dc.contributor.author | Paolucci, Ugo | |
dc.contributor.author | Vigneau-Callahan, Karen E. | |
dc.contributor.author | Shi, Honglian | |
dc.contributor.author | Matson, Wayne R. | |
dc.contributor.author | Kristal, Bruce S. | |
dc.date.accessioned | 2012-05-16T19:58:04Z | |
dc.date.available | 2012-05-16T19:58:04Z | |
dc.date.issued | 2004 | |
dc.identifier.citation | Paolucci U, Vigneau-Callahan KE, Shi H, Shestopalov AI, Milbury PE, Matson WR, and Kristal BS. Development of biomarkers based on diet-dependent metabolic serotypes: characteristics of component-based models of metabolic serotypes. OMICS J Integr Biol 8 (3): 221-238; 2004. | |
dc.identifier.uri | http://hdl.handle.net/1808/9577 | |
dc.description | This is the publisher's version, also available electronically from: http://online.liebertpub.com/doi/pdfplus/10.1089/omi.2004 | |
dc.description.abstract | Our research seeks to identify a scrum profile, or serotype, that reflects the systemic physiologic
modifications resultant from dietary restriction (DR), in part such that this knowledge
can be applied for biomarker studies. Direct comparison suggests that component-based
classification algorithms consistently out-perform distance-based metrics for studies of nutritional
modulation of metabolic serotype, but are subject to over-fitting concerns. Intercohort
differences in the sera metabolome could partially obscure the effects of DR. Further
analysis now shows that implementation of component-based approaches (also called projection
methods) optimized for class separation and controlled for over-fitting have >97%
accuracy for distinguishing sera from control or DR rats. DR's effect on the metabolome is
shown to be robust across cohorts, but differs in males and females (although some metabolites
are affected in both). We demonstrate the utility of projection-based methods for both
sample and variable diagnostics, including identification of critical metabolites and samples
that are atypical with respect to both class and variable models. Inclusion of non-statistically
different variables enhances classification models. Variables that contribute to these
models are sharply dependent on mathematical processing techniques; some variables that
do not contribute under one paradigm arc powerful under alternative mathematical paradigms.
In practical terms, this information may find purpose in other endeavors, such as
mechanistic studies of DR. Application of these approaches confirms the utility of megavariate
data analysis techniques for optimal generation of biomarkers based on nutritional modulation
of physiological processes. | |
dc.language.iso | en | |
dc.publisher | Mary Ann Liebert, Inc. | |
dc.title | Development of Biomarkers Based on Diet-Dependent Metabolic Serotypes: Characteristics of Component-Based Models of Metabolic Serotypes | |
dc.type | Article | |
kusw.kuauthor | Shi, Honglian | |
kusw.kudepartment | Pharmacology and Toxicology | |
kusw.oastatus | fullparticipation | |
dc.identifier.doi | 10.1089/omi.2004.8.221 | |
kusw.oaversion | Scholarly/refereed, publisher version | |
kusw.oapolicy | This item meets KU Open Access policy criteria. | |
dc.rights.accessrights | openAccess | |