Genome-wide characterization of circulating metabolic biomarkers
Authors: Karjalainen Minna K. , Karthikeyan Savita , Oliver-Williams Clare , Sliz Eeva , Allara Elias , Fung Wing Tung , Surendran Praveen , Zhang Weihua , Jousilahti Pekka , Kristiansson Kati , Salomaa Veikko , Goodwin Matt , Hughes David A. , Boehnke Michael , Fernandes Silva Lilian , Yin Xianyong , Mahajan Anubha , Neville Matt J. , van Zuydam Natalie R. , de Mutsert Renée , Li-Gao Ruifang , Mook-Kanamori Dennis O. , Demirkan Ayse , Liu Jun , Noordam Raymond , Trompet Stella , Chen Zhengming , Kartsonaki Christiana , Li Liming , Lin Kuang , Hagenbeek Fiona A. , Hottenga Jouke Jan , Pool René , Ikram M. Arfan , van Meurs Joyce , Haller Toomas , Milaneschi Yuri , Kähönen Mika , Mishra Pashupati P. , Joshi Peter K. , Macdonald-Dunlop Erin , Mangino Massimo , Zierer Jonas , Acar Ilhan E. , Hoyng Carel B. , Lechanteur Yara T. E. , Franke Lude , Kurilshikov Alexander , Zhernakova Alexandra , Beekman Marian , van den Akker Erik B. , Kolcic Ivana , Polasek Ozren , Rudan Igor , Gieger Christian , Waldenberger Melanie , Asselbergs Folkert W. ,   China Kadoorie Biobank Collaborative Group,   Estonian Biobank Research Team,   FinnGen, Hayward Caroline , Fu Jingyuan , den Hollander Anneke I. , Menni Cristina , Spector Tim D. , Wilson James F. , Lehtimäki Terho , Raitakari Olli T. , Penninx Brenda W. J. H. , Esko Tonu , Walters Robin G. , Jukema J. Wouter , Sattar Naveed , Ghanbari Mohsen , Willems van Dijk Ko , Karpe Fredrik , McCarthy Mark I. , Laakso Markku , Järvelin Marjo-Riitta , Timpson Nicholas J. , Perola Markus , Kooner Jaspal S. , Chambers John C. , van Duijn Cornelia , Slagboom P. Eline , Boomsma Dorret I. , Danesh John , Ala-Korpela Mika , Butterworth Adam S. , Kettunen Johannes 
Published: March 2024

AbstractGenome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1–7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases8–11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases.