PuSH - Publication Server of Helmholtz Zentrum München

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1.
Bentley, A.R.* et al.: Multi-ancestry genome-wide gene–smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids. Nat. Genet. 51, 636-648 (2019)
2.
de Vries, P.S.* et al.: Multi-ancestry genome-wide association study of lipid levels incorporating gene-alcohol interactions. Am. J. Epidemiol., accepted (2019)
3.
Kilpeläinen, T.O.* et al.: Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nat. Commun. 10:376 (2019)
4.
Flannick, J.* et al.: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls. Sci. Data 5:180002 (2018)
5.
Mahajan, A.* et al.: Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nat. Genet. 50, 559-571 (2018)
6.
Sung, Y.J.* et al.: A large-scale multi-ancestry genome-wide study accounting for smoking behavior identifies multiple significant loci for blood pressure. Am. J. Hum. Genet. 102, 375-400 (2018)
7.
van Zuydam, N.R.* et al.: A genome-wide association study of diabetic kidney disease in subjects with type 2 diabetes. Diabetes 67, 1414-1427 (2018)
8.
Zhou, B.* et al.: Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants. Int. J. Epidemiol. 47, 872–883i (2018)
9.
Ezzati, M.* et al.: Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: A pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults. Lancet 390, 2627-2642 (2017)
10.
Flannick, J.* et al.: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls. Sci. Data 4:170179 (2017)
11.
Lu, X.* et al.: Exome chip meta-analysis identifies novel loci and East Asian-specific coding variants that contribute to lipid levels and coronary artery disease. Nat. Genet. 49, 1722–1730 (2017)
12.
Manning, A.* et al.: A low-frequency inactivating Akt2 variant enriched in the Finnish population is associated with fasting insulin levels and type 2 diabetes risk. Diabetes 66, 2019-2032 (2017)
13.
Rannikme, K.* et al.: COL4A2 is associated with lacunar ischemic stroke and deep ICH: Meta-analyses among 21,500 cases and 40,600 controls. Neurology 89, 1829-1839 (2017)
14.
Wheeler, E.* et al.: Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis. PLoS Med. 14:e1002383 (2017)
15.
Zhang, W.* et al.: PRMT5 restricts hepatitis B virus replication via epigenetic repression of cccDNA transcription and interference with pgRNA encapsidation. Hepatology 66, 398-415 (2017)
16.
NCD Risk Factors Collaboration et al.: Trends in adult body-mass index in 200 countries from 1975 to 2014: A pooled analysis of 1698 population-based measurement studies with 19.2 million participants. Lancet 387, 1377-1396 (2016)
17.
de Vries, P.S.* et al.: A meta-analysis of 120,246 individuals identifies 18 new loci for fibrinogen concentration. Hum. Mol. Genet. 25, 358-370 (2016)
18.
Fuchsberger, C.* et al.: The genetic architecture of type 2 diabetes. Nature 536, 41-47 (2016)
19.
Malik, R.* et al.: Low-frequency and common genetic variation in ischemic stroke: The METASTROKE collaboration. Neurology 86, 1217-1226 (2016)
20.
Tang, Q.* et al.: Lipase-driven epoxidation is a two-stage synergistic process. ChemistrySelect 1, 836-839 (2016)