Introduction: Biomarkers may help understand the toxic effects of vaping. Herein, we identified blood transcriptomic and proteomic biomarkers of vaping, related them to prospective health outcomes, and investigated their ability to accurately distinguish vapers from smokers.
Methods: We grouped 3,892 COPDGene study participants as vapers, current smokers, former smokers, or dual users. We tested for associations with 21,471 blood RNA transcripts and 4,979 plasma proteins. We related the significant biomarkers to 6.5 years of incident health events. To assess the discriminative performance of multi-omics for vaping, we constructed linear discriminant analysis models with 10-fold cross-validation for RNA and proteins considered separately and in combination. We evaluated the model performance at the optimal cutoff on the receiver-operating characteristic curve using the Youden index (YI).
Results: We identified 2 transcriptomic and 148 proteomic associations to vaping, and 25 transcriptomic and 323 proteomic associations to dual-use (FDR 10%). Vapers proteins, previously linked to obstructive lung disease and heart disease, were associated with increased cardiovascular disease and cancer mortality risks. Dual-use genes, previously implicated in inflammation and cancer, were associated with increased prospective diabetes. The combined RNA and protein predictive model that respectively incorporated a mean of 79 and 298 biomarkers showed excellent discriminative performance for dual users versus former smokers (YI=0.82±0.03) and modest discrimination for vapers versus former smokers (YI=0.50±0.05). The top predictors included genes related to immunity and tumor suppression and proteins linked to interleukin signaling and vasculogenesis.
Conclusion: A blood-based multi-marker panel may help predict vaping and its associated health outcomes.