Relationship between gut microbiota and circulating metabolites in population-based cohorts

Gut microbiota has been implicated in major diseases affecting the human population and has also been linked to triglycerides and high-density lipoprotein levels in the circulation. Recent development in metabolomics allows classifying the lipoprotein particles into more details. Here, we examine the impact of gut microbiota on circulating metabolites measured by Nuclear Magnetic Resonance technology in 2309 individuals from the Rotterdam Study and the LifeLines-DEEP cohort. We assess the relationship between gut microbiota and metabolites by linear regression analysis while adjusting for age, sex, body-mass index, technical covariates, medication use, and multiple testing. We report an association of 32 microbial families and genera with very-low-density and high-density subfractions, serum lipid measures, glycolysis-related metabolites, ketone bodies, amino acids, and acute-phase reaction markers. These observations provide insights into the role of microbiota in host metabolism and support the potential of gut microbiota as a target for therapeutic and preventive interventions.


Supplementary Figure 2
Plot of the effect estimate and 95% confidence interval for some of the large and medium VLDL lipoprotein subfractions generated in the analysis of gut microbiota and circulating metabolites while adjusting for age, sex, BMI, medication use and multiple testing (n=2,309). The results per cohort and combined summary statistic results are shown. Blue square denotes effect estimate in the Rotterdam Study, green in LifeLines-DEEP and red in meta-analysis. The solid vertical line represents a mean difference of 0 or no effect. Source data are provided as a Source Data file.

Supplementary Figure 3
Plot of the effect estimate and 95% confidence interval for medium VLDL lipoprotein subfractions generated in the analysis of gut microbiota and circulating metabolites while adjusting for age, sex, BMI, medication use and multiple testing (n=2,309). The results per cohort and combined summary statistic results are shown. Blue square denotes effect estimate in the Rotterdam Study, green in LifeLines-DEEP and red in meta-analysis. The solid vertical line represents a mean difference of 0 or no effect. Source data are provided as a Source Data file.
Plot of the effect estimate and 95% confidence interval for small VLDL, IDL, LDL, and some of the very-large HDL lipoprotein subfractions generated in the analysis of gut microbiota and circulating metabolites while adjusting for age, sex, BMI, medication use and multiple testing (n=2,309). The results per cohort and combined summary statistic results are shown. Blue square denotes effect estimate in the Rotterdam Study, green in LifeLines-DEEP and red in meta-analysis. The solid vertical line represents a mean difference of 0 or no effect. Source data are provided as a Source Data file.

Supplementary Figure 5
Plot of the effect estimate and 95% confidence interval for very-large, large, and medium HDL subfractions generated in the analysis of gut microbiota and circulating metabolites while adjusting for age, sex, BMI, medication use and multiple testing (n=2,309). The results per cohort and combined summary statistic results are shown. Blue square denotes effect estimate in the Rotterdam Study, green in LifeLines-DEEP and red in meta-analysis. The solid vertical line represents a mean difference of 0 or no effect. Source data are provided as a Source Data file.

Supplementary Figure 6
Plot of the effect estimate and 95% confidence interval for small HDL subfractions, particle size, and some of the glycerides generated in the analysis of gut microbiota and circulating metabolites while adjusting for age, sex, BMI, medication use and multiple testing (n=2,309). The results per cohort and combined summary statistic results are shown. Blue square denotes effect estimate in the Rotterdam Study, green in LifeLines-DEEP and red in meta-analysis. The solid vertical line represents a mean difference of 0 or no effect. Source data are provided as a Source Data file.
Plot of the effect estimate and 95% confidence interval for glycerides, cholesterol, fatty and amino acids, and acute-phase reaction markers generated in the analysis of gut microbiota and circulating metabolites while adjusting for age, sex, BMI, medication use and multiple testing (n=2,309). The results per cohort and combined summary statistic results are shown. Blue square denotes effect estimate in the Rotterdam Study, green in LifeLines-DEEP and red in meta-analysis. The solid vertical line represents a mean difference of 0 or no effect. Source data are provided as a Source Data file.

Supplementary Figure 8
Plot of the effect estimate and 95% confidence interval for very-large and large VLDL lipoprotein subfractions generated in the analysis of gut microbiota and circulating additionally adjusted for smoking and alcohol (n=2,309). The results per cohort and combined summary statistic results are shown. Blue square denotes effect estimate in the Rotterdam Study, green in LifeLines-DEEP and red in meta-analysis. The solid vertical line represents a mean difference of 0 or no effect. Source data are provided as a Source Data file.

Supplementary Figure 9
Plot of the effect estimate and 95% confidence interval for some of the large and medium VLDL lipoprotein subfractions generated in the analysis of gut microbiota and circulating additionally adjusted for smoking and alcohol (n=2,309). The results per cohort and combined summary statistic results are shown. Blue square denotes effect estimate in the Rotterdam Study, green in LifeLines-DEEP and red in meta-analysis. The solid vertical line represents a mean difference of 0 or no effect. Source data are provided as a Source Data file.