Kettunen Johannes, Demirkan Ayşe, Würtz Peter, Draisma Harmen H M, Haller Toomas, Rawal Rajesh, Vaarhorst Anika, Kangas Antti J, Lyytikäinen Leo-Pekka, Pirinen Matti, Pool René, Sarin Antti-Pekka, Soininen Pasi, Tukiainen Taru, Wang Qin, Tiainen Mika, Tynkkynen Tuulia, Amin Najaf, Zeller Tanja, Beekman Marian, Deelen Joris, van Dijk Ko Willems, Esko Tõnu, Hottenga Jouke-Jan, van Leeuwen Elisabeth M, Lehtimäki Terho, Mihailov Evelin, Rose Richard J, de Craen Anton J M, Gieger Christian, Kähönen Mika, Perola Markus, Blankenberg Stefan, Savolainen Markku J, Verhoeven Aswin, Viikari Jorma, Willemsen Gonneke, Boomsma Dorret I, van Duijn Cornelia M, Eriksson Johan, Jula Antti, Järvelin Marjo-Riitta, Kaprio Jaakko, Metspalu Andres, Raitakari Olli, Salomaa Veikko, Slagboom P Eline, Waldenberger Melanie, Ripatti Samuli, Ala-Korpela Mika
Computational Medicine, Faculty of Medicine, University of Oulu, PO Box 5000, 90014 Oulu, Finland.
National Institute for Health and Welfare, PO Box 30, FI-00271 Helsinki, Finland.
Nat Commun. 2016 Mar 23;7:11122. doi: 10.1038/ncomms11122.
Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk.
全基因组关联研究已经确定了许多与复杂疾病相关的基因座，但其分子机制在很大程度上仍不清楚。对循环代谢物进行全面的分子分析可以捕捉到高度可遗传的特征，这有助于揭示既定疾病变异背后的代谢病理生理学。我们对多达24925名个体通过核磁共振代谢组学量化的123种循环代谢特征进行了基因影响的扩展全基因组关联研究，并确定了八个与氨基酸、丙酮酸和脂肪酸相关的新基因座。与心血管风险相关的LPA基因座例证了详细的代谢分析如何通过与极低密度脂蛋白和甘油三酯代谢的广泛关联来揭示潜在病因。基因精细定位和孟德尔随机化揭示了脂蛋白(a)对整体脂蛋白代谢的广泛因果效应，我们通过电子医疗记录评估了基因水平升高的脂蛋白(a)对多种疾病的潜在多效性后果。我们的研究结果强化了针对LPA进行安全干预以降低心血管风险的论据。
