Biomarkers for therapeutic response and adverse outcomes in atopic dermatitis: A systematic review.

INTRODUCTION AND

OBJECTIVES

Atopic dermatitis (AD) is a chronic, inflammatory cutaneous disease characterized by intense itch that affects approximately 20% of children and up to 10% of adults. Our systematic review aims to identify biomarkers with clinical significance for predicting response to systemic therapies and treatment-related adverse events (AEs) for AD patients.

MATERIALS AND

METHODS

A systematic search was conducted across the electronic databases Embase and MEDLINE from database inception to September 2024. All records were independently screened at both the title/abstract and full-text stages. Included articles were randomized controlled trials, cohort studies or case-control studies that reported relevant data for investigating associations between biomarkers and disease progression and/or change in disease activity over time. All discrepancies at any stage were resolved through adjudication by a senior reviewer.

RESULTS

We identified 28 papers evaluating biomarkers for treatment response and 11 for AEs. Across treatment response studies, biomarkers investigated included IgE, eosinophils, LDH, TARC, cytokines, genetic variants and the skin microbiome. Most studies investigated the association between biomarkers and dupilumab, while studies reporting associations between biomarkers and AEs were limited to dupilumab-related conjunctivitis and ocular surface disease (DAOSD). The primary findings on treatment response were inconsistent, demonstrating that while elevated LDH was associated with poorer response to dupilumab, neither IgE nor eosinophil count showed consistent predictive value. Regarding the association between biomarkers and AEs, IgE was identified as the most promising predictor of DAOSD.

CONCLUSIONS

Predicting therapeutic responses and identifying patients at risk of developing AEs will be increasingly important with an expanding range of treatment options for AD. Finding robust predictive biomarkers for AD, however, is complicated by its clinical heterogeneity and multifactorial aetiology. Collaborative projects, such as BIOMAP, hold great potential to advance precision medicine and enhance individualized care.