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Early multiplexed detection of cirrhosis by giant magnetoresistive biosensors with protein biomarkers.
Early multiplexed detection of cirrhosis by giant magnetoresistive biosensors with protein biomarkers. ACS sensors Ng, E. n., Le, A. K., Nguyen, M. H., Wang, S. X. 2020Abstract
Liver cirrhosis is one of the leading causes of death in adults worldwide. It is highly prevalent in developing countries and is growing in prevalence in developed countries mostly due to chronic liver diseases, such as chronic hepatitis B and C, and alcoholic and nonalcoholic fatty liver disease. However, the prevalence of cirrhosis may be highly underestimated because early stages are asymptomatic and current early detection methods are inadequate. Here, we evaluate the potential of a set of novel cirrhotic protein biomarkers, including soluble intercellular adhesion molecule-1 (sICAM-1) and mac-2 binding protein glycosylation isomer (M2BPGi), for early detection of cirrhosis in a multiplexed assay using our giant magnetoresistive (GMR) sensor arrays. We evaluated the diagnostic performance of the biomarkers, individually and in combination, using multivariate logistic regression and random forest in a blinded proof-of-concept retrospective case-controlled study. The biomarkers in combination exhibited high diagnostic performance in both logistic regression and random forest models, with area under the curve (AUC) of 0.98 (0.94 - 1.00). In addition, the combination of biomarkers resulted in high sensitivity of 0.97 (0.95 - 1.00) and high specificity of 1.00. We showed that the diagnostic performance of our novel set of cirrhotic protein biomarkers on our multiplexed GMR sensor arrays is higher than the performance of currently used clinical biomarkers and factors (i.e. age, sex, alanine aminotransferase (ALT), aspartate aminotransferase (AST), etc.). With this combination of novel biomarkers and the GMR technology, we could potentially boost the diagnostic power of early cirrhosis detection.
View details for DOI 10.1021/acssensors.0c00232
View details for PubMedID 32896123