The gut microbiota-bile acid axis links the positive association between chronic insomnia and cardiometabolic diseases

Abstract

Evidence from human cohorts indicates that chronic insomnia is associated with higher risk of cardiometabolic diseases (CMD), yet whether gut microbiota plays a role is unclear. Here, in a longitudinal cohort (n = 1809), we find that the gut microbiota-bile acid axis may link the positive association between chronic insomnia and CMD. Ruminococcaceae UCG-002 and Ruminococcaceae UCG-003 are the main genera mediating the positive association between chronic insomnia and CMD. These results are also observed in an independent cross-sectional cohort (n = 6122). The inverse associations between those gut microbial biomarkers and CMD are mediated by certain bile acids (isolithocholic acid, muro cholic acid and nor cholic acid). Habitual tea consumption is prospectively associated with the identified gut microbiota and bile acids in an opposite direction compared with chronic insomnia. Our work suggests that microbiota-bile acid axis may be a potential intervention target for reducing the impact of chronic insomnia on cardiometabolic health.

Fig. 1. Study diagram and gut microbiota diversity by chronic insomnia status.

a Conceptual diagram of the present study. b The association of chronic insomnia with α-/β- microbial diversity among the four groups (n = 1809). The association of chronic insomnia with the overall microbial α-diversity parameter Observed species was evaluated using a multivariable linear regression, adjusted for potential confounding factors (three models in the text). Box plots indicate median and interquartile range (IQR). The upper and lower whiskers indicate 1.5 times the IQR from above the upper quartile and below the lower quartile. The results of Shannon index, Chao 1 index, ACE index and Simpson index are reported in Supplementary Fig. 1. β-diversity was evaluated using principal coordinate analysis (PCoA) plot based on Bray-Cutis distance at the genus level. Permutational ANOVA (PERMANOVA) (999 permutations) was used to identify the variation of β-diversity in the human gut microbiota structure comparing the four groups, adjusted for the same covariates. The Benjamini-Hochberg method was used to adjust p values for multiple testing. Value with symbol is significantly different (model 1: *p < 0.05, **p < 0.01, ***p < 0.001; model 2: ⁺p < 0.05, ⁺⁺p < 0.01, ⁺⁺⁺p < 0.001; model 3: ^#p < 0.05, ^##p < 0.01, ^###p < 0.001). All statistical tests were two-sided. Source data are provided as a Source Data file.

Fig. 2. Association of chronic insomnia with gut microbiota and bile acids.

a Observed species in the discovery cohort (n = 1809) and validation cohort (n = 6122). The results of Shannon index, Chao 1 index, ACE index and Simpson index are reported in Supplementary Fig. 2 (discovery cohort) and Supplementary Fig. 3 (validation cohort). p value was calculated from multivariable-adjusted linear regression with three different models (Methods; model 1: *, model 2: +, model 3: #). Box plots indicate median and interquartile range (IQR). The upper and lower whiskers indicate 1.5 times the IQR from above the upper quartile and below the lower quartile. b β-diversity: principal coordinate analysis (PCoA) of genus-level Bray-Cutis distance in the discovery and validation cohorts. Permutational ANOVA (999 permutations) was used to identify the variation of β-diversity, adjusted for the same covariates as α-diversity. c Multivariate Analysis by Linear Models (MaAsLin) was used to identify the gut microbial biomarkers for chronic insomnia comparing Chronic insomnia group with Long-term healthy group. The q values (false discovery rate adjusted p value) were calculated using the Benjamini-Hochberg method (*q < 0.25, **q < 0.05). d Multivariable linear regression was used to assess the association of chronic insomnia with the gut microbial biomarkers in the discovery and validation cohorts, adjusted for the same covariates as α-diversity. Error bars are beta coefficient with 95% confidence intervals. e, Bile acid biomarkers of chronic insomnia in the GNHS (n = 954). Box plots indicate median and interquartile range. Orthogonal partial least squares discrimination analysis (OPLS-DA) (Supplementary Fig. 5) and multivariable-adjusted linear regression were used to identify potential bile acids associated with chronic insomnia (*p < 0.05, **p < 0.01, ***p < 0.001). f Partial correlation analysis was used to assess the interrelationships between the identified gut microbiota and bile acid biomarkers, adjusted for age, sex and BMI. Orange/sky blue circles indicate chronic insomnia-positive/negative biomarkers. Orange/sky blue lines indicate positive/negative associations. The Benjamini-Hochberg method was used to correct for multiple testing. All statistical tests were two-sided. Source data are provided as a Source Data file. α-MCA α-muricholic acid; β-HDCA β-hyodeoxycholic acid; HDCA hyodeoxycholic acid; HCA hyocholic acid; IsoLCA isolithocholic acid; LCA lithocholic acid; MCA Muro cholic acid; NorCA Nor cholic acid; NorDCA Nor deoxycholic acid; UDCA ursodeoxycholic acid.

Fig. 3. Association of the chronic insomnia-related gut microbiota-bile acid axis with cardiometabolic diseases.

Multivariable logistic regression was used to estimate the association of the chronic insomnia inverse-related microbial biomarkers Ruminococcaceae UCG-002 (a) and Ruminococcaceae UCG-003 (b) with different CMD in the discovery and validation cohorts, respectively. The effect estimates from the discovery and validation cohorts were pooled using random effects meta-analysis. c Multivariable logistic regression was used to estimate the association of the chronic insomnia-related bile acid biomarkers with CMD in the discovery cohort. d The prospective associations of the above identified gut microbiota biomarkers (measurement of gut microbiota data at the second follow-up) with the incidence of CMD (dyslipidemia) at the third follow-up using multivariable logistic regression, adjusted for potential confounders. Error bars in a–d are odds ratios with 95% confidence intervals. e Associations of the identified gut microbiota and bile acid biomarkers with CMD-related risk factors (BMI, DBP, SBP, waist circumference, fasting serum TG, TC, HDL, LDL, glucose, insulin, and HbA1c) using multivariable linear regression model in the GNHS, adjusted for potential confounders. f Parallel coordinate chart showing the association among gut microbes, bile acid biomarkers and CMD outcomes. The left panel shows the microbial biomarkers, the middle panel shows the bile acid biomarkers, and the right panel shows the CMD outcomes. The red lines across panels indicate the positive association. The green lines across panels indicate the inverse association. g The chronic insomnia inverse-related microbial biomarker Ruminococcaceae UCG-002 affects risk of MetS and T2D though specific bile acid biomarkers, respectively. h The chronic insomnia inverse-related microbial biomarker Ruminococcaceae UCG-003 affects the risk of MetS and T2D through specific bile acid biomarkers, respectively. The gray lines indicate the associations, with corresponding normalized beta values and p values. The red arrowed lines indicate the microbial effects on CMD mediated by specific bile acid biomarkers, with the corresponding mediation p values. p value < 0.05 is considered significantly different. Throughout the above analyses, FDR from multiple testing was controlled by the Benjamini-Hochberg method. All statistical tests were two-sided. Source data are provided as a Source Data file. CMD cardiometabolic disease; T2D type 2 diabetes; MetS metabolic syndrome; SBP systolic blood pressure; DBP diastolic blood pressure; TG triglycerides; TC total cholesterol; HDL high-density lipoprotein cholesterol; LDL low-density lipoprotein cholesterol; HbAlc glycated hemoglobin.

Fig. 4. Habitual dietary intake and gut microbiota-bile acid axis.

a Prospective association of dietary factors with the identified microbial biomarker Ruminococcaceae UCG-002 in the discovery and validation cohorts. The results of Ruminococcaceae UCG-003 are reported in the Supplementary Fig. 7. Values presented are beta coefficients (95% confidence intervals) with corresponding p-values. b Prospective association of dietary factors with the identified bile acid biomarkers linking chronic insomnia and cardiometabolic diseases (CMD) in the GNHS. Multivariable linear regression was used to examine the prospective association of dietary factors with microbial and bile acid biomarkers, adjusted for the potential confounders. p value < 0.05 is considered significantly different. Value presented are beta coefficients (95% confidence intervals) with corresponding p-values. c Diagram of the link between habitual tea consumption, the gut microbiota-bile acid axis, and CMD. Habitual tea consumption was associated with higher abundance of Ruminococcaceae UCG-002 and lower abundance of the Nor cholic acid (NorCA). Value with asterisk is significantly different. (*p < 0.05, **p < 0.01, ***p < 0.001). Throughout the above analyses, FDR was controlled by the Benjamini-Hochberg method. All statistical tests were two-sided. Source data are provided as a Source Data file.