PT -期刊文章盟Shivakoti鲁派克AU -纽曼,John w . AU -汉娜,卢克伊丽莎白AU -奎罗斯,阿图尔T.L. AU - Borkowski,卡米尔盟——圣人,阿卡什n . AU - Paradkar都非盟- Satyamurthi Pattabiraman AU - Kulkarni Vandana盟——热带雨林,Murugesh AU -普拉丹,Neeta盟——Shivakumar先生维贾伊巴拉约根德拉盟——Natarajan萨拉瓦南AU - Karunaianantham,拉梅什盟——圣人,Nikhil AU - Thiruvengadam Kannan盟——Fiehn奥利弗AU -巴拉Renu盟——Kagal安居非盟- Gaikwad,桑杰盟——Sangle Shashikala盟,Golub乔纳森•e . AU -安德拉德布鲁诺b . AU - Mave维迪雅盟-古普塔,Amita盟——Padmapriyadarsini Chandrasekaran TI -主机lipidome和肺结核治疗失败援助- 10.1183/13993003.04532 -2020 DP - 2022年1月01 TA -欧洲呼吸杂志》第六PG - 2004532 - 59 IP - 1 4099 - //www.qdcxjkg.com/content/59/1/2004532.short 4100 - //www.qdcxjkg.com/content/59/1/2004532.full所以欧元和J2022 1月01;宿主脂质在结核病(TB)的发病机制中起着重要作用。结核病治疗开始(基线)时的宿主脂质是否影响后续治疗结果尚未得到很好的描述。我们使用无偏脂质组学来研究宿主脂质与结核病治疗失败的前瞻性关联。方法采用前瞻性队列研究中嵌套的病例对照研究(n=192)，研究成人肺结核患者基线血脂与肺结核治疗失败的关系。病例(n=46)定义为结核病治疗失败，对照组(n=146)定义为未治疗失败的患者。用液相色谱质谱技术测定复合脂质和炎性脂质介质。调整后的最小二乘回归用于评估组间的差异。此外，机器学习识别曲线下面积(AUC)最高的脂类来对病例和对照进行分类。Results Baseline levels of 32 lipids differed between controls and those with treatment failure after false discovery rate adjustment. Treatment failure was associated with lower baseline levels of cholesteryl esters and oxylipin, and higher baseline levels of ceramides and triglycerides compared to controls. Two cholesteryl ester lipids combined in a unique classifier model provided an AUC of 0.79 (95% CI 0.65–0.93) in the test dataset for prediction of TB treatment failure.Conclusions We identified lipids, some with known roles in TB pathogenesis, associated with TB treatment failure. In addition, a lipid signature with prognostic accuracy for TB treatment failure was identified. These lipids could be potential targets for risk-stratification, adjunct therapy and treatment monitoring.In this study, unbiased lipidomics were used to identify host lipids prospectively associated with TB treatment failure. These lipids, some with known roles in TB pathogenesis, could be potential targets for adjunct therapy and treatment monitoring. https://bit.ly/3vHZ0Ec