High-dimensional profiling clusters asthma severity by lymphoid and non-lymphoid status

Camiolo, Matthew; Zhou, Xiaoying; Oriss, Timothy B.; Yan, Qi; Gorry, Michael; Horne, William; Trudeau, John B.; Scholl, Kathryn; Chen, Wei; Kolls, Jay K.; Ray, Prabir; Weisel, Florian; Weisel, Nadine M.; Aghaeepour, Nima; Nadeau, Kari; Wenzel, Sally E.; Ray, Anuradha

doi:10.1016/j.celrep.2021.108974

Cited by 35 publications

(39 citation statements)

References 75 publications

(85 reference statements)

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“…In our recent work with the IMSA cohort, we identified a subset of patients with SA characterized by enrichment of IFN-γ + T cells in their BAL fluid in whom IL-18 may be an upstream regulator ( 52 ). It is important to note that these patients also displayed concomitant T2 inflammation, which was indistinguishable from those without the high T1 phenotype.…”

Section: Discussionmentioning

confidence: 99%

Machine learning implicates the IL-18 signaling axis in severe asthma

Camiolo¹,

Zhou²,

Wei³

et al. 2021

JCI Insight

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Asthma is a common disease with profoundly variable natural history and patient morbidity.Heterogeneity has long been appreciated and much work has focused on identifying subgroups of patients with similar pathobiological underpinnings. Previous studies of the Severe Asthma Research Program (SARP) cohort linked gene expression changes to specific clinical and physiologic characteristics. While invaluable for hypothesis generation, these data include extensive candidate gene lists that complicate target identification and validation. In this analysis, we performed unsupervised clustering of the SARP cohort using bronchial epithelial cell gene expression data, identifying a transcriptional signature for participants suffering exacerbation prone asthma with impaired lung function. Clinically, participants in this asthma cluster exhibited a mixed inflammatory process and bore transcriptional hallmarks of nuclear factor kappa B (NF-κB) and activator protein 1 (AP-1) activation despite high corticosteroid exposure. Using supervised machine learning, we found a set of 31 genes that classified patients with high accuracy and could reconstitute clinical and transcriptional hallmarks of our patient clustering in an external cohort. Of these genes, IL18R1 (IL-18 Receptor 1) negatively associated with lung function and was highly expressed in the most severe patient cluster. We validated IL18R1 protein expression in lung tissue and identified downstream NF-κB and AP-1 activity, supporting IL-18 signaling in severe asthma pathogenesis and highlighting this approach for gene/pathway discovery.

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Section: Discussionmentioning

confidence: 99%

Machine learning implicates the IL-18 signaling axis in severe asthma

Camiolo¹,

Zhou²,

Wei³

et al. 2021

JCI Insight

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“…Applying mass cytometry and machine learning to BAL cells from corticosteroid‐resistant asthma generated two clusters: one enriched in IL‐4+ innate immune cells and another dominated by IFN‐γ+ T cells, including tissue‐resident memory cells. The immune cell linkage developed through Exploratory Matrices (ICLite) algorithm showed signatures of mitosis and IL‐7 signalling in CD206‐FcεRI+CD127+IL‐4+ innate cells in the first cluster, and adaptive immune responses in T cells in the other 84 …”

Section: Precision Medicine In Asthma—biomarkers and Novel Toolsmentioning

confidence: 99%

“…from corticosteroid-resistant asthma generated two clusters: one enriched in IL-4+ innate immune cells and another dominated by IFN-γ+ T cells, including tissue-resident memory cells. The immune cell linkage developed through Exploratory Matrices (ICLite) algorithm showed signatures of mitosis and IL-7 signalling in CD206-FcεRI+CD127+IL-4+ innate cells in the first cluster, and adaptive immune responses in T cells in the other 84. Merged Affinity Network Association Clustering (MANAclust) is a coding-free, automated pipeline enabling integration of categorical and numeric data spanning clinical and multi-omic profiles for unsupervised clustering to identify disease subsets.…”

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confidence: 99%

Advances and highlights in asthma in 2021

Agache

Eguiluz‐Gracia

Cojanu

et al. 2021

Allergy

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Last year brought a significant advance in asthma management, unyielding to the pressure of the pandemics. Novel key findings in asthma pathogenesis focus on the resident cell compartment, epigenetics and the innate immune system. The precision immunology unbiased approach was supplemented with novel tools and greatly facilitated by the use of artificial intelligence. Several randomised clinical trials and good quality realworld evidence shed new light on asthma treatment and supported the revision of several asthma guidelines (GINA, Expert Panel Report 3, ERS/ATS guidelines on severe asthma) and the conception of new ones (EAACI Guidelines for the use of biologicals in severe asthma). Integrating asthma management within the broader context of Planetary Health has been put forward. In this review, recently published articles and clinical trials are summarised and discussed with the goal to provide clinicians and researchers with a concise update on asthma research from a translational perspective.

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“… 51 Importantly, our recent study of human severe asthma has identified lung macrophages expressing the Type 2 cytokine IL-4 in a subset of these patients whose airways were enriched in IL-4+ innate immune cells. 52 It stands to reason, therefore, that tolerance induces a contraction of both DC and macrophage numbers in the lungs.…”

Section: Discussionmentioning

confidence: 99%

Early life exposure to house dust mite allergen prevents experimental allergic asthma requiring mitochondrial H2O2

Yuan

Chen

et al. 2022

Mucosal Immunology

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Immune tolerance to allergens in early-life decreases the risk for asthma in later life. Here we show establishment of stable airway tolerance to the allergen, house dust mite (HDM), by exposing newborn mice repeatedly to a low dose of the allergen. Lung dendritic cells (DCs) from tolerized mice induced a low Th2 response in vitro mirroring impact of tolerance in vivo . In line with our previous finding of increased mitochondrial H 2 O 2 production from lung DCs of mice tolerized to ovalbumin, depletion of mitochondrial H 2 O 2 in MCAT mice abrogated HDM-induced airway tolerance (Tol) with elevated Th2 effector response, airway eosinophilia and increased airway hyperreactivity. WT Tol mice displayed a decrease in total, cDC1 and cDC2 subsets in the lung as compared to that in naïve mice. In contrast, the lungs of MCAT Tol mice showed 3-fold higher numbers of cDCs including those of the subsets as compared to that in WT mice. Our study demonstrates an important role of mitochondrial H 2 O 2 in constraining lung DC numbers towards establishment of early-life airway tolerance to allergens.

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High-dimensional profiling clusters asthma severity by lymphoid and non-lymphoid status

Cited by 35 publications

References 75 publications

Machine learning implicates the IL-18 signaling axis in severe asthma

Machine learning implicates the IL-18 signaling axis in severe asthma

Advances and highlights in asthma in 2021

Early life exposure to house dust mite allergen prevents experimental allergic asthma requiring mitochondrial H2O2

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