Exploring the skin microbiome in atopic dermatitis pathogenesis and disease modification.

Inflammatory skin diseases, like atopic eczema (atopic dermatitis, AD), affect children and adults globally. In AD, the skin barrier is impaired on multiple levels. Underlying factors include genetic, chemical, immunological, and microbial components. Increased skin pH in AD is part of the altered microbial microenvironment that promotes overgrowth of the skin microbiome with Staphylococcus aureus (S. aureus). The secretion of virulence factors, like toxins and proteases, by S. aureus further aggravates the skin barrier deficiency and additionally off-balances the already skewed immune response. Skin commensal bacteria, however, can inhibit the growth and pathogenicity of S. aureus through quorum sensing systems. Therefore, restoring a healthy skin microbiome could contribute to remission induction in AD. This review discusses direct and indirect approaches to targeting the skin microbiome through modulation of the skin pH, UV treatment, and pre-, pro-, and postbiotics. Furthermore, exploratory techniques like skin microbiome transplantation, ozone therapy, and phage therapy are discussed. Finally, we summarize the latest findings on disease and microbiome modification through targeted immunomodulatory, systemic treatments and biologicals. We believe that targeting the skin microbiome should be considered a crucial component of successful AD treatment in the future.

Association of Skin Microbiome Dynamics With Radiodermatitis in Patients With Breast Cancer.

Importance: The interindividual differences in severity of acute radiation dermatitis are not well understood. To date, the pathomechanism and interplay of microbiome and radiodermatitis before and during treatment remain largely unknown. Objective: To assess the association of skin microbiome baseline composition and dynamics with severity of radiodermatitis in patients undergoing adjuvant radiotherapy for breast cancer. Design, Setting, and Participants: A longitudinal prospective pilot observational study was conducted between January 2017 and January 2019. Sequencing results were received in March 2021, and the data were analyzed from August 2021 to March 2023. This study was performed at an urban academic university cancer center. A total of 21 female patients with breast cancer after surgery were consecutively approached, of which 1 patient withdrew consent before the study started. Exposure: Adjuvant radiotherapy for breast cancer for 7 weeks. Main Outcomes and Measures: The main outcome was the association of baseline skin microbiome composition and its dynamics with the severity of radiodermatitis. A total of 360 skin microbiome samples from patients were analyzed, taken before, during, and after radiotherapy, from both the treated and contralateral healthy sides. The skin microbiome samples were analyzed using 16S (V1-V3) amplicon sequencing and quantitative polymerase chain reaction bacterial enumeration. Results: Twenty female patients with breast cancer after surgery who underwent radiotherapy enrolled in the study had a median (range) age of 61 (37-81) years. The median (range) body mass index of the patients was 24.2 (17.6-38.4). The 16S sequencing revealed that low (<5%) relative abundance of commensal skin bacteria (Staphylococcus epidermidis, Staphylococcus hominis, Cutibacterium acnes) at baseline composition was associated with the development of severe radiodermatitis with an accuracy of 100% (sensitivity and specificity of 100%, P < .001). Furthermore, in patients with severe radiodermatitis, quantitative polymerase chain reaction bacterial enumeration revealed a general non-species-specific overgrowth of skin bacterial load before the onset of severe symptoms. Subsequently, the abundance of commensal bacteria increased in severe radiodermatitis, coinciding with a decline in total bacterial load. Conclusions and Relevance: The findings of this observational study indicated a potential mechanism associated with the skin microbiome for the pathogenesis of severe radiodermatitis, which may be a useful biomarker for personalized prevention of radiodermatitis in patients undergoing adjuvant radiotherapy for breast cancer.

Benchmarking MicrobIEM - a user-friendly tool for decontamination of microbiome sequencing data.

