PuSH - Publication Server of Helmholtz Zentrum München

21 Records found.
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1.
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)
2.
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)
3.
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)
4.
Spracklen, C.N.* et al.: Exome-Derived Adiponectin-Associated Variants Implicate Obesity and Lipid Biology. Am. J. Hum. Genet. 105, 15-28 (2019)
5.
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)
6.
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)
7.
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)
8.
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)
9.
Macé, A.* et al.: CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits. Nat. Commun. 8:744 (2017)
10.
Horikoshi, M.* et al.: Genome-wide associations for birth weight and correlations with adult disease. Nature 538, 248-252 (2016)
11.
Kanoni, S.* et al.: Analysis with the exome array identifies multiple new independent variants in lipid loci. Hum. Mol. Genet. 25, 4094-4106 (2016)
12.
Lessard, S.* et al.: Testing the role of predicted gene knockouts in human anthropometric trait variation. Hum. Mol. Genet. 25, 2082-2092 (2016)
13.
Scott, R.A.* et al.: A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease. Sci. Transl. Med. 8:341ra76 (2016)
14.
Surendran, P.* et al.: Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension. Nat. Genet. 48, 1151-1161 (2016)
15.
Wood, A.R.* et al.: Variants in the FTO and CDKAL1 loci have recessive effects on risk of obesity and type 2 diabetes, respectively. Diabetologia 59, 1214-1221 (2016)
16.
Westra, H.J.* et al.: Cell specific eQTL analysis without sorting cells. PLoS Genet. 11:e1005223 (2015)
17.
Horikoshi, M.* et al.: New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism. Nat. Genet. 45, 76-82 (2013)
18.
Westra, H.J.* et al.: Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 45, 1238-1243 (2013)
19.
Boraska, V.* et al.: Genome-wide association study to identify common variants associated with brachial circumference: A meta-analysis of 14 cohorts. PLoS ONE 7:e31369 (2012)
20.
Manning, A.K.* et al.: A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat. Genet. 44, 659-669 (2012)