作者
Minna K Karjalainen, Savita Karthikeyan, Clare Oliver-Williams, Eeva Sliz, Elias Allara, Wing Tung Fung, Praveen Surendran, Weihua Zhang, Pekka Jousilahti, Kati Kristiansson, Veikko Salomaa, Matt Goodwin, David A Hughes, Michael Boehnke, Lilian Fernandes Silva, Xianyong Yin, Anubha Mahajan, Matt J Neville, Natalie R Van Zuydam, Renée de Mutsert, Ruifang Li-Gao, Dennis O Mook-Kanamori, Ayse Demirkan, Jun Liu, Raymond Noordam, Stella Trompet, Zhengming Chen, Christiana Kartsonaki, Liming Li, Kuang Lin, Fiona A Hagenbeek, Jouke Jan Hottenga, René Pool, M Arfan Ikram, Joyce van Meurs, Toomas Haller, Yuri Milaneschi, Mika Kähönen, Pashupati P Mishra, Peter K Joshi, Erin Macdonald-Dunlop, Massimo Mangino, Jonas Zierer, Ilhan E Acar, Carel B Hoyng, Yara TE Lechanteur, Lude Franke, Alexander Kurilshikov, Alexandra Zhernakova, Marian Beekman, Erik B van den Akker, Ivana Kolcic, Ozren Polasek, Igor Rudan, Christian Gieger, Melanie Waldenberger, Folkert W Asselbergs, China Kadoorie Biobank Collaborative Group, Estonian Biobank Research Team, FinnGen, Caroline Hayward, Jingyuan Fu, Anneke I den Hollander, Cristina Menni, Tim D Spector, James F Wilson, Terho Lehtimäki, Olli T Raitakari, Brenda WJH Penninx, Tonu Esko, Robin G Walters, J Wouter Jukema, Naveed Sattar, Mohsen Ghanbari, Ko Willems van Dijk, Fredrik Karpe, Mark I McCarthy, Markku Laakso, Marjo-Riitta Järvelin, Nicholas J Timpson, Markus Perola, Jaspal S Kooner, John C Chambers, Cornelia van Duijn, P Eline Slagboom, Dorret I Boomsma, John Danesh, Mika Ala-Korpela, Adam S Butterworth, Johannes Kettunen
发表日期
2024/4/4
期刊
Nature
卷号
628
期号
8006
页码范围
130-138
出版商
Nature Publishing Group UK
简介
Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism, , , , , –. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases, , –. 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 …
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