Integrating population-based metabolomics with computational microbiome modelling identifies methanol as a urinary biomarker for protective diet–microbiome–host interactions

<i>Background</i>: 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. <i>Methods</i>: Using the population-based SHIP-START-0 cohort (<i>n</i> = 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 (<i>n</i> = 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. <i>Results</i>: 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 <i>via</i> pectin degradation with the genera <i>Bacteroides</i> (68.9%) and <i>Faecalibacterium</i> (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. <i>Conclusion</i>: 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.