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实验性人类甲状腺毒症模型的血浆蛋白质组和代谢组特征分析

Plasma proteome and metabolome characterization of an experimental human thyrotoxicosis model.

作者信息

Pietzner Maik, Engelmann Beatrice, Kacprowski Tim, Golchert Janine, Dirk Anna-Luise, Hammer Elke, Iwen K Alexander, Nauck Matthias, Wallaschofski Henri, Führer Dagmar, Münte Thomas F, Friedrich Nele, Völker Uwe, Homuth Georg, Brabant Georg

机构信息

Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Straße, 17475, Greifswald, Germany.

DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.

出版信息

BMC Med. 2017 Jan 9;15(1):6. doi: 10.1186/s12916-016-0770-8.

DOI:10.1186/s12916-016-0770-8
PMID:28065164
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5220622/
Abstract

BACKGROUND

Determinations of thyrotropin (TSH) and free thyroxine (FT) represent the gold standard in evaluation of thyroid function. To screen for novel peripheral biomarkers of thyroid function and to characterize FT-associated physiological signatures in human plasma we used an untargeted OMICS approach in a thyrotoxicosis model.

METHODS

A sample of 16 healthy young men were treated with levothyroxine for 8 weeks and plasma was sampled before the intake was started as well as at two points during treatment and after its completion, respectively. Mass spectrometry-derived metabolite and protein levels were related to FT serum concentrations using mixed-effect linear regression models in a robust setting. To compile a molecular signature discriminating between thyrotoxicosis and euthyroidism, a random forest was trained and validated in a two-stage cross-validation procedure.

RESULTS

Despite the absence of obvious clinical symptoms, mass spectrometry analyses detected 65 metabolites and 63 proteins exhibiting significant associations with serum FT. A subset of 15 molecules allowed a robust and good prediction of thyroid hormone function (AUC = 0.86) without prior information on TSH or FT. Main FT-associated signatures indicated increased resting energy expenditure, augmented defense against systemic oxidative stress, decreased lipoprotein particle levels, and increased levels of complement system proteins and coagulation factors. Further association findings question the reliability of kidney function assessment under hyperthyroid conditions and suggest a link between hyperthyroidism and cardiovascular diseases via increased dimethylarginine levels.

CONCLUSION

Our results emphasize the power of untargeted OMICs approaches to detect novel pathways of thyroid hormone action. Furthermore, beyond TSH and FT, we demonstrated the potential of such analyses to identify new molecular signatures for diagnosis and treatment of thyroid disorders. This study was registered at the German Clinical Trials Register (DRKS) [DRKS00011275] on the 16th of November 2016.

摘要

背景

促甲状腺激素(TSH)和游离甲状腺素(FT)的测定是评估甲状腺功能的金标准。为了筛选甲状腺功能的新型外周生物标志物,并表征人血浆中与FT相关的生理特征,我们在甲状腺毒症模型中采用了非靶向组学方法。

方法

16名健康年轻男性样本接受左甲状腺素治疗8周,分别在开始服药前、治疗期间的两个时间点以及治疗结束后采集血浆。在稳健的环境中,使用混合效应线性回归模型将质谱衍生的代谢物和蛋白质水平与FT血清浓度相关联。为了编制区分甲状腺毒症和甲状腺功能正常的分子特征,在两阶段交叉验证程序中训练并验证了随机森林。

结果

尽管没有明显的临床症状,但质谱分析检测到65种代谢物和63种蛋白质与血清FT存在显著关联。15种分子的子集能够在没有TSH或FT先验信息的情况下,对甲状腺激素功能进行稳健且良好的预测(AUC = 0.86)。主要的FT相关特征表明静息能量消耗增加、对全身氧化应激的防御增强、脂蛋白颗粒水平降低以及补体系统蛋白和凝血因子水平增加。进一步的关联发现质疑了甲状腺功能亢进状态下肾功能评估的可靠性,并表明甲状腺功能亢进与心血管疾病之间可能通过二甲基精氨酸水平升高存在联系。

结论

我们的结果强调了非靶向组学方法在检测甲状腺激素作用新途径方面的能力。此外,除了TSH和FT之外,我们还证明了此类分析在识别甲状腺疾病诊断和治疗新分子特征方面的潜力。本研究于2016年11月16日在德国临床试验注册中心(DRKS)注册[DRKS00011275]。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05bf/5220622/0368f134e595/12916_2016_770_Fig5_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05bf/5220622/0368f134e595/12916_2016_770_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05bf/5220622/f58f8f365d21/12916_2016_770_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05bf/5220622/ca2b40e2ec8c/12916_2016_770_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05bf/5220622/bb1b2313e4ef/12916_2016_770_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05bf/5220622/e743613b6cc6/12916_2016_770_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05bf/5220622/0368f134e595/12916_2016_770_Fig5_HTML.jpg

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