IMI-DIRECT 研究发现的人体血浆代谢物在糖尿病前期和 2 型糖尿病中的作用。

IF 8.4 1区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Sapna Sharma, Qiuling Dong, Mark Haid, Jonathan Adam, Roberto Bizzotto, Juan J Fernandez-Tajes, Angus G Jones, Andrea Tura, Anna Artati, Cornelia Prehn, Gabi Kastenmüller, Robert W Koivula, Paul W Franks, Mark Walker, Ian M Forgie, Giuseppe Giordano, Imre Pavo, Hartmut Ruetten, Manolis Dermitzakis, Mark I McCarthy, Oluf Pedersen, Jochen M Schwenk, Konstantinos D Tsirigos, Federico De Masi, Soren Brunak, Ana Viñuela, Andrea Mari, Timothy J McDonald, Tarja Kokkola, Jerzy Adamski, Ewan R Pearson, Harald Grallert
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引用次数: 0

摘要

目的/假设:2 型糖尿病是一种由高血糖引起的慢性疾病。我们的目的是描述代谢组学的特征,找出它们与血糖谱的关联,并找出代谢物与 2 型糖尿病之间的因果关系:作为创新药物倡议--糖尿病患者分层研究(IMI-DIRECT)联盟的一部分,我们使用 Biocrates AbsoluteIDQ p150 试剂盒和 Metabolon 分析仪测量了 3000 份血浆样本。共有 911 个代谢物(132 个靶向代谢组学、779 个非靶向代谢组学)通过了质量控制。以每种代谢物的浓度/峰面积为解释变量,以血糖状况为因变量,计算出多变量线性回归和逻辑回归分析估计值。该分析在基本模型中对年龄、性别、体重指数和研究中心进行了调整,在完整模型中对酒精、吸烟、血压、空腹高密度脂蛋白胆固醇和空腹三酰甘油进行了调整。统计显著性均经过 Bonferroni 校正。除了关联之外,我们还研究了中介效应和因果效应,分别采用了因果中介检验和双样本孟德尔随机化(2SMR)方法:在靶向代谢组学中,我们分别观察到 4 个(15 个)、34 个(99 个)和 50 个(108 个)代谢物(括号内为非靶向代谢组学中观察到的代谢物数量)在比较正常血糖调节与受损血糖调节/糖尿病、正常血糖调节与 2 型糖尿病、受损血糖调节与 2 型糖尿病时存在显著差异。重要的代谢物主要是支链氨基酸(BCAAs),还有一些衍生的支链氨基酸、脂类、异生物体和一些未知物。C17:0 的溶血磷脂酰胆碱、六糖总和、BCAA 代谢产生的氨基酸(包括亮氨酸、异亮氨酸、缬氨酸、N-乳酰缬氨酸、N-乳酰亮氨酸和甲脒谷氨酸)和乳酸盐等代谢物以及一种未知代谢物(X-24295)与 HbA1c 进展率有关,并且是 2 型糖尿病从基线到 18 个月和 48 个月随访期间的重要介质。2SMR 是利用英国生物库全基因组关联研究的汇总统计来估计暴露对结果的因果效应。我们发现,2 型糖尿病对三种代谢物(己糖、谷氨酸和己酸[脂肪酸 (FA) 6:0])的水平有因果效应,而脂质,如特定的磷脂酰胆碱(PC)(即 PC aa C36:2、PC aa C36:5、PC ae C36:3和PC ae C34:3)以及两种n-3脂肪酸硬脂酸酯(18:4n3)和二十二碳五烯酸酯(22:5n3)可能在2型糖尿病的发病中起着诱因作用。结论/解释:我们的研究结果确定了已知的 BCAAs 和脂类,以及新型 N-乳酰氨基酸代谢物,它们与糖尿病前期和糖尿病有显著相关性,从基线到随访(18 个月和 48 个月)都能介导糖尿病的影响。利用基因变异进行的因果推断显示,脂质代谢和 n-3 脂肪酸是代谢物对 2 型糖尿病的因果关系,而六糖总和则是 2 型糖尿病对代谢物的因果关系。已确定的代谢物标记物有助于根据个人的风险进展对其进行分层,并应能采取有针对性的干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Role of human plasma metabolites in prediabetes and type 2 diabetes from the IMI-DIRECT study.