BACKGROUND: Microbiome analysis is becoming a standard component in many scientific studies, but also requires extensive quality control of the 16S rRNA gene sequencing data prior to analysis. In particular, when investigating low-biomass microbial environments such as human skin, contaminants distort the true microbiome sample composition and need to be removed bioinformatically. We introduce MicrobIEM, a novel tool to bioinformatically remove contaminants using negative controls. RESULTS: We benchmarked MicrobIEM against five established decontamination approaches in four 16S rRNA amplicon sequencing datasets: three serially diluted mock communities (108-103 cells, 0.4-80% contamination) with even or staggered taxon compositions and a skin microbiome dataset. Results depended strongly on user-selected algorithm parameters. Overall, sample-based algorithms separated mock and contaminant sequences best in the even mock, whereas control-based algorithms performed better in the two staggered mocks, particularly in low-biomass samples (≤ 106 cells). We show that a correct decontamination benchmarking requires realistic staggered mock communities and unbiased evaluation measures such as Youden's index. In the skin dataset, the Decontam prevalence filter and MicrobIEM's ratio filter effectively reduced common contaminants while keeping skin-associated genera. CONCLUSIONS: MicrobIEM's ratio filter for decontamination performs better or as good as established bioinformatic decontamination tools. In contrast to established tools, MicrobIEM additionally provides interactive plots and supports selecting appropriate filtering parameters via a user-friendly graphical user interface. Therefore, MicrobIEM is the first quality control tool for microbiome experts without coding experience.

Combining 16S Sequencing and qPCR Quantification Reveals Staphylococcus aureus Driven Bacterial Overgrowth in the Skin of Severe Atopic Dermatitis Patients.

Atopic dermatitis (AD) is an inflammatory skin disease with a microbiome dysbiosis towards a high relative abundance of Staphylococcus aureus. However, information is missing on the actual bacterial load on AD skin, which may affect the cell number driven release of pathogenic factors. Here, we combined the relative abundance results obtained by next-generation sequencing (NGS, 16S V1-V3) with bacterial quantification by targeted qPCR (total bacterial load = 16S, S. aureus = nuc gene). Skin swabs were sampled cross-sectionally (n = 135 AD patients; n = 20 healthy) and longitudinally (n = 6 AD patients; n = 6 healthy). NGS and qPCR yielded highly inter-correlated S. aureus relative abundances and S. aureus cell numbers. Additionally, intra-individual differences between body sides, skin status, and consecutive timepoints were also observed. Interestingly, a significantly higher total bacterial load, in addition to higher S. aureus relative abundance and cell numbers, was observed in AD patients in both lesional and non-lesional skin, as compared to healthy controls. Moreover, in the lesional skin of AD patients, higher S. aureus cell numbers significantly correlated with the higher total bacterial load. Furthermore, significantly more severe AD patients presented with higher S. aureus cell number and total bacterial load compared to patients with mild or moderate AD. Our results indicate that severe AD patients exhibit S. aureus driven increased bacterial skin colonization. Overall, bacterial quantification gives important insights in addition to microbiome composition by sequencing.

Elderly and Patients with Large Breast Volume Have an Increased Risk of Seroma Formation after Mastectomy-Results of the SerMa Pilot Study.

The collective of the SerMa pilot study included 100 cases of primary breast cancer or Carcinoma in situ who had undergone a mastectomy procedure with or without reconstruction of the breast using an implant or expander at Augsburg University Hospital between 12/2019 and 12/2022. The study aimed to investigate possible causes of seroma formation; reported here are the clinicopathological correlations between seroma formation and tumor biology and surgical procedures. Seroma occurred significantly more often in patients with older age (median patient age in cases with seroma was 73 years vs. 52 years without seroma; p < 0.001). In addition, patients with larger mastectomy specimen were significantly more likely to develop seroma (median ablation weight in cases with seroma 580 g vs. 330 g without seroma; p < 0.001). Other significant parameters for seroma formation were BMI (p = 0.005), grading (p = 0.015) and tumor size (p = 0.036). In addition, with insertion of implant or expander, a seroma occurred significantly less frequently (p < 0.001). In a binary logistic regression, age in particular was confirmed as a significant risk factor. In contrast, tumor biological characteristics, number of lymph nodes removed or affected showed no significant effect on seroma formation. The present study shows the need for patient education about the development of seroma in particular in older patients and patients with large breast volumes within the preoperative surgical clarification. These clinicopathological data support the previously published results hypothesizing that seroma formation is related to autoimmune/inflammatory processes and will be tested on a larger collective in the planned international multicenter SerMa study.

