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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)
de Vries, P.S.* et al.: Multi-ancestry genome-wide association study of lipid levels incorporating gene-alcohol interactions. Am. J. Epidemiol., accepted (2019)
Ji, Y.* et al.: Genome-wide and abdominal MRI data provide evidence that a genetically determined favorable adiposity phenotype is characterized by lower ectopic liver fat and lower risk of type 2 diabetes, heart disease, and hypertension. Diabetes 68, 207-219 (2019)
Justice, A.E.* et al.: Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution. Nat. Genet. 51, 452–469 (2019)
Kilpeläinen, T.O.* et al.: Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nat. Commun. 10:376 (2019)
Skaaby, T.* et al.: Association of alcohol consumption with allergic disease and asthma: A multi-centre Mendelian randomization analysis. Addiction 114, 216-225 (2019)
Warrington, N.M.* et al.: Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat. Genet. 51, 804-814 (2019)
Bihlmeyer, N.A.* et al.: ExomeChip-wide analysis of 95 626 individuals identifies 10 novel loci associated with QT and JT intervals. Circ. Genom. Precis. Med. 11:e001758 (2018)
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)
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)
Li-Gao, R.* et al.: Postprandial metabolite profiles associated with type 2 diabetes clearly stratify individuals with impaired fasting glucose. Metabolomics 14:13 (2018)
Lin, H.* et al.: Common and rare coding genetic variation underlying the electrocardiographic PR interval. Circ. Genom. Precis. Med. 11:e002037 (2018)
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)
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)
Zaghlool, S.B.* et al.: Deep molecular phenotypes link complex disorders and physiological insult to CpG methylation. Hum. Mol. Genet. 27, 1106-1121 (2018)
Boon, M.R.* et al.: LysoPC-acyl C16:0 is associated with brown adipose tissue activity in men. Metabolomics 13:48 (2017)
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)
Do, K.T. et al.: Phenotype-driven identification of modules in a hierarchical map of multifluid metabolic correlations. NPJ Syst. Biol. Appl. 3:28 (2017)
Li, M.* et al.: SOS2 and ACP1 loci identified through large-scale exome chip analysis regulate kidney development and function. J. Am. Soc. Nephrol. 28, 981-994 (2017)
Skaaby, T.* et al.: Investigating the causal effect of smoking on hay fever and asthma: A Mendelian randomization meta-analysis in the CARTA consortium. Sci. Rep. 7:2224 (2017)