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Near-infrared spectroscopy and chemometric modelling for rapid diagnosis of kidney disease

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Abstract

Rapid diagnosis is important for efficient treatment in clinical medicine. This study aimed at development of a method for rapid and reliable diagnosis using near-infrared (NIR) spectra of human serum samples with the help of chemometric modelling. The NIR spectra of sera from 48 healthy individuals and 16 patients with suspected kidney disease were analyzed. Discrete wavelet transform (DWT) and variable selection were adopted to extract the useful information from the spectra. Principal component analysis (PCA), linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLSDA) were used for discrimination of the samples. Classification of the two-class sera was obtained using LDA and PLSDA with the help of DWT and variable selection. DWT-LDA produced 93.8% and 83.3% of the recognition rates for the validation samples of the two classes, and 100% recognition rates were obtained using DWT-PLSDA. The results demonstrated that the tiny differences between the spectra of the sera were effectively explored using DWT and variable selection, and the differences can be used for discrimination of the sera from healthy and possible patients. NIR spectroscopy and chemometrics may be a potential technique for fast diagnosis of kidney disease.

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Acknowledgments

This study was supported by the National Natural Science Foundation of China (21475068) and MOE Innovation Team (IRT13022) of China.

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Authors and Affiliations

  1. Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin, 300071, China

    Mengli Fan, Xiuwei Liu, Xiaoyu Cui, Wensheng Cai & Xueguang Shao

  2. Laboratory of Clinic, People’s Hospital of Gaomi City, Gaomi, 261000, China

    Xiaoming Yu

  3. Tianjin Key Laboratory of Biosensing and Molecular Recognition, Tianjin, 300071, China

    Xueguang Shao

  4. State Key Laboratory of Medicinal Chemical Biology, Tianjin, 300071, China

    Xueguang Shao

  5. Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin, 300071, China

    Xueguang Shao

Authors
  1. Mengli Fan
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  2. Xiuwei Liu
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  3. Xiaoming Yu
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  4. Xiaoyu Cui
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  5. Wensheng Cai
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  6. Xueguang Shao
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Correspondence to Xueguang Shao.

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Fan, M., Liu, X., Yu, X. et al. Near-infrared spectroscopy and chemometric modelling for rapid diagnosis of kidney disease. Sci. China Chem. 60, 299–304 (2017). https://doi.org/10.1007/s11426-016-0092-6

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  • DOI: https://doi.org/10.1007/s11426-016-0092-6

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