Clinical Proteomics

Abstract

Clinical proteomics involves the analysis of protein expression of disease proteomes, with the aim of solving a specific clinical problem. Discoveries made from proteomicbased studies contribute to the growing need for innovative medical diagnostics for disease detection. Taking into consideration the global health burden of cardiac disease, clinical proteomics is a valuable tool to improve risk stratification associated with this disease. In cardiovascular medicine, the identification of novel proteins, or biomarkers, that are differentially expressed in cardiac disease proteomes may enable early detection of the disease state, thereby preventing progression to disease end points. This review outlines various proteomic platforms and their technical advancements and relates these to the cardiovascular sciences. The entire protein complement of the cell, or proteome, is dynamic and changes in response to the disease state. 1 Proteomic-based experiments can be used to characterize such alterations in protein expression during disease progression. 2 With combined improvements in mass spectrometry (MS) technology as well as innovative molecular biology screening tools, there has been widespread growth in the characterization of cardiac disease proteomes. In fact, proteomic technology has been an important tool in the analysis of heart failure (HF), 3,4 cardiac hypertrophy, 5,6 and dilated cardiomyopathy.7 Several of the overarching aims of such studies include providing greater understanding of general biological mechanisms as well as identifying unique proteins that are clinically useful in the detection of cardiac disease in the early stages or potentially used as novel therapeutic targets. Clinical proteomics continues to benefit from advancements in technologies that allow for fast and consistent identification of proteins with corresponding increases in the dynamic range of proteins detectable in the disease proteome. MS-related technologies have improved in their ability to detect low-abundance proteins as well as membrane proteins and have benefited from sample preprocessing strategies that decrease the complexity of large-scale analyses. With the emergence of different methodologies for biomarker identification, the following 3 criteria must be taken into careful consideration to determine whether the protein is, in fact,