Rationale: Chronic obstructive pulmonary disease (COPD) is characterized by pathologic changes in the airways, lung parenchyma, and persistent inflammation, but the links between lung structural changes and patterns of systemic inflammation have not been fully described. Objectives: To identify novel relationships between lung structural changes measured by chest computed tomography (CT) and systemic inflammation measured by blood RNA sequencing. Methods: CT scan images and blood RNA-seq gene expression from 1,223 subjects in the COPDGene study were jointly analyzed using deep learning to identify shared aspects of inflammation and lung structural changes that we refer to as Image-Expression Axes (IEAs). We related IEAs to COPD-related measurements and prospective health outcomes through regression and Cox proportional hazards models and tested them for biological pathway enrichment. Measurements and Main Results: We identified two distinct IEAs: IEAemph captures an emphysema-predominant process with a strong positive correlation to CT emphysema and a negative correlation to FEV1 and Body Mass Index (BMI); IEAairway captures an airway-predominant process with a positive correlation to BMI and airway wall thickness and a negative correlation to emphysema. In multivariable models, IEAairway was significantly associated with the risk of mortality (HR 2.24, CI 1.50-3.33). Pathway enrichment analysis identified 29 and 13 pathways significantly associated with IEAemph and IEAairway, respectively (adjusted p<0.001). Conclusions: Integration of CT scans and gene expression data identified two IEAs that capture distinct inflammatory processes associated with emphysema and airway predominant COPD. Keywords: machine learning, emphysema, genomics

Peter J. Castaldi has received grant support from Bayer and consulting fees from Novartis and GSK. Craig P. Hersh reports grant support from Bayer, Boehringer-Ingelheim, and Vertex, and consulting fees from AstraZeneca and Takeda. Edwin K. Silverman has received grant support from Bayer and GSK.

This work was supported by NHLBI K08 HL141601, R01 HL124233, R01 HL126596, R01 HL147326, U01 HL089897, and U01 HL089856. The COPDGene study (NCT00608764) is also supported by the COPD Foundation through contributions made to an Industry Advisory Board that has included AstraZeneca, Bayer Pharmaceuticals, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Novartis, Pfizer, and Sunovion.

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Institutional review board (IRB) approval was obtained. IRB Protocol Title: Genetic Epidemiology of COPD. IRB Protocol Number: Brigham and Women's Hospital / 2007P000554.

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