Wang Pangbo, Chen Wei, Fang Hongwei, Xu Liwei, Zhao Jun, Huang Jing
Department of Neurosurgery and State Key Laboratory of Trauma, Burn and Combined Injury, Southwest Hospital, Chongqing, China.
Chongqing Key Laboratory of Precision Neuromedicine and Neuroregenaration, Third Military Medical University (Army Medical University), Chongqing, China.
Front Public Health. 2025 Jul 15;13:1613435. doi: 10.3389/fpubh.2025.1613435. eCollection 2025.
Volatile organic compounds (VOCs) are emerging environmental pollutants linked to various health problems. However, the relationship between exposure to urinary volatile organic compound metabolites (mVOCs) and sarcopenia remains unclear.
We used data from the National Health and Nutrition Examination Survey (NHANES 2011-2018) to assess the association between mVOCs and sarcopenia through multivariable logistic regression and restricted cubic spline (RCS) regression. We also employed Weighted Quantile Sum (WQS) regression model, a high-dimensional statistical approach used to evaluate the joint effects of multiple exposures, and Bayesian Kernel Machine regression (BKMR) model, a combination of Bayesian and statistical learning methods, to assess the mixture effects of mVOCs on sarcopenia risk. These methods account for non-linearity, collinearity, and dimensionality in exposure data. Mediation analysis was used to identify metabolic, endocrine, and inflammatory mediators in these associations. Subgroup analyses were conducted by gender and age. Network pharmacology analysis was performed to identify potential pathways and targets.
A total of 2,898 participants were included, with 145 (8%) diagnosed with sarcopenia. Logistic regression showed a positive correlation between mVOCs (3,4-MHA, ATCA, CEMA, CYMA, 2HPMA, 3HPMA, MHBMA3, and PGA) and sarcopenia. RCS results confirmed linear dose-response associations ( for overall <0.05, for non-linear ≥0.05). Subgroup analysis indicated stronger associations in older participants. The WQS and BKMR models consistently showed a positive link between VOC exposure and sarcopenia. Mediation analysis identified alkaline phosphatase (ALP), white blood cell count (WBC), systemic immune-inflammation index (SII), and vitamin D as mediators. Network analysis revealed significant enrichment in the endocrine resistance pathway.
Our findings suggest that co-exposure to VOCs is associated with increased sarcopenia risk, potentially through disruption of endocrine and inflammatory pathways, as indicated by elevated alkaline phosphatase (ALP), white blood cell count (WBC), the systemic immune-inflammation index (SII), and reduced vitamin D levels, with enrichment observed in the endocrine resistance signaling pathway.
挥发性有机化合物（VOCs）是新出现的环境污染物，与各种健康问题相关。然而，接触尿中挥发性有机化合物代谢物（mVOCs）与肌肉减少症之间的关系仍不清楚。
我们使用了国家健康与营养检查调查（NHANES 2011 - 2018）的数据，通过多变量逻辑回归和受限立方样条（RCS）回归来评估mVOCs与肌肉减少症之间的关联。我们还采用了加权分位数和（WQS）回归模型（一种用于评估多种暴露联合效应的高维统计方法）以及贝叶斯核机器回归（BKMR）模型（一种贝叶斯和统计学习方法的组合）来评估mVOCs对肌肉减少症风险的混合效应。这些方法考虑了暴露数据中的非线性、共线性和维度问题。中介分析用于确定这些关联中的代谢、内分泌和炎症介质。按性别和年龄进行亚组分析。进行网络药理学分析以确定潜在的途径和靶点。
共纳入2898名参与者，其中145名（8%）被诊断为肌肉减少症。逻辑回归显示mVOCs（3,4 - MHA、ATCA、CEMA、CYMA、2HPMA、3HPMA、MHBMA3和PGA）与肌肉减少症之间存在正相关。RCS结果证实了线性剂量反应关联（总体<0.05，非线性≥0.05）。亚组分析表明老年参与者中的关联更强。WQS和BKMR模型一致显示VOC暴露与肌肉减少症之间存在正相关。中介分析确定碱性磷酸酶（ALP）、白细胞计数（WBC）、全身免疫炎症指数（SII）和维生素D为介质。网络分析显示内分泌抵抗途径有显著富集。
我们的研究结果表明，接触VOCs与肌肉减少症风险增加相关，可能是通过破坏内分泌和炎症途径，如碱性磷酸酶（ALP）、白细胞计数（WBC）、全身免疫炎症指数（SII）升高以及维生素D水平降低所表明的，并且在内分泌抵抗信号通路中观察到了富集。
