Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2008-6-4
pubmed:abstractText
Little is known about the human intra-individual metabolic profile changes over an extended period of time. Here, we introduce a novel concept suggesting that children even at a very young age can be categorized in terms of metabolic state as they advance in development. The hidden Markov models were used as a method for discovering the underlying progression in the metabolic state. We applied the methodology to study metabolic trajectories in children between birth and 4 years of age, based on a series of samples selected from a large birth cohort study. We found multiple previously unknown age- and gender-related metabolome changes of potential medical significance. Specifically, we found that the major developmental state differences between girls and boys are attributed to sphingolipids. In addition, we demonstrated the feasibility of state-based alignment of personal metabolic trajectories. We show that children have different development rates at the level of metabolome and thus the state-based approach may be advantageous when applying metabolome profiling in search of markers for subtle (patho)physiological changes.
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-11317658, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-11872662, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-12809995, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-15087313, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-15450501, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-15533678, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-15722563, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-15821725, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-15890747, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-16002999, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-16403790, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-16478464, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-16824031, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-16904954, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-17183729, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-17234128, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-17411081, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-17929959, http://linkedlifedata.com/resource/pubmed/commentcorrection/18523432-3999932
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1744-4292
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
4
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
197
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Gender-dependent progression of systemic metabolic states in early childhood.
pubmed:affiliation
Department of Information and Computer Science, Adaptive Informatics Research Centre and Helsinki Institute for Information Technology, Helsinki University of Technology, Espoo, Finland.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't