Unraveling the complexity of atopic dermatitis: The CK-CARE approach toward precision medicine

A quantitative systems pharmacology workflow toward optimal design and biomarker stratification of atopic dermatitis clinical trials

BACKGROUND

The development of atopic dermatitis (AD) drugs is challenged by many disease phenotypes and trial design options, which are hard to explore experimentally.

OBJECTIVE

We aimed to optimize AD trial design using simulations.

METHODS

We constructed a quantitative systems pharmacology model of AD and standard of care (SoC) treatments and generated a phenotypically diverse virtual population whose parameter distribution was derived from known relationships between AD biomarkers and disease severity and calibrated using disease severity evolution under SoC regimens.

RESULTS

We applied this workflow to the immunomodulator OM-85, currently being investigated for its potential use in AD, and calibrated the investigational treatment model with the efficacy profile of an existing trial (thereby enriching it with plausible marker levels and dynamics). We assessed the sensitivity of trial outcomes to trial protocol and found that for this particular example the choice of end point is more important than the choice of dosing regimen and patient selection by model-based responder enrichment could increase the expected effect size. A global sensitivity analysis revealed that only a limited subset of baseline biomarkers is needed to predict the drug response of the full virtual population.

CONCLUSIONS

This AD quantitative systems pharmacology workflow built around knowledge of marker-severity relationships as well as SoC efficacy can be tailored to specific development cases to optimize several trial protocol parameters and biomarker stratification and therefore has promise to become a powerful model-informed AD drug development and personalized medicine tool.

The ability of biomarkers to assess the severity of atopic dermatitis

Background

To develop precision medicine for atopic dermatitis (AD), it is critical to establish relevant biomarkers. However, the characteristics of various biomarkers have not been fully understood. We previously carried out the Biomarkers to Predict Clinical Improvement of AD in Patients Treated with Dupilumab (B-PAD) study, a comprehensive nationwide study in Japan, to explore biomarkers for AD.

Objective

The aim of this study is to find biomarkers associated with objective and subjective clinical findings in patients with moderate-to-severe AD based on the B-PAD study and to identify biomarkers sensitive enough to assess the severity of AD.

Methods

We performed the B-PAD study as a consortium composed of 19 medical facilities in Japan, enrolling 110 patients with moderate-to-severe AD. We evaluated the Eczema Area and Severity Index (EASI) for objective assessment as well as the Patient-Oriented Eczema Measure (POEM) and a numeric rating scale for pruritus (pruritis-NRS) for subjective assessment, measuring 19 biomarkers at baseline.

Results

We found that 12, 6, and 7 biomarkers showed significant and positive associations with the EASI, POEM, and pruritis-NRS, respectively. Most of the biomarkers associated with either the POEM or the pruritis-NRS were included among the biomarkers associated with EASI. Of the biomarkers examined, CCL26/eotaxin-3 and SCCA2 were the most capable of assessing severity for EASI, as shown by the 2 kinds of receiver operating characteristic analyses, respectively, whereas lactate dehydrogenase was the best for both the POEM and pruritis-NRS, again using the 2 analyses.

Conclusion

We found biomarkers associated with the EASI, POEM, and pruritis-NRS, respectively, based on the B-PAD study. Moreover, we identified CCL26/eotaxin-3 and/or SCCA2 as the biomarkers having the greatest ability to assess severity in the EASI; lactate dehydrogenase did the same for the POEM and pruritis-NRS. These findings will be useful in treating patients with moderate-to-severe AD.

Development of a clinical algorithm to predict phenotypic switches between atopic dermatitis and psoriasis (the "Flip-Flop" phenomenon)

BACKGROUND

Atopic dermatitis (AD) and psoriasis vulgaris (PV) are almost mutually exclusive diseases with different immune polarizations, mechanisms and therapeutic targets. Switches to the other disease ("Flip-Flop" [FF] phenomenon) can occur with or without systemic treatment and are often referred to as paradoxical reactions under biological therapy.

METHODS

The objective was to develop a diagnostic algorithm by combining clinical criteria of AD and PV to identify FF patients. The algorithm was prospectively validated in patients enrolled in the CK-CARE registry in Bonn, Germany. Afterward, algorithm refinements were implemented based on machine learning.

