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1.
Flