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血浆代谢物预测代谢综合征的发生和逆转。

Plasma metabolite predictors of metabolic syndrome incidence and reversion.

机构信息

Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.

出版信息

Metabolism. 2024 Feb;151:155742. doi: 10.1016/j.metabol.2023.155742. Epub 2023 Nov 24.

Abstract

BACKGROUND

Metabolic Syndrome (MetS) is a progressive pathophysiological state defined by a cluster of cardiometabolic traits. However, little is known about metabolites that may be predictors of MetS incidence or reversion. Our objective was to identify plasma metabolites associated with MetS incidence or MetS reversion.

METHODS

The study included 1468 participants without cardiovascular disease (CVD) but at high CVD risk at enrollment from two case-cohort studies nested within the PREvención con DIeta MEDiterránea (PREDIMED) study with baseline metabolomics data. MetS was defined in accordance with the harmonized International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute criteria, which include meeting 3 or more thresholds for waist circumference, triglyceride, HDL cholesterol, blood pressure, and fasting blood glucose. MetS incidence was defined by not having MetS at baseline but meeting the MetS criteria at a follow-up visit. MetS reversion was defined by MetS at baseline but not meeting MetS criteria at a follow-up visit. Plasma metabolome was profiled by LC-MS. Multivariable-adjusted Cox regression models and elastic net regularized regressions were used to assess the association of 385 annotated metabolites with MetS incidence and MetS reversion after adjusting for potential risk factors.

RESULTS

Of the 603 participants without baseline MetS, 298 developed MetS over the median 4.8-year follow-up. Of the 865 participants with baseline MetS, 285 experienced MetS reversion. A total of 103 and 88 individual metabolites were associated with MetS incidence and MetS reversion, respectively, after adjusting for confounders and false discovery rate correction. A metabolomic signature comprised of 77 metabolites was robustly associated with MetS incidence (HR: 1.56 (95 % CI: 1.33-1.83)), and a metabolomic signature of 83 metabolites associated with MetS reversion (HR: 1.44 (95 % CI: 1.25-1.67)), both p < 0.001. The MetS incidence and reversion signatures included several lipids (mainly glycerolipids and glycerophospholipids) and branched-chain amino acids.

CONCLUSION

We identified unique metabolomic signatures, primarily comprised of lipids (including glycolipids and glycerophospholipids) and branched-chain amino acids robustly associated with MetS incidence; and several amino acids and glycerophospholipids associated with MetS reversion. These signatures provide novel insights on potential distinct mechanisms underlying the conditions leading to the incidence or reversion of MetS.

摘要

背景

代谢综合征(MetS)是一种由一组心血管代谢特征定义的进行性病理生理状态。然而,对于可能预测 MetS 发病或逆转的代谢物知之甚少。我们的目的是确定与 MetS 发病或 MetS 逆转相关的血浆代谢物。

方法

本研究纳入了来自两个嵌套于 PREvención con DIeta MEDiterránea(PREDIMED)研究的病例-队列研究的 1468 名无心血管疾病(CVD)但基线时 CVD 风险较高的参与者,这些参与者具有基线代谢组学数据。MetS 按照国际糖尿病联合会和美国心脏协会/国家心肺血液研究所的统一标准定义,包括满足腰围、甘油三酯、高密度脂蛋白胆固醇、血压和空腹血糖 3 个或更多标准。MetS 发病定义为基线时无 MetS,但随访时符合 MetS 标准。MetS 逆转定义为基线时 MetS,但随访时不符合 MetS 标准。通过 LC-MS 对血浆代谢组进行分析。多变量调整后的 Cox 回归模型和弹性网络正则化回归用于评估调整潜在风险因素后,385 种注释代谢物与 MetS 发病和 MetS 逆转的相关性。

结果

在 603 名基线时无 MetS 的参与者中,有 298 名在中位 4.8 年的随访期间发生了 MetS。在 865 名基线时患有 MetS 的参与者中,有 285 名经历了 MetS 逆转。在调整混杂因素和错误发现率校正后,分别有 103 种和 88 种个体代谢物与 MetS 发病和 MetS 逆转相关。由 77 种代谢物组成的代谢组学特征与 MetS 发病显著相关(HR:1.56(95%CI:1.33-1.83)),由 83 种代谢物组成的代谢组学特征与 MetS 逆转相关(HR:1.44(95%CI:1.25-1.67)),均 P<0.001。MetS 发病和逆转特征包括几种脂质(主要是甘油酯和甘油磷脂)和支链氨基酸。

结论

我们确定了与 MetS 发病相关的独特代谢组学特征,主要由脂质(包括糖脂和甘油磷脂)和支链氨基酸组成,与 MetS 发病显著相关;以及与 MetS 逆转相关的几种氨基酸和甘油磷脂。这些特征提供了潜在的新见解,即导致 MetS 发病或逆转的情况可能存在不同的机制。

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