Abstract
Introduction
Atopic dermatitis (AD) is thought to arise from the interplay of skin barrier dysfunction, type 2 immune dysregulation, and cutaneous dysbiosis, the last of these characterized by reduced bacterial diversity and predominance of Staphylococcus aureus. The urban exposome, including air pollution and reduced environmental microbial diversity, may modulate this dysbiosis. We hypothesized that patients with AD residing in a metropolitan area with a higher pollutant burden would show greater skin dysbiosis, reflected by a higher relative abundance of S. aureus, than patients residing in a municipality with a lower pollutant load and greater environmental biodiversity.
Methods
This cross-sectional, comparative study enrolled ten children (6–12 years) and ten adults (20–31 years) with active AD, without specific treatment in the preceding 30 days, residing in the metropolitan region of São Paulo or in Botucatu, an interior municipality of São Paulo State, Brazil. Skin swabs were collected from eczematous lesions and characterized by 16S ribosomal RNA (rRNA) gene (V3–V4) sequencing. Alpha and beta diversity and the relative abundance of S. aureus, S. epidermidis, and S. hominis were compared between municipalities and age groups using generalized linear models, Bray–Curtis dissimilarity, principal coordinates analysis (PCoA), and permutational multivariate analysis of variance (PERMANOVA).
Results
The sample (n = 20) had a predominance of male sex (60%) and moderate AD severity (75%). A total of 658 taxa were identified. Alpha diversity did not differ by municipality or age group, and PERMANOVA revealed no global difference in bacterial community composition (p > 0.1). However, participants residing in the metropolitan municipality showed a significantly higher relative abundance of S. aureus and higher proportions of S. aureus relative to total bacteria and to other staphylococci than those residing in the interior municipality.
Conclusion
Despite similar overall microbial diversity, patients with AD living in a metropolitan municipality showed selective enrichment of S. aureus compared with those in a less polluted interior municipality. These exploratory findings generate the hypothesis that the urban exposome contributes to cutaneous dysbiosis in AD and warrant confirmation in larger studies with objective exposure measurement.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1007/s13555-026-01927-3.
Keywords: Atopic dermatitis, Skin microbiome, Exposome, Air pollution, Staphylococcus aureus, Dysbiosis
Key Summary Points
| The skin microbiome in atopic dermatitis (AD) is shaped not only by disease severity but also by environmental exposures, yet the role of the urban exposome remains poorly characterized. |
| We compared the skin microbiome of patients with AD residing in a highly polluted metropolitan municipality versus a less polluted interior municipality in São Paulo State, Brazil. |
| Overall bacterial diversity (alpha and beta diversity) did not differ between municipalities or age groups. |
| Patients residing in the metropolitan municipality showed a significantly higher relative abundance of Staphylococcus aureus, both in its relative abundance and in its proportion relative to total bacteria and to other staphylococci. |
| These findings suggest that the urban exposome may selectively promote S. aureus overgrowth in AD, supporting further research into environmental modulation of cutaneous dysbiosis. |
Introduction
Atopic dermatitis (AD) is a chronic inflammatory dermatosis thought to result from the interaction of skin barrier defects, immune dysregulation (predominantly mediated by type 2 responses), and alterations of the skin microbiome. These components form interdependent pathophysiological axes, in which barrier dysfunction favors abnormal microbial colonization and penetration of environmental antigens, while type 2 inflammation amplifies dysbiosis and further impairs skin integrity [1].
Cutaneous dysbiosis in AD is characterized by disruption of the symbiosis between the host and its microbiota, with reduced bacterial diversity and predominance of Staphylococcus aureus [1, 2]. This phenomenon extends beyond a simple compositional shift, reflecting a functional disturbance of the skin ecosystem, with loss of regulatory mechanisms that contribute to immune tolerance, antimicrobial defense, and barrier maintenance [2]. Intense ecological succession of skin microbial communities occurs from the earliest years of life [3], and the exposome plays an important role in shaping microbiome diversity and stability throughout the lifespan [2].
The exposome encompasses the set of environmental exposures accumulated over a lifetime and influences the susceptibility, clinical expression, and progression of AD. Among its external components, air pollution stands out for inducing oxidative stress, compromising skin barrier integrity, and amplifying type 2-mediated inflammatory pathways [4, 5]. In addition, reduced contact with soil and natural environments, low environmental microbial diversity, urban microclimates, and exposure to indoor allergens may contribute to alterations in skin and microbiome homeostasis [6, 7]. In this context, investigations exploring the interaction between the urban exposome and the skin microbiota may help elucidate pathophysiological mechanisms underlying the dynamic relationship between the microbiome and AD.
We hypothesized that patients with AD residing in a metropolitan area, characterized by a higher burden of vehicular and urban air pollutants, would present greater skin microbiome dysbiosis than patients residing in a less urbanized municipality with lower pollutant load and greater environmental microbial diversity, manifested as reduced bacterial diversity and a higher relative abundance of S. aureus. This study aimed to compare the skin microbiome of patients with AD, across different age groups, residing in two Brazilian municipalities with distinct environmental profiles.
Methods
Study Design and Participants
This was a cross-sectional, comparative study involving ten children (6–12 years) and ten adults (20–31 years) with active AD, without specific topical or systemic treatment in the preceding 30 days, residing in the metropolitan region of São Paulo (metropolis) or in Botucatu, an interior municipality of São Paulo State (interior), Brazil. The São Paulo metropolitan region has a high concentration of air pollutants, resulting mainly from vehicular emissions and urban activity. In contrast, municipalities in the interior of São Paulo State are characterized by a lower atmospheric pollutant load and reduced influence from large-scale anthropogenic sources. Factors such as lower population density, greater vegetation cover, greater contact with natural environments, greater environmental microbial diversity, and different microclimatic conditions contribute to distinguishing the urban exposomes of these two municipalities [8]. The municipality of São Paulo alone concentrates over 3000 documented fixed pollution sources [9], and the metropolitan region is a major source of regionally transported ozone reaching interior municipalities, accounting for up to 57.1% of ambient ozone measured at a fixed air-quality station in Botucatu [10]. That same station recorded a lower secondary fine particulate matter (PM2.5) fraction (39%) than reported for metropolitan stations (51%) [10], consistent with a comparatively lower burden of locally generated photochemical pollution in the interior municipality; however, paired, simultaneous ambient concentration data for both municipalities during the present study period were not available.
Botucatu is a medium-sized municipality in the central region of São Paulo State, approximately 235 km from the state capital. At the 2022 national census it had 145,155 inhabitants distributed over 1482.6 km2, corresponding to a population density of 97.9 inhabitants/km2, compared with 11,451,999 inhabitants and 7528.3 inhabitants/km2 in the municipality of São Paulo [11]. Although its resident population is predominantly urban, the built-up area is small relative to the municipal territory and is embedded in an agricultural matrix of sugarcane, pasture, and remnant native vegetation over the Cuesta escarpment, and the local economy is centered on agriculture, agro-industry, and a university campus rather than on heavy industry. Botucatu is therefore characterized here not as a rural setting but as a lower-density interior municipality whose residents are exposed to a distinct urban exposome, lower traffic-related emission density, and greater proximity to soil, vegetation, and agricultural environments while remaining subject to its own regional sources, notably seasonal biomass burning associated with sugarcane production [10].
The study was conducted in accordance with the ethical principles of the 1964 Declaration of Helsinki and its later amendments, and the protocol was approved by the Research Ethics Committee of the Universidade Federal de São Paulo (CAAE: 64567022.4.3001.5411). Written informed consent was obtained from all adult participants and from the legal guardians of all participating children, who additionally provided written assent.
Sample Collection and Sequencing
Skin microbiome samples were collected between August 2023 and July 2024 from eczematous lesions at the antecubital or popliteal fossae using a sterile swab pre-moistened with saline solution, applied over a standardized area of 15 cm2. Samples were stabilized in DNA/RNA Shield (Zymo Research, Irvine, CA, USA) at the time of collection to preserve nucleic acid integrity. DNA was subsequently extracted with the QIAamp UCP Pathogen Mini Kit (QIAGEN, Hilden, Germany; cat. no. 50214), following the manufacturer’s protocol for purification of microbial DNA from swabs, which comprises mechanical pre-lysis in Pathogen Lysis Tubes, proteinase K digestion under denaturing conditions, adsorption to a silica membrane, two wash steps, and elution in buffer AVE. The columns and buffers of this kit undergo ultra-clean production and are certified by the manufacturer to contain no detectable contaminating microbial DNA, which limits reagent-derived background in low-biomass samples such as skin swabs. The protocol followed also incorporates procedural safeguards against cross-contamination, including aerosol-barrier pipette tips, tip changes between all liquid transfers, single-use disposable connectors, frequent glove changes, and handling of a single column at a time. The bacterial profile was characterized by next-generation sequencing of the 16S rRNA gene (V3–V4 regions) using the MiSeq platform (Illumina®), performed as a single batch in August 2024 by a third-party laboratory (Inside Diagnósticos, São Paulo, Brazil). Library amplification of the V3–V4 region was performed with 40 PCR cycles, as reported by the service laboratory. Negative extraction and no-template amplification controls were processed alongside the study samples as part of the service laboratory’s standard 16S workflow. The laboratory reported no detectable amplification in these controls; they were consequently not carried forward to sequencing.
Statistical Analysis
To compare skin microbiome composition between participants residing in the two municipalities, as well as between age groups, complementary microbial diversity metrics were assessed. Alpha diversity was used to estimate the richness and heterogeneity of bacterial communities within each individual sample, while beta diversity allowed evaluation of differences in microbial composition between study groups. Additionally, the relative abundance of S. aureus, S. epidermidis, and S. hominis species considered relevant to AD dysbiosis was analyzed [1, 2].
Comparisons of alpha diversity indices, as well as the abundances of Staphylococcus taxa, were performed using a generalized linear model with fixed effects for municipality and age group. Effect size was defined by the beta estimator, with its 95% confidence interval (CI) calculated using 5000 bootstrap resamplings. Beta diversity was investigated using Bray–Curtis dissimilarity of bacterial taxa, and the multivariate structure was explored by principal coordinates analysis (PCoA). Global differences between groups were assessed by permutational multivariate analysis of variance (PERMANOVA). Statistical significance was inferred when the 95% CI excluded the null value (zero), equivalent to p < 0.05; this bootstrap-based approach was preferred over asymptotic point p values given the small sample size and the non-normal distribution of several abundance variables.
Results
The composition of the two municipal samples in terms of sex and age is presented in Table 1, with an overall predominance of male sex (60%) and moderate disease severity (75%).
Table 1.
Composition of the sample by sex and age group, for the two municipalities (n = 20)
| Variables | Metropolis | Interior | Total |
|---|---|---|---|
| Sex, n (%) | |||
| Female | 2 (20%) | 6 (60%) | 8 (40%) |
| Male | 8 (80%) | 4 (40%) | 12 (60%) |
| Age (years), mean (SD) | |||
| Adult | 28 (4) | 23 (3) | 26 (4) |
| Child | 7 (1) | 10 (1) | 9 (2) |
| Severity, n (%) | |||
| Moderate | 8 (80%) | 7 (70%) | 15 (75%) |
| Severe | 2 (20%) | 3 (30%) | 5 (25%) |
SD standard deviation
A total of 658 taxa were identified in the sample. Figure 1 presents the individual-level relative abundance of S. aureus, S. epidermidis, and S. hominis for each of the 20 participants, stratified by municipality and age group, illustrating substantial interindividual variation as well as a visually higher relative abundance of S. aureus among several participants residing in the metropolitan municipality. Alpha diversity values did not differ between groups, either by age group or by municipality of residence.
Fig. 1.
Individual-level relative abundance of Staphylococcus aureus, S. epidermidis, and S. hominis (as a percentage of total bacterial reads) for each of the 20 participants, grouped by municipality of residence and age group. Bars are ordered by participant code within each subgroup
Table 2 presents the relative abundances of different Staphylococcus taxa and their ratios. A higher relative abundance of S. aureus was observed among participants residing in the metropolitan municipality (β = − 1.6; 95% CI − 2.5 to − 0.6). Likewise, the proportions of S. aureus relative to total bacteria (β = − 1.6; 95% CI − 2.5 to − 0.6) and relative to other Staphylococcus species (β = − 1.5; 95% CI − 2.4 to − 0.6) were also higher in the metropolitan municipality. The ratios between S. aureus and S. hominis or S. epidermidis were lower in adults than in children, whereas the ratio between S. aureus and S. epidermidis was also lower in the interior municipality.
Table 2.
