Community-Acquired Pneumonia: Disease Course Prediction With a 5-Gene Signature

Clinical decision-making for patients with community-acquired pneumonia (CAP) at risk of organ dysfunction and death is currently guided by clinical evaluation and scores. Every fifth patient with CAP requires admission to the ICU, with a subsequent high mortality; delayed admission to the ICU increases this risk.

Can a transcriptomic signature improve identification of at-risk patients compared with conventional scores and metrics?

Time-course transcriptomic data were obtained from blood samples taken from 455 participants in 41 centers enrolled in the Progression of Community-Acquired Pneumonia in the Hospital (PROGRESS) trial, a prospective observational cohort study of hospitalized patients with CAP who did not initially require organ support. Discovery (n = 240) and validation (n = 215) cohorts were randomly assigned. Transcriptome data were analyzed for association with a severe CAP course, defined as a composite of requirement for ICU admission or 28-day mortality. Predictive performance of the gene expression profiles was compared against clinical scores and serum markers, and validated in publicly available transcriptomic data sets.

A 5-gene signature consisting of SIGLEC14, TNFSF14, YOD1, CLEC4A, and KLRB1 (STYCK) was identified and validated to predict clinical deterioration with subsequent ICU admission or 28-day mortality (AUC_discovery, 0.82; 95% CI, 0.71-0.90; P = 0.00000065; AUC_validation, 0.81; 95% CI, 0.70-0.90; P = 0.0000013). The signature outperformed clinical scores in predicting severe CAP and improved prediction when added to the Sequential Organ Failure Assessment score (AUC_SOFA, 0.70 vs AUC_SOFA+STYCK, 0.83; P = .0002). Prognostic value was confirmed in 6 of 17 publicly available sepsis cohorts, particularly those with low case fatality.

We identified a 5-gene transcriptomic signature that, taken soon after hospital admission, was shown to predict disease course of hospitalized patients with CAP. STYCK was superior to conventional, currently used scores and clinical metrics in predicting this deterioration and improved, if added to the Sequential Organ Failure Assessment, its performance.

ClinicalTrials.gov; No.: NCT02782013; URL: www.clinicaltrials.gov.