Spatial transcriptomics combined with single-cell RNA-sequencing unravels the complex inflammatory cell network in atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD) is the most common chronic inflammatory skin disease with complex pathogenesis for which the cellular and molecular crosstalk in AD skin has not been fully understood. METHODS: Skin tissues examined for spatial gene expression were derived from the upper arm of 6 healthy control (HC) donors and 7 AD patients (lesion and nonlesion). We performed spatial transcriptomics sequencing to characterize the cellular infiltrate in lesional skin. For single-cell analysis, we analyzed the single-cell data from suction blister material from AD lesions and HC skin at the antecubital fossa skin (4 ADs and 5 HCs) and full-thickness skin biopsies (4 ADs and 2 HCs). The multiple proximity extension assays were performed in the serum samples from 36 AD patients and 28 HCs. RESULTS: The single-cell analysis identified unique clusters of fibroblasts, dendritic cells, and macrophages in the lesional AD skin. Spatial transcriptomics analysis showed the upregulation of COL6A5, COL4A1, TNC, and CCL19 in COL18A1-expressing fibroblasts in the leukocyte-infiltrated areas in AD skin. CCR7-expressing dendritic cells (DCs) showed a similar distribution in the lesions. Additionally, M2 macrophages expressed CCL13 and CCL18 in this area. Ligand-receptor interaction analysis of the spatial transcriptome identified neighboring infiltration and interaction between activated COL18A1-expressing fibroblasts, CCL13- and CCL18-expressing M2 macrophages, CCR7- and LAMP3-expressing DCs, and T cells. As observed in skin lesions, serum levels of TNC and CCL18 were significantly elevated in AD, and correlated with clinical disease severity. CONCLUSION: In this study, we show the unknown cellular crosstalk in leukocyte-infiltrated area in lesional skin. Our findings provide a comprehensive in-depth knowledge of the nature of AD skin lesions to guide the development of better treatments.

Th2/Th17 cell associated cytokines found in seroma fluids after breast cancer surgery.

PURPOSE: The development of a seroma after breast cancer surgery is a common postoperative complication seen after simple mastectomy and axillary surgery. We could recently demonstrate that breast cancer patients undergoing a simple mastectomy with subsequent seroma formation developed a T-helper cell increase within the aspirated fluid measured by flow cytometry. The same study revealed a Th2 and/or a Th17 immune response in peripheral blood and seroma fluid of the same patient. Based on these results and within the same study population, we now analyzed the Th2/Th17 cell associated cytokine content as well as the best known clinical important cytokine IL-6. METHODS: Multiplex cytokine measurements (IL-4, IL-5, IL-13, IL-10, IL-17, and IL-22) were done on 34 seroma fluids (Sf) after fine needle aspiration of patients who developed a seroma after a simple mastectomy. Serum of the same patient (Sp) and that of healthy volunteers (Sc) were used as controls. RESULTS: We found the Sf to be highly cytokine rich. Almost all analyzed cytokines were significantly higher in abundance in the Sf compared to Sp and Sc, especially IL-6, which promotes Th17 differentiation as well as suppresses Th1 differentiation in favor of Th2 development. CONCLUSION: Our Sf cytokine measurements reflect a local immune event. In contrast, former study results on T-helper cell populations in both Sf and Sp tend to demonstrate a systemic immune process.

Atopic dermatitis: Correlation of distinct risk factors with age of onset in adulthood compared to childhood.

