Generally-healthy individuals with aberrant bowel movement frequencies show enrichment for microbially-derived blood metabolites associated with reduced kidney function

Abstract

Bowel movement frequency (BMF) has been linked to changes in the composition of the human gut microbiome and to many chronic conditions, like metabolic disorders, neurodegenerative diseases, chronic kidney disease (CKD), and other intestinal pathologies like irritable bowel syndrome and inflammatory bowel disease. Lower BMF (constipation) can lead to compromised intestinal barrier integrity and a switch from saccharolytic to proteolytic fermentation within the microbiota, giving rise to microbially-derived toxins that may make their way into circulation and cause damage to organ systems. However, the connections between BMF, gut microbial metabolism, and the early-stage development and progression of chronic disease remain underexplored. Here, we examined the phenotypic impact of BMF variation in a cohort of generally-healthy, community dwelling adults with detailed clinical, lifestyle, and multi-omic data. We showed significant differences in microbially-derived blood plasma metabolites, gut bacterial genera, clinical chemistries, and lifestyle factors across BMF groups that have been linked to inflammation, cardiometabolic health, liver function, and CKD severity and progression. We found that the higher plasma levels of 3-indoxyl sulfate (3-IS), a microbially-derived metabolite associated with constipation, was in turn negatively associated with estimated glomerular filtration rate (eGFR), a measure of kidney function. Causal mediation analysis revealed that the effect of BMF on eGFR was significantly mediated by 3-IS. Finally, we identify self-reported diet, lifestyle, and psychological factors associated with BMF variation, which indicate several common-sense strategies for mitigating constipation and diarrhea. Overall, we suggest that aberrant BMF is an underappreciated risk factor in the development of chronic diseases, even in otherwise healthy populations.

Figure 1.. Data collection strategy.

Arivale participants were sampled for blood plasma and stool, in addition to filling out extensive diet, health, and lifestyle questionnaires. Clinical chemistries, untargeted metabolomics, and proteomics data were generated from blood plasma samples. Gut microbiome 16S rRNA amplicon sequencing data were generated from stool samples collected using at-home kits. BMF data were extracted from the questionnaire data as self-reported frequencies per week or day.

Figure 2.. Plotting covariates that showed a significant association with BMF: sex, age, BMI, and the first three principal components of genetic ancestry (PC1-PC3)

(A-F). POLR was used to regress BMF against the covariates (sex, age, BMI, eGFR, LDL, CRP, A1C, plus the first three principal components of genetic ancestry in the cohort, PC1, PC2, PC3). The result was that sex (p = 3.68E-16), BMI (p = 1.82E-3), age (p = 2.075E-3), and PCs1–3 (p < 0.00001, respectively) were significantly associated with BMF.

Figure 3.. Associations between gut microbiome alpha-diversity and BMF.

(A) Richness of amplicon sequence variants (ASVs) across BMF categories (ordinal BMF variable, Linear Regression, p = 2.85E-3). (B) Shannon Diversity across BMF categories (ordinal BMF variable, Linear Regression, p = 1.07E-3). (C) Pielou’s Evenness across BMF categories (ordinal BMF variable, Linear Regression, p = 8.5E-2).

Figure 4.. Heatmap of average z-scored CLR abundances within each BMF category for all annotated genera significantly associated with BMF.

46 significant taxa, in order of decreasing average relative abundance, with their z-scored, CLR-transformed abundances averaged within each BMF category plotted as a heatmap. Covariates included sex, age, BMI, eGFR, LDL, CRP, A1C, and PCs1–3. Asterisks denote the individual FDR-corrected significance threshold for the Wald Test p-value of the β_BMF-coefficient for each BMF category, relative to the high-normal reference category. Rows without asterisks showed a significant overall model (FDR p-value <0.05), despite a lack of significance for the individual coefficients. (***): p < 0.0001, (**): 0.0001 < p < 0.01, (*): 0.01 < p < 0.05.

Figure 5.. Heatmap of average z-scored blood plasma metabolites levels

within each BMF category for all metabolites significantly associated with BMF. 11 significant blood plasma metabolites, with average z-scores within each BMF category plotted as a heatmap. Significant associations were identified using LIMMA, with FDR-corrected p-values of the ratio test between the main model and the null model. Here, the covariates included sex, age, BMI, eGFR, LDL, CRP, A1C, and PCs1–3. Asterisks denote metabolites with significant β_BMF coefficient(s) in the linear regression model after FDR correction. (***): p < 0.0001, (**): 0.0001 < p < 0.01, (*): 0.01 < p < 0.05.

Figure 6.. Heatmap of average z-scored clinical chemistries within each BMF category for all chemistries significantly associated with BMF.

22 BMF-associated chemistries, identified using LIMMA models with FDR-corrected p-values of the ratio test between the main model and the null model, with average z-scores within each BMF category plotted as a heatmap. Here, the covariates included sex, age, BMI, eGFR, LDL, CRP, A1C, and PCs1–3. Asterisks denote FDR-corrected p-value thresholds for metabolites with significant β_BMF coefficient(s) in the linear regression model. (***): p < 0.0001, (**): 0.0001 < p < 0.01, (*): 0.01 < p < 0.05.

Figure 7.. Ordinal regression odds ratio for health, diet, and lifestyle survey data vs BMF and covariates.

Variables are colored by category: questions related to diet, exercise, and lifestyle (Diet/Lifestyle), and questions related to current digestive symptoms/function and health history (Health/Digestion). The BMF reference category was “high-normal” BMF (7–21 bowel movements per week). Each tick on the vertical axes represents a directional association in likelihood across the horizontal axis. The center line over the plots at x = 1.0 represents an equal likelihood of reporting an increase in number, intensity, frequency, or agreement (depending on the response variable) between the left side of the arrow on the vertical axis tick and the right side of the arrow on the vertical axis tick. A confidence interval that does not span the center line is significantly associated with the independent variable on the vertical axis tick. (*): FDR-corrected p-value < 0.05.

Figure 8.. Causal mediation analysis, with BMF as the treatment variable, 3-IS as the mediator variable, and eGFR as the response variable.

The average direct effect (ADE) of BMF on eGFR and the average causal mediated effect (ACME) of BMF on eGFR via 3-IS were found to be significant (N = 572; ADE −4.458, p = 0.012; ACME 1.343 p < 2E-16). The total effect and the proportion mediated terms did not pass our significance threshold of alpha=0.05.