The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Genome-wide association analysis of metabolic traits in a birth cohort from a founder population
Open accessAbstract
Genome-wide association studies (GWAS) of longitudinal birth cohorts enable joint investigation of environmental and genetic influences on complex traits. We report GWAS results for nine quantitative metabolic traits (triglycerides, high-density lipoprotein, low-density lipoprotein, glucose, insulin, C-reactive protein, body mass index, and systolic and diastolic blood pressure) in the Northern Finland Birth Cohort 1966 (NFBC1966), drawn from the most genetically isolated Finnish regions. We replicate most previously reported associations for these traits and identify nine new associations, several of which highlight genes with metabolic functions: high-density lipoprotein with NR1H3 (LXRA), low-density lipoprotein with AR and FADS1-FADS2, glucose with MTNR1B, and insulin with PANK1. Two of these new associations emerged after adjustment of results for body mass index. Gene–environment interaction analyses suggested additional associations, which will require validation in larger samples. The currently identified loci, together with quantified environmental exposures, explain little of the trait variation in NFBC1966. The association observed between low-density lipoprotein and an infrequent variant in AR suggests the potential of such a cohort for identifying associations with both common, low-impact and rarer, high-impact quantitative trait loci.
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
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
Self-citationGenome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
Self-citationThe metabolic syndrome—a new worldwide definition
Alberti, K. G. M., Zimmet, P., & Shaw, J. (2005) · The Lancet · doi:10.1016/s0140-6736(05)67402-8 · Cited by 9,352
Trajectories of growth among children who have coronary events as adults
Barker, D. J. P., Osmond, C., Forsén, T. J., Kajantie, E., & Eriksson, J. G. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa044160 · Cited by 1,517
Replicating genotype–phenotype associations
NCI-NHGRI Working Group on Replication in Association Studies, Chanock, S. J., Manolio, T., Boehnke, M., Boerwinkle, E., Hunter, D. J., Thomas, G., Hirschhorn, J. N., Abecasis, G., Altshuler, D., et al. (2007) · Nature · doi:10.1038/447655a · Cited by 1,352
Self-citationCommon variants near MC4R are associated with fat mass, weight and risk of obesity
The Prostate, L., Loos, R. J. F., KORA, Study, N. H., Initiative, D. G., Study, T. S., The Wellcome Trust Case Control Consortium, FUSION, Lindgren, C. M., Li, S., et al. (2008) · Nature Genetics · doi:10.1038/ng.140 · Cited by 1,325
Self-citationMultiple Rare Alleles Contribute to Low Plasma Levels of HDL Cholesterol
Cohen, J. C., Kiss, R. S., Pertsemlidis, A., Marcel, Y. L., McPherson, R., & Hobbs, H. H. (2004) · Science · doi:10.1126/science.1099870 · Cited by 1,108
Liver X receptors as integrators of metabolic and inflammatory signaling
Zelcer, N. (2006) · Journal of Clinical Investigation · doi:10.1172/jci27883 · Cited by 978
Relationship of Metabolic Risk Factors and Development of Cardiovascular Disease and Diabetes
Haffner, S. M. (2006) · Obesity · doi:10.1038/oby.2006.291 · Cited by 200
Morin-Papunen, L., Martikainen, H., McCarthy, M. I., Franks, S., Sovio, U., Hartikainen, A.-L., Ruokonen, A., Leinonen, M., Laitinen, J., Järvelin, M.-R., et al. (2008) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2008.04.013 · Cited by 78
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Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336
Self-citationBiological, 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
Self-citationVariance component model to account for sample structure in genome-wide association studies
Kang, H. M., Sul, J. H., Service, S. K., Zaitlen, N. A., Kong, S.-Y., Freimer, N. B., Sabatti, C., & Eskin, E. (2010) · Nature Genetics · doi:10.1038/ng.548 · Cited by 2,817
New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk
DIAGRAM Consortium, Dupuis, J., GIANT Consortium, Global BPgen Consortium, Anders Hamsten on behalf of Procardis Consortium, the MAGIC investigators, Langenberg, C., Prokopenko, I., Saxena, R., Soranzo, N., et al. (2010) · Nature Genetics · doi:10.1038/ng.520 · Cited by 2,166
Self-citationSystematic identification of trans eQTLs as putative drivers of known disease associations
Westra, H.-J., Peters, M. J., Esko, T., Yaghootkar, H., Schurmann, C., Kettunen, J., Christiansen, M. W., Fairfax, B. P., Schramm, K., Powell, J. E., et al. (2013) · Nature Genetics · doi:10.1038/ng.2756 · Cited by 1,658
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Metadata
- Authors
- Sabatti, C., Service, S. K., Hartikainen, A.-L., Pouta, A., Ripatti, S., Brodsky, J., Jones, C. G., Zaitlen, N. A., Varilo, T., Kaakinen, M., Sovio, U., Ruokonen, A., Laitinen, J., Jakkula, E., Coin, L., Hoggart, C., Collins, A., Turunen, H., Gabriel, S., Elliot, P., McCarthy, M. I., Daly, M. J., Järvelin, M.-R., Freimer, N. B., & Peltonen, L.
- Venue
- Nature Genetics
- Published
- 2008-12-07
- Volume
- 41
- Issue
- 1
- Pages
- 35-46
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- OpenAlex
- W2071759640
- Cited by
- 736
- References
- 11
- FWCI
- 42.19
- Type
- journal article
- Language
- en
- Open access
- green
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