Prediction and stratification of longitudinal risk for chronic obstructive pulmonary disease across smoking behaviors

• Authors: Yixuan He, Massachusetts Institute of Technology; David Qian, Emory University; James A. Diao, Harvard University; Michael H. Cho, Brigham and Women's Hospital; Edwin K. Silverman, Harvard University; Alexander Gusev, Dana-Farber Cancer Institute; Arjun K. Manrai, Harvard University; Alicia R. Martin, Massachusetts Institute of Technology; Chirag J. Patel, Harvard University
• Journal Title: Nature Communications
• Volume: Volume 14
• Publisher: Springer Nature | 2023-12-14, Pages 8297-None
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1038/s41467-023-44047-8
• Subjects: Health Sciences, Public Health; Health Sciences, Epidemiology
• Keywords: Predictive medicine; Medical genetics; Genome-wide association studies

Abstract

Smoking is the leading risk factor for chronic obstructive pulmonary disease (COPD) worldwide, yet many people who never smoke develop COPD. We perform a longitudinal analysis of COPD in the UK Biobank to derive and validate the Socioeconomic and Environmental Risk Score which captures additive and cumulative environmental, behavioral, and socioeconomic exposure risks beyond tobacco smoking. The Socioeconomic and Environmental Risk Score is more predictive of COPD than smoking status and pack-years. Individuals in the highest decile of the risk score have a greater risk for incident COPD compared to the remaining population. Never smokers in the highest decile of exposure risk are more likely to develop COPD than previous and current smokers in the lowest decile. In general, the prediction accuracy of the Social and Environmental Risk Score is lower in non-European populations. While smoking status is often considered in screening COPD, our finding highlights the importance of other non-smoking environmental and socioeconomic variables.