Evaluating the Vascular Risk of PFCs: An Integrated XGBoost-Driven Structure-Activity Prediction and Experimental...

Area of Science:

• Environmental Chemistry
• Toxicology
• Cardiovascular Health

Background:

• Perfluorochemicals (PFCs) are persistent organic pollutants with increasing detection in human serum.
• While endocrine disruption by PFCs is known, their impact on vascular function and related structure-activity relationships remain understudied.
• Endothelial cell function is critical for maintaining cardiovascular health.

Purpose of the Study:

• To investigate the impact of PFCs on endothelial cell function.
• To establish structure-activity relationships (SAR) for PFCs concerning vascular effects.
• To assess population health risks associated with PFC exposure.

Main Methods:

• Utilized a machine learning-based quantitative structure-activity relationship (QSAR) model with the XGBoost algorithm.
• Analyzed 16 structural descriptors for 23 prevalent PFCs.
• Integrated computational modeling with in vitro cell culture experiments and in vivo exposure data for risk assessment.

Main Results:

• Identified short-chain PFCs with strong acid groups as particularly detrimental to endothelial cells.
• Elucidated detailed structure-activity and dose-response relationships for PFCs.
• Population health risk assessment revealed high risk for the entire Chinese population, varying by gender and industrialization.

Conclusions:

• Short-chain PFCs pose a significant risk to vascular health through endothelial cell dysfunction.
• The study provides a framework for managing toxic PFCs and developing safer alternatives.
• Global disparities in PFC risk are evident, with specific populations facing elevated threats.