Molecular diagnosis of causality in T cell mediated severe cutaneous adverse drug reactions

Background One of the most severe forms of T cell mediated cutaneous adverse drug reactions is ‘drug reaction with eosinophilia and systemic symptoms’ (DRESS), hence subsequent avoidance of the causal drug is imperative. However, attribution of drug culpability in DRESS is challenging and standard skin allergy tests are not recommended due to for patient safety reasons. We sought to identify potential biomarkers for development of a diagnostic test. Methods Peripheral blood mononuclear cells (PBMCs) from a ‘discovery’ cohort (n=5) challenged to drug or control were analysed for transcriptomic profile. A signature panel of genes was then tested in a validation cohort (n=6), and compared to tolerant controls and other inflammatory conditions which can clinically mimic DRESS. A scoring system to identify presence of drug hypersensitivity was developed based on gene expression alterations of this panel. Results Whole transcriptome analysis identified 4 major gene clusters including those regulating T cell activation via NFAT and cytokine receptor activity. 22 differentially expressed gene transcripts were identified as a DRESS signature including Type 1 interferon pathways and Th2 activation. The DRESS transcriptomic panel identified antibiotic-DRESS cases in a validation cohort but was not altered in other inflammatory conditions. Machine learning or differential expression selection of a biomarker panel showed high sensitivity and specificity (100% and 85.7-100% respectively) for identification of the culprit drug in DRESS. Conclusion Transcriptomic analysis of DRESS revealed important insights into the key activated pathways and identified a transcriptional signature which shows potential as a test with high sensitivity for drug culpability attribution.