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Berndt, S. I., Gustafsson, S., Magi, R., Ganna, A., Wheeler, E., Feitosa, M. F., et al. (2013). Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nat Genet, 45(5), 501–512.
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Chen, C. H., Peng, Q., Schork, A. J., Lo, M. T., Fan, C. C., Wang, Y., et al. (2015). Large-scale genomics unveil polygenic architecture of human cortical surface area. Nature communications, 6, 7549.
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Cuypers, K., De Ridder, K., Kvaloy, K., Knudtsen, M. S., Krokstad, S., Holmen, J., et al. (2012). Leisure time activities in adolescence in the presence of susceptibility genes for obesity: risk or resilience against overweight in adulthood? The HUNT study. BMC Public Health, 12, 820.
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Graff, M., Scott, R. A., Justice, A. E., Young, K. L., Feitosa, M. F., Barata, L., et al. (2017). Genome-wide physical activity interactions in adiposity – A meta-analysis of 200,452 adults (Vol. 13).
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Holmen, O. L., Zhang, H., Fan, Y., Hovelson, D. H., Schmidt, E. M., Zhou, W., et al. (2014). Systematic evaluation of coding variation identifies a candidate causal variant in TM6SF2 influencing total cholesterol and myocardial infarction risk. Nat Genet, 46(4), 345–351.
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Hung, R. J., McKay, J. D., Gaborieau, V., Boffetta, P., Hashibe, M., Zaridze, D., et al. (2008). A susceptibility locus for lung cancer maps to nicotinic acetylcholine receptor subunit genes on 15q25. Nature, 452(7187), 633–637.
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Johnson, M. P., Brennecke, S. P., East, C. E., Dyer, T. D., Roten, L. T., Proffitt, J. M., et al. (2013). Genetic dissection of the pre-eclampsia susceptibility locus on chromosome 2q22 reveals shared novel risk factors for cardiovascular disease. Mol Hum Reprod, 19(7), 423–437.
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Kvehaugen, A. S., Melien, O., Holmen, O. L., Laivuori, H., Dechend, R., & Staff, A. C. (2014). Hypertension after preeclampsia and relation to the C1114G polymorphism (rs4606) in RGS2: data from the Norwegian HUNT2 study. BMC Med Genet, 15, 28.
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Lange, L. A., Hu, Y., Zhang, H., Xue, C., Schmidt, E. M., Tang, Z. - Z., et al. (2014). Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol. Am J Hum Genet, 94(2), 233–245.
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Liu, D. J., Peloso, G. M., Yu, H., Butterworth, A. S., Wang, X., Mahajan, A., et al. (2017). Exome-wide association study of plasma lipids in >300,000 individuals. Nat Genet, 49(12), 1758–1766.
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Liu, D. J., Peloso, G. M., Zhan, X., Holmen, O. L., Zawistowski, M., Feng, S., et al. (2014). Meta-analysis of gene-level tests for rare variant association. Nat Genet, 46(2), 200–204.
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Lu, X., Peloso, G. M., Liu, D. J., Wu, Y., Zhang, H., Zhou, W., et al. (2017). Exome chip meta-analysis identifies novel loci and East Asian-specific coding variants that contribute to lipid levels and coronary artery disease (Vol. 49).
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Marquez, M., Huyvaert, M., Perry, J. R. B., Pearson, R. D., Falchi, M., Morris, A. P., et al. (2012). Low-frequency variants in HMGA1 are not associated with type 2 diabetes risk. Diabetes, 61(2), 524–530.
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Palmer, N. D., McDonough, C. W., Hicks, P. J., Roh, B. H., Wing, M. R., An, S. S., et al. (2012). A genome-wide association search for type 2 diabetes genes in African Americans. PLoS One, 7(1), e29202.
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Tang, C. S., Zhang, H., Cheung, C. Y., Xu, M., Ho, J. C., Zhou, W., et al. (2015). Exome-wide association analysis reveals novel coding sequence variants associated with lipid traits in Chinese. Nature communications, 6, 10206.
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Thomsen, L. C. V., McCarthy, N. S., Melton, P. E., Cadby, G., Austgulen, R., Nygard, O. K., et al. (2017). The antihypertensive MTHFR gene polymorphism rs17367504-G is a possible novel protective locus for preeclampsia. J Hypertens, 35(1), 132–139.
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von Krogh, A. S., Kremer Hovinga, J. A., Romundstad, P. R., Roten, L. T., Lammle, B., Waage, A., et al. (2015). ADAMTS13 gene variants and function in women with preeclampsia: a population- based nested case- control study from the HUNT Study. Thrombosis research, 136(2), 282–288.
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Zhou, W., Fritsche, L. G., Das, S., Zhang, H., Nielsen, J. B., Holmen, O. L., et al. (2017). Improving power of association tests using multiple sets of imputed genotypes from distributed reference panels. Genet Epidemiol, 41(8), 744–755.
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