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Karlsson Linnér, R.* et al.: Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences. Nat. Genet. 51, 245-257 (2019)
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)
Aslibekyan, S.* et al.: Association of methylation signals with incident coronary heart disease in an epigenome-wide assessment of circulating tumor necrosis factor. JAMA Cardiol. 3, 463-472 (2018)
Kenttä, T.V.* et al.: Repolarization heterogeneity measured with T-wave area dispersion in standard 12-lead ECG predicts sudden cardiac death in general population. Circ.-Arrhythmia Electrophysiol. 11:e005762 (2018)
Müller-Nurasyid, M. et al.: Pharmacogenetic effects in population-based metabolic profiles. Genet. Epidemiol. 42, 719-720 (2018)
Qi, T.* et al.: Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood. Nat. Commun. 9:2282 (2018)
Roselli, C.* et al.: Multi-ethnic genome-wide association study for atrial fibrillation. Nat. Genet. 50, 1225–1233 (2018)
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)
Wahl, S. et al.: Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature 541, 81-86 (2017)
Zeller, T.* et al.: Transcriptome-wide analysis identifies novel associations with blood pressure. Hypertension 70, 713-750 (2017)
Huan, T.* et al.: A whole-blood transcriptome meta-analysis identifies gene expression signatures of cigarette smoking. Hum. Mol. Genet. 25, 4611-4623 (2016)
Kriebel, J. et al.: Association between DNA methylation in whole blood and measures of glucose metabolism: Kora F4 study. PLoS ONE 11:e0152314 (2016)
Ligthart, S.* et al.: DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases. Genome Biol. 17:255 (2016)
Teumer, A.* et al.: Analyzing illumina gene expression microarray data obtained from human whole blood cell and blood monocyte samples. Methods Mol. Biol. 1368, 85-97 (2016)
Bartel, J. et al.: The human blood metabolome-transcriptome interface. PLoS Genet. 11:e1005274 (2015)
Homuth, G.* et al.: Extensive alterations of the whole-blood transcriptome are associated with body mass index: Results of an mRNA profiling study involving two large population-based cohorts. BMC Med. Genomics 8:65 (2015)
Huan, T.* et al.: A meta-analysis of gene expression signatures of blood pressure and hypertension. PLoS Genet. 11:e1005035 (2015)
Peters, M.J.* et al.: The transcriptional landscape of age in human peripheral blood. Nat. Commun. 6:8570 (2015)
Pfeiffer, L. et al.: DNA methylation of lipid-related genes affects blood lipid levels. Circ. Cardiovasc. Genet. 8, 334-342 (2015)
Singmann, P. et al.: Characterization of whole-genome autosomal differences of DNA methylation between men and women. Epigenetics Chromatin 8:43 (2015)