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<p>Biomarkers have become crucial tools in the diagnosis, prognosis, and therapeutic monitoring of various diseases. This review focuses on the classification of biomarkers based on three core categories: (i) their characteristics, (ii) clinical applications, and (iii) relevance in genetic and molecular biology. The importance of biomarkers across diseases is emphasized, along with recent advancements in their detection. A comprehensive discussion on the biomarker development pipeline, particularly mass spectrometry (MS)-based biomarker discovery, validation, and verification, is presented. The article also delves into MS-based techniques used for the detection of disease biomarkers such as Alzheimer’s, hepatocellular carcinoma, ovarian cancer, kidney diseases, diabetes and tuberculosis, as well as highlighting recent research. Finally, the review explores future perspectives on biomarker discovery and detection, focusing on the evolving role of MS in advancing biomarker science and its application in clinical and research settings. In each disease area, we provide an important review of the limitations in individual studies. We also outline new solutions that use mass spectrometry to fill gaps in analysis and translation for biomarker development.</p>

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Biomarkers in Disease Diagnosis and Monitoring: Insights into Clinical Applications and Mass Spectrometry-based Detection

  • 期刊论文

  • 发表日期：

    2026年1月3日

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  • Shibam Das,
  • Ankit Awasthi,
  • Ravindra Kumar Rawal,
  • Rohit Bhatia

摘要

Biomarkers have become crucial tools in the diagnosis, prognosis, and therapeutic monitoring of various diseases. This review focuses on the classification of biomarkers based on three core categories: (i) their characteristics, (ii) clinical applications, and (iii) relevance in genetic and molecular biology. The importance of biomarkers across diseases is emphasized, along with recent advancements in their detection. A comprehensive discussion on the biomarker development pipeline, particularly mass spectrometry (MS)-based biomarker discovery, validation, and verification, is presented. The article also delves into MS-based techniques used for the detection of disease biomarkers such as Alzheimer’s, hepatocellular carcinoma, ovarian cancer, kidney diseases, diabetes and tuberculosis, as well as highlighting recent research. Finally, the review explores future perspectives on biomarker discovery and detection, focusing on the evolving role of MS in advancing biomarker science and its application in clinical and research settings. In each disease area, we provide an important review of the limitations in individual studies. We also outline new solutions that use mass spectrometry to fill gaps in analysis and translation for biomarker development.