RESULTS

Three hundred adult Caucasian patients were included in the validation study (n = 238 with AD, n = 49 with PV, n = 13 with FF; mean age 41.2 years; n = 161 [53.7%] female). The total FF scores of the PV and AD groups differed significantly from the FF group in the validation data (p < .001). The predictive mean generalized Youden-Index of the initial model was 78.9% [95% confidence interval 72.0%-85.6%] and the accuracy was 89.7%. Disease group-specific sensitivity was 100% (FF), 95.0% (AD), and 61.2% (PV). The specificity was 89.2% (FF), 100% (AD), and 100% (PV), respectively.

CONCLUSION

The FF algorithm represents the first validated tool to identify FF patients.

Immunoglobulin E autoantibodies in atopic dermatitis associate with Type-2 comorbidities and the atopic march

BACKGROUND

Autoreactive immunoglobulin E (IgE) antibodies to self-peptides within the epidermis have been identified in patients with atopic dermatitis (AD). Prevalence, concomitant diseases, patient characteristics, and risk factors of IgE autoantibody development remain elusive. We aimed to determine IgE autoantibodies in serum samples (n = 672) from well-characterized patients with AD and controls (1.2-88.9 years).

METHODS

Atopic dermatitis patients were sub-grouped in AD with comorbid Type-2 diseases ("AD + Type 2"; asthma, allergic rhinitis, food allergy, n = 431) or "solely AD" (n = 115). Also, subjects without AD but with Type-2 diseases ("atopic controls," n = 52) and non-atopic "healthy controls" (n = 74) were included. Total proteins from primary human keratinocytes were used for the immunoassay to detect IgE autoantibodies. Values were compared to already known positive and negative serum samples.

RESULTS

Immunoglobulin E autoantibodies were found in 15.0% (82/546) of all analyzed AD-patients. "AD + Type 2" showed a higher prevalence (16.4%) than "solely AD" (9.6%). "Atopic controls" (9.6%) were comparable with "solely AD" patients, while 2.7% of healthy controls showed IgE autoantibodies. Of those with high levels of IgE autoantibodies, 15 out of 16 were patients with "AD + Type 2". AD patients with IgE autoantibodies were younger than those without. Patients with IgE autoreactivity also displayed higher total serum IgE levels. Factors that affected IgE autoantibody development were as follows: birth between January and June, cesarean-section and diversity of domestic pets.

CONCLUSIONS

Immunoglobulin E autoantibodies in AD seem to associate with the presence of atopic comorbidities and environmental factors. The potential value of IgE autoantibodies as a predictive biomarker for the course of AD, including the atopic march, needs further exploration.

Disease modification in inflammatory skin disorders: opportunities and challenges

Progress in understanding of the mechanisms underlying chronic inflammatory skin disorders, such as atopic dermatitis and psoriasis vulgaris, has led to new treatment options with the primary goal of alleviating symptoms. In addition, this knowledge has the potential to inform on new strategies aimed at inducing deep and therapy-free remission, that is, disease modification, potentially impacting on associated comorbidities. However, to reach this goal, key areas require further exploration, including the definitions of disease modification and disease activity index, further understanding of disease mechanisms and systemic spillover effects, potential windows of opportunity, biomarkers for patient stratification and successful intervention, as well as appropriate study design. This Perspective article assesses the opportunities and challenges in the discovery and development of disease-modifying therapies for chronic inflammatory skin disorders.

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.

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 (r_S  = 0.53, p < 0.001) and slightly better with the microbiome diversity measure Evenness (r_S  = -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.

Biomarkers associated with the development of comorbidities in patients with atopic dermatitis: A systematic review

Biomarkers associated with the development of comorbidities in atopic dermatitis (AD) patients have been reported, but have not yet been systematically reviewed. Seven electronic databases were searched, from database inception to September 2021. English language randomized controlled trials, prospective and retrospective cohort, and case-control studies that investigated the association between a biomarker and the development of comorbidities in AD patients were included. Two authors independently screened the records for eligibility, one extracted all data, and critically appraised the quality of studies and risk of bias. Fifty six articles met the inclusion criteria, evaluating 146 candidate biomarkers. The most frequently reported biomarkers were filaggrin mutations and allergen specific-IgE. Promising biomarkers include specific-IgE and/or skin prick tests predicting the development of asthma, and genetic polymorphisms predicting the occurrence of eczema herpeticum. The identified studies and biomarkers were highly heterogeneous, and associated with predominately moderate-to-high risk of bias across multiple domains. Overall, findings were inconsistent. High-quality studies assessing biomarkers associated with the development of comorbidities in people with AD are lacking. Harmonized datasets and independent validation studies are urgently needed.

