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. 2018 Mar 30;132(6):701-718.
doi: 10.1042/CS20180087. Print 2018 Mar 30.

Imbalance of gut microbiome and intestinal epithelial barrier dysfunction in patients with high blood pressure

Seungbum Kim  1 , Ruby Goel  1 , Ashok Kumar  1 , Yanfei Qi  2 , Gil Lobaton  1 , Koji Hosaka  3 , Mohammed Mohammed  2 , Eileen M Handberg  2 , Elaine M Richards  1 , Carl J Pepine  4 , Mohan K Raizada  5
Affiliations

Imbalance of gut microbiome and intestinal epithelial barrier dysfunction in patients with high blood pressure

Seungbum Kim et al. Clin Sci (Lond). .

Abstract

Recent evidence indicates a link between gut pathology and microbiome with hypertension (HTN) in animal models. However, whether this association exists in humans is unknown. Thus, our objectives in the present study were to test the hypotheses that high blood pressure (BP) patients have distinct gut microbiomes and that gut-epithelial barrier function markers and microbiome composition could predict systolic BP (SBP). Fecal samples, analyzed by shotgun metagenomics, displayed taxonomic and functional changes, including altered butyrate production between patients with high BP and reference subjects. Significant increases in plasma of intestinal fatty acid binding protein (I-FABP), lipopolysaccharide (LPS), and augmented gut-targetting proinflammatory T helper 17 (Th17) cells in high BP patients demonstrated increased intestinal inflammation and permeability. Zonulin, a gut epithelial tight junction protein regulator, was markedly elevated, further supporting gut barrier dysfunction in high BP. Zonulin strongly correlated with SBP (R2 = 0.5301, P<0.0001). Two models predicting SBP were built using stepwise linear regression analysis of microbiome data and circulating markers of gut health, and validated in a separate cohort by prediction of SBP from zonulin in plasma (R2 = 0.4608, P<0.0001). The mouse model of HTN, chronic angiotensin II (Ang II) infusion, was used to confirm the effects of butyrate and gut barrier function on the cardiovascular system and BP. These results support our conclusion that intestinal barrier dysfunction and microbiome function are linked to HTN in humans. They suggest that manipulation of gut microbiome and its barrier functions could be the new therapeutic and diagnostic avenues for HTN.

Keywords: Butyrate; High blood pressure; Hypertension; Microbiome; Zonulin; gastrointestinal physiology.

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Conflict of interest statement

Competing interests

The authors declare that there are no competing interests associated with the manuscript.

