血浆脂质组学谱改善了 2 型糖尿病心血管事件的传统危险因素预测。

Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus.

机构信息

From Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia (Z.H.A., P.A.M., C.K.B., N.A.M., G.W., P.J.N., B.A.K., P.J.M.); King Fahad Medical City, Riyadh, Saudi Arabia (Z.H.A.); Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, VIC, Australia (Z.H.A., M.J.M., P.J.M.); NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia (J.S., E.H.B.); School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia (A.M.T., S.Z.); Royal Prince Alfred Hospital, Sydney, NSW, Australia (D.R.S.); Hópital Bichat-Claude Bernard and Université Paris 7, Paris, France (M.M.); George Institute for Global Health, Sydney, NSW, Australia (B.N., N.R.P., S.Z., G.S.H., J.C., M.W.); University College London and National Institute for Health Research, University College London Hospitals, Biomedical Research Centre, London, UK (B.W.); Department of Cardiology, Royal Perth Hospital/University of Western Australia, Perth, WA, Australia (G.S.H.); George Institute for Global Health, University of Oxford, Oxford, UK (M.W.); and Department of Epidemiology, Johns Hopkins University, Baltimore, MD (M.W.).

出版信息

Circulation. 2016 Nov 22;134(21):1637-1650. doi: 10.1161/CIRCULATIONAHA.116.023233. Epub 2016 Oct 18.

DOI:10.1161/CIRCULATIONAHA.116.023233

PMID:27756783

Abstract

BACKGROUND

Clinical lipid measurements do not show the full complexity of the altered lipid metabolism associated with diabetes mellitus or cardiovascular disease. Lipidomics enables the assessment of hundreds of lipid species as potential markers for disease risk.

METHODS

Plasma lipid species (310) were measured by a targeted lipidomic analysis with liquid chromatography electrospray ionization-tandem mass spectrometry on a case-cohort (n=3779) subset from the ADVANCE trial (Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation). The case-cohort was 61% male with a mean age of 67 years. All participants had type 2 diabetes mellitus with ≥1 additional cardiovascular risk factors, and 35% had a history of macrovascular disease. Weighted Cox regression was used to identify lipid species associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death) and cardiovascular death during a 5-year follow-up period. Multivariable models combining traditional risk factors with lipid species were optimized with the Akaike information criteria. C statistics and NRIs were calculated within a 5-fold cross-validation framework.

RESULTS

Sphingolipids, phospholipids (including lyso- and ether- species), cholesteryl esters, and glycerolipids were associated with future cardiovascular events and cardiovascular death. The addition of 7 lipid species to a base model (14 traditional risk factors and medications) to predict cardiovascular events increased the C statistic from 0.680 (95% confidence interval [CI], 0.678-0.682) to 0.700 (95% CI, 0.698-0.702; P<0.0001) with a corresponding continuous NRI of 0.227 (95% CI, 0.219-0.235). The prediction of cardiovascular death was improved with the incorporation of 4 lipid species into the base model, showing an increase in the C statistic from 0.740 (95% CI, 0.738-0.742) to 0.760 (95% CI, 0.757-0.762; P<0.0001) and a continuous net reclassification index of 0.328 (95% CI, 0.317-0.339). The results were validated in a subcohort with type 2 diabetes mellitus (n=511) from the LIPID trial (Long-Term Intervention With Pravastatin in Ischemic Disease).

CONCLUSIONS

The improvement in the prediction of cardiovascular events, above traditional risk factors, demonstrates the potential of plasma lipid species as biomarkers for cardiovascular risk stratification in diabetes mellitus.

CLINICAL TRIAL REGISTRATION

URL: https://clinicaltrials.gov. Unique identifier: NCT00145925.

摘要

背景

临床血脂检测无法显示与糖尿病或心血管疾病相关的脂质代谢改变的全貌。脂质组学能够评估数百种脂质作为疾病风险潜在标志物的特性。

方法

采用液相色谱-电喷雾电离-串联质谱对 ADVANCE 试验（糖尿病和血管疾病的行动：培哚普利和氨氯地平的控制评估）中的病例-队列（n=3779）亚组进行靶向脂质组分析，检测血浆脂质种类（310 种）。该病例-队列中 61%为男性，平均年龄 67 岁。所有参与者均患有 2 型糖尿病且至少有 1 个其他心血管危险因素，35%有大血管疾病史。使用加权 Cox 回归来确定与未来心血管事件（非致死性心肌梗死、非致死性卒中和心血管死亡）和 5 年随访期间心血管死亡相关的脂质种类。使用赤池信息量准则（Akaike information criteria）优化了将传统危险因素与脂质种类相结合的多变量模型。在 5 倍交叉验证框架内计算 C 统计量和净重新分类指数。

结果

鞘脂、磷脂（包括溶血磷脂和醚类）、胆固醇酯和甘油磷脂与未来心血管事件和心血管死亡相关。在基本模型（14 项传统危险因素和药物）中添加 7 种脂质种类来预测心血管事件可将 C 统计量从 0.680（95%置信区间 [CI]，0.678-0.682）提高到 0.700（95% CI，0.698-0.702；P<0.0001），连续净重新分类指数相应提高 0.227（95% CI，0.219-0.235）。将 4 种脂质种类纳入基本模型可提高心血管死亡的预测能力，C 统计量从 0.740（95% CI，0.738-0.742）提高到 0.760（95% CI，0.757-0.762；P<0.0001），净重新分类指数连续提高 0.328（95% CI，0.317-0.339）。在 LIPID 试验（缺血性疾病中普伐他汀的长期干预）的 2 型糖尿病亚组（n=511）中对结果进行了验证。