Comparative analysis of the abundance of major Staphylococcus-related taxa and proportions in the skin microbiome of the sample (n = 20)
| Abundance index | Value | Age groupa | Municipalityb |
|---|---|---|---|
| Staphylococcus sp. (103) | 67.6 (30.3) | – 5.0 (– 33.4 to 23.5) | 9.6 (– 19.2 to 39.8) |
| S. aureus (103) | 1.8 (0.2–10.2) | – 0.5 (– 1.5 to 0.4) | – 1.6 (– 2.5 to – 0.6)* |
| S. epidermidis (103) | 8.9 (2.3–51.6) | 0.4 (– 1.0 to 1.3) | 0.4 (– 1.0 to 1.3) |
| S. hominis (103) | 0.6 (0.0–2.3) | – 0.8 (– 1.8 to 0.1) | – 0.8 (– 1.7 to 0.2) |
| S. aureus / total (%) | 3.7 (0.5–12.0) | – 0.3 (– 1.2 to 0.5) | – 1.6 (– 2.5 to – 0.6)* |
| S. aureus/Staphylococcus sp. (%) | 3.8 (0.5–12.4) | – 0.4 (– 1.2 to 0.5) | – 1.5 (– 2.4 to – 0.6)* |
| S. aureus/S. epidermidis (%) | 12.9 (3.6–34.1) | – 3.0 (– 4.3 to – 1.8)* | – 2.8 (– 4.0 to – 1.6)* |
| S. aureus/S. hominis (%) | 4.3 (0.2–51.2) | – 1.4 (– 2.5 to – 0.3)* | – 1.0 (– 2.1 to 0.1) |
Data are presented as mean (SD) or median (p25–p75)
CI confidence interval, SD standard deviation
aβ (95% CI), adults vs. children
bβ (95% CI), interior vs. metropolis
*p < 0.05
Figure 2 presents the PCoA analysis based on Bray–Curtis dissimilarity. The first two axes explained 45.5% of the observed variability, with no global differences in bacterial community composition according to municipality or age group (PERMANOVA, p > 0.1).
Fig. 2.
Principal coordinates analysis (PCoA) of the skin microbiome based on Bray–Curtis dissimilarity. Samples are colored according to municipality of residence (metropolitan or interior) and differentiated by symbol shape according to age group (children or adults). Ellipses represent 95% confidence regions for each municipality
Discussion
Although no global differences were observed in skin microbiome alpha or beta diversity, differences were identified in the relative abundance of specific taxa, particularly involving S. aureus. Patients residing in the metropolis showed a higher relative abundance of S. aureus and a higher proportion of this species relative to total bacteria and to other Staphylococcus species compared with those from the interior municipality. These findings are consistent with experimental evidence demonstrating that air pollutants can favor type 2 inflammatory responses [5, 7], and alter cutaneous microbial ecology [12]. Direct evidence indicates that pollution exerts a deleterious effect on commensal skin bacteria and that chronic exposure predisposes to the predominance of pathogenic species [12]. Certain pollutants have been associated with increased healthcare utilization for AD in different populations worldwide, corroborating the role of pollution as an aggravating factor for the disease [13]. These findings are also consistent with the substantially greater density of documented fixed pollution sources in the metropolitan region compared with the interior municipality [9, 10], and with the metropolis’s role as a major source of regionally transported pollutants reaching smaller interior municipalities [10]. Nonetheless, direct, paired measurement of ambient pollutant concentrations in both municipalities during the study period was not performed, and this remains an important limitation for attributing the observed microbiome differences specifically to differential air pollutant exposure rather than to the broader set of environmental, geographic, and socioecological factors that also differ between the two municipalities.
Consistently, participants residing in the interior municipality and children showed a lower relative predominance of S. aureus compared with commensal staphylococci (S. epidermidis and S. hominis). Although exploratory, these findings suggest a microbial structure potentially closer to homeostasis in individuals with lower cumulative exposure to urban pollutants, reinforcing the hypothesis that environmental factors and cumulative exposures may influence the ecological balance of the skin microbiome in AD [5–7].
The absence of global differences in alpha and beta diversity, despite taxon-specific differences in S. aureus abundance, suggests that the urban exposome may act as a selective pressure on specific dysbiotic taxa rather than uniformly restructuring the overall skin bacterial community. This pattern raises the possibility that S. aureus expansion is a more sensitive indicator of environmentally associated dysbiosis than global diversity metrics, although the cross-sectional design does not allow us to establish a temporal sequence between the two.
