PROJECT SUMMARY/ABSTRACT
The goal of this project is to investigate the upper airway molecular and clinical predictors of systemic relapse
in antineutrophil cytoplasmic autoantibody (ANCA)-associated vasculitis (AAV). AAV is a multi-organ rheumatic
disease with prominent upper airway involvement that often precedes disease in other organs. Relapses are
common and difficult to predict, resulting in long-term use of immunosuppressive therapies. There is a critical
need to understand the events leading up to relapse which may provide new insights into early processes which
incite or amplify autoimmune responses as well as facilitate development of prognostic biomarkers which can
inform treatment decision (e.g., escalate or de-escalate systemic immunosuppressive therapy). This proposal is
based on preliminary data indicating that, in patients with AAV who are in clinical remission, nasal gene
expression and bacterial profiling identifies epithelial and microbial alterations which are detectable 6 months
prior to systemic disease relapse, even in patients without sinonasal symptoms at relapse and regardless of
immunosuppressive therapy. Similarly, when examining upper airway disease using a patient-reported outcome
measure, the SinoNasal Outcome Test-22 (SNOT-22), greater sinonasal symptom burden was associated with
a 3-fold higher risk of relapse within 2 years. The central hypothesis is that, among patients with quiescent
AAV, there exists a relapse-prone disease state that is detectable using a combination of molecular profiling,
clinical, and patient-reported measures. This project will perform a longitudinal cohort study by leveraging an
existing upper airway-dedicated biorepository of AAV (banked nasal samples from 847 visits in 191 patients) as
well as prospectively recruit 150 new patients at a major vasculitis-focused clinical and research center. Also,
longitudinal collection of patient-reported data will be electronically captured in 300 patients through the Vasculitis
Patient-Powered Research Network, a national research network with over 2,000 highly engaged patients with
AAV. The specific aims are to: (1) define molecular changes in the upper airway that precede relapse of AAV
using high-throughput sequencing, and (2) define the patient-reported upper airway symptoms preceding relapse
of AAV and the added value of clinical and molecular data to identify the relapse-prone subgroup. We will
evaluate the contribution of each data type as well as combine data using machine learning approaches to train
and validate a prediction model of relapse within 2 years. Using integrative multi-omic analyses, we will identify
biologically distinct subtypes of patients who are in clinical remission. The long-term translational objective is to
use the biologic insights gained in this study to create reliable prognostic biomarkers which inform treatment
decision-making (e.g., escalate/maintain vs de-escalate immunosuppressive therapy) as well as gain
mechanistic insights in this highly-morbid, relapsing rheumatic disease. By investigating the transition from
quiescent to active disease, the proposed work will advance our understanding of disease progression in AAV
and uncover a new area of investigation which may be applicable to other rheumatologic conditions.