Ultra‐Fast Label‐Free Serum Metabolic Diagnosis of Coronary Heart Disease via a Deep Stabilizer

Abstract

Abstract Although mass spectrometry (MS) of metabolites has the potential to provide real‐time monitoring of patient status for diagnostic purposes, the diagnostic application of MS is limited due to sample treatment and data quality/reproducibility. Here, the generation of a deep stabilizer for ultra‐fast, label‐free MS detection and the application of this method for serum metabolic diagnosis of coronary heart disease (CHD) are reported. Nanoparticle‐assisted laser desorption/ionization‐MS is used to achieve direct metabolic analysis of trace unprocessed serum in seconds. Furthermore, a deep stabilizer is constructed to map native MS results to high‐quality results obtained by established methods. Finally, using the newly developed protocol and diagnosis variation characteristic surface to characterize sensitivity/specificity and variation, CHD is diagnosed with advanced accuracy in a high‐throughput/speed manner. This work advances design of metabolic analysis tools for disease detection as it provides a direct label‐free, ultra‐fast, and stabilized platform for future protocol development in clinics.

Keywords

• deep learning
• diagnostics
• coronary heart diseases
• mass spectrometry
• metabolites