Citations

Objective To identify and validate, using computer‐driven methods, patterns of arterial disease in Takayasu arteritis (TAK) and giant cell arteritis (GCA). Methods Patients with TAK or GCA were studied from the Diagnostic and Classification Criteria for Vasculitis (DCVAS) cohort and a combined North American cohort. Case inclusion required evidence of large‐vessel involvement, defined as stenosis, occlusion, or aneurysm by angiography/ultrasonography, or increased 18 F‐fluorodeoxyglucose (FDG) uptake by positron emission tomography (PET) in at least 1 of 11 specified arterial territories. K‐means cluster analysis identified groups of patients based on the pattern of arterial involvement. Cluster groups were identified in the DCVAS cohort and independently validated in the North American cohort. Results A total of 1,068 patients were included (DCVAS cohort: TAK = 461, GCA = 217; North American cohort: TAK = 225, GCA = 165). Six distinct clusters of patients were identified in DCVAS and validated in the North American cohort. Patients with TAK were more likely to have disease in the abdominal vasculature, bilateral disease of the subclavian and carotid arteries, or focal disease limited to the left subclavian artery than GCA ( P < 0.01). Patients with GCA were more likely to have diffuse disease, involvement of bilateral axillary/subclavian arteries, or minimal disease without a definable pattern than TAK ( P < 0.01). Patients with TAK were more likely to have damage by angiography, and patients with GCA were more likely to have arterial FDG uptake by PET without associated vascular damage. Conclusion Arterial patterns of disease highlight both shared and divergent vascular patterns between TAK and GCA and should be incorporated into classification criteria for large‐vessel vasculitis.

Abstract Objectives To develop and replicate, using data-driven methods, a novel classification system in Takayasu’s arteritis based on distribution of arterial lesions. Methods Patients were included from four international cohorts at major academic centres: India (Christian Medical College Vellore); North America (National Institutes of Health, Vasculitis Clinical Research Consortium and Cleveland Clinic Foundation). All patients underwent whole-body angiography of the aorta and branch vessels, with categorization of arterial damage (stenosis, occlusion or aneurysm) in 13 territories. K-means cluster analysis was performed to identify subgroups of patients based on pattern of angiographic involvement. Cluster groups were identified in the Indian cohort and independently replicated in the North American cohorts. Results A total of 806 patients with Takayasu’s arteritis from India (n = 581) and North America (n = 225) were included. Three distinct clusters defined by arterial damage were identified in the Indian cohort and replicated in each of the North American cohorts. Patients in cluster one had significantly more disease in the abdominal aorta, renal and mesenteric arteries (P &lt; 0.01). Patients in cluster two had significantly more bilateral disease in the carotid and subclavian arteries (P &lt; 0.01). Compared with clusters one and two, patients in cluster three had asymmetric disease with fewer involved territories (P &lt; 0.01). Demographics, clinical symptoms and clinical outcomes differed by cluster. Conclusion This large study in Takayasu’s arteritis identified and replicated three novel subsets of patients based on patterns of arterial damage. Angiographic-based disease classification requires validation by demonstrating potential aetiological or prognostic implications.

Abstract Objectives To describe tracheobronchial disease in patients with granulomatosis with polyangiitis (GPA) and evaluate the utility of dynamic expiratory CT to detect large-airway disease. Methods Demographic and clinical features associated with the presence of subglottic stenosis (SGS) or endobronchial involvement were assessed in a multicentre, observational cohort of patients with GPA. A subset of patients with GPA from a single-centre cohort underwent dynamic chest CT to evaluate the airways. Results Among 962 patients with GPA, SGS and endobronchial disease were identified in 95 (10%) and 59 (6%) patients, respectively. Patients with SGS were more likely to be female (72% vs 53%, P &lt; 0.01), younger at time of diagnosis (36 vs 49 years, P &lt; 0.01), and have saddle-nose deformities (28% vs 10%, P &lt; 0.01), but were less likely to have renal involvement (39% vs 62%, P &lt; 0.01). Patients with endobronchial disease were more likely to be PR3-ANCA positive (85% vs 66%, P &lt; 0.01), with more ENT involvement (97% vs 77%, P &lt; 0.01) and less renal involvement (42% vs 62%, P &lt; 0.01). Disease activity in patients with large-airway disease was commonly isolated to the subglottis/upper airway (57%) or bronchi (32%). Seven of 23 patients screened by dynamic chest CT had large-airway pathology, including four patients with chronic, unexplained cough, discovered to have tracheobronchomalacia. Conclusion SGS and endobronchial disease occur in 10% and 6% of patients with GPA, respectively, and may occur without disease activity in other organs. Dynamic expiratory chest CT is a potential non-invasive screening test for large-airway involvement in GPA.

ObjectiveTo discover biomarkers involved in the pathophysiology of antineutrophil cytoplasmic antibody–associated vasculitis (AAV) and to determine whether low‐density granulocytes (LDGs) contribute to gene expression signatures in AAV.MethodsThe source of clinical data and linked biologic specimens was a randomized controlled treatment trial in AAV. RNA sequencing of whole blood from patients with AAV was performed during active disease at the baseline visit and during remission 6 months later. Gene expression was compared between patients who met versus those who did not meet the primary trial outcome of clinical remission at 6 months (responders versus nonresponders). Measurement of neutrophil‐related gene expression was confirmed in peripheral blood mononuclear cells (PBMCs) to validate the findings in whole blood. A negative‐selection strategy isolated LDGs from PBMC fractions.ResultsDifferential expression between responders (n = 77) and nonresponders (n = 35) was detected in 2,346 transcripts at the baseline visit (P < 0.05). Unsupervised hierarchical clustering demonstrated a cluster of granulocyte‐related genes, including myeloperoxidase (MPO) and proteinase 3 (PR3). A granulocyte multigene composite score was significantly higher in nonresponders than in responders (P < 0.01) and during active disease than during remission (P < 0.01). This signature strongly overlapped an LDG signature identified previously in lupus (false discovery rate by gene set enrichment analysis <0.01). Transcription of PR3 measured in PBMCs was associated with active disease and treatment response (P < 0.01). LDGs isolated from patients with AAV spontaneously formed neutrophil extracellular traps containing PR3 and MPO.ConclusionIn AAV, increased expression of a granulocyte gene signature is associated with disease activity and decreased response to treatment. The source of this signature is likely LDGs, a potentially pathogenic cell type in AAV.