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CASI CLINICI – Case Reports

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Biochimica Clinica 2013; 37(5) 419-427

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Metabolomica e scoperta di biomarcatori cardiovascolari

AUTORI

Eugene P. Rhee1,3, Robert E. Gerszten2,3
1Nephrology Division and 2Cardiology Division and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
3Broad Institute, Cambridge, MA, USA

ABSTRACT

Metabolomics and Cardiovascular Biomarker Discovery

Metabolomics, the systematic analysis of low MW biochemical compounds in a biological specimen, has been increasingly applied to biomarker discovery. Because no single analytical method can accommodate the chemical diversity of the entire metabolome, various methods such as nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) have been employed, with the latter coupled to an array of separation techniques including gas and liquid chromatography. Whereas NMR can provide structural information and absolute quantification for select metabolites without the use of exogenous standards, MS tends to have much higher analytical sensitivity, enabling broader surveys of the metabolome. Both NMR and MS can be used to characterize metabolite data either in a targeted manner or in a nontargeted, pattern-recognition manner. In addition to technical considerations, careful sample selection and study design are important to minimize potential confounding influences on the metabolome, including diet, medications, and comorbitidies. To this end, metabolite profiling has been applied to human biomarker discovery in small-scale interventions, in which individuals are extremely well phenotyped and able to serve as their own biological controls, as well as in larger epidemiological cohorts. Understanding how metabolites relate to each other and to established risk markers for diseases such as diabetes and renal failure will be important in evaluating the potential value of these metabolites as clinically useful biomarkers. Applied to both experimental and epidemiological study designs, metabolite profiling has begun to highlight the breadth metabolic disturbances that accompany human disease. Experimental work in model systems and integration with other functional genomic approaches will be required to establish a causal link between select biomarkers and disease pathogenesis.

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