BACKGROUND: Atopic dermatitis (AD) has long been regarded as a primarily pediatric disease. However, there is growing evidence for a high rate of adult-onset AD. We aimed to characterize factors associated with adult-onset versus childhood-onset AD and controls. METHODS: We analyzed cross-sectional data of the CK-CARE-ProRaD cohorts Bonn, Augsburg, Davos, Zürich of 736 adult patients stratified by age of AD onset (childhood-onset <18 years: 76.4% (subsets: 0 to 2; ≥2 to 6; ≥7 to 11; ≥12 to 18); adult-onset ≥18 years: 23.6% (subsets: ≥18 to 40; ≥41 to 60; ≥61) and 167 controls (91 atopic, 76 non-atopic)). RESULTS: We identified active smoking to be associated with adult-onset AD versus controls (adjusted Odds Ratio (aOR) = 5.54 [95% Confidence Interval: 1.06-29.01] vs. controlsnon-atopic , aOR = 4.03 [1.20-13.45] vs. controlsatopic ). Conjunctivitis showed a negative association versus controlsatopic (aOR = 0.36 [0.14-0.91]). Food allergy (aOR = 2.93 [1.44-5.96]), maternal food allergy (aOR = 9.43 [1.10-80.95]), palmar hyperlinearity (aOR = 2.11 [1.05-4.25]), and academic background (aOR = 2.14 [1.00-4.54]) increased the odds of childhood-onset AD versus controlsatopic . Shared AD-associated factors were maternal AD (4-34x), increased IgE (2-20x), atopic stigmata (2-3x) with varying effect sizes depending on AD onset and control group. Patients with adult-compared to childhood-onset had doubled odds of allergic rhinitis (aOR = 2.15 [1.12-4.13]), but reduced odds to feature multiple (3-4) atopic comorbidities (aOR = 0.34 [0.14-0.84]). Adult-onset AD, particularly onset ≥61 years, grouped mainly in clusters with low contributions of personal and familial atopy and high frequencies of physical inactivity, childhood-onset AD, particularly infant-onset, mainly in "high-atopic"-clusters. CONCLUSIONS: The identified associated factors suggest partly varying endo- and exogeneous mechanisms underlying adult-onset versus childhood-onset AD. Our findings might contribute to better assessment of the individual risk to develop AD throughout life and encourage prevention by non-smoking and physical activity as modifiable lifestyle factors.

Skin microbiome and its association with host cofactors in determining atopic dermatitis severity.

BACKGROUND: Atopic dermatitis (AD) is a heterogeneous, chronic inflammatory skin disease linked to skin microbiome dysbiosis with reduced bacterial diversity and elevated relative abundance of Staphylococcus aureus (S. aureus). OBJECTIVES: We aimed to characterize the yet incompletely understood association between the skin microbiome and patients' demographic and clinical cofactors in relation to AD severity. METHODS: The skin microbiome in 48 adult moderate-to-severe AD patients was investigated using next-generation deep sequencing (16S rRNA gene, V1-V3 region) followed by denoising (DADA2) to obtain amplicon sequence variant (ASV) composition. RESULTS: In lesional skin, AD severity was associated with S. aureus relative abundance (rS  = 0.53, p < 0.001) and slightly better with the microbiome diversity measure Evenness (rS  = -0.58, p < 0.001), but not with Richness. Multiple regression confirmed the association of AD severity with microbiome diversity, including Shannon (in lesional skin, p < 0.001), Evenness (in non-lesional skin, p = 0.015) or S. aureus relative abundance (p < 0.012), and with patient's IgE levels (p < 0.001), race (p < 0.032), age (p < 0.034) and sex (p = 0.012). The lesional model explained 62% of the variation in AD severity, and the non-lesional model 50% of the variation. CONCLUSIONS: Our results specify the frequently reported "reduced diversity" of the AD-related skin microbiome to reduced Evenness, which was in turn mainly driven by S. aureus relative abundance, rather than to a reduced microbiome Richness. Finding associations between AD severity, the skin microbiome and patient's cofactors is a key aspect in developing new personalized AD treatments, particularly those targeting the AD microbiome.

An Overview of the Latest Metabolomics Studies on Atopic Eczema with New Directions for Study.

Atopic eczema (AE) is an inflammatory skin disorder affecting approximately 20% of children worldwide and early onset can lead to asthma and allergies. Currently, the mechanisms of the disease are not fully understood. Metabolomics, the analysis of small molecules in the skin produced by the host and microbes, opens a window to observe the mechanisms of the disease which then may lead to new drug targets for AE treatment. Here, we review the latest advances in AE metabolomics, highlighting both the lipid and non-lipid molecules, along with reviewing the metabolites currently known to reside in the skin.

Molecular Assessment of Staphylococcus Aureus Strains in STAT3 Hyper-IgE Syndrome Patients.

