Rapid monitoring of T- lymphocyte CD4+/CD8+ ratio in patient immune management by infrared spectroscopy of whole leukocytes

  • Leiying Xie
  • , Na Wang
  • , Qianqian Yin
  • , Xiaoming Zhang
  • , Lei Chen
  • , Changning Hao
  • , Tingting Liu*
  • , Shaowei Wang*
  • , Junli Duan
  • , Kun Du
  • , Md Dulal Haque
  • , Xuechu Shen
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

As an essential indicator of human immune status, the T- lymphocyte CD4+/CD8+ ratio can be used to monitor the progression of diverse pathological status, assess the effectiveness of treatment and prognosis. Unfortunately, the conventional method for detecting the T- lymphocyte CD4+/CD8+ ratio is time-consuming and costly. Here, the Fourier transform infrared (FTIR) spectroscopy analysis method was applied to 52 clinical samples of varying immune statuses, revealing the nature of changes in immune status. A fitted model was built using FTIR spectroscopy based on fluorescence activated cell sorting (FACS), providing a correlation formula between the concentration of leukocyte subpopulations and the corresponding infrared spectrum. It was shown that the T- lymphocyte CD4+/CD8+ ratio can be identified from the spectral features of whole leukocyte populations using the principal component analysis- linear discriminant analysis (PCA-LDA) model. To this end, it has been demonstrated that the parameter of β-sheets/α-helix can separate sample sets in normal immune status with 100 % specificity and in abnormal immune status with 92 % sensitivity successfully by fitting protein secondary structures. It's an effective way to rapidly monitor T- lymphocyte CD4+/CD8+ ratio in patient immune management, which improves the effectiveness of clinical decision-making of treatment response. This way may serve as the basis for subsequent direct blood testing, and may be potentially utilized by hospitals in the future.

Original languageEnglish
Article number111070
JournalMicrochemical Journal
Volume204
DOIs
StatePublished - Sep 2024
Externally publishedYes

Keywords

  • Immune management
  • Infrared spectrum
  • Machine learning
  • Rapid detection

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