代谢物谱分析与心血管事件风险：基于人群的3个队列的前瞻性研究
Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts.
作者信息
Würtz Peter, Havulinna Aki S, Soininen Pasi, Tynkkynen Tuulia, Prieto-Merino David, Tillin Therese, Ghorbani Anahita, Artati Anna, Wang Qin, Tiainen Mika, Kangas Antti J, Kettunen Johannes, Kaikkonen Jari, Mikkilä Vera, Jula Antti, Kähönen Mika, Lehtimäki Terho, Lawlor Debbie A, Gaunt Tom R, Hughes Alun D, Sattar Naveed, Illig Thomas, Adamski Jerzy, Wang Thomas J, Perola Markus, Ripatti Samuli, Vasan Ramachandran S, Raitakari Olli T, Gerszten Robert E, Casas Juan-Pablo, Chaturvedi Nish, Ala-Korpela Mika, Salomaa Veikko
机构信息
From Computational Medicine, Institute of Health Sciences, University of Oulu, Finland (P.W., P.S., T. Tynkkynen, Q.W., M.T., A.J.K., J. Kettunen, M.A.-K.); Department of Chronic Disease Prevention, National Institute for Health and Welfare, Finland (P.W., A.S.H., J. Kettunen, A.J., M.P., V.S.); Institute for Molecular Medicine Finland, University of Helsinki (P.W., A.S.H., M.P., S.P.); NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio (P.S., T. Tynkkynen, Q.W., M.T., M.A.-K.); Faculty of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, United Kingdom (D.P.-M., J.-P.C.); Institute of Cardiovascular Science, University College London, United Kingdom (T. Tillin, A.D.H., J.-P.C., N.C.); Framingham Heart Study of the National Heart, Lung, and Blood Institute and Boston University School of Medicine, Framingham, MA (A.G., R.S.V.); Genome Analysis Center, Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany (A.A., J.A.); Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Finland (J. Kaikkonen, V.M., O.T.R.); Department of Food and Environmental Sciences, University of Helsinki, Finland (V.M.,); Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Finland (M.K.); Department of Clinical Chemistry, Fimlab Laboratories, and School of Medicine, University of Tampere, Finland (T.L.); Medical Research Council Integrative Epidemiology Unit at the University of Bristol, United Kingdom (D.A.L., T.R.G., M.A.-K.); School of Social and Community Medicine, University of Bristol, United Kingdom (D.A.L., T.R.G., M.A.-K.); Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (N.S.); Hannover Medical School, Hannover Unified Biobank, Germany (T.I.); Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
出版信息
Circulation. 2015 Mar 3;131(9):774-85. doi: 10.1161/CIRCULATIONAHA.114.013116. Epub 2015 Jan 8.
BACKGROUND
High-throughput profiling of circulating metabolites may improve cardiovascular risk prediction over established risk factors.
METHODS AND RESULTS
We applied quantitative nuclear magnetic resonance metabolomics to identify the biomarkers for incident cardiovascular disease during long-term follow-up. Biomarker discovery was conducted in the National Finnish FINRISK study (n=7256; 800 events). Replication and incremental risk prediction was assessed in the Southall and Brent Revisited (SABRE) study (n=2622; 573 events) and British Women's Health and Heart Study (n=3563; 368 events). In targeted analyses of 68 lipids and metabolites, 33 measures were associated with incident cardiovascular events at P<0.0007 after adjusting for age, sex, blood pressure, smoking, diabetes mellitus, and medication. When further adjusting for routine lipids, 4 metabolites were associated with future cardiovascular events in meta-analyses: higher serum phenylalanine (hazard ratio per standard deviation, 1.18; 95% confidence interval, 1.12-1.24; P=4×10(-10)) and monounsaturated fatty acid levels (1.17; 1.11-1.24; P=1×10(-8)) were associated with increased cardiovascular risk, while higher omega-6 fatty acids (0.89; 0.84-0.94; P=6×10(-5)) and docosahexaenoic acid levels (0.90; 0.86-0.95; P=5×10(-5)) were associated with lower risk. A risk score incorporating these 4 biomarkers was derived in FINRISK. Risk prediction estimates were more accurate in the 2 validation cohorts (relative integrated discrimination improvement, 8.8% and 4.3%), albeit discrimination was not enhanced. Risk classification was particularly improved for persons in the 5% to 10% risk range (net reclassification, 27.1% and 15.5%). Biomarker associations were further corroborated with mass spectrometry in FINRISK (n=671) and the Framingham Offspring Study (n=2289).
CONCLUSIONS
Metabolite profiling in large prospective cohorts identified phenylalanine, monounsaturated fatty acids, and polyunsaturated fatty acids as biomarkers for cardiovascular risk. This study substantiates the value of high-throughput metabolomics for biomarker discovery and improved risk assessment.
背景
循环代谢物的高通量分析可能比既定风险因素更能改善心血管疾病风险预测。
方法与结果
我们应用定量核磁共振代谢组学来识别长期随访期间新发心血管疾病的生物标志物。在芬兰全国FINRISK研究（n = 7256；800例事件）中进行生物标志物发现。在南索尔和布伦特再研究（SABRE）（n = 2622；573例事件）以及英国女性健康与心脏研究（n = 3563；368例事件）中评估重复验证和增量风险预测。在对68种脂质和代谢物的靶向分析中，在调整年龄、性别、血压、吸烟、糖尿病和用药情况后，33项指标与新发心血管事件相关，P<0.0007。在荟萃分析中，当进一步调整常规脂质时，4种代谢物与未来心血管事件相关：较高的血清苯丙氨酸（每标准差风险比，1.18；95%置信区间，1.12 - 1.24；P = 4×10⁻¹⁰）和单不饱和脂肪酸水平（1.17；1.11 - 1.24；P = 1×10⁻⁸）与心血管风险增加相关，而较高的ω-6脂肪酸（0.89；0.84 - 0.94；P = 6×10⁻⁵）和二十二碳六烯酸水平（0.90；0.86 - 0.95；P = 5×10⁻⁵）与较低风险相关。在FINRISK中得出了包含这4种生物标志物的风险评分。在2个验证队列中，风险预测估计更准确（相对综合鉴别改善率分别为8.8%和4.3%），尽管鉴别能力未增强。对于处于5%至10%风险范围的人群，风险分类有显著改善（净重新分类率分别为27.1%和15.5%）。在FINRISK（n = 671）和弗雷明汉后代研究（n = 2289）中，通过质谱法进一步证实了生物标志物的相关性。
结论
在大型前瞻性队列中的代谢物分析确定了苯丙氨酸、单不饱和脂肪酸和多不饱和脂肪酸为心血管疾病风险的生物标志物。本研究证实了高通量代谢组学在生物标志物发现和改善风险评估方面的价值。
Zotero 插件