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Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways
Open accessAbstract
Jose Florez, Claudia Langenberg, Erik Ingelsson, Inga Prokopenko, Inês Barroso and colleagues perform large-scale association analyses using the Metabochip to gain further insights into the genetic architecture of glucose regulation. They identify 38 new loci influencing 1 or more glycemic traits and show that many of these loci also modify risk of type 2 diabetes. Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.
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Cites
Quantifying heterogeneity in a meta‐analysis
Higgins, J. P. T., & Thompson, S. G. (2002) · Statistics in Medicine · doi:10.1002/sim.1186 · Cited by 36,763
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
Genetics of Food Intake Self-Regulation in Childhood: Literature Review and Research Opportunities
Faith, M. S., Carnell, S., & Kral, T. V. E. (2013) · Human Heredity · doi:10.1159/000353879 · Cited by 7,601
Lippa, N. C., & Sanderson, S. C. (2013) · Human Heredity · doi:10.1159/000353712 · Cited by 6,078
METAL: fast and efficient meta-analysis of genomewide association scans
Willer, C. J., Li, Y., & Abecasis, G. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq340 · Cited by 5,205
Frayling, T. M., Timpson, N. J., Weedon, M. N., Zeggini, E., Freathy, R. M., Lindgren, C. M., Perry, J. R. B., Elliott, K. S., Lango, H., Rayner, N. W., et al. (2007) · Science · doi:10.1126/science.1141634 · Cited by 4,531
Self-citationCommon SNPs explain a large proportion of the heritability for human height
Yang, J., Benyamin, B., McEvoy, B. P., Gordon, S., Henders, A. K., Nyholt, D. R., Madden, P. A., Heath, A. C., Martin, N. G., Montgomery, G. W., et al. (2010) · Nature Genetics · doi:10.1038/ng.608 · Cited by 4,446
Howie, B. N., Donnelly, P., & Marchini, J. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000529 · Cited by 3,928
Mutation of the mouse klotho gene leads to a syndrome resembling ageing
Kuro-o, M., Matsumura, Y., Aizawa, H., Kawaguchi, H., Suga, T., Utsugi, T., Ohyama, Y., Kurabayashi, M., Kaname, T., Kume, E., et al. (1997) · Nature · doi:10.1038/36285 · Cited by 3,837
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487
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Cited by
Verbanck, M., Chen, C.-Y., Neale, B., & Do, R. (2018) · Nature Genetics · doi:10.1038/s41588-018-0099-7 · Cited by 8,591
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534
Self-citationA comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease
the CARDIoGRAMplusC4D Consortium (2015) · Nature Genetics · doi:10.1038/ng.3396 · Cited by 2,447
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segrè, A. V., Steinthorsdottir, V., Strawbridge, R. J., Khan, H., Grallert, H., et al. (2012) · Nature Genetics · doi:10.1038/ng.2383 · Cited by 1,912
Self-citationEPIC- InterAct Consortium, Burgess, S., Scott, R. A., Timpson, N. J., Davey Smith, G., & Thompson, S. G. (2015) · European Journal of Epidemiology · doi:10.1007/s10654-015-0011-z · Cited by 1,803
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Metadata
- Authors
