生活方式相关的代谢物特征与晚发性哮喘风险
2026/02/02
背景：不健康的生活方式行为可导致全身性代谢紊乱，并与晚发性哮喘风险显著相关。然而，其背后与代谢相关的机制尚不清楚。本研究旨在识别与生活方式相关的代谢物，并评估其对哮喘发病的预测价值。
方法：利用英国生物样本库人群（年龄40-69岁）的核磁共振代谢组学数据，通过多元线性回归识别与健康生活方式评分相关的血浆代谢物。采用Cox比例风险回归进一步筛选与晚发性哮喘风险相关的代谢物。通过弹性网络正则化筛选出关键代谢物，用于构建一个纳入常规临床特征和生活方式因素的哮喘风险预测模型。基于非零正则化系数推导出代谢评分，并通过生存分析评估其与哮喘风险的关联。模型及代谢评分的性能在英国生物样本库未使用的内部参与者以及一个外部的中国kadoorie生物样本库队列中进行了验证。
结果：在198,607名参与者（平均年龄56.4岁）中，有159种血浆代谢物与健康生活方式评分显著相关，其中103种与哮喘发病风险相关。筛选出9种代谢物纳入哮喘风险预测模型，该模型显著提升了预测性能（曲线下面积为0.812 vs. 0.758）。与具有有利代谢特征的个体相比，具有不利代谢特征的个体患哮喘的风险增加了77.0%（风险比 1.770，95% 置信区间 1.634-1.918），此效应在女性中更为显著（风险比 1.914，95% 置信区间 1.729-2.118）。预测模型和代谢评分的有效性在内部和外部验证中均得到证实。
结论：多种与生活方式相关的代谢物与晚发性哮喘风险相关，有助于对哮喘风险进行分层，尤其是在女性群体中。
Lifestyle-associated metabolite signatures and the risk of late-onset asthma
Chang Q, Chen L, Zhu Y, Liu B, Zhou X, Liang H, Lin F, Li D, Zhu Z, Pan Z, Chen X, Liu H, Sun D, Lv J, Li L, Pan P, Yu C, Zhang Y.
Abstract
Abstract
BACKGROUND:Unhealthy lifestyle behaviors, leading to systemic metabolic disturbances, are significantly linked to the risk of late-onset asthma. However, the underlying metabolism-related mechanisms remain unclear. We sought to identify lifestyle-related metabolites and assess their predictive value for incident asthma.
METHODS:Using nuclear magnetic resonance metabolomics data from the UK Biobank population (ages 40-69), plasma metabolites associated with healthy lifestyle scores were identified through multiple linear regression. Cox proportional hazards regression was used to further screen metabolites linked to late-onset asthma risk. Elastic net regularization selected critical metabolites for developing an asthma risk prediction model, incorporating conventional clinical characteristics and lifestyle factors. A metabolic score based on nonzero regularization coefficients was derived, and its association with asthma risk was evaluated through survival analysis. Models and metabolic score performance were validated in unused internal UK Biobank participants and an external China Kadoorie Biobank cohort.
RESULTS:Among 198,607 participants (mean age 56.4 years), 159 plasma metabolites were significantly related to healthy lifestyle scores, 103 of which were associated with incident asthma risk. Nine metabolites were selected and incorporated into the asthma risk prediction model, significantly improving its predictive performance (area under the curve 0.812 vs 0.758). Individuals with an unfavorable metabolic signature exhibited a 77.0% increased risk (hazard ratio 1.770, 95% CI 1.634-1.918) of developing asthma compared with individuals with a favorable metabolic signature, with a stronger effect observed in women (hazard ratio 1.914, 95% CI 1.729-2.118). The results for the predictive model and metabolic score were confirmed in both internal and external validations.
CONCLUSION:Multiple lifestyle-related metabolites are associated with late-onset asthma risk and can help stratify asthma risk, particularly among women.
