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.

IL-13, periostin and dipeptidyl-peptidase-4 reveal endotype-phenotype associations in atopic dermatitis.

BACKGROUND: The heterogeneous (endo)phenotypes of atopic dermatitis (AD) require precision medicine. Currently, systemic therapy is recommended to patients with an Eczema Area and Severity Index (EASI)≥16. Previous studies have demonstrated an improved treatment response to the anti-interleukin (IL)-13 antibody tralokinumab in AD subgroups with elevated levels of the IL-13-related biomarkers dipeptidyl-peptidase (DPP)-4 and periostin. METHODS: Herein, 373 AD patients aged≥12 years were stratified by IL-13high , periostinhigh and DPP-4high endotypes using cross-sectional data from the ProRaD cohort Bonn. "High" was defined as >80th quantile of 47 non-atopic controls. We analyzed endotype-phenotype associations using machine-learning gradient boosting compared to logistic regression. RESULTS: AD severity and eosinophils correlated with IL-13 and periostin levels. Correlations of IL-13 with EASI were stronger in patients with increased (rs=0.482) than with normal (rs=0.342) periostin levels. We identified eosinophilia>6% and an EASI range of 5.5-17 dependent on the biomarker combination to be associated with increasing probabilities of biomarkerhigh endotypes. Also patients with mild-to-low-moderate severity (EASI<16) featured increased biomarkers (IL-13high : 41%, periostinhigh : 48.4%, DPP-4high : 22.3%). Herthoge sign (adjusted Odds Ratio (aOR)=1.89, 95% Confidence Interval (CI) [1.14-3.14]) and maternal allergic rhinitis (aOR=2.79-4.47) increased the probability of an IL-13high -endotype, "dirty neck" (aOR=2.83 [1.32-6.07]), orbital darkening (aOR=2.43 [1.08-5.50]), keratosis pilaris (aOR=2.21 [1.1-4.42]) and perleche (aOR=3.44 [1.72-6.86]) of a DPP-4high -endotype. CONCLUSIONS: A substantial proportion of patients with EASI<16 featured high biomarker levels suggesting systemic impact of skin inflammation already below the current cut-off for systemic therapy. Our findings facilitate the identification of patients with distinct endotypes potentially linked to response to IL-13-targeted therapy.

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.