PURPOSE OF REVIEW: To highlight the usefulness of amino acid profiling in clinical diagnosis and current developments in analysis revealing underlying metabolic relationships. RECENT FINDINGS: Recent innovations in metabolomics and systems biology enable high throughput measurement of diverse amino acids and the subsequent data mining for various uses. Recent studies show new possibilities of using plasma amino acid analysis as biomarker discovery tools by generating diagnostic indices through systematic computation. Such studies show that amino acid-based clinical diagnostic indices for hepatic fibrosis in type C hepatitis patients can be generated. In addition, several studies show the potential of treating amino acid profile data as a metabolomic subset, which can be integrated through the analysis of correlation with different types of 'omics' data for describing metabolite-to-metabolite or metabolite-to-gene interaction networks. CONCLUSION: Amino acid profiling of biological samples could be used to generate indices that could be used for clinical diagnosis and is a useful tool for understanding metabolic implications under various physiological conditions. Although further improvements in analytical methods are needed, amino acids could be useful indicators for facilitating nutritional management of specific physiological and pathological states.
PURPOSE OF REVIEW: To highlight the usefulness of amino acid profiling in clinical diagnosis and current developments in analysis revealing underlying metabolic relationships. RECENT FINDINGS: Recent innovations in metabolomics and systems biology enable high throughput measurement of diverse amino acids and the subsequent data mining for various uses. Recent studies show new possibilities of using plasma amino acid analysis as biomarker discovery tools by generating diagnostic indices through systematic computation. Such studies show that amino acid-based clinical diagnostic indices for hepatic fibrosis in type C hepatitispatients can be generated. In addition, several studies show the potential of treating amino acid profile data as a metabolomic subset, which can be integrated through the analysis of correlation with different types of 'omics' data for describing metabolite-to-metabolite or metabolite-to-gene interaction networks. CONCLUSION: Amino acid profiling of biological samples could be used to generate indices that could be used for clinical diagnosis and is a useful tool for understanding metabolic implications under various physiological conditions. Although further improvements in analytical methods are needed, amino acids could be useful indicators for facilitating nutritional management of specific physiological and pathological states.