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During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
The association between exposure to volatile organic compounds (VOCs) and chronic kidney disease (CKD) risk is an important issue of public health. However, the underlying biological pathways, particularly the role of insulin resistance (IR), remain unclear. This study aimed to investigate the association between urinary VOC metabolites and CKD risk and to assess the potential mediating role of insulin resistance.
This community-based cross-sectional study recruited 859 participants (186 CKD cases, 673 controls) from the Human Biomonitoring and Environmental Health Program (HBEHP) in central Taiwan. We measured 12 urinary VOC metabolites using LC-MS/MS. CKD was defined as an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m² or by ICD codes from the Taiwan National Health Insurance Research Database. Insulin Resistance (HOMA-IR) was calculated to assess insulin resistance. We used multivariable logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression for variable selection, and a Support Vector Machine (SVM) model with SHapley Additive exPlanations (SHAP) analysis to identify the predictors. Causal mediation analysis was performed to quantify the effect of HOMA-IR on the VOC-CKD association.
After adjusting for potential confounders, urinary α-Aminoadipic Acid (AAMA) (OR: 1.80, 95% CI: 1.07-3.04), PGA (OR: 2.06, 95% CI: 1.17-3.62), and t,tMA (OR: 2.10, 95% CI: 1.12-3.94) were significantly associated with increased CKD risk. LASSO regression identified AAMA as a key predictive metabolite. An SVM model achieved high predictive performance (AUC = 0.822). SHAP analysis identified uric acid, HOMA-IR, age, hs-CRP, and AAMA as the top five predictors of CKD, with AAMA being the most important VOC contributor. Causal mediation analysis revealed that HOMA-IR partially mediated the association between AAMA and CKD, accounting for 21.93% of the total effect.
Exposure to specific VOCs, particularly AAMA, is associated with an increased risk of CKD in the general population. Our findings suggest that insulin resistance, as measured by HOMA-IR, is a significant mediator in this pathway. These results highlight a potential mechanism linking environmental chemical exposure to the development of CKD.
