Tu59 - Multicohort Meta-Analysis of Bronchial Epithelial Cells Classifies Asthma from Healthy Subjects and Identifies Pathways in Asthma

Tuesday, June 21, 2022

6:15 PM – 7:45 PM PT

Presenting Author(s)

Ian Lee, MD

Pediatric Pulmonary Fellow
Stanford University
Redwood City, California, United States

Co-Author(s)

AG

Ananthakrishnan Ganesan, BE

PhD. Candidate
Stanford University
Palo Alto, California, United States
Laurynas Kalesinskas, BS

PhD Candidate
Stanford University
Palo Alto, California, United States
SE

Serpil C. Erzurum, MD

Chief Research & Academic Officer, Cleveland Clinic; Chair, Lerner Research Institute
University of WisconsinMadison, K6/350 CSC, MC 9988 600 Highland Avenue Madison, WI 53792
Cleveland, Ohio, United States
JF

John V. Fahy, MD, MSc

Professor of Medicine in the Division of Pulmonary and Critical Care Medicine and Medicine
University of California – San Francisco
San Francisco, California, United States
WM

Wendy C. Moore, MD

Internal Medicine, Pulmonary, Critical Care, Allergy and Immunologic Diseases
Wake Forest School of Medicine
Charlottesville, Virginia, United States
LD

Loren C. Delinger, MD, PHD

Professor
University of Wisconsin-Madison
Madison, Wisconsin, United States
MC

Mario Castro, M.D., MPH

Chief, Division Chief, Pulmonary, Critical Care and Sleep Medicine
University of Missouri-Kansas City School of Medicine
Kansas City, Kansas, United States
NJ

Nizar N. Jarjour, MD

Chief of the Division of Allergy, Pulmonary & Critical Care Medicine in the Department of Medicine
University of Wisconsin-Madison
Madison, Wisconsin, United States
SW

Sally E. Wenzel, MD

Professor of Medicine and Immunology
University of Pittsburgh, School of Medicine
Pittsburgh, Pennsylvania, United States
BL

Bruce D. Levy, MD

Chief, Division of Pulmonary and Critical Care Medicine
Brigham and Women’s Hospital
Boston, Massachusetts, United States
DM

Deborah A. Meyers, PhD

Professor of Medicine
University of Arizona
Tucson, Arizona, United States
EB

Eugene E. Bleecker, MD

Professor of Medicine
University of Arizona
Tucson, Arizona, United States
PW

Prescott Woodruff, MD, MPH

Professor, Medicine
University of California – San Francisco
San Francisco, California, United States
VO

Victor Ortega, MD, PhD

Senior Associate Consultant
Mayo Clinic Arizona
Scottsdale, Arizona, United States
PK

Purvesh Khatri, PhD

Associate Professor (Research), Medicine
Stanford University
Stanford, California, United States

Individuals with asthma exhibit a broad range of symptoms, triggers, and responses to treatments despite carrying the same diagnosis. The current view describes two general endotypes, “T-helper cell 2 (T2)-high” and “T2-low”. However, these two classes incompletely describe the spectrum of asthma and the true number of endotypes remains unclear, particularly within the Th2-low population. We hypothesized a robust set of genes that accurately distinguishes patients with asthma from healthy subjects can be identified by integrating publicly available data sets. We used seven transcriptome data sets of 366 bronchial epithelial cell (BEC) samples from 148 healthy controls (HC) and 218 patients with asthma used as “discovery cohorts.” Using a Bayesian multi-cohort analysis framework, we identified 505 differentially expressed genes. A BEC score, defined as the difference between the geometric mean of over-expressed genes and under-expressed genes, distinguished patients with asthma from HCs with high accuracy with summary area under the receive operating characteristic curve (AUROC) of 0.906 (range: 0.841-0.986) in the discovery cohorts. We used 311 BEC samples from the Severe Asthma Research Program (SARP), an intensive and comprehensive characterization study, as validation cohorts. The BEC score distinguished patients with asthma with AUROC of 0.844 (range: 8.22-8.70), demonstrating it is robust to the real-world heterogeneity. Importantly, in 4 cohorts (2 discovery, 2 validation) with samples from each severity group, the BEC score significantly correlated with severity (JT trend test p-value < 1e-06).