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To evaluate early disease diagnosis, disease progression, medication response, disease prevention, and therapeutic target selection, biomarker discovery is a crucial tool. It is of paramount clinical importance to identify biomarkers using various detection techniques and to characterize these biomarkers. The combination of proteomics, metabolomics, LC-MS, and NMR holds great promise for the easy identification of biomarkers by mapping the early biochemical alterations in illnesses. Analyzing a complex biological system calls for a robust and intelligent method. As a result of its adaptability, clarity, accuracy, speed, and increased productivity, LC-MS has become the gold standard approach for biomarker research. Proteins and nucleic acids are examples of big molecules that have been studied using the same approach. NMR spectroscopy enables the nondestructive detection and measurement of a vast array of novel metabolite biomarkers in biological fluids and tissues. Thus, NMR & LC-MS-based metabolomics are a huge help in illness diagnosis and biomarker identification.
This article discusses the present function of LC-MS and NMR in developing biomarkers for disease diagnosis and strategies for identifying biomarkers in various diseases.
The methodology employed is based on the extraction of data (2002-2024) from various databases such as PubMed, Google Scholar, Web of Science, and Google with strict inclusion and exclusion criteria.
Drug discovery, early disease diagnosis, and the identification of impaired metabolic reactions have all been made more efficient by merging mass spectrometry and 1H NMR spectroscopic studies with comprehensive statistical data analysis.
Emerging high-throughput technologies for biomarker detection in disease diagnostics are the subject of this review. To improve therapy and illness prevention, personalization will be essential.
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