Intestinal microbiota in patients with uncomplicated lower urinary tract infection: an observational case-control study

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Abstract

Background. Uncomplicated lower urinary tract infection (ULUTI) is one of the most common infectious and inflammatory diseases and is characterized by a high recurrence rate. It is known that the main source of pathogens is the intestine, where uropathogens exist among a complex microecological community – the intestinal microbiota (IM). To date, there are a limited number of studies on the relationship between ULUTI and IM, and there are no studies of this relationship using the gas chromatography-mass spectrometry (GCMS) method by the microbial marker mass spectrometry (MMMS) technique.

Objective. Assessment of the state of the IM and its impact on the development of the disease in patients with ULUTI.

Methods. An observational case-control study was conducted in the period from 01.08.2021 to 28.02.2023 with the participation of 33 patients with episodes of symptomatic ULUTI (first-time or relapse). The state of the IM was assessed using GCMS by the MSMM method on fecal samples.

Results. In the ULUTI group, a decrease in the number of Eubacterium spp. biomarkers (median (Me)=7.18, interquartile range (IQR) [4.24; 11.98] vs. Me=19.56, IQR [7.21; 26.85] ×109 cells/g; p=0.005), Clostridium propionicum (Me=0.26, IQR [0.05; 0.49] vs. Me=0.76, IQR [0.25; 4.14] ×109 cells/g; p=0.007), Propionibacterium jensenii (Me=4.71, IQR [2.06; 7.65] vs. Me=8.18, IQR [3.67; 15.57] ×109 cells/g; p=0.045), and a higher number of Peptostreptococcus anaerobius 18623 (Me=4.31, IQR [2.29; 6.53] vs. Me=2.07, IQR [0.59; 4.53] ×109 cells/g; p=0.031) compared to the group of healthy volunteers (HV) was noted. No significant differences in the number of Bifidobacterium spp. and Lactobacillus spp. markers were found (p>0.05).

It was determined that the most significant factor in the IM structure that has a protective effect in the context of ULUTI is Eubacterium spp. In the logistic regression model, it was found that an increase in the number of Eubacterium spp. was associated with a lower probability of having the disease (OR=0.885, 95% CI [0.817, 0.959]; p=0.003).

According to GCMS data, the level of Eubacterium spp. below 15.16×109 cells/g in fecal microbiota can be considered as a risk factor for the development of ULUTI (OR=15.95, 95% CI [3.60, 70.54]; p<0.001).

Conclusion. The state of the intestinal microbiota can have a significant impact on the risk of developing ULUTI. Further extensive studies to obtain a more complete picture of the relationship between intestinal microbiota and ULUTI and to develop new therapeutic approaches to disease prevention are required.

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About the authors

N. V. Sturov

Peoples’ Friendship University of Russia

Email: sturov_nv@rudn.ru
ORCID iD: 0000-0002-3138-8410

Cand. Sci. (Med.), Associate Professor, Head of the Department of General Medical Practice, Medical Institute

Russian Federation, Moscow

Sergey V. Popov

Peoples’ Friendship University of Russia

Author for correspondence.
Email: popov_serv@pfur.ru
ORCID iD: 0000-0002-0567-4616

Dr. Sci. (Med.), Professor, Department of General Medical Practice, Medical Institute

Russian Federation, Moscow

V. A. Zhukov

Peoples’ Friendship University of Russia

Email: zhukov_vlan@rudn.ru
ORCID iD: 0000-0001-9995-264X

Cand. Sci. (Med.), Associate Professor, Department of General Medical Practice, Medical Institute

Russian Federation, Moscow

T. V. Lyapunova

Peoples’ Friendship University of Russia

Email: lyapunova_tv@rudn.ru
ORCID iD: 0000-0002-1141-0764

Cand. Sci. (Med.), Associate Professor, Department of Medical Informatics and Telemedicine

Russian Federation, Moscow

I. V. Zelensky

Peoples’ Friendship University of Russia

Email: zelenskiy_iv@pfur.ru
ORCID iD: 0009-0004-9603-0067

Laboratory Assistant, Department of General Medical Practice, Medical Institute

Russian Federation, Moscow

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2. Fig. 1. Statistically significant differences in the number of bacterial markers between the NINMP and ZD groups

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3. Fig. 2. Spearman correlation heat maps

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4. Fig. 2

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5. Fig. 3. LASSO regression for 11 and 4 predictors of NINMP development

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6. Fig. 4. ROC curve for the predictor Eubacterium spp.

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7. Fig. 5. Frequency of occurrence of Eubacterium spp. <15.16x10⁹ cells/g

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