Pro-Inflammatory versus Anti-Inflammatory cytokines in atopic dermatitis patients: A case control study

Atopic dermatitis (AD) is a chronic relapsing inflammatory skin disorder with significant morbidity and impairment of life quality. Prevalence is increasing around the world; therefore, intensive research is ongoing to understand the mechanisms of development of AD and offer new treatment options for AD patients.

AIMS

To investigate the association between Inflammatory (IL-17, TNF-α, IFN-γ) versus anti-Inflammatory Cytokines (IL-35, TGF-β) in AD patients.

PATIENTS AND METHODS

A case control study included 40 AD patients and 20 age- and sex-matched healthy subjects. Cases were subjected to full history taking and full dermatological examination. The assessment of disease severity was conducted by using SCORAD score. Assessment of inflammatory (IL-17, TNF-α, IFN-γ) and anti-Inflammatory Cytokines (IL-35, TGF-β) was performed by using ELISA technique.

RESULTS

The mean level of TNF-α, IL-17 was statistically significantly higher in the AD cases as compared with the control group. The mean level of TGF-β, Il-35, and IFN-γ was statistically significantly lower in the Atopic dermatitis cases as compared with the control group. There was statistically significant strong positive correlation between TNF-α with SCORAD score and IL-17 while there was statistically significant strong negative correlation between TNF-α with TGF-β and IL-35. There was statistically significant strong positive correlation between IL-17 with SCORAD score and TNF-α while there was statistically significant strong negative correlation between IL-17 with TGF-β and IL-35.

CONCLUSION

The current results could be used as a clue for the utilization of inflammatory (IL-17, TNF-α, IFN-γ) versus anti-inflammatory Cytokines (IL-35, TGF-β) in AD as a diagnostic biomarker for severity of cases with Atopic dermatitis. IL-17 plays an important role in the pathogenesis of AD, and IL-17 blocker may be used as a potential future treatment of AD.

Advances and highlights in biomarkers of allergic diseases

During the past years, there has been a global outbreak of allergic diseases, presenting a considerable medical and socioeconomical burden. A large fraction of allergic diseases is characterized by a type 2 immune response involving Th2 cells, type 2 innate lymphoid cells, eosinophils, mast cells, and M2 macrophages. Biomarkers are valuable parameters for precision medicine as they provide information on the disease endotypes, clusters, precision diagnoses, identification of therapeutic targets, and monitoring of treatment efficacies. The availability of powerful omics technologies, together with integrated data analysis and network‐based approaches can help the identification of clinically useful biomarkers. These biomarkers need to be accurately quantified using robust and reproducible methods, such as reliable and point‐of‐care systems. Ideally, samples should be collected using quick, cost‐efficient and noninvasive methods. In recent years, a plethora of research has been directed toward finding novel biomarkers of allergic diseases. Promising biomarkers of type 2 allergic diseases include sputum eosinophils, serum periostin and exhaled nitric oxide. Several other biomarkers, such as pro‐inflammatory mediators, miRNAs, eicosanoid molecules, epithelial barrier integrity, and microbiota changes are useful for diagnosis and monitoring of allergic diseases and can be quantified in serum, body fluids and exhaled air. Herein, we review recent studies on biomarkers for the diagnosis and treatment of asthma, chronic urticaria, atopic dermatitis, allergic rhinitis, chronic rhinosinusitis, food allergies, anaphylaxis, drug hypersensitivity and allergen immunotherapy. In addition, we discuss COVID‐19 and allergic diseases within the perspective of biomarkers and recommendations on the management of allergic and asthmatic patients during the COVID‐19 pandemic.

