Predicting thrombotic cardiovascular outcomes induced by waterpipe-associated chemicals using comparative toxicogenomic database: Genes, phenotypes, and pathways

Abstract

Hookah, or waterpipe, is a tobacco smoking device that has gained popularity in the United States. A growing body of evidence demonstrates that waterpipe smoke (WPS) is associated with various adverse effects on human health, including infectious diseases, cancer, and cardiovascular diseases (CVDs), particularly thrombotic events. However, the molecular mechanisms through which WPS contributes to disease development remain unclear. In this study, we utilized an analytical approach based on the Comparative Toxicogenomics Database (CTD) to integrate chemical, gene, phenotype, and disease data to predict potential molecular mechanisms underlying the effects of WPS, based on its chemical and toxicant profile. Our analysis revealed that CVDs were among the top disease categories with regard to the number of curated interactions with WPS chemicals. We identified 5674 genes common between those modulated by WPS chemicals and traditional tobacco smoking. The CVDs with the most curated interactions with WPS chemicals were hypertension, atherosclerosis, and myocardial infarction, whereas "particulate matter", "heavy metals", and "nicotine" showed the highest number of curated interactions with CVDs. Our analysis predicted that the potential mechanisms underlying WPS-induced thrombotic diseases involve common phenotypes, such as inflammation, apoptosis, and cell proliferation, which are shared across all thrombotic diseases and the three aforementioned chemicals. In terms of enriched signaling pathways, we identified several, including chemokine and MAPK signaling, with particulate matter exhibiting the most statistically significant association with all 12 significant signaling pathways related to WPS chemicals. Collectively, our predictive comprehensive analysis provides evidence that WPS negatively impacts health and offers insights into the potential mechanisms through which it exerts these effects. This information should guide further research to explore and better understand the WPS and other tobacco product-related health consequences.

Fig. 1.

Edges weight measured by two measurements, Jaccard similarity and Overlap index. Those weights coincide very well with the number of common genes between the nodes. This network prioritizes the Triads of (Disease, Chemical, Phenotype) by the value of the minimum Gene similarity Network GS = Gene Similarity.

Fig. 2.

The top 20 categories of diseases with direct relationships to chemicals in WPS; detailing the number of curated interactions in these categories and distribution by chemical, PAHs - Polycyclic aromatic hydrocarbons, TSNAs - Tobacco-Specific Nitrosamines, VOC - Volatile organic compounds.

Fig. 3.

Protein coding genes overlap between WPS chemicals and tobacco smoke.

Fig. 4.

Most common molecular signaling pathways impacted by WPS chemicals.

Fig. 5.

Top 10 CVDs with the highest curated interactions with WPS chemicals. PAHs - Polycyclic aromatic hydrocarbons, TSNAs - Tobacco-Specific Nitrosamines, VOC - Volatile organic compounds.

Fig. 6.

The number of curated phenotype interactions related to WPS chemicals.

Fig. 7.

(A) Common phenotypes between myocardial infarction, stroke and pulmonary embolism across the three common WPS chemicals. (B, C & D) Number of overlapped and distinctive phenotypes for each chemical. MI - myocardial infarction, PE - pulmonary embolism.

Fig. 8.

Overview of the effects on genes and pathways exerted by the three selected chemicals on the three selected diseases (MI, stroke and PE). For the full network, check Supplemental file 3.