as the optimal asthma biomarker. The sensitivity, specificity and accuracy of the 31-gene Support Vector Machine predictor evaluated with Leave-One-Out Cross Validation were 0.870, 0.816 and 0.841, respectively. Through literature survey, many biomarker genes have asthma associated functions. Our results not only provided the easy-to-apply blood gene expression biomarkers for early detection of asthma, but also an explainable qualitative model with biological significance.

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Acknowledgements

This study is supported by The Key Science-Technology Innovation Team of Zhejiang Province (2011R50016), National Natural Science Foundation of China (31701151), Shanghai Sailing Program (16YF1413800) and The Youth Innovation Promotion Association of Chinese Academy of Sciences (2016245).

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Authors and Affiliations

  1. Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China

    Shao-Bin Wang

  2. Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China

    Tao Huang

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  1. Shao-Bin Wang
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  2. Tao Huang
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Correspondence to Shao-Bin Wang or Tao Huang.

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Wang, SB., Huang, T. The early detection of asthma based on blood gene expression. Mol Biol Rep 46, 217–223 (2019). https://doi.org/10.1007/s11033-018-4463-6

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