However, these results have limitations. The cross-sectional design, the absence of individual measures of pollution exposure, and the limited sample size preclude robust causal inferences, and no non-AD controls were included. The sample size (n = 20) was determined by the exploratory, pilot nature of the project and by the cost of sequencing; it limits statistical power and precludes adjustment for potential confounders. The absence of a non-AD control group in each municipality further means that we cannot determine whether the observed municipal difference in S. aureus abundance is specific to AD skin or reflects a broader environmental influence on the cutaneous microbiota of the general population. Confirmation in larger samples including healthy controls from both municipalities is therefore required before these findings can be generalized. In addition, factors known to influence the skin microbiome including AD severity, hygiene habits, treatment regimens (topical and systemic), and local socioenvironmental characteristics could not be fully controlled for. Future studies incorporating individual-level exposure monitoring, larger and more diverse cohorts, and longitudinal follow-up are needed to clarify the causal role of the urban exposome in cutaneous dysbiosis. Sample collection also spanned a 12-month period (August 2023–July 2024), during which seasonal variation in climate and air pollutant levels in the metropolitan region may have introduced additional, uncontrolled variability in environmental exposure across participants, independent of municipality of residence. Species-level resolution within the genus Staphylococcus using short-read 16S rRNA V3–V4 sequencing is also inherently limited, as several staphylococcal species share highly similar sequences across this region, which can reduce classification accuracy relative to full-length 16S or whole-genome approaches [14, 15]. While the bioinformatic pipeline used here (RefSeq and Ribosomal Database Project [RDP] 16S databases) is widely applied in skin microbiome profiling, culture-based confirmation or long-read, full-length 16S sequencing would provide additional confidence in the species-level classifications reported and should be considered in future validation studies.
Conclusion
This exploratory study identified differences in the relative abundance of specific skin microbiome taxa among patients with AD residing in municipalities with distinct environmental profiles, particularly related to the greater representation of S. aureus in the metropolitan municipality. These findings generate a hypothesis regarding the interaction between the urban exposome and cutaneous dysbiosis in AD, which should be confirmed in larger studies with objective measurement of environmental exposure and control for disease severity.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We thank the participants of the study.
Medical Writing/Editorial Assistance
A generative artificial intelligence language tool (Claude, Anthropic, San Francisco, CA, USA) was used by the authors solely for language editing and revision of the English text; no funding was received for this assistance. The authors reviewed, edited, and take full responsibility for the entire content of the manuscript.
Author Contributions
Heloísa Silva de Avó Freixo: conceptualization, data curation, funding acquisition, investigation, methodology, and writing original draft. Hélio Amante Miot: formal analysis, project administration, validation, visualization, and writing review and editing. Marília Marufuji Ogawa: supervision and writing review and editing. Ivanka Miranda de Castro Martins: data curation. Vânia Rodrigues Leite e Silva: resources. Newton Andreo Filho: resources. Patrícia Santos Lopes: resources. Romualdo Morandi Filho: software. Ediléia Bagatin: project administration, validation, supervision, and writing – review and editing. All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship of this article, have read and approved the final version of the manuscript, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.
Funding
This study was supported by the Vichy Exposome Grant – Expertise L’Oréal, administered through the Fundação de Apoio à Universidade Federal de São Paulo (FapUNIFESP). The funder had no role in the study design, data collection, data analysis, interpretation of the data, or preparation of the manuscript. The Rapid Service Fee was waived.
Data Availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Conflict of Interest
Heloísa Silva de Avó Freixo, Hélio Amante Miot, Marília Marufuji Ogawa, Ivanka Miranda de Castro Martins, Vânia Rodrigues Leite e Silva, Newton Andreo Filho, Patrícia Santos Lopes and Romualdo Morandi Filho have nothing to disclose. Ediléia Bagatin is an Editorial Board member of Dermatology and Therapy. Ediléia Bagatin was not involved in the selection of peer reviewers for the manuscript nor any of the subsequent editorial decisions.
Ethical Approval
This study was performed in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments. The protocol was approved by the Research Ethics Committee of the Universidade Federal de São Paulo (CAAE: 64567022.4.3001.5411). Written informed consent was obtained from all adult participants and from the legal guardians of all participating children, who additionally provided written assent.
Footnotes
Prior Publication: The content of this manuscript is original and has not been previously published or presented, in whole or in part, at any meeting or in any other publication.
Publisher's Note
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Associated Data
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Supplementary Materials
Data Availability Statement
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.