Role of human plasma metabolites in prediabetes and type 2 diabetes from the IMI-DIRECT study.

Aims/hypothesis: Type 2 diabetes is a chronic condition that is caused by hyperglycaemia. Our aim was to characterise the metabolomics to find their association with the glycaemic spectrum and find a causal relationship between metabolites and type 2 diabetes.

Methods: As part of the Innovative Medicines Initiative - Diabetes Research on Patient Stratification (IMI-DIRECT) consortium, 3000 plasma samples were measured with the Biocrates AbsoluteIDQ p150 Kit and Metabolon analytics. A total of 911 metabolites (132 targeted metabolomics, 779 untargeted metabolomics) passed the quality control. Multivariable linear and logistic regression analysis estimates were calculated from the concentration/peak areas of each metabolite as an explanatory variable and the glycaemic status as a dependent variable. This analysis was adjusted for age, sex, BMI, study centre in the basic model, and additionally for alcohol, smoking, BP, fasting HDL-cholesterol and fasting triacylglycerol in the full model. Statistical significance was Bonferroni corrected throughout. Beyond associations, we investigated the mediation effect and causal effects for which causal mediation test and two-sample Mendelian randomisation (2SMR) methods were used, respectively.

Results: In the targeted metabolomics, we observed four (15), 34 (99) and 50 (108) metabolites (number of metabolites observed in untargeted metabolomics appear in parentheses) that were significantly different when comparing normal glucose regulation vs impaired glucose regulation/prediabetes, normal glucose regulation vs type 2 diabetes, and impaired glucose regulation vs type 2 diabetes, respectively. Significant metabolites were mainly branched-chain amino acids (BCAAs), with some derivatised BCAAs, lipids, xenobiotics and a few unknowns. Metabolites such as lysophosphatidylcholine a C17:0, sum of hexoses, amino acids from BCAA metabolism (including leucine, isoleucine, valine, N-lactoylvaline, N-lactoylleucine and formiminoglutamate) and lactate, as well as an unknown metabolite (X-24295), were associated with HbA1c progression rate and were significant mediators of type 2 diabetes from baseline to 18 and 48 months of follow-up. 2SMR was used to estimate the causal effect of an exposure on an outcome using summary statistics from UK Biobank genome-wide association studies. We found that type 2 diabetes had a causal effect on the levels of three metabolites (hexose, glutamate and caproate [fatty acid (FA) 6:0]), whereas lipids such as specific phosphatidylcholines (PCs) (namely PC aa C36:2, PC aa C36:5, PC ae C36:3 and PC ae C34:3) as well as the two n-3 fatty acids stearidonate (18:4n3) and docosapentaenoate (22:5n3) potentially had a causal role in the development of type 2 diabetes.

Conclusions/interpretation: Our findings identify known BCAAs and lipids, along with novel N-lactoyl-amino acid metabolites, significantly associated with prediabetes and diabetes, that mediate the effect of diabetes from baseline to follow-up (18 and 48 months). Causal inference using genetic variants shows the role of lipid metabolism and n-3 fatty acids as being causal for metabolite-to-type 2 diabetes whereas the sum of hexoses is causal for type 2 diabetes-to-metabolite. Identified metabolite markers are useful for stratifying individuals based on their risk progression and should enable targeted interventions.

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来源期刊
Diabetologia
Diabetologia 医学-内分泌学与代谢
CiteScore
18.10
自引率
2.40%
发文量
193
审稿时长
1 months
期刊介绍: Diabetologia, the authoritative journal dedicated to diabetes research, holds high visibility through society membership, libraries, and social media. As the official journal of the European Association for the Study of Diabetes, it is ranked in the top quartile of the 2019 JCR Impact Factors in the Endocrinology & Metabolism category. The journal boasts dedicated and expert editorial teams committed to supporting authors throughout the peer review process.
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