- Scott, R. A., Lagou, V., Welch, R. P., Wheeler, E., Montasser, M. E., Luan, J., Mägi, R., Strawbridge, R. J., Rehnberg, E., Gustafsson, S., Kanoni, S., Rasmussen-Torvik, L. J., Yengo, L., Lecoeur, C., Shungin, D., Sanna, S., Sidore, C., Johnson, P. C. D., Jukema, J. W., Johnson, T., Mahajan, A., Verweij, N., Thorleifsson, G., Hottenga, J.-J., Shah, S., Smith, A. V., Sennblad, B., Gieger, C., Salo, P., Perola, M., Timpson, N. J., Evans, D. M., Pourcain, B. S., Wu, Y., Andrews, J. S., Hui, J., Bielak, L. F., Zhao, W., Horikoshi, M., Navarro, P., Isaacs, A., O'Connell, J. R., Stirrups, K., Vitart, V., Hayward, C., Esko, T., Mihailov, E., Fraser, R. M., Fall, T., Voight, B. F., Raychaudhuri, S., Chen, H., Lindgren, C. M., Morris, A. P., Rayner, N. W., Robertson, N., Rybin, D., Liu, C.-T., Beckmann, J. S., Willems, S. M., Chines, P. S., Jackson, A. U., Kang, H. M., Stringham, H. M., Song, K., Tanaka, T., Peden, J. F., Goel, A., Hicks, A. A., An, P., Müller-Nurasyid, M., Franco-Cereceda, A., Folkersen, L., Marullo, L., Jansen, H., Oldehinkel, A. J., Bruinenberg, M., Pankow, J. S., North, K. E., Forouhi, N. G., Loos, R. J. F., Edkins, S., Varga, T. V., Hallmans, G., Oksa, H., Antonella, M., Nagaraja, R., Trompet, S., Ford, I., Bakker, S. J. L., Kong, A., Kumari, M., Gigante, B., Herder, C., Munroe, P. B., Caulfield, M., Antti, J., Mangino, M., Small, K., Miljkovic, I., Liu, Y., Atalay, M., Kiess, W., James, A. L., Rivadeneira, F., Uitterlinden, A. G., Palmer, C. N. A., Doney, A. S. F., Willemsen, G., Smit, J. H., Campbell, S., Polasek, O., Bonnycastle, L. L., Hercberg, S., Dimitriou, M., Bolton, J. L., Fowkes, G. R., Kovacs, P., Lindström, J., Zemunik, T., Bandinelli, S., Wild, S. H., Basart, H. V., Rathmann, W., Grallert, H., DIAbetes Genetics Replication and Meta-analysis (DIAGRAM) Consortium, Maerz, W., Kleber, M. E., Boehm, B. O., Peters, A., Pramstaller, P. P., Province, M. A., Borecki, I. B., Hastie, N. D., Rudan, I., Campbell, H., Watkins, H., Farrall, M., Stumvoll, M., Ferrucci, L., Waterworth, D. M., Bergman, R. N., Collins, F. S., Tuomilehto, J., Watanabe, R. M., de Geus, E. J. C., Penninx, B. W., Hofman, A., Oostra, B. A., Psaty, B. M., Vollenweider, P., Wilson, J. F., Wright, A. F., Hovingh, G. K., Metspalu, A., Uusitupa, M., Magnusson, P. K. E., Kyvik, K. O., Kaprio, J., Price, J. F., Dedoussis, G. V., Deloukas, P., Meneton, P., Lind, L., Boehnke, M., Shuldiner, A. R., van Duijn, C. M., Morris, A. D., Toenjes, A., Peyser, P. A., Beilby, J. P., Körner, A., Kuusisto, J., Laakso, M., Bornstein, S. R., Schwarz, P. E. H., Lakka, T. A., Rauramaa, R., Adair, L. S., Smith, G. D., Spector, T. D., Illig, T., de Faire, U., Hamsten, A., Gudnason, V., Kivimaki, M., Hingorani, A., Keinanen-Kiukaanniemi, S. M., Saaristo, T. E., Boomsma, D. I., Stefansson, K., van der Harst, P., Dupuis, J., Pedersen, N. L., Sattar, N., Harris, T. B., Cucca, F., Ripatti, S., Salomaa, V., Mohlke, K. L., Balkau, B., Froguel, P., Pouta, A., Jarvelin, M.-R., Wareham, N. J., Bouatia-Naji, N., McCarthy, M. I., Franks, P. W., Meigs, J. B., Teslovich, T. M., Florez, J. C., Langenberg, C., Ingelsson, E., Prokopenko, I., & Barroso, I.
- Venue
- Nature Genetics
- Published
- 2012-08-12
- Volume
- 44
- Issue
- 9
- Pages
- 991-1005
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- OpenAlex
- W2126237420
- Cited by
- 828
- References
- 99
- FWCI
- 36.85
- Type
- journal article
- Language
- en
- Open access
- hybrid
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