Analysis of metabolomics data from twin families

Leiden Repository

Analysis of metabolomics data from twin families

Type: Doctoral Thesis
Title: Analysis of metabolomics data from twin families
Author: Draisma, Hermanus Henricus Maria
Publisher: Division of Analytical Biosciences, Leiden/Amsterdam Center for Drug Research (LACDR), Faculty of Science, Leiden University
Issue Date: 2011-05-10
Keywords: Metabolomics
Twin study
Batch effects
Quantitative genetic analysis
Systems biology
Structural equation modeling
Analytical chemistry
Abstract: Metabolomics is the comprehensive analysis of small molecules involved in metabolism, on the basis of samples that have been obtained from organisms in a given physiological state. Data obtained from measurements of trait levels in twin families can be used to elucidate the importance of genetic and environmental variation for individual differences in trait levels. I describe the results of various analyses using metabolomics data from twin families. These data originated from analysis of blood plasma lipids by liquid chromatography-mass spectrometry, and from analysis of blood plasma and urine by proton nuclear magnetic resonance spectroscopy. Data analyses with a newly developed method, based on hierarchical clustering analysis of family members, suggested that shared genetic variation and shared environmental variation are important for similarities in blood plasma lipid profiles among individuals. Also, a method called “quantile equating” was developed and applied that enables combination of semiquantitative metabolomics data sets originating from different measurement “blocks”. Univariate quantitative genetic analyses based on structural equation modeling revealed interesting differences in heritability among different metabolites. In multivariate analysis, relationships among genetic sources of phenotypic variation in different metabolites were investigated. These results bear relevance for the interpretation of the results from genome-wide association analyses.
Description: Promotores: J. van der Greef, T. Hankemeier, J.J. Meulman, Co-promotor: T.H. Reijmers
With Summary in Dutch
Faculty: Faculteit der Wiskunde en Natuurwetenschappen
Citation: Draisma, H.H.M., 2011, Doctoral Thesis, Leiden University
ISBN: 9789074538756
Sponsor: Netherlands Bioinformatics Centre (NBIC)

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