代谢物概况和心血管事件风险:对3个基于人口的队列进行前性研究
Peter Würtz1, Aki S Havulinna1, Pasi Soininen1
1From 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
高通量代谢学确定了四个关键生物标志物用于心血管疾病风险预测. 这些包括氨酸和单不和脂肪酸 (风险增加),以及omega-6和多可萨赫萨赫酸脂肪酸 (风险降低).
科学领域:
- 心血管疾病研究研究
- 代谢学 代谢学 代谢学
- 生物标志物发现发现
背景情况:
- 已确定的心血管风险因素在预测疾病方面存在局限性.
- 循环代谢物的高通量分析为改善心血管风险预测提供了潜力.
研究的目的:
- 用定量核磁共振代谢学来识别发生心血管疾病的新生物标志物.
- 评估大型潜在队列中已识别的代谢物的增量风险预测值.
主要方法:
- 量子核磁共振代谢学应用于FINRISK,SABRE和英国妇女健康和心脏研究队列.
- 针对68种脂质和代谢物的有针对性的分析,其次是对临床因素和常规脂质进行调整的元分析.
- 使用四个经过验证的生物标志物制定风险评分,并评估其预测性能的评估.
主要成果:
- 在调整后,有四种与心血管事件相关的代谢物:氨酸和单不和脂肪酸 (风险增加),欧米茄-6脂肪酸和多可沙赫酸 (风险降低).
- 结合这些生物标志物的风险评分提高了风险预测准确性和验证队列中的分类.
- 在独立的队列中,使用质谱测量证实了生物标志物协会.
结论:
- 在大型潜在队列中进行的代谢物分析确定了氨酸,单不和脂肪酸和多不和脂肪酸作为心血管风险的有价值的生物标志物.
- 高通量代谢学为生物标志物发现提供了一个强大的平台,并增强了心血管风险评估能力.
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