方法：利用英国生物样本库人群（年龄40-69岁）的核磁共振代谢组学数据，通过多元线性回归识别与健康生活方式评分相关的血浆代谢物。采用Cox比例风险回归进一步筛选与晚发性哮喘风险相关的代谢物。通过弹性网络正则化筛选出关键代谢物，用于构建一个纳入常规临床特征和生活方式因素的哮喘风险预测模型。基于非零正则化系数推导出代谢评分，并通过生存分析评估其与哮喘风险的关联。模型及代谢评分的性能在英国生物样本库未使用的内部参与者以及一个外部的中国kadoorie生物样本库队列中进行了验证。
结果：在198,607名参与者（平均年龄56.4岁）中，有159种血浆代谢物与健康生活方式评分显著相关，其中103种与哮喘发病风险相关。筛选出9种代谢物纳入哮喘风险预测模型，该模型显著提升了预测性能（曲线下面积为0.812 vs. 0.758）。与具有有利代谢特征的个体相比，具有不利代谢特征的个体患哮喘的风险增加了77.0%（风险比 1.770，95% 置信区间 1.634-1.918），此效应在女性中更为显著（风险比 1.914，95% 置信区间 1.729-2.118）。预测模型和代谢评分的有效性在内部和外部验证中均得到证实。
结论：多种与生活方式相关的代谢物与晚发性哮喘风险相关，有助于对哮喘风险进行分层，尤其是在女性群体中。
（中日友好医院呼吸与危重症医学科 沈焜路 摘译 林江涛 审校）
（J Allergy Clin Immunol. 2026 Jan; DOI: 10.1016/j.jaci.2025.09.020 ）
（J Allergy Clin Immunol. 2026 Jan; DOI: 10.1016/j.jaci.2025.09.020 ）
Lifestyle-associated metabolite signatures and the risk of late-onset asthma
Chang Q, Chen L, Zhu Y, Liu B, Zhou X, Liang H, Lin F, Li D, Zhu Z, Pan Z, Chen X, Liu H, Sun D, Lv J, Li L, Pan P, Yu C, Zhang Y.
Abstract
Abstract
BACKGROUND:Unhealthy lifestyle behaviors, leading to systemic metabolic disturbances, are significantly linked to the risk of late-onset asthma. However, the underlying metabolism-related mechanisms remain unclear. We sought to identify lifestyle-related metabolites and assess their predictive value for incident asthma.
METHODS:Using nuclear magnetic resonance metabolomics data from the UK Biobank population (ages 40-69), plasma metabolites associated with healthy lifestyle scores were identified through multiple linear regression. Cox proportional hazards regression was used to further screen metabolites linked to late-onset asthma risk. Elastic net regularization selected critical metabolites for developing an asthma risk prediction model, incorporating conventional clinical characteristics and lifestyle factors. A metabolic score based on nonzero regularization coefficients was derived, and its association with asthma risk was evaluated through survival analysis. Models and metabolic score performance were validated in unused internal UK Biobank participants and an external China Kadoorie Biobank cohort.
RESULTS:Among 198,607 participants (mean age 56.4 years), 159 plasma metabolites were significantly related to healthy lifestyle scores, 103 of which were associated with incident asthma risk. Nine metabolites were selected and incorporated into the asthma risk prediction model, significantly improving its predictive performance (area under the curve 0.812 vs 0.758). Individuals with an unfavorable metabolic signature exhibited a 77.0% increased risk (hazard ratio 1.770, 95% CI 1.634-1.918) of developing asthma compared with individuals with a favorable metabolic signature, with a stronger effect observed in women (hazard ratio 1.914, 95% CI 1.729-2.118). The results for the predictive model and metabolic score were confirmed in both internal and external validations.
CONCLUSION:Multiple lifestyle-related metabolites are associated with late-onset asthma risk and can help stratify asthma risk, particularly among women.
上一篇：
没有了
下一篇：
没有了
