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<p>Metabolomics, based on laser desorption/ionization mass spectrometry (LDI-MS), has been successfully utilized for the high-throughput metabolic analysis of biofluids. This technique shows great promises as a powerful tool for disease screening. Although various nanomaterials have been developed as alternatives to traditional organic matrices in LDI-MS, the signals of most metabolites are limited due to their low abundance in complex biofluids. Herein, four hydroxyl-functionalized covalent organic frameworks (COFs) were designed as substrates for LDI-MS, named COF-OH-<i>n</i> (<i>n</i> = 0–3, demonstrating the number of hydroxyl units). Since hydroxyl groups can facilitate proton transfer and promote the ionization process effectively, hydroxyl-rich COF-OH-2 enabled sensitive and efficient LDI-MS analysis of serum directly, resulting in highly reproducible serum metabolic profiles (SMPs). An orthogonal partial least squares discriminant analysis (OPLS-DA) model was successfully used to distinguish 30 gout patients from 38 healthy volunteers, with an area under the curve (AUC) of 0.974. Furthermore, the roles of 12 biomarker candidates, which were characterised following statistical analysis, in the metabolic pathway of gout were initially explored. Furthermore, the roles of 12 biomarker candidates, which were characterized following statistical analysis, in the metabolic pathway of gout were initially explored. This work demonstrates the potential of COF-OH-2-assisted LDI-MS in clinical metabolic analysis and offers a rational design strategy for advanced LDI-MS substrates.</p>

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Hydroxyl-Functionalized Covalent Organic Framework Assisted Laser Desorption/Ionization Mass Spectrometry-Based Direct Serum Metabolic Profiling for Gout Screening

  • 期刊论文

  • 发表日期：

    2025年11月22日

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  • Jiajing Chen,
  • Juan Lin,
  • Dan Ouyang,
  • Zian Lin

摘要

Metabolomics, based on laser desorption/ionization mass spectrometry (LDI-MS), has been successfully utilized for the high-throughput metabolic analysis of biofluids. This technique shows great promises as a powerful tool for disease screening. Although various nanomaterials have been developed as alternatives to traditional organic matrices in LDI-MS, the signals of most metabolites are limited due to their low abundance in complex biofluids. Herein, four hydroxyl-functionalized covalent organic frameworks (COFs) were designed as substrates for LDI-MS, named COF-OH-n (n = 0–3, demonstrating the number of hydroxyl units). Since hydroxyl groups can facilitate proton transfer and promote the ionization process effectively, hydroxyl-rich COF-OH-2 enabled sensitive and efficient LDI-MS analysis of serum directly, resulting in highly reproducible serum metabolic profiles (SMPs). An orthogonal partial least squares discriminant analysis (OPLS-DA) model was successfully used to distinguish 30 gout patients from 38 healthy volunteers, with an area under the curve (AUC) of 0.974. Furthermore, the roles of 12 biomarker candidates, which were characterised following statistical analysis, in the metabolic pathway of gout were initially explored. Furthermore, the roles of 12 biomarker candidates, which were characterized following statistical analysis, in the metabolic pathway of gout were initially explored. This work demonstrates the potential of COF-OH-2-assisted LDI-MS in clinical metabolic analysis and offers a rational design strategy for advanced LDI-MS substrates.