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1.
J Adv Res ; 2024 May 04.
Article in English | MEDLINE | ID: mdl-38705256

ABSTRACT

INTRODUCTION: Per- and polyfluoroalkyl substances (PFAS) have infiltrated countless everyday products, raising concerns about potential effects on human health, specifically on the cardiovascular system and the development of abdominal aortic calcification (AAC). However, our understanding of this relationship is still limited. OBJECTIVES: This study aims to investigate the effects of PFAS on AAC using machine learning algorithms. METHODS: Leveraging the power of machine learning technique, extreme gradient boosting (XGBoost), we assessed the relationship between PFAS exposure and AAC risk. We focused on three PFAS compounds, perfluorodecanoic acid (PFDeA), perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA) through multiple logistic regression, restricted cubic spline (RCS), and quantile g-computation (QGC) models. To get more insight into the underlying mechanisms, mediation analyses are used to investigate the potential mediating role of fatty acids and blood cell fractions in AAC. RESULTS: Our findings indicate that elevated serum levels of PFHxS and PFDeA are associated with the increased risk of AAC. The QGC analyses underscore the overall positive association between the PFAS mixture and AAC risk, with PFHxS carrying the greatest weight, followed by PFDeA. The RCS analyses reveal a dose-dependent increase between serum PFHxS concentration and AAC risk in an inverted V-shape way. Moreover, age and PFHxS exposure are identified as the primary factors contributing to abdominal aortic calcification risk in SHapley Additive exPlanation (SHAP) summary plot combined with XGBoost technique. Although PFAS significantly change the profile of fatty acids, we do not find any mediating roles of them in AAC. Despite strong associations between PFAS exposure and hematological indicators, our analysis does not find evidence that these indicators mediate the development of AAC. CONCLUSIONS: In summary, our study highlights the detrimental impact of PFAS on abdominal aortic health and emphasizes the need for further research to understand the underlying mechanisms involved.

2.
Sci Total Environ ; 932: 173085, 2024 Jul 01.
Article in English | MEDLINE | ID: mdl-38729377

ABSTRACT

The presence of perfluoroalkyl and polyfluoroalkyl substances (PFAS) in various everyday products has raised concerns about their potential impact on prostate health. This study aimed to investigate the effects of different types of PFAS on prostate health, including PFDeA, PFOA, PFOS, PFHxS, and PFNA. To assess the relationship between PFAS exposure and prostate injury, machine learning algorithms were employed to analyze prostate-specific antigen (PSA) metrics. The analysis revealed a linear and positive dose-dependent association between PFOS and the ratio of free PSA to total PSA (f/tPSA). Non-linear dose-response relationships were observed between the other four types of PFAS and the f/tPSA ratio. Additionally, the analysis showed a positive association between the mixture of PFAS and prostate hyperplasia, with PFNA having the highest impact followed by PFOS. These findings suggest that elevated serum levels of PFDeA, PFOA, PFOS, and PFNA are linked to prostate hyperplasia. Therefore, this study utilized advanced machine learning techniques to uncover potential hazardous effects of PFAS exposure on prostate health, specifically the positive association between PFAS and prostate hyperplasia.


Subject(s)
Fluorocarbons , Prostatic Hyperplasia , Male , Fluorocarbons/blood , Humans , Environmental Exposure/statistics & numerical data , Environmental Pollutants/blood , Machine Learning , Alkanesulfonic Acids/blood , Prostate-Specific Antigen/blood
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