Altered serum phospholipids in atopic dermatitis and association with clinical status

Circulating phospholipids have been considered as biomarkers and therapeutic targets in multiple disorders. Atopic dermatitis (AD) is the most common inflammatory skin disease. Although there are numerous studies having addressed stratum corneum lipids in the context of epidermal barrier, little is known about the circulating lipids in patients with AD. In this study, we explored the changes of serum phospholipids in AD using liquid chromatography coupled to tandem mass spectrometry and sought serum lipids’ contribution to clinical status. Several serum levels of phospholipids were altered in the AD group (n = 179) compared with that in healthy controls (n = 47) and patients without AD with atopic comorbidities (n = 22); lipids exhibiting the apparent changes included increased sphingosine, multiple variants of phosphatidylcholine, and decreased ceramide (16:0) in patients with AD. Moreover, serum levels of sphingosine correlated with the severity of AD, and sphingosine and ceramide(16:0) were also detected as the risk-increasing effect and risk-reduction effect of AD, respectively. In summary, alterations in the serum concentration of phospholipids are seen in patients with AD. Although more detailed investigations will be needed to evaluate the significance of the changes in circulating lipids in AD, these findings can provide, to our knowledge, previously unreported insight into AD’s pathogenesis and therapeutic strategies.

Predictive biomarker modeling of pediatric atopic dermatitis severity based on longitudinal serum collection

The pathogenesis of atopic dermatitis (AD) results from complex interactions between environmental factors, barrier defects, and immune dysregulation resulting in systemic inflammation. Therefore, we sought to characterize circulating inflammatory profiles in pediatric AD patients and identify potential signaling nodes which drive disease heterogeneity and progression. We analyzed a sample set of 87 infants that were at high risk for atopic disease based on atopic dermatitis diagnoses. Clinical parameters, serum, and peripheral blood mononuclear cells (PBMCs) were collected upon entry, and at one and four years later. Within patient serum, 126 unique analytes were measured using a combination of multiplex platforms and ultrasensitive immunoassays. We assessed the correlation of inflammatory analytes with AD severity (SCORAD). Key biomarkers, such as IL-13 (rmcorr=0.47) and TARC/CCL17 (rmcorr=0.37), among other inflammatory signals, significantly correlated with SCORAD across all timepoints in the study. Flow cytometry and pathway analysis of these analytes implies that CD4 T cell involvement in type 2 immune responses were enhanced at the earliest time point (year 1) relative to the end of study collection (year 5). Importantly, forward selection modeling identified 18 analytes in infant serum at study entry which could be used to predict change in SCORAD four years later. We have identified a pediatric AD biomarker signature linked to disease severity which will have predictive value in determining AD persistence in youth and provide utility in defining core systemic inflammatory signals linked to pathogenesis of atopic disease.

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.

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.

Atopic dermatitis: an expanding therapeutic pipeline for a complex disease

Atopic dermatitis (AD) is a common chronic inflammatory skin disease with a complex pathophysiology that underlies a wide spectrum of clinical phenotypes. AD remains challenging to treat owing to the limited response to available therapies. However, recent advances in understanding of disease mechanisms have led to the discovery of novel potential therapeutic targets and drug candidates. In addition to regulatory approval for the IL-4Ra inhibitor dupilumab, the anti-IL-13 inhibitor tralokinumab and the JAK1/2 inhibitor baricitinib in Europe, there are now more than 70 new compounds in development. This Review assesses the various strategies and novel agents currently being investigated for AD and highlights the potential for a precision medicine approach to enable prevention and more effective long-term control of this complex disease.

Recent advances in understanding of the complex phenotype and mechanisms underlying atopic dermatitis (AD) have revealed multiple new potential targets for pharmacological intervention. Here, Bieber reviews therapeutic strategies and assesses the expanding pipeline for the therapy of AD, highlighting the potential for a precision medicine approach to the management of this complex disorder.

Atopic Eczema: Pathophysiological Findings as the Beginning of a New Era of Therapeutic Options

Atopic eczema (AE) is a chronic inflammatory disease hallmarked by intense pruritus and eczematous lesions. It depicts one of the most common skin diseases affecting a major part of children and several percentages of adults.Both pathogenesis and pathophysiology are based on complex orchestrated interactions of skin barrier defects, immunological changes, the environment, and an abundance of other contributing factors. Frequently, AE displays the starting point for other allergic diseases such as allergic asthma and rhinoconjunctivitis. Additionally, the risk of developing food allergy is increased. Furthermore, the disease is accompanied by a susceptibility to bacterial, fungal, and viral infections. The development of new therapies received great impetus by an ample research of the pathophysiological mechanisms, leading to a new era in the treatment of severe atopic eczema due to targeted treatments, e.g. the IL-4R alpha specific monoclonal antibody dupilumab.This article provides an overview of the causative and pathophysiological characteristics, the clinical and diagnostic aspects as well as current and future therapeutical possibilities focusing allergic aspects contributing to the course of the disease.

