Guo Yi Tong, Mazidi Mohsen, Wright Neil, Yao Pang, Wang Baihan, Niu Yue, Xia Xi, Meng Xia, Liu Cong, Clarke Robert, Lam Kin Bong Hubert, Kartsonaki Christiana, Millwood Iona, Chen Yiping, Yang Ling, Du Huaidong, Yu Canqing, Sun Dianjianyi, Lv Jun, Li Liming, Chen Junshi, Barnard Maxim, Tian Xiaocao, Ho Kin Fai, Chan Ka Hung, Gasparrini Antonio, Kan Haidong, Chen Zhengming
JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, U.K.
Environ Sci Technol. 2025 Mar 18;59(10):4868-4882. doi: 10.1021/acs.est.4c13020. Epub 2025 Mar 3.
Nonoptimal ambient temperatures (i.e., cold and heat) are leading environmental determinants of major diseases worldwide, but the underlying pathological mechanisms are still poorly understood. We used distributed-lag nonlinear models to examine the associations of cold (5 percentile: -2.1 °C) and heat (95 percentile: 29.5 °C) with 2923 plasma proteins in 3926 adults from 10 areas across China. Overall, 949 proteins were significantly (5% false discovery rate) associated with ambient temperature, including 387 (216/171 down/upregulated) with cold, 770 (656/114 down/upregulated) with heat, and 208 with both cold and heat. Above the median reference temperature (17.7 °C), the associations were largely linear, while below it, they were nonlinear with attenuation below 5 °C, potentially reflecting mediation by heating. Among the 949 proteins, >80% were also associated with systolic blood pressure and incident ischemic heart disease risk and enriched in relevant pathological pathways (e.g., inflammation, immunity, and platelet aggregation). Our study provided a novel atlas of plasma proteins associated with nonoptimal temperatures in Chinese adults.
非最佳环境温度（即寒冷和炎热）是全球主要疾病的主要环境决定因素，但其潜在的病理机制仍知之甚少。我们使用分布滞后非线性模型，研究了来自中国10个地区的3926名成年人中，寒冷（第5百分位数：-2.1°C）和炎热（第95百分位数：29.5°C）与2923种血浆蛋白之间的关联。总体而言，949种蛋白质与环境温度显著相关（错误发现率为5%），其中387种（216种下调/171种上调）与寒冷相关，770种（656种下调/114种上调）与炎热相关，208种与寒冷和炎热均相关。高于中位数参考温度（17.7°C）时，关联大多呈线性，而低于该温度时，关联呈非线性，在5°C以下出现衰减，这可能反映了供暖的中介作用。在这949种蛋白质中，超过80%还与收缩压和缺血性心脏病发病风险相关，并在相关病理途径（如炎症、免疫和血小板聚集）中富集。我们的研究提供了一份中国成年人中与非最佳温度相关的血浆蛋白新图谱。