Figures

Figure 1
Figure 1. Gut microbiome in patients with HBP is taxonomically and functionally different
(A) PLS-DA plot of the two cohorts based on bacterial taxonomy (REF, n=18; HBP, n=22). (B) PLS-DA plot based on KO for functional differences. (C) Volcano plot displaying significantly enriched functional genes (KO terms) in REF cohort (green) or HBP (red). The x-axis is log2 fold change and the y-axis is transformed P-value. Genes not different between cohorts are shown in black, A quasi-likelihood F-test transformed P-value threshold of 13 (P<0.05) was utilized to highlight significantly differentiating data points. (D) Significantly enriched KO terms from the volcano plot displayed within a heat map. The top dendrogram, and top row colored red (HBP) and green (REF), shows that the subjects tend to cluster by BP; abundances of the KO terms also cluster, dendrogram on the left. Rows are KO terms, columns individual subjects, and abundance is shown in individual cells on a sliding color scale of blue (low) to high (red). (E) LEfSe identified significantly different bacterial taxa enriched in each cohort at LDA score > 2.5, P<0.05 (red bars HBP enriched, green bars reference enriched). Bars represent bacterial species, except Klebsiella (genus).
Figure 2
Figure 2. Bacterial taxa positively and negatively correlated with SBP
(A) Bacterial species that were significantly positively correlated with SBP were analyzed using the Pearson correlation coefficient (except A. finegoldii). Please note the break in the y-axis. (B) Bacterial species significantly negatively correlated with SBP (Pearson correlation coefficient). (C) Symbols from panels (A,B), and correlation coefficients are explained in the tables. *P<0.05; **P<0.01; ***P<0.001.
Figure 3
Figure 3. Gut microbiome of the HBP cohort has reduced capacity for butyrate production
(A) PCoA plot was generated based on the abundance of the butyrate-producing bacteria and butyrate generating enzymes (butyrate kinase and acetate-CoA transferase) in each fecal sample. (B) Adonis summary from the PCoA plot was shown. (C) Plasma butyrate measured by GC (n=7 for each cohort, P=0.0175 by Mann–Whitney test). *P<0.05. Abbreviation: RA; relative abundance in fecal bacterial genes.
Figure 4
Figure 4. Increased gut epithelial barrier markers and gut-homing proinflammatory Th17 cells in HBP patients
(A) Plasma I-FABP. (B) Plasma LPS. (C) Plasma zonulin. n=17 and 18 for REF and HBP cohorts, respectively for panels (A–C). (D) Increased peripheral blood CD161+ Th17 cells, imprinted for gut-homing and inflammation [41], in the HBP cohort. (E) Increased expression of integrin β7 and CCR6, homing receptors for migration of lymphocytes to the intestinal mucosa [41], n=10 and 12 for REF and HBP cohorts, respectively for panels (D,E). *P<0.05; **P<0.01; ***P<0.001 with Student’s t tests.
Figure 5
Figure 5. Stepwise linear regression analysis to predict subject’s SBP based on gut factors
(A) The relationship between SBP and plasma zonulin (REF, n=17; HBP, n=18). (B) Stepwise linear regression analysis was performed using SBP as a dependent value and various gut/microbiome factors as independent values to build a model for SBP prediction (details in Supplementary Table S3). (C) A graph showing SBP predicted for each individual using models 1 (blue symbols) and 2 (green symbols) from the stepwise linear regression analyses and actual SBP measured in the clinic (red symbols) for validation. (D) Comparison of clinically measured SBP and estimated SBP from plasma zonulin in a separate validation cohort for model 1 (n=36). SBP from the validation cohort ranged from 98 to 174 mmHg (average: 134 mmHg). Only two samples were incorrectly categorized by the model (REF predicted as HBP and HBP as REF, marked in red circles). See ‘Results’ section for details.
Figure 6
Figure 6. Butyrate treatment attenuated Ang II-induced HTN and altered gut microbiome in C57BL6 mice
(A) Representative radiotelemetry tracings of MAP in saline, Ang II, butyrate, and Ang II + Butyrate treated mice; (B) weekly MAP in each cohort. (C,D) Spectral analysis of SBP and pulse interval waveforms of the telemetry data. Cardiac sBRG was attenuated in the Ang II-infused animals but reversed by butyrate co-treatment (C). Increased cardiac sympathetic tone in Ang II mice accompanied this as shown by the low frequency (LF):high frequency (HF) ratio; this was also attenuated by co-treatment with butyrate (D). (E) PCoA plot with weighted UniFrac metric showing distinct microbiome composition in each group. (F) Heat map analysis of the most abundant bacterial genera detected in Saline and Ang II-treated groups showing the distinct separation of the Ang II and saline-treated mice. The heat map colors represent the relative percentage of microbial genus assigned within each sample. Comparisons of other groups were shown in Supplementary Figure S4. Oval shades surrounding the majority of symbols of each group in panel (E) are visual aids. *P<0.05; **P<0.01; ***P<0.001; ****P<0.0001, ANOVA with Tukey’s multiple comparison tests. n=6 per cohort except for the butyrate, n=5, throughout all panels. **P<0.01; ***P<0.001; ****P<0.0001. Abbreviation: A.U., arbitrary unit.
Figure 7
Figure 7. Butyrate treatment restored hypoxia in the gut epithelia of Ang II-infused mice
(A) Representative images of pimonidazole staining showing hypoxia in the gut barrier; greener the tissue the more it is hypoxic. (B) Quantitation of pimonidazole-positive areas in small and large intestines. *P<0.05.
Figure 8
Figure 8. Butyrate treatment normalized gut barrier dysfunction in Ang II-induced HTN mice
(A) Representative in vivo fluorescent images of the abdomen at 2 and 4 h after oral feeding of FITC-dextran (0.44 mg/g body weight). (B) Serum concentration of FITC-dextran measured the permeability of the intestine. n=5 per mouse cohort. (C) Evaluation of intestinal wall integrity by qPCR of tight junction proteins in gut epithelial cells. (D) FACS analysis of proinflammatory CCR2+ CD4+ Il-17+ Th17 cells in the blood after 4 weeks of treatment. *P<0.05; **P<0.01.
Figure 9
Figure 9. Cardiac functions impaired at 4 weeks of Ang II treatment were restored by butyrate treatment
Measurements shown in panels (A–C) were made after 4 weeks of Ang II treatment (five mice/group). (A) Cardiac hypertrophy, as the ratio of heart weight (HW) to body weight (BW). (B) Echocardiographic measurements of LV systolic function assessed by FS. (C) LV diastolic function measured using mitral valve E wave /A wave (MV E/A) ratio. (D–G) Measurements shown in panels (D–G) were made in hearts isolated from SD rats using the Langendorff technique (n=5/group). LVDP and rate of LV pressure development (+dp/dt) and decline (–dp/dt) of the SD rats’ hearts were averaged over the duration of perfusion in isovolumetric Langendorff preparation with 0, 10, and 100 mM of sodium butyrate (D,E). Heart rate, beats per min (BPM), (F) and coronary flow (G) following perfusion with 0, 10, or 100 mM sodium butyrate. n=5 for each group, *P<0.05; **P<0.01; ***P<0.001.
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