EAACI Biologicals Guidelines-dupilumab for children and adults with moderate-to-severe atopic dermatitis

Atopic dermatitis imposes a significant burden on patients, families and healthcare systems. Management is difficult, due to disease heterogeneity, co-morbidities, complexity in care pathways and differences between national or regional healthcare systems. Better understanding of the mechanisms has enabled a stratified approach to the management of atopic dermatitis, supporting the use of targeted treatments with biologicals. However, there are still many issues that require further clarification. These include the definition of response, strategies to enhance the responder rate, the duration of treatment and its regimen (in the clinic or home-based), its cost-effectiveness and long-term safety. The EAACI Guidelines on the use of dupilumab in atopic dermatitis follow the GRADE approach in formulating recommendations for each outcome and age group. In addition, future approaches and research priorities are discussed.

Biomarkers for diagnosis and prediction of therapy responses in allergic diseases and asthma

Modern health care requires a proactive and individualized response to diseases, combining precision diagnosis and personalized treatment. Accordingly, the approach to patients with allergic diseases encompasses novel developments in the area of personalized medicine, disease phenotyping and endotyping, and the development and application of reliable biomarkers. A detailed clinical history and physical examination followed by the detection of IgE immunoreactivity against specific allergens still represents the state of the art. However, nowadays, further emphasis focuses on the optimization of diagnostic and therapeutic standards and a large number of studies have been investigating the biomarkers of allergic diseases, including asthma, atopic dermatitis, allergic rhinitis, food allergy, urticaria and anaphylaxis. Various biomarkers have been developed by omics technologies, some of which lead to a better classification of distinct phenotypes or endotypes. The introduction of biologicals to clinical practice increases the need for biomarkers for patient selection, prediction of outcomes and monitoring, to allow for an adequate choice of the duration of these costly and long‐lasting therapies. Escalating healthcare costs together with questions about the efficacy of the current management of allergic diseases require further development of a biomarker‐driven approach. Here, we review biomarkers in diagnosis and treatment of asthma, atopic dermatitis, allergic rhinitis, viral infections, chronic rhinosinusitis, food allergy, drug hypersensitivity and allergen immunotherapy with a special emphasis on specific IgE, the microbiome and the epithelial barrier. In addition, EAACI guidelines on biologicals are discussed within the perspective of biomarkers.

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.

Outside-in hypothesis revisited: The role of microbial, epithelial, and immune interactions

OBJECTIVE

Our understanding of the origin of allergic diseases has increased in recent years, highlighting the importance of microbial dysbiosis and epithelial barrier dysfunction in affected tissues. Exploring the microbial-epithelial-immune crosstalk underlying the mechanisms of allergic diseases will allow the development of novel prevention and treatment strategies for allergic diseases.

DATA SOURCES

This review summarizes the recent advances in microbial, epithelial, and immune interactions in atopic dermatitis, allergic rhinitis, chronic rhinosinusitis, and asthma.

STUDY SELECTIONS

We performed a literature search, identifying relevant recent primary articles and review articles.

RESULTS

Dynamic crosstalk between the environmental factors and microbial, epithelial, and immune cells in the development of atopic dermatitis, allergic rhinitis, chronic rhinosinusitis, and asthma underlies the pathogenesis of these diseases. There is substantial evidence in the literature suggesting that environmental factors directly affect barrier function of the epithelium. In addition, T-helper 2 (T_H2) cells, type 2 innate lymphoid cells, and their cytokine interleukin 13 (IL-13) damage skin and lung barriers. The effects of environmental factors may at least in part be mediated by epigenetic mechanisms. Histone deacetylase activation by type 2 immune response has a major effect on leaky barriers and blocking of histone deacetylase activity corrects the defective barrier in human air-liquid interface cultures and mouse models of allergic asthma with rhinitis. We also present and discuss a novel device to detect and monitor skin barrier dysfunction, which provides an opportunity to rapidly and robustly assess disease severity.

CONCLUSION

A complex interplay between environmental factors, epithelium, and the immune system is involved in the development of systemic allergic diseases.