Hyper-IgE syndromes (HIES) are a group of inborn errors of immunity (IEI) caused by monogenic defects such as in the gene STAT3 (STAT3-HIES). Patients suffering from HIES show an increased susceptibility to Staphylococcus aureus (S. aureus) including skin abscesses and pulmonary infections. To assess if the underlying immune defect of STAT3-HIES patients influences the resistance patterns, pathogenicity factors or strain types of S. aureus. We characterized eleven S. aureus strains isolated from STAT3-HIES patients (n = 4) by whole genome sequencing (WGS) to determine presence of resistance and virulence genes. Additionally, we used multi-locus sequence typing (MLST) and protein A (spa) typing to classify these isolates. Bacterial isolates collected from this cohort of STAT3-HIES patients were identified as common spa types in Germany. Only one of the isolates was classified as methicillin-resistant S. aureus (MRSA). For one STAT3 patient WGS illustrated that infection and colonization occurred with different S. aureus isolates rather than one particular clone. The identified S. aureus carriage profile on a molecular level suggests that S. aureus strain type in STAT3-HIES patients is determined by local epidemiology rather than the underlying immune defect highlighting the importance of microbiological assessment prior to antibiotic treatment.

Seroma after Simple Mastectomy in Breast Cancer-The Role of CD4+ T Helper Cells and the Evidence as a Possible Specific Immune Process.

Seroma development after breast cancer surgery is the most common postoperative complication seen after mastectomy but neither its origin nor its cellular composition is known. To investigate the assumption of immunological significance, one of the first aims of this pilot study is to describe the cellular content of collected seroma fluids and its corresponding serum in patients with simple mastectomy after needle aspiration, as well as the serum of healthy controls. The content of red blood cells (RBC) was measured by haemato-counter analyses, and the lymphocyte identification/quantification was conducted by flow cytometry analyses in seroma fluid (SFl) and the sera of patients (PBp) as well as controls (PBc). Significantly lower numbers of RBCs were measured in SFl. Cytotoxic T cells are significantly reduced in SFl, whereas T helper (Th) cells are significantly enriched compared to PBp. Significantly higher numbers of Th2 cells were found in SFl and PBp compared to PBc. The exact same pattern is seen when analyzing the Th17 subgroup. In conclusion, in contrast to healthy controls, significantly higher Th2 and Th17 cell subgroup-mediated immune responses were measured in seroma formations and were further confirmed in the peripheral blood of breast cancer (including DCIS) patients after simple mastectomy. This could lead to the assumption of a possible immunological cause for the origin of a seroma.

Complete and Draft Genome Sequences of 48 Staphylococcus aureus Isolates Obtained from Atopic Dermatitis Patients and Healthy Controls.

Staphylococcus aureus is a widely distributed, opportunistic pathogen and has been linked to the human skin disease atopic dermatitis (AD). Here, we present 44 complete and 4 draft genome sequences of S. aureus strains isolated from the nose and skin of AD patients and healthy controls from a German study cohort.

Microbiome of Barrier Organs in Allergy: Who Runs the World? Germs!

Over the last few decades, allergic diseases have been steadily increasing worldwide, a phenomenon that is not yet completely understood. Recent evidence, however, suggests that alterations in the microbiome may be a contributing factor. The microbiome refers to all microorganisms in a habitat including bacteria, fungi, and viruses. Using modern sequencing technologies, we are now capable of detecting and analyzing the human microbiome in more detail than ever before. Epidemiological and experimental studies have indicated that a complex intestinal microbiome supports the development of the immune system during childhood, thus providing protection from allergic diseases, including food allergy. The microbiome becomes an important part of human physiology and forms dynamic relationships with our various barrier systems. For example, bacterial dysbiosis is a hallmark of atopic eczema and correlates with disease progression. Similarly, the lung and nasopharyngeal microbiome is altered in patients with asthma and allergic rhinitis. While these results are interesting, the underlying mechanisms are still unclear and need to be investigated with functional studies. This review gives a short overview of the terminology and methods used in microbiome research before highlighting results concerning the lung, skin, and intestinal microbiome in allergic diseases.

Machine Learning-Based Deep Phenotyping of Atopic Dermatitis: Severity-Associated Factors in Adolescent and Adult Patients.

