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. 2018 Sep 25;6(4):98.
doi: 10.3390/microorganisms6040098.

Gut Microbiota in Patients with Different Metabolic Statuses: Moscow Study

Daria A Kashtanova  1 , Olga N Tkacheva  2 , Ekaterina N Doudinskaya  3 , Irina D Strazhesko  4 , Yulia V Kotovskaya  5 , Anna S Popenko  6 , Alexander V Tyakht  7 , Dmitry G Alexeev  8
Affiliations

Gut Microbiota in Patients with Different Metabolic Statuses: Moscow Study

Daria A Kashtanova et al. Microorganisms. .

Abstract

The aim of this paper was to study gut microbiota composition in patients with different metabolic statuses.

Methods: 92 participants aged 25⁻76 years (26 of whom were men), with confirmed absence of cardiovascular and other chronic diseases (but with the possible presence of cardiovascular risk factors) were included. Carotid ultrasound examinations, 16S rRNA sequencing of stool samples and diet assessments were performed. Statistical analysis was performed using R programming language, 3.1.0.

Results: Enterotyping yielded two clusters differentiated by alpha-diversity. Intima-media thickness was higher in the cluster with lower diversity (adj. p < 0.001). Obesity was associated with higher Serratia (adj. p = 0.003) and Prevotella (adj. p < 0.0003) in relative abundance. Abdominal obesity was associated with higher abundance of Serratia (adj. p = 0.004) and Prevotella (adj. p = 0.0008) and lower levels of Oscillospira (adj. p = 0.0005). Glucose metabolism disturbances were associated with higher Blautia (adj. p = 0.0007) and Serratia (adj. p = 0.003) prevalence. Arterial hypertension was associated with high Blautia levels (adj. p = 0.002). The Blautia genus strongly correlated with low resistant starch consumption (adj. p = 0.007). A combination of high-fat diet and elevated Blautia levels was very common for diabetes mellitus type 2 patients (adj. p = 0.0001).

Conclusion: The results show that there is a relationship between metabolic changes and higher representation of opportunistic pathogens and low diversity of gut microbiota even in apparently healthy participants.

Keywords: cardiovascular risk factors; diet; glucose metabolism; gut microbiota; metabolic status.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Prevalence of cardiovascular risk factors in participants. DM-2—diabetes mellitus type 2, AH—arterial hypertension.
Figure 2
Figure 2
Heatmap of the genus-level taxonomic composition (only the major genera forming 85% of the total abundance are displayed). First cluster samples are marked in red color, second cluster in blue.
Figure 3
Figure 3
Distribution of alpha-diversity across the microbiota clusters.
See this image and copyright information in PMC

References

    1. Sekirov I., Russell S.L., Antunes L.C., Finlay B.B. Gut microbiota in health and disease. Physiol. Rev. 2010;90:859–904. doi: 10.1152/physrev.00045.2009. - DOI - PubMed
    1. Cox A.J., West N.P., Cripps A.W. Obesity, inflammation, and the gut microbiota. Lancet Diabetes Endocrinol. 2015;3:207–215. doi: 10.1016/S2213-8587(14)70134-2. - DOI - PubMed
    1. Stein J.H., Korcarz C.E., Hurst R.T., Lonn E., Kendall C.B., Mohler E.R., Post W.S. Use of carotid ultrasound to identify subclinical vascular disease and evaluate cardiovascular disease risk: A consensus statement from the American Society of Echocardiography Carotid Intima-Media Thickness Task Force. Endorsed by the Society for Vascular Medicine. J. Am. Soc. Echocardiogr. 2008;21:93–111. - PubMed
    1. Caporaso J.G., Kuczynski J., Stombaugh J., Bittinger K., Bushman F.D., Costello E.K., Huttley G.A. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods. 2010;7:335–336. doi: 10.1038/nmeth.f.303. - DOI - PMC - PubMed
    1. Zhang H., Lu N., Feng C., Thurston S.W., Xia Y., Zhu L., Tu X.M. On fitting generalized linear mixed-effects models for binary responses using different statistical packages. Stat. Med. 2011;30:2562–2572. doi: 10.1002/sim.4265. - DOI - PMC - PubMed

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