👤 Georg Ehret

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Jian Gong, Fredrick Schumacher, Unhee Lim +43 more · 2013 · American journal of human genetics · Elsevier · added 2026-04-24
Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whet Show more
Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10(-8)) and DHX34 (rs4802349, p = 1.2 × 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci. Show less
no PDF DOI: 10.1016/j.ajhg.2013.08.012
SEC16B
John C Chambers, Weihua Zhang, Joban Sehmi +140 more · 2011 · Nature genetics · Nature · added 2026-04-24
John C Chambers, Weihua Zhang, Joban Sehmi, Xinzhong Li, Mark N Wass, Pim Van der Harst, Hilma Holm, Serena Sanna, Maryam Kavousi, Sebastian E Baumeister, Lachlan J Coin, Guohong Deng, Christian Gieger, Nancy L Heard-Costa, Jouke-Jan Hottenga, Brigitte Kühnel, Vinod Kumar, Vasiliki Lagou, Liming Liang, Jian'an Luan, Pedro Marques Vidal, Irene Mateo Leach, Paul F O'Reilly, John F Peden, Nilufer Rahmioglu, Pasi Soininen, Elizabeth K Speliotes, Xin Yuan, Gudmar Thorleifsson, Behrooz Z Alizadeh, Larry D Atwood, Ingrid B Borecki, Morris J Brown, Pimphen Charoen, Francesco Cucca, Debashish Das, Eco J C de Geus, Anna L Dixon, Angela Döring, Georg Ehret, Gudmundur I Eyjolfsson, Martin Farrall, Nita G Forouhi, Nele Friedrich, Wolfram Goessling, Daniel F Gudbjartsson, Tamara B Harris, Anna-Liisa Hartikainen, Simon Heath, Gideon M Hirschfield, Albert Hofman, Georg Homuth, Elina Hyppönen, Harry L A Janssen, Toby Johnson, Antti J Kangas, Ido P Kema, Jens P Kühn, Sandra Lai, Mark Lathrop, Markus M Lerch, Yun Li, T Jake Liang, Jing-Ping Lin, Ruth J F Loos, Nicholas G Martin, Miriam F Moffatt, Grant W Montgomery, Patricia B Munroe, Kiran Musunuru, Yusuke Nakamura, Christopher J O'Donnell, Isleifur Olafsson, Brenda W Penninx, Anneli Pouta, Bram P Prins, Inga Prokopenko, Ralf Puls, Aimo Ruokonen, Markku J Savolainen, David Schlessinger, Jeoffrey N L Schouten, Udo Seedorf, Srijita Sen-Chowdhry, Katherine A Siminovitch, Johannes H Smit, Timothy D Spector, Wenting Tan, Tanya M Teslovich, Taru Tukiainen, Andre G Uitterlinden, Melanie M Van der Klauw, Ramachandran S Vasan, Chris Wallace, Henri Wallaschofski, H-Erich Wichmann, Gonneke Willemsen, Peter Würtz, Chun Xu, Laura M Yerges-Armstrong, Alcohol Genome-wide Association (AlcGen) Consortium, Diabetes Genetics Replication and Meta-analyses (DIAGRAM+) Study, Genetic Investigation of ANthropometric Traits (GIANT) Consortium, Global Lipids Genetics Consortium, Genetics of Liver Disease (GOLD) Consortium, International Consortium for Blood Pressure (ICBP-GWAS), Meta-analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), Goncalo R Abecasis, Kourosh R Ahmadi, Dorret I Boomsma, Mark Caulfield, William O Cookson, Cornelia M Van Duijn, Philippe Froguel, Koichi Matsuda, Mark I McCarthy, Christa Meisinger, Vincent Mooser, Kirsi H Pietiläinen, Gunter Schumann, Harold Snieder, Michael J E Sternberg, Ronald P Stolk, Howard C Thomas, Unnur Thorsteinsdottir, Manuela Uda, Gérard Waeber, Nicholas J Wareham, Dawn M Waterworth, Hugh Watkins, John B Whitfield, Jacqueline C M Witteman, Bruce H R Wolffenbuttel, Caroline S Fox, Mika Ala-Korpela, Kari Stefansson, Peter Vollenweider, Henry Völzke, Eric E Schadt, James Scott, Marjo-Riitta Järvelin, Paul Elliott, Jaspal S Kooner Show less
Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with conc Show more
Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function. Show less
📄 PDF DOI: 10.1038/ng.970
FADS1