Title |
Metabolomics: moving towards personalized medicine
|
---|---|
Published in |
Italian Journal of Pediatrics, October 2009
|
DOI | 10.1186/1824-7288-35-30 |
Pubmed ID | |
Authors |
Eugenio Baraldi, Silvia Carraro, Giuseppe Giordano, Fabiano Reniero, Giorgio Perilongo, Franco Zacchello |
Abstract |
In many fields of medicine there is a growing interest in characterizing diseases at molecular level with a view to developing an individually tailored therapeutic approach. Metabolomics is a novel area that promises to contribute significantly to the characterization of various disease phenotypes and to the identification of personal metabolic features that can predict response to therapies. Based on analytical platforms such as mass spectrometry or NMR-based spectroscopy, the metabolomic approach enables a comprehensive overview of the metabolites, leading to the characterization of the metabolic fingerprint of a given sample. These metabolic fingerprints can then be used to distinguish between different disease phenotypes and to predict a drug's effectiveness and/or toxicity.Several studies published in the last few years applied the metabolomic approach in the field of pediatric medicine. Being a highly informative technique that can be used on samples collected non-invasively (e.g. urine or exhaled breath condensate), metabolomics has appeal for the study of pediatric diseases. Here we present and discuss the pediatric clinical studies that have taken the metabolomic approach. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Spain | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Italy | 1 | <1% |
Unknown | 112 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 25 | 22% |
Researcher | 25 | 22% |
Student > Master | 10 | 9% |
Student > Doctoral Student | 8 | 7% |
Student > Postgraduate | 6 | 5% |
Other | 19 | 17% |
Unknown | 20 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 24 | 21% |
Agricultural and Biological Sciences | 21 | 19% |
Chemistry | 18 | 16% |
Biochemistry, Genetics and Molecular Biology | 8 | 7% |
Computer Science | 4 | 4% |
Other | 17 | 15% |
Unknown | 21 | 19% |