Transcriptomic evaluation of skin tape-strips in children with allergic asthma uncovers epidermal barrier dysfunction and asthma-associated biomarkers abnormalities.

INTRODUCTION: Tape-strips, a minimally invasive method validated for the evaluation of several skin diseases, may help identify asthma-specific biomarkers in the skin of children with allergic asthma. METHODS: Skin tape-strips were obtained and analyzed with RNA-Seq from children with moderate allergic asthma (MAA) (n = 11, mean age 7.00; SD = 1.67), severe allergic asthma (SAA) (n = 9, mean age 9.11; SD = 2.37), and healthy controls (HCs) (n = 12, mean age 7.36; SD = 2.03). Differentially expressed genes (DEGs) were identified by fold change ≥2 with a false discovery rate <0.05. Transcriptomic biomarkers were analyzed for their accuracy in distinguishing asthma from HCs, their relationships with asthma-related outcomes (exacerbation rate, lung function-FEV1, IOS-R5-20, and lung inflammation-FeNO), and their links to skin (barrier and immune response) and lung (remodeling, metabolism, aging) pathogenetic pathways. RESULTS: RNA-Seq captured 1113 in MAA and 2117 DEGs in SAA. Epidermal transcriptomic biomarkers for terminal differentiation (FLG/filaggrin), cell adhesion (CDH19, JAM2), lipid biosynthesis/metabolism (ACOT2, LOXL2) were significantly downregulated. Gene set variation analysis revealed enrichment of Th1/IFNγ pathways (p < .01). MAA and SAA shared downregulation of G-protein-coupled receptor (OR4A16, TAS1R3), upregulation of TGF-ß/ErbB signaling-related (ACVR1B, EGFR, ID1/2), and upregulation of mitochondrial-related (HIGD2A, VDAC3, NDUFB9) genes. Skin transcriptomic biomarkers correlated with the annualized exacerbation rate and with lung function parameters. A two-gene classifier (TSSC4-FAM212B) was able to differentiate asthma from HCs with 100% accuracy. CONCLUSION: Tape-strips detected epithelial barrier and asthma-associated signatures in normal-appearing skin from children with allergic asthma and may serve as an alternative to invasive approaches for evaluating asthma endotypes.

Having concomitant asthma phenotypes is common and independently relates to poor lung function in NHANES 2007-2012.

BACKGROUND: Evidence for distinct asthma phenotypes and their overlap is becoming increasingly relevant to identify personalized and targeted therapeutic strategies. In this study, we aimed to describe the overlap of five commonly reported asthma phenotypes in US adults with current asthma and assess its association with asthma outcomes. METHODS: Data from the National Health and Nutrition Examination Surveys (NHANES) 2007-2012 were used (n = 30,442). Adults with current asthma were selected. Asthma phenotypes were: B-Eos-high [if blood eosinophils (B-Eos) ≥ 300/mm3]; FeNO-high (FeNO ≥ 35 ppb); B-Eos&FeNO-low (B-Eos < 150/mm3 and FeNO < 20 ppb); asthma with obesity (AwObesity) (BMI ≥ 30 kg/m2); and asthma with concurrent COPD. Data were weighted for the US population and analyses were stratified by age (< 40 and ≥ 40 years old). RESULTS: Of the 18,619 adults included, 1059 (5.6% [95% CI 5.1-5.9]) had current asthma. A substantial overlap was observed both in subjects aged < 40 years (44%) and ≥ 40 years (54%). The more prevalent specific overlaps in both age groups were AwObesity associated with either B-Eos-high (15 and 12%, respectively) or B-Eos&FeNO-low asthma (13 and 11%, respectively). About 14% of the current asthma patients were "non-classified". Regardless of phenotype classification, having concomitant phenotypes was significantly associated with (adjusted OR, 95% CI) ≥ 2 controller medications (2.03, 1.16-3.57), and FEV1 < LLN (3.21, 1.74-5.94), adjusted for confounding variables. CONCLUSIONS: A prevalent overlap of commonly reported asthma phenotypes was observed among asthma patients from the general population, with implications for objective asthma outcomes. A broader approach may be required to better characterize asthma patients and prevent poor asthma outcomes.