The overarching hypothesis underpinning our research is that inter-individual differences in asthma control result from the interplay of genetic and environmental factors organized in discrete molecular networks. During the first grant cycle, we explored this hypothesis by defining the molecular determinants of asthma control in well characterized patient populations using integrative genomic approaches. Among our most notable observations was our discovery that asthmatics with suboptimal asthma control demonstrate a peripheral blood gene expression signature indicative of activation of the TREM1 signaling pathway. Triggering Receptor Expressed On Myeloid Cells 1 (TREM1) is a cell-surface receptor expressed on monocytes and macrophages that plays a critical role in modulating both the innate and adaptive immune response. We now hypothesize that the activation of TREM1 is a critical early molecular event in the worsening of asthma control, and that inhibition of this signaling pathway represents new and effective non-steroidal strategy for maintaining long- term asthma control. We will test these hypotheses in the following complementary Specific Aims:
In Specific Aim 1 we will use both single cell and bulk RNA-sequencing to characterize the patterns of TREM1 expression and pathway activation in monocyte subtypes from 100 children and young adults with variable asthma control. Our goals are to define and classify monocyte subsets based on their TREM1 activation status; correlate monocyte-specific TREM1 activation signatures with asthma control; and assess whether these signatures can predict deterioration in asthma control and exacerbation.
In Specific Aim 2 we will evaluate soluble TREM1 (sTREM1) as a potential biomarker of asthma control. sTREM1 is shed from cell surfaces and plasma sTREM1 levels correlate with clinical severity in several inflammatory conditions. We will measure sTREM1 plasma levels in samples from more than 2,500 asthmatics to determine (i) if sTREM1 can serve as a biomarker of asthma control and predict asthma exacerbation; (ii) if high sTREM1 levels define a specific clinical asthma subtype or responsiveness to specific asthma therapies; and (iii) if sTREM1 levels are determined by specific genetic or environmental exposures, and, if so, do they mediate correlations with asthma control? In Specific Aim 3, we will use an established mouse model of allergic airway inflammation to evaluate the therapeutic potential of inhibition of the TREM1 signaling pathway in the treatment of asthma. We anticipate that LR12 will demonstrate strong efficacy in these models, providing essential pre-clinical data to support future first-in- human trials of this compound in asthmatic patients.

Public Health Relevance

Failure to maintain asthma symptom control is a major cause of lost school and workdays. This project aims to evaluate the role of the Triggering Receptor Expressed On Myeloid Cells 1 (TREM1) signaling pathway in the pathobiology of poor asthma control. We will use genomics to define the pathway components most pertinent in asthma control. We will evaluate a soluble form of TREM1 (sTREM1) as a potential biomarker of asthma control. We will also evaluate a TREM1 inhibitor as a potential non-steroidal therapy for asthma management.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project (R01)
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Respiratory Integrative Biology and Translational Research Study Section (RIBT)
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Gan, Weiniu
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Boston Children's Hospital
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Sharma, Amitabh; Kitsak, Maksim; Cho, Michael H et al. (2018) Integration of Molecular Interactome and Targeted Interaction Analysis to Identify a COPD Disease Network Module. Sci Rep 8:14439
Croteau-Chonka, Damien C; Raby, Benjamin A (2018) TREM-1 Response Signatures Common to Expression Profiles of Both Asthma Affection and Asthma Control. Am J Respir Crit Care Med 198:401-404
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Sharma, Amitabh; Menche, Jörg; Huang, C Chris et al. (2015) A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma. Hum Mol Genet 24:3005-20
Yan, Xiting; Chu, Jen-Hwa; Gomez, Jose et al. (2015) Noninvasive analysis of the sputum transcriptome discriminates clinical phenotypes of asthma. Am J Respir Crit Care Med 191:1116-25

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