IMPORTANCE: Atopic dermatitis (AD) is the most common chronic inflammatory skin disease and is driven by a complex pathophysiology underlying highly heterogeneous phenotypes. Current advances in precision medicine emphasize the need for stratification. OBJECTIVE: To perform deep phenotyping and identification of severity-associated factors in adolescent and adult patients with AD. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional data from the baseline visit of a prospective longitudinal study investigating the phenotype among inpatients and outpatients with AD from the Department of Dermatology and Allergy of the University Hospital Bonn enrolled between November 2016 and February 2020. MAIN OUTCOMES AND MEASURES: Patients were stratified by severity groups using the Eczema Area and Severity Index (EASI). The associations of 130 factors with AD severity were analyzed applying a machine learning-gradient boosting approach with cross-validation-based tuning as well as multinomial logistic regression. RESULTS: A total of 367 patients (157 male [42.8%]; mean [SD] age, 39 [17] years; 94% adults) were analyzed. Among the participants, 177 (48.2%) had mild disease (EASI ≤7), 120 (32.7%) had moderate disease (EASI >7 and ≤ 21), and 70 (19.1%) had severe disease (EASI >21). Atopic stigmata (cheilitis: odds ratio [OR], 8.10; 95% CI, 3.35-10.59; white dermographism: OR, 4.42; 95% CI, 1.68-11.64; Hertoghe sign: OR, 2.75; 95% CI, 1.27-5.93; nipple eczema: OR, 4.97; 95% CI, 1.56-15.78) was associated with increased probability of severe AD, while female sex was associated with reduced probability (OR, 0.30; 95% CI, 0.13-0.66). The probability of severe AD was associated with total serum immunoglobulin E levels greater than 1708 IU/mL and eosinophil values greater than 6.8%. Patients aged 12 to 21 years or older than 52 years had an elevated probability of severe AD; patients aged 22 to 51 years had an elevated probability of mild AD. Age at AD onset older than 12 years was associated with increased probability of severe AD up to a peak at 30 years; age at onset older than 33 years was associated with moderate to severe AD; and childhood onset was associated with mild AD (peak, 7 years). Lifestyle factors associated with severe AD were physical activity less than once per week and (former) smoking. Alopecia areata was associated with moderate (OR, 5.23; 95% CI, 1.53-17.88) and severe (OR, 4.67; 95% CI, 1.01-21.56) AD. Predictive performance of machine learning-gradient boosting vs multinomial logistic regression differed only slightly (mean multiclass area under the curve value: 0.71 [95% CI, 0.69-0.72] vs 0.68 [0.66-0.70], respectively). CONCLUSIONS AND RELEVANCE: The associations found in this cross-sectional study among patients with AD might contribute to a deeper disease understanding, closer monitoring of predisposed patients, and personalized prevention and therapy.

The power and potential of BIOMAP to elucidate host-microbiome interplay in skin inflammatory diseases.

The two most common chronic inflammatory skin diseases are atopic dermatitis (AD) and psoriasis. The underpinnings of the remarkable degree of clinical heterogeneity of AD and psoriasis are poorly understood and, as a consequence, disease onset and progression are unpredictable and the optimal type and time point for intervention are as yet unknown. The BIOMAP project is the first IMI (Innovative Medicines Initiative) project dedicated to investigating the causes and mechanisms of AD and psoriasis and to identify potential biomarkers responsible for the variation in disease outcome. The consortium includes 7 large pharmaceutical companies and 25 non-industry partners including academia. Since there is mounting evidence supporting an important role for microbial exposures and our microbiota as factors mediating immune polarization and AD and psoriasis pathogenesis, an entire work package is dedicated to the investigation of skin and gut microbiome linked to AD or psoriasis. The large collaborative BIOMAP project will enable the integration of patient cohorts, data and knowledge in unprecedented proportions. The project has a unique opportunity with a potential to bridge and fill the gaps between current problems and solutions. This review highlights the power and potential of the BIOMAP project in the investigation of microbe-host interplay in AD and psoriasis.

A new era of atopic eczema research: Advances and highlights.

Atopic eczema (AE) is an inflammatory skin disease with involvement of genetic, immunological and environmental factors. One hallmark of AE is a skin barrier disruption on multiple, highly interconnected levels: filaggrin mutations, increased skin pH and a microbiome dysbiosis towards Staphylococcus aureus overgrowth are observed in addition to an abnormal type 2 immune response. Extrinsic factors seem to play a major role in the development of AE. As AE is a first step in the atopic march, its prevention and appropriate treatment are essential. Although standard therapy remains topical treatment, powerful systemic treatment options emerged in the last years. However, thorough endotyping of the individual patients is still required for ideal precision medicine approaches in future. Therefore, novel microbial and immunological biomarkers were described recently for the prediction of disease development and treatment response. This review summarizes the current state of the art in AE research.

