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Sökning: L773:0169 7439 OR L773:1873 3239 > (2020-2024) > Identification of m...

Identification of metabotypes in complex biological data using tensor decomposition

Skantze, Viktor, 1992 (författare)
Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik (FCC),Fraunhofer-Chalmers Research Centre for Industrial Mathematics (FCC),Chalmers tekniska högskola,Chalmers University of Technology
Wallman, Mikael, 1979 (författare)
Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik (FCC),Fraunhofer-Chalmers Research Centre for Industrial Mathematics (FCC)
Sandberg, Ann-Sofie, 1951 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
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Landberg, Rikard, 1981 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Jirstrand, Mats, 1968 (författare)
Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik (FCC),Fraunhofer-Chalmers Research Centre for Industrial Mathematics (FCC)
Brunius, Carl, 1974 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
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 (creator_code:org_t)
Elsevier BV, 2023
2023
Engelska.
Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier BV. - 0169-7439 .- 1873-3239. ; 233
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Differences in the physiological response to treatment, such as dietary intervention, has led to the development of precision approaches in nutrition and medicine to tailor treatment for improved benefits to the individual. One such approach is to identify metabotypes, i.e., groups of individuals with similar metabolic profiles and/or regulation. Metabotyping has previously been performed using e.g., principal component analysis (PCA) on matrix data. However, metabotyping methods suitable for more complex experimental designs such as repeated measures or cross-over studies are needed. We have developed a metabotyping method for tensor data, based on CANDECOMP/PARAFAC (CP) tensor decomposition. Metabotypes are inferred from CP scores using k-means clustering, and robustness is evaluated using bootstrapping of metabolites. As a proof-of-concept, we identified metabotypes from metabolomics data where 79 metabolites were analyzed in 8 time points postprandially in 17 overweight men that underwent a three-arm dietary crossover intervention. Two metabotypes were found, characterized by differences in amino acid metabolite concentration, that were differentially associated with baseline plasma creatinine (p = 0.007) and with the baseline metabolome (p = 0.004). These results suggest that CP decomposition provides a viable approach for metabotype identification directly from complex, high-dimensional data with improved biological interpretation compared to the more simplistic PCA approach. A simulation study together with results from measured data concluded that several preprocessing methods should be taken into consideration for CP-based metabotyping on complex tensor data.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Farmaceutiska vetenskaper (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Pharmaceutical Sciences (hsv//eng)
NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskap -- Näringslära (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Health Sciences -- Nutrition and Dietetics (hsv//eng)

Nyckelord

Metabotyping
Data mining
Multiway analysis
Personalized nutrition
Tensor decomposition

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