Early Epidemiologic and Immune Predictors of Atopic Dermatitis: Reduced Cord Blood Regulatory B10 Cells in the Munich Atopy Prediction Study (MAPS).

Abstract

A complex interaction between environmental and lifestyle factors, immune dysregulation, and skin barrier integrity is believed to contribute to the development of atopic dermatitis (AD). However, the precise mechanisms underlying disease onset in infants remain largely unclear. The "Munich Atopic Prediction Study" (MAPS) is a comprehensive clinical and biological investigation of a prospective birth cohort from Munich, Germany. Information on pregnancy, child development, environmental influences, parental exposure to potential allergens, as well as illnesses affecting both children and parents is gathered through questionnaires. This is complemented by thorough clinical examinations conducted by trained dermatologists, with a particular focus on allergies and skin health. Biomarker analyses were performed, for example, on cord blood immune cells using flow cytometry (FACS analysis). Maternal AD (aOR = 3.06, p = 0.020) and affected siblings (aOR = 4.80, p = 0.039) are associated with an increased risk of AD, whereas cold-remedy intake showed a protective association (aOR = 0.11, p = 0.047). Infants later diagnosed with AD (total 74 infants, AD n = 27, healthy n = 47) are characterized by reduced frequencies of CD4⁺ T cells (p = 0.0247) and increased B-cell counts (p = 0.0067). Moreover, for the first time, we could identify a significant reduction in regulatory B (Breg)-cell frequencies in these infants (p = 0.0015). Furthermore, our findings suggest that maternal allergen-specific immunotherapy may have a beneficial effect on the development and frequency of Breg cells (p = 0.0497). Our study identifies early immune alterations, particularly a reduction in cord blood Breg cells, as potential contributors to AD pathogenesis. Incorporating Breg-cell measurements into neonatal immune panels, along with key perinatal and familial risk factors, may enhance early risk stratification and enable more personalized prevention of atopic diseases.