Sun Yu, Tang Hao, Du Shuang, Chen Yang, Ou Zheyuan, Zhang Mei, Chen Zhuoru, Tang Zhiwei, Zhang Dongjun, Chen Tianyi, Xu Yanyi, Li Jiufeng, Norback Dan, Hashim Jamal Hisham, Hashim Zailina, Shao Jie, Fu Xi, Zhao Zhuohui
Guangdong Provincial Key Laboratory of Protein Function and Regulation in Agricultural Organisms, College of Life Sciences, South China Agricultural University, Guangzhou 510642, China.
Department of Environmental Health, School of Public Health, Fudan University, NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai 200032, China.
Eco Environ Health. 2023 Aug 22;2(4):208-218. doi: 10.1016/j.eehl.2023.08.001. eCollection 2023 Dec.
Indoor microorganisms impact asthma and allergic rhinitis (AR), but the associated microbial taxa often vary extensively due to climate and geographical variations. To provide more consistent environmental assessments, new perspectives on microbial exposure for asthma and AR are needed. Home dust from 97 cases (32 asthma alone, 37 AR alone, 28 comorbidity) and 52 age- and gender-matched controls in Shanghai, China, were analyzed using high-throughput shotgun metagenomic sequencing and liquid chromatography-mass spectrometry. Homes of healthy children were enriched with environmental microbes, including , , and , and metabolites like keto acids, indoles, pyridines, and flavonoids (astragalin, hesperidin) (False Discovery Rate < 0.05). A neural network co-occurrence probability analysis revealed that environmental microorganisms were involved in producing these keto acids, indoles, and pyridines. Conversely, homes of diseased children were enriched with mycotoxins and synthetic chemicals, including herbicides, insecticides, and food/cosmetic additives. Using a random forest model, characteristic metabolites and microorganisms in Shanghai homes were used to classify high and low prevalence of asthma/AR in an independent dataset in Malaysian schools (N = 1290). Indoor metabolites achieved an average accuracy of 74.9% and 77.1% in differentiating schools with high and low prevalence of asthma and AR, respectively, whereas indoor microorganisms only achieved 51.0% and 59.5%, respectively. These results suggest that indoor metabolites and chemicals rather than indoor microbiome are potentially superior environmental indicators for childhood asthma and AR. This study extends the traditional risk assessment focusing on allergens or air pollutants in childhood asthma and AR, thereby revealing potential novel intervention strategies for these diseases.
室内微生物会影响哮喘和过敏性鼻炎(AR),但由于气候和地理差异,相关的微生物类群往往差异很大。为了提供更一致的环境评估,需要对哮喘和AR的微生物暴露有新的认识。利用高通量鸟枪法宏基因组测序和液相色谱-质谱联用技术,分析了中国上海97例患者(32例单纯哮喘、37例单纯AR、28例合并症)和52例年龄和性别匹配的对照家庭的室内灰尘。健康儿童家庭富含环境微生物,包括[具体微生物名称未给出]、[具体微生物名称未给出]和[具体微生物名称未给出],以及酮酸、吲哚、吡啶和黄酮类化合物(黄芪苷、橙皮苷)等代谢物(错误发现率<0.05)神经网络共现概率分析表明,环境微生物参与了这些酮酸、吲哚和吡啶的产生。相反,患病儿童家庭富含霉菌毒素和合成化学品,包括除草剂、杀虫剂和食品/化妆品添加剂。使用随机森林模型,利用上海家庭中的特征代谢物和微生物对马来西亚学校独立数据集中哮喘/AR的高患病率和低患病率进行分类(N = 1290)。室内代谢物在区分哮喘和AR高患病率和低患病率的学校时,平均准确率分别达到74.9%和77.1%,而室内微生物的准确率分别仅为51.0%和59.5%。这些结果表明,室内代谢物和化学物质而非室内微生物群可能是儿童哮喘和AR更优越的环境指标。本研究扩展了传统的针对儿童哮喘和AR中过敏原或空气污染物的风险评估,从而揭示了这些疾病潜在的新干预策略