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Current Chemical Biology


ISSN (Print): 2212-7968
ISSN (Online): 1872-3136

Mini-Review Article

Serum Biomarkers for Noninvasive Diagnosis of Liver Diseases: How Laudable are These Tools?

Author(s): Ankita Singh, Vipul Ranjan, Rina Das*, Karun Bhatti, Dinesh Kumar Mehta and Ram Mohan Chidurala

Volume 15, Issue 2, 2021

Published on: 11 November, 2020

Page: [128 - 138] Pages: 11

DOI: 10.2174/2212796814999201111204639

Price: $65


Innumerable reasons have been reported that affect and infect the liver and cause liver diseases. The evaluation and follow-up of liver fibrosis and cirrhosis have been traditionally performed by liver biopsy. However, it has become evident that this once defined as “gold-standard” is now not the best method as it involves many limitations. Attempts to reveal non-invasive diagnostic tools have generated serum biomarkers, multiple scores, formulae, and imaging modalities. All are better tolerated, safer, more acceptable to the patient, and are less expensive than a liver biopsy. Biomarkers have various advantages like minimally invasive, easy to apply with great availability and easier reproducibility, useful for monitoring therapy and less expensive. But then, direct biomarkers involved in extracellular matrix turnover need further validation in different geographic population and indirect biomarkers may not predict early pathophysiological changes in liver parenchyma. The accuracy and diagnostic value of most, if not all, of these biomarkers remain controversial. Hence, there is a need for a biomarker that is specific for the liver and can identify the magnitude of the clinical outcome of the disease.

In this review, we discuss the clinical utility, limitations, and development of noninvasive biomarkers in their use as diagnostic and prognostic tests and analyze whether the present known serum biomarkers are laudable and accurate tools for the diagnosis of liver diseases.

Keywords: Biomarkers, direct biomarkers, indirect biomarkers, liver diseases, non-invasive, liver diseases.

Graphical Abstract
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