Evidence of different metabolic phenotypes in humans
Author(s) -
Michael Assfalg,
Ivano Bertini,
Donato Colangiuli,
Claudio Luchinat,
Hartmut Schäfer,
Birk Schütz,
Manfred Spraul
Publication year - 2008
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.0705685105
Subject(s) - phenotype , computational biology , metabolomics , snapshot (computer storage) , fingerprint (computing) , metabolic pathway , bioinformatics , biology , computer science , genetics , artificial intelligence , biochemistry , metabolism , gene , operating system
The study of metabolic responses to drugs, environmental changes, and diseases is a new promising area of metabonomic research. Metabolic fingerprints can be obtained by analytical techniques such as nuclear magnetic resonance (NMR). In principle, alterations of these fingerprints due to appearance/disappearance or concentration changes of metabolites can provide early evidences of, for example, onset of diseases. A major drawback in this approach is the strong day-to-day variability of the individual metabolic fingerprint, which should be rather called a metabolic "snapshot." We show here that a thorough statistical analysis performed on NMR spectra of human urine samples reveals an invariant part characteristic of each person, which can be extracted from the analysis of multiple samples of each single subject. This finding (i) provides evidence that individual metabolic phenotypes may exist and (ii) opens new perspectives to metabonomic studies, based on the possibility of eliminating the daily "noise" by multiple sample collection.
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