Journal Article

DZNE-2025-01106

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Integrating population-based metabolomics with computational microbiome modelling identifies methanol as a urinary biomarker for protective diet-microbiome-host interactions.

Klier, K. ; Mehrjerd, A. ; Fässler, D. ; Franck, M. ; Weihs, A.DZNE* ; Budde, K. ; Bahls, M. ; Frost, F. ; Henning, A.-K. ; Heinken, A. ; Völzke, H. ; Dörr, M. ; Nauck, M. ; Grabe, H. J.DZNE* ; Friedrich, N. ; Hertel, J.

2025
RSC Cambridge

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Please use a persistent id in citations: doi:10.1039/D5FO00761E

Abstract: Background: Diet-microbiome interactions are core to human health, in particular through bacterial fibre degradation pathways. However, biomarkers reflective of these interactions are not well described. Methods: Using the population-based SHIP-START-0 cohort (n = 4017), we combined metabolome-wide screenings with elastic net machine learning models on 33 food items captured using a food frequency questionnaire (FFQ) and 43 targeted urine nuclear magnetic resonance (NMR) metabolites, identifying methanol as a marker of plant-derived food items. We utilised the independent SHIP-START-0 cohort for the replication of food-metabolite associations. Moreover, constraint-based microbiome community modelling using the Human Microbiome data (n = 149) was performed to predict and analyse the contribution of the microbiome to the human methanol pools through bacterial fibre degradation. Finally, we employed prospective survival analysis in the SHIP-START-0 cohort, testing urinary methanol on its predictive value for mortality. Results: Among 21 metabolites associated with 17 dietary FFQ variables after correction for multiple testing, urinary methanol emerged as the top hit for a range of plant-derived food items. In line with this, constraint-based community modelling demonstrated that gut microbiomes can produce methanol via pectin degradation with the genera Bacteroides (68.9%) and Faecalibacterium (20.6%) being primarily responsible. Moreover, microbial methanol production capacity was a marker of high microbiome diversity. Finally, prospective survival analysis in SHIP-START-0 revealed that higher urinary methanol is associated with lower all-cause mortality in fully adjusted Cox regressions. Conclusion: Integrating population-based metabolomics and computational microbiome modelling identified urinary methanol as a promising biomarker for protective diet-microbiome interactions linked to microbial pectin degradation.

Keyword(s): Humans (MeSH) ; Biomarkers: urine (MeSH) ; Methanol: urine (MeSH) ; Methanol: metabolism (MeSH) ; Metabolomics (MeSH) ; Male (MeSH) ; Gastrointestinal Microbiome: physiology (MeSH) ; Female (MeSH) ; Middle Aged (MeSH) ; Diet (MeSH) ; Adult (MeSH) ; Host Microbial Interactions (MeSH) ; Aged (MeSH) ; Biomarkers ; Methanol

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Contributing Institute(s):

1. Translational Health Care Research (AG Hoffmann)
2. Biomarkers of Dementia in the General Population (AG Grabe)

Research Program(s):

1. 353 - Clinical and Health Care Research (POF4-353) (POF4-353)

Appears in the scientific report 2025

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Database coverage:
; ; ; Clarivate Analytics Master Journal List ; Essential Science Indicators ; IF >= 5 ; JCR ; National-Konsortium ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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