TY  - JOUR
AU  - Klier, Kristin
AU  - Mehrjerd, Ameneh
AU  - Fässler, Daniel
AU  - Franck, Maximilien
AU  - Weihs, Antoine
AU  - Budde, Kathrin
AU  - Bahls, Martin
AU  - Frost, Fabian
AU  - Henning, Ann-Kristin
AU  - Heinken, Almut
AU  - Völzke, Henry
AU  - Dörr, Marcus
AU  - Nauck, Matthias
AU  - Grabe, Hans Jörgen
AU  - Friedrich, Nele
AU  - Hertel, Johannes
TI  - Integrating population-based metabolomics with computational microbiome modelling identifies methanol as a urinary biomarker for protective diet-microbiome-host interactions.
JO  - Food & function
VL  - 16
IS  - 18
SN  - 2042-6496
CY  - Cambridge
PB  - RSC
M1  - DZNE-2025-01106
SP  - 7067 - 7081
PY  - 2025
AB  - 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
KW  - Humans
KW  - Biomarkers: urine
KW  - Methanol: urine
KW  - Methanol: metabolism
KW  - Metabolomics
KW  - Male
KW  - Gastrointestinal Microbiome: physiology
KW  - Female
KW  - Middle Aged
KW  - Diet
KW  - Adult
KW  - Host Microbial Interactions
KW  - Aged
KW  - Biomarkers (NLM Chemicals)
KW  - Methanol (NLM Chemicals)
LB  - PUB:(DE-HGF)16
C6  - pmid:40856313
DO  - DOI:10.1039/D5FO00761E
UR  - https://pub.dzne.de/record/281359
ER  -