Acute urticaria (AU) is one of the current and significant problems in modern pediatrics. According to the results of epidemiological studies, the prevalence of urticaria in the pediatric population reaches 6.7% [1][2]. The development of this urgent condition is associated with a variety of etiological factors, which often complicates the diagnostic search for a leading trigger and therapeutic tactics [3][4].

Currently, a special role is attributed to the microbiota and/or skin microbiome in the development of various allergic dermatoses [5][6]. In particular, a correlation between the diversity of the skin microbiome and the severity of the course of atopic dermatitis was established [7]. A correlation was revealed between an increase in the count of S. aureus on the skin and an increase in serum IgE concentration. S. aureus has a powerful arsenal of pathogenicity factors that often act as triggers of allergic reactions [8]. At the same time, the role of changes in the skin microbiota in the genesis and the influence on the severity of the course of AU remains understudied.

The study aimed to evaluate changes in the skin microbiota of children with AU of varying severity.

A clinical and laboratory examination was performed in 94 children aged 3 to 12 years old (mean age – 8.3±3.2 years). The subjects were divided into four groups. The first three groups were children diagnosed with AU of varying severity: Group I (n=15) – mild course of the disease, Group II (n=32) – moderate course, and Group III (n=16) – a severe form of AU. Group IV (n=31), the control group, included children of health groups 1 and 2a. The inclusion criteria for Groups I, II, and III were age 3–12 years old, diagnosis of AU, absence of concomitant dermatological diseases, and informed parental consent. Group IV inclusion criteria were age 3–12 years old, health groups 1 and 2a, and informed parental consent. In children with AU, the skin microbiota of two areas (the affected and symmetrical unaffected) of the middle third of the inner surface of the forearm was examined. In the control group, material was collected from the surface of the topically corresponding locus. Bacteriological skin examination was performed according to the method of Pokatilov (1993). The smear-prints were taken according to methodical guidelines MU 4.2.2 039-05 (2006), recommendations by Menshikov (2009) and Murray (2015), using a bacterial stamp sampler with different nutrient media [9][10]. The authors used an extended set of nutrient media for aerobic and anaerobic microbiota taxa in aerobic and anaerobic cultivation conditions, respectively. AnaeroHiGas PaK was used to create the latter. Identification of microorganisms verified in the studied loci was performed according to generally accepted methods.

Statistical analysis was performed in the software R (version 3.2, R Foundation for Statistical Computing, Vienna, Austria). The differences were analyzed based on the occurrence rate and concentration estimates. In the analysis of quantitative characteristics of different microbiota taxa verified on the skin, mean values were calculated as median (Me), lower quartile (LQ), and upper quartile (VQ). Ward’s method (Bray–Curtis dissimilarity) was used for similarity analysis. The Mann-Whitney test and Fisher’s exact test were also used to compare unrelated groups.

A comparative analysis of the microbiota in the unaffected skin area in the studied groups of patients with AU and the control group revealed significant differences in 8 microbial taxa (Table 1). Group I patients showed an increase in the detection rate of Propionibacterium spp. (p=0.04), and in Group II – Bacteroides spp. (p=0.001). In patients with severe AU (Group III), there was an increase in the studied index for S. aureus (p=0.003) and a decrease in Micrococcus spp. (0.001). In Group IV, there was an increase in the detection rate of S. epidermidis (p=0.006) and Bacillus spp.

A comparison of the microbiota in the affected skin area of patients with AU of different severity and children from the control group (Table 2) revealed several differences in the occurrence rate of bacteria. In Group II, the detection rate of Bacteroides spp. (p=0.0005) increased and Bacillus spp. –decreased (p=0.009). In Group II, the studied indicator for S. aureus was elevated (p=0.02). At the same time, in the control group, the detection rate of S. epidermidis was significantly increased (p=0.009) and there were no Bacteroides spp. detected.

It should be noted that there was a significant increase in the detection rate of S. aureus in children with severe AU in both studied skin loci.

A comparative analysis of the mean concentrations of microorganisms verified on the unaffected skin area in patients with AU and the control group revealed significant differences in some microbial taxa (Table 3). In Group I, there was an increase in the studied index for S. epidermidis and a decrease for Peptococcus spp., Peptostreptococcus spp., and Veillonella spp. Group II showed a decrease in the concentration of Propionibacterium spp. In Group III, an increase in the concentration of Peptococcus spp. was registered. At the same time, in the control group, an increase in the concentration of Peptostreptococcus spp. and Propionibacterium spp. and a decrease in S. epidermidis were recorded compared to patients with AU of different severity.

A similar analysis of the affected skin area of patients with AU compared to that of control children revealed significant differences in only 1 taxon (Veillonella spp.) (Table 4). Thus, regardless of the severity of the studied pathology, the median value of Veillonella spp. concentration was 100.3 CFU/cm², and in Group IV, this value was 103 CFU/cm².

Skin microbiota and its species composition directly affect the course of various skin diseases and AU is not an exception [11]. Quantitative and qualitative changes in the skin microbiota are associated with the severity of the course of atopic dermatitis [12]. S. aureus often acts as a direct microbial marker of such conditions [13]. Clausen et al. in their works draw attention to the fact that the increase in skin colonization by S. aureus contributes to a decrease in filaggrin levels. It leads to increased skin pH and skin barrier impairments, thereby, aggravating the course of atopic dermatitis [14][15]. S. aureus can exacerbate the course of atopy by expressing virulence factors, causing skin barrier disruption and inflammatory changes [7].

The present study of microbiota in the affected and unaffected skin areas in patients with urticaria proves the influence of dysbiotic changes in the skin microbiocenosis on the course and prognosis of the disease. The obtained data on the increased detection rate of S. aureus on the skin of children with AU of various severity compared to healthy children are consistent with the results of studies on the skin microbiota in other atopic diseases [13]. According to the present study, the detection rate of S. aureus tends to increase with the aggravation of the course of AU. Thus, the obtained results suggested the influence of Staphylococcus aureus on the development of the severity of the course of urticaria.

Changes in the composition of the bacterial communities of the skin microbiota may be an important inducer of clinical manifestations in patients with established atopic dermatitis and contribute to the development of exacerbations [13]. Drawing an analogy between the results of the available studies [5][8] and the data obtained in the present study, it can be concluded that the identified changes in the skin microbiota may act as a trigger factor for the development of AU and influence the severity of the disease.

To date, research is underway to optimize the therapy for atopic dermatitis through microbiota transplantation. Thus, the obtained data can serve as a basis for studying the transplantation of certain types of microorganisms in severe recurrent forms of urticaria in children.

Authors’ contribution:

Naboka Y.L., Lebedenko A.A. – development of research design, text editing and approval of the final version of the manuscript.

Posevina A.N. – search for literary sources, obtaining and analyzing data, writing the text of the manuscript.

Averkina L.A., Ivannikova E.V. – search for references, data acquisition and analysis.

Financing. The study did not have sponsorship.

Conflict of interest. The authors declare no conflict of interest.