Network-based approach for analyzing intra- and interfluid metabolite associations in human blood, urine, and saliva

Kieu Trinh Do, Gabi Kastenmüller, Dennis O. Mook-Kanamori, Noha Yousri, Fabian J. Theis, Karsten Suhre, Jan Krumsiek

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

Most studies investigating human metabolomics measurements are limited to a single biofluid, most often blood or urine. An organism's biochemical pool, however, comprises complex transboundary relationships, which can only be understood by investigating metabolic interactions and physiological processes spanning multiple parts of the human body. Therefore, we here propose a data-driven network-based approach to generate an integrated picture of metabolomics associations over multiple fluids. We performed an analysis of 2251 metabolites measured in plasma, urine, and saliva, from 374 participants of the Qatar Metabolomics Study on Diabetes (QMDiab). Gaussian graphical models (GGMs) were used to estimate metabolite-metabolite interactions on different subsets of the data set. First, we compared similarities and differences of the metabolome and the association networks between the three fluids. Second, we investigated the cross-talk between the fluids by analyzing correlations occurring between them. Third, we propose a framework for the analysis of medically relevant phenotypes by integrating type 2 diabetes, sex, age, and body mass index into our networks. In conclusion, we present a generic, data-driven network-based approach for structuring and visualizing metabolite correlations within and between multiple body fluids, enabling unbiased interpretation of metabolomics multifluid data.

Original languageEnglish
Pages (from-to)1183-1194
Number of pages12
JournalJournal of Proteome Research
Volume14
Issue number2
DOIs
Publication statusPublished - 6 Feb 2015

Fingerprint

Metabolomics
Metabolites
Saliva
Blood
Urine
Medical problems
Fluids
Qatar
Physiological Phenomena
Metabolome
Body fluids
Body Fluids
Human Body
Type 2 Diabetes Mellitus
Body Mass Index
Phenotype
Plasmas

Keywords

  • Gaussian graphical models
  • metabolomics
  • multifluid
  • multiple body fluids
  • network inference
  • partial correlation
  • type 2 diabetes

ASJC Scopus subject areas

  • Chemistry(all)
  • Biochemistry

Cite this

Network-based approach for analyzing intra- and interfluid metabolite associations in human blood, urine, and saliva. / Do, Kieu Trinh; Kastenmüller, Gabi; Mook-Kanamori, Dennis O.; Yousri, Noha; Theis, Fabian J.; Suhre, Karsten; Krumsiek, Jan.

In: Journal of Proteome Research, Vol. 14, No. 2, 06.02.2015, p. 1183-1194.

Research output: Contribution to journalArticle

Do, Kieu Trinh ; Kastenmüller, Gabi ; Mook-Kanamori, Dennis O. ; Yousri, Noha ; Theis, Fabian J. ; Suhre, Karsten ; Krumsiek, Jan. / Network-based approach for analyzing intra- and interfluid metabolite associations in human blood, urine, and saliva. In: Journal of Proteome Research. 2015 ; Vol. 14, No. 2. pp. 1183-1194.
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