Impaired resolution of blood transcriptomes through tuberculosis treatment with diabetes comorbidity
Impaired resolution of blood transcriptomes through tuberculosis treatment with diabetes comorbidity
复制标题
合并糖尿病合并症的结核病治疗导致血液转录组分辨率受损
DOI：
10.1101/2022.02.07.22269422
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Eckold C
中科院分区：
文献类型：
--
作者：
Eckold C
背景：糖尿病患者比非糖尿病患者更容易患结核病，并且结核病治疗效果较差。我们之前的研究表明，结核病-糖尿病（TB - DM）共发病患者的血液转录组在诊断时具有过度炎症和干扰素反应降低。目前尚不清楚这种情况是否在治疗过程中持续存在并导致不良后果。方法根据结核诊断时和结核治疗6个月后的糖化血红蛋白浓度，在南非、印度尼西亚和罗马尼亚招募的肺结核患者被分为结核-糖尿病、结核伴前驱糖尿病、结核相关高血糖或结核-单纯结核。在诊断和整个治疗期间，通过无偏置RNA - Seq和靶向多重连接依赖探针扩增检测血液中的基因表达。通过纵向混合模型回归分析转录组数据，以确定基因在不同临床组之间是否随时间存在差异表达。建立了跨组结核病治疗反应的预测模型并进行了交叉检验。结果TB - DM和TB - DM患者的基因表达在诊断时存在差异，并且在所有临床组中都受到TB治疗的调节，但程度不同，因此TB - DM患者的基因表达与TB - DM患者的基因表达始终存在差异。一些基因的表达在结核病治疗过程中增加，而另一些基因的表达则减少：一些基因在TB - DM患者中持续高表达，另一些基因在TB - DM患者中持续高表达。参与先天免疫反应、抗微生物免疫和炎症的基因在TB - DM患者治疗过程中显著上调。无论糖尿病状况如何，临床组的总体变化模式是相似的，这使得预测结核病治疗的模型得以开发。结论：TB - DM患者转录组变化的加剧在治疗期间需要更长的时间才能消退，这意味着它们在治疗结束后仍与未合并结核病患者不同。这可能表明TB - DM的炎症反应延长，需要长期治疗或宿主定向治疗才能完全治愈。基于转录组的结核病治疗反应生物标志物特征的开发应包括糖尿病患者，以便在人群中使用。
BackgroundPeople with diabetes are more likely to develop tuberculosis (TB) and to have poor TB‐treatment outcomes than those without. We previously showed that blood transcriptomes in people with TB‐diabetes (TB‐DM) co‐morbidity have excessive inflammatory and reduced interferon responses at diagnosis. It is unknown whether this persists through treatment and contributes to the adverse outcomes.MethodsPulmonary TB patients recruited in South Africa, Indonesia and Romania were classified as having TB‐DM, TB with prediabetes, TB‐related hyperglycaemia or TB‐only, based on glycated haemoglobin concentration at TB diagnosis and after 6 months of TB treatment. Gene expression in blood at diagnosis and intervals throughout treatment was measured by unbiased RNA‐Seq and targeted Multiplex Ligation‐dependent Probe Amplification. Transcriptomic data were analysed by longitudinal mixed‐model regression to identify whether genes were differentially expressed between clinical groups through time. Predictive models of TB‐treatment response across groups were developed and cross‐tested.ResultsGene expression differed between TB and TB‐DM patients at diagnosis and was modulated by TB treatment in all clinical groups but to different extents, such that differences remained in TB‐DM relative to TB‐only throughout. Expression of some genes increased through TB treatment, whereas others decreased: some were persistently more highly expressed in TB‐DM and others in TB‐only patients. Genes involved in innate immune responses, anti‐microbial immunity and inflammation were significantly upregulated in people with TB‐DM throughout treatment. The overall pattern of change was similar across clinical groups irrespective of diabetes status, permitting models predictive of TB treatment to be developed.ConclusionsExacerbated transcriptome changes in TB‐DM take longer to resolve during TB treatment, meaning they remain different from those in uncomplicated TB after treatment completion. This may indicate a prolonged inflammatory response in TB‐DM, requiring prolonged treatment or host‐directed therapy for complete cure. Development of transcriptome‐based biomarker signatures of TB‐treatment response should include people with diabetes for use across populations.
登录
查看更多内容
DOI：
10.1093/bioinformatics/btu638
发表时间：
2015-01-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Anders S;Pyl PT;Huber W
通讯作者：
Huber W
影响因子：
9.1
作者：
Geluk, Annemieke;van Meijgaarden, Krista E.;Ottenhoff, Tom H. M.
通讯作者：
Ottenhoff, Tom H. M.
DOI：
--
发表时间：
2013
期刊：
--
影响因子：
--
作者：
Florencia Aguiree;Alex Brown;N. H. Cho;G. Dahlquist;S. Dodd;T. Dunning;Michael Hirst;Christopher K Hwang;D. Magliano;C. Patterson;Courtney Scott;Jonathon Shaw;G. Soltész;J. Usher-Smith;D. Whiting
通讯作者：
Florencia Aguiree;Alex Brown;N. H. Cho;G. Dahlquist;S. Dodd;T. Dunning;Michael Hirst;Christopher K Hwang;D. Magliano;C. Patterson;Courtney Scott;Jonathon Shaw;G. Soltész;J. Usher-Smith;D. Whiting
影响因子：
3.7
作者：
Kumar NP;Banurekha VV;Nair D;Sridhar R;Kornfeld H;Nutman TB;Babu S
通讯作者：
Babu S
影响因子：
6.4
作者：
Boillat-Blanco, Noemie;Ramaiya, Kaushik L.;Probst-Hensch, Nicole
通讯作者：
Probst-Hensch, Nicole