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1.
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)
2.
Knüppel, S.* et al.: Design and characterization of dietary assessment in the German National Cohort. Eur. J. Clin. Nutr., accepted (2019)
3.
Wittenbecher, C.* et al.: Insulin-like growth factor binding protein 2 (IGFBP-2) and the risk of developing type 2 diabetes. Diabetes 68, 188-197 (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.
Floegel, A.* et al.: Serum metabolites and risk of myocardial infarction and ischemic stroke: A targeted metabolomic approach in two German prospective cohorts. Eur. J. Epidemiol. 33, 55–66 (2018)
6.
Herrmann, W.J.* et al.: Assessing incident cardiovascular and metabolic diseases in epidemiological cohort studies in Germany. Bundesgesundheitsbl.-Gesund. 61, 420-431 (2018)
7.
Iqbal, K.* et al.: Comparison of metabolite networks from four German population-based studies. Int. J. Epidemiol. 47, 2070-2081 (2018)
8.
Kroeger, J.* et al.: Circulating fetuin - A and risk of type 2 diabetes : A mendelian randomization analysis. Diabetes 67, 1200-1205 (2018)
9.
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)
10.
Pinart, M.* et al.: Joint data analysis in nutritional epidemiology: Identification of observational studies and minimal requirements. J. Nutr. 148, 285-297 (2018)
11.
Turcot, V.* et al.: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat. Genet. 50, 26-41 (2018)
12.
Turcot, V.* et al.: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 765, 2017). Nat. Genet. 50, 764-768 (2018)
13.
Wood, A.M.* et al.: Risk thresholds for alcohol consumption: Combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies. Lancet 391, 1513-1523 (2018)
14.
Bachlechner, U.* et al.: Predicting risk of substantial weight gain in German adults-a multi-center cohort approach. Eur. J. Public Health 27, 768-774 (2017)
15.
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)
16.
Flannick, J.* et al.: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls. Sci. Data 4:170179 (2017)
17.
Jäger, S.* et al.: Genetic variants including markers from the exome chip and metabolite traits of type 2 diabetes. Sci. Rep. 7:6037 (2017)
18.
Kleiser, C. et al.: Are sleep duration, midpoint of sleep and sleep quality associated with dietary intake among Bavarian adults? Eur. J. Clin. Nutr. 71, 631-637 (2017)
19.
Marouli, E.* et al.: Rare and low-frequency coding variants alter human adult height. Nature 542, 186-190 (2017)
20.
Molnos, S. et al.: Metabolite ratios as potential biomarkers for type 2 diabetes: A DIRECT study. Diabetologia 61, 117-129 (2017)