PuSH - Publication Server of Helmholtz Zentrum München

140 Records found.
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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.: Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions. Am. J. Epidemiol. 188, 1033-1054 (2019)
3.
Erzurumluoglu, A.M.* et al.: Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci. Mol. Psychiatry, accepted (2019)
4.
Kilpeläinen, T.O.* et al.: Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nat. Commun. 10:376 (2019)
5.
Sung, Y.J.* et al.: A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure. Hum. Mol. Genet., accepted (2019)
6.
Timmers, P.R.* et al.: Genomics of 1 million parent lifespans implicates novel pathways and common diseases and distinguishes survival chances. eLife 8:e39856 (2019)
7.
Wuttke, M.* et al.: A catalog of genetic loci associated with kidney function from analyses of a million individuals. Nat. Genet. 51, 957-972 (2019)
8.
Barrios, C.* et al.: Circulating metabolic biomarkers of renal function in diabetic and non-diabetic populations. Sci. Rep. 8:15249 (2018)
9.
Evangelou, E.* et al.: Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat. Genet. 50, 1412-1425 (2018)
10.
Evangelou, E.* et al.: Erratum to: Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits (Nature Genetics, (2018), 50, 10, (1412-1425), 10.1038/s41588-018-0205-x). Nat. Genet., accepted (2018)
11.
Flannick, J.* et al.: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls. Sci. Data 5:180002 (2018)
12.
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)
13.
Mahajan, A.* et al.: Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nat. Genet. 50, 1505-1513 (2018)
14.
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)
15.
Tedja, M.S.* et al.: Genome-wide association meta-analysis highlights light-induced signaling as a driver for refractive error. Nat. Genet. 50, 834-848 (2018)
16.
Xue, A.* et al.: Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nat. Commun. 9:2941 (2018)
17.
Allebrandt, K.V.* et al.: Identifying pathways modulating sleep duration: From genomics to transcriptomics. Sci. Rep. 7:4555 (2017)
18.
Day, F.R.* et al.: Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk. Nat. Genet. 49, 834-841 (2017)
19.
Direk, N.* et al.: An analysis of two genome-wide association meta-analyses identifies a new locus for broad depression phenotype. Biol. Psychiatry 82, 322-329 (2017)
20.
Doucet, M.* et al.: Quality Matters: 2016 Annual Conference of the National Infrastructures for Biobanking. Biopreserv. Biobank. 15, 270-276 (2017)