Enhanced Access to the Health-Related Skin Metabolome by Fast, Reproducible and Non-Invasive WET PREP Sampling.

Our skin influences our physical and mental health, and its chemical composition can reflect environmental and disease conditions. Therefore, through sampling the skin metabolome, we can provide a promising window into the mechanisms of the body. However, the broad application of skin metabolomics has recently been hampered by a lack of easy and widely applicable sampling methods. Here, we present a novel rapid, simple, and, most importantly, painless and non-invasive sampling technique suitable for clinical studies of fragile or weakened skin. The method is called WET PREP and is simply a lavage of the skin which focuses on capturing the metabolome. We systematically evaluate WET PREPs in comparison with the non-invasive method of choice in skin metabolomics, swab collection, using ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS2) on two complementary chromatographic columns (C18 reversed phase and hydrophilic interaction chromatography). We also integrate targeted analyses of key metabolites of skin relevance. Overall, WET PREP provides a strikingly more stable shared metabolome across sampled individuals, while also being able to capture unique individual metabolites with a high consistency in intra-individual reproducibility. With the exception of (phospho-)lipidomic studies, we recommend WET PREPs as the preferred skin metabolome sampling technique due to the quick preparation time, low cost, and gentleness for the patient.

[The skin microbiome-useful for diagnosis and therapy?] / Hautmikrobiom ­ Wertvoll für Diagnostik und Therapie?

BACKGROUND: Our skin is a very important and complex organ of the body. The microorganisms of the skin, the so-called microbiome, represent an important part of the healthy skin barrier and are influenced by various external and internal factors. AIM: The question to what extent the skin microbiome represents a diagnostic or even therapeutic target in the context of skin diseases is discussed. MATERIALS AND METHODS: A literature search was performed. RESULTS: Several diseases are associated with negative alterations of the skin microbiome. In atopic dermatitis, a correlation between severity and increased availability of Staphylococcus aureus is known, with a loss of bacterial diversity on the skin. In the future, S. aureus will not only be used as a diagnostic marker in atopic dermatitis, but also represents a promising target as a predictive marker for therapeutic success. The role of the skin microbiome in psoriasis has not yet been researched in depth. However, there is evidence that dysbiosis of the skin microbiome contributes to the course of psoriasis and that there is a disturbance in immune tolerance in patients. In the case of acne, the involvement of Cutibacterium acnes in the clinical picture is well known; however, recent findings show that it is not sufficient to identify the species, but certain characteristics of C. acnes strains are associated. CONCLUSION: Microbial biomarkers are currently only established in atopic dermatitis. For other diseases, this might be the case in the future; however combinations of microorganisms, single species and also strains with specific characteristics must be considered.

Skin pH-dependent Staphylococcus aureus abundance as predictor for increasing atopic dermatitis severity.

BACKGROUND: Atopic eczema (atopic dermatitis, AD) is characterized by disrupted skin barrier associated with elevated skin pH and skin microbiome dysbiosis, due to high Staphylococcus aureus loads, especially during flares. Since S aureus shows optimal growth at neutral pH, we investigated the longitudinal interplay between these factors and AD severity in a pilot study. METHOD: Emollient (with either basic pH 8.5 or pH 5.5) was applied double-blinded twice daily to 6 AD patients and 6 healthy (HE) controls for 8 weeks. Weekly, skin swabs for microbiome analysis (deep sequencing) were taken, AD severity was assessed, and skin physiology (pH, hydration, transepidermal water loss) was measured. RESULTS: Physiological, microbiome, and clinical results were not robustly related to the pH of applied emollient. In contrast to longitudinally stable microbiome in HE, S aureus frequency significantly increased in AD over 8 weeks. High S aureus abundance was associated with skin pH 5.7-6.2. High baseline S aureus frequency predicted both increase in S aureus and in AD severity (EASI and local SCORAD) after 8 weeks. CONCLUSION: Skin pH is tightly regulated by intrinsic factors and limits the abundance of S aureus. High baseline S aureus abundance in turn predicts an increase in AD severity over the study period. This underlines the importance and potential of sustained intervention regarding the skin pH and urges for larger studies linking skin pH and skin S aureus abundance to understand driving factors of disease progression.