A study published on Sept. 10 in the American Journal of Respiratory and Critical Care Medicine has revealed a proteomic signature that indicates increased respiratory susceptibility, offering insights into the risk of respiratory-related death, chronic obstructive pulmonary disease (COPD), and respiratory exacerbations.

Led by Dr. Gabrielle Y. Liu from the University of California, Davis, School of Medicine, the research aimed to determine whether a proteomic risk score, based on the accelerated decline of lung function, could predict future respiratory disease and mortality. The study utilized data from the Coronary Artery Risk Development in Young Adults (CARDIA) cohort, a population-based study that began in young adulthood.

The research team employed forced expiratory volume in one second (FEV1), a key measure of lung function, to track accelerated versus normal decline in lung health. Using this data, protein aptamers associated with rapid lung function decline were identified, leading to the creation of a proteomic respiratory susceptibility score. This score was then applied to two external datasets: the U.K. Biobank and the COPDGene study, to evaluate its predictive validity.

The study found that individuals with higher susceptibility scores were more likely to face adverse respiratory outcomes. In both the U.K. Biobank and COPDGene cohorts, elevated scores were independently associated with a higher risk of all-cause mortality, respiratory mortality, and the development of COPD. In the U.K. Biobank, a higher susceptibility score corresponded to an 84% increased likelihood of developing COPD, while in the COPDGene study, individuals with higher scores were more prone to respiratory exacerbations, particularly those severe enough to require hospitalization.

The proteins identified in the study show potential as biomarkers for impaired respiratory health. The researchers suggest that further investigation could clarify their role as modifiable targets for preventing or intercepting chronic lung diseases in high-risk populations. The study, which was partially funded by contributions from pharmaceutical companies, underscores the potential of using proteomic data to guide future therapeutic interventions aimed at improving respiratory health outcomes.