Letter to the editor

Transcriptional determinants of individualized inflammatory responses at anatomically separate sites

The response to inhaled corticosteroids (ICS) in asthma is affected by the interplay of several factors. Among these, the role of the upper-airway microbiome has been scarcely investigated. We aimed to evaluate the association between the salivary, pharyngeal, and nasal microbiome with asthma exacerbations despite receipt of ICS.

Samples from 250 asthma patients from the Genomics and Metagenomics of Asthma Severity (GEMAS) study treated with ICS were analyzed. Control/case subjects were defined by the absence/presence of asthma exacerbations in the past 6 months despite being treated with ICS. The bacterial microbiota was profiled by sequencing the V3-V4 region of the 16S rRNA gene. Differences between groups were assessed by PERMANOVA and regression models adjusted for potential confounders. A false discovery rate (FDR) of 5% was used to correct for multiple comparisons. Classification models of asthma exacerbations despite ICS treatment were built with machine learning approaches based on clinical, genetic, and microbiome data.

In nasal and saliva samples, case subjects had lower bacterial diversity (Richness, Shannon, and Faith indices) than control subjects (.007 ≤ P ≤ .037). Asthma exacerbations accounted for 8% to 9% of the interindividual variation of the salivary and nasal microbiomes (.003 ≤ P ≤ .046). Three, 4, and 11 bacterial genera from the salivary, pharyngeal, and nasal microbiomes were differentially abundant between groups (4.09 × 10⁻¹² ≤ FDR ≤ 0.047). Integrating clinical, genetic, and microbiome data showed good discrimination for the development of asthma exacerbations despite receipt of ICS (AUC_training: 0.82 and AUC_validation: 0.77).

The diversity and composition of the upper-airway microbiome are associated with asthma exacerbations despite ICS treatment. The salivary microbiome has a potential application as a biomarker of asthma exacerbations despite receipt of ICS.

A major issue with the current management of psoriasis is our inability to predict treatment response.

Our aim was to evaluate the ability to use baseline molecular expression profiling to assess treatment outcome for patients with psoriasis.

We conducted a longitudinal study of 46 patients with chronic plaque psoriasis treated with anti-TNF agent etanercept, and molecular profiles were assessed in more than 200 RNA-seq samples.

We demonstrated correlation between clinical response and molecular changes during the course of the treatment, particularly for genes responding to IL-17A/TNF in keratinocytes. Intriguingly, baseline gene expressions in nonlesional, but not lesional, skin were the best marker of treatment response at week 12. We identified USP18, a known regulator of IFN responses, as positively correlated with Psoriasis Area and Severity Index (PASI) improvement (P = 9.8 × 10⁻⁴) and demonstrate its role in regulating IFN/TNF responses in keratinocytes. Consistently, cytokine gene signatures enriched in baseline nonlesional skin expression profiles had strong correlations with PASI improvement. Using this information, we developed a statistical model for predicting PASI75 (ie, 75% of PASI improvement) at week 12, achieving area under the receiver-operating characteristic curve value of 0.75 and up to 80% accurate PASI75 prediction among the top predicted responders.

Our results illustrate feasibility of assessing drug response in psoriasis using nonlesional skin and implicate involvement of IFN regulators in anti-TNF responses.

Many psoriasis patients treated with biologics do not achieve total skin clearance. These patients possess residual plaques despite ongoing biologic treatment. To elucidate mechanisms of plaque persistence despite overall good drug response, we studied 50 subjects: psoriasis patients with residual plaques treated with one of three different biologics, untreated patients, and healthy controls. Skin biopsies from all subjects were characterized using three methods: mRNA expression, histology, and FACS of hematopoietic skin cells. Although all three methods provided evidence of drug effect, gene expression analysis revealed the persistence of key psoriasis pathways in treated plaques, including granulocyte adhesion and diapedesis, T helper type17 activation pathway, and interferon signaling with no novel pathways emerging. Focal decreases in parakeratosis and keratinocyte proliferation and differential reduction in IL-17 producing CD103^– T cells, but no change in CD103⁺ tissue-resident memory T cells were observed. Of note, antitumor necrosis factor increased the interferon signaling pathway already present. Interestingly mast cells were the dominant source of IL-22 in all psoriasis subjects. These data suggest that while subtle differences can be observed in drug-treated plaques, underlying biologic mechanisms are similar to those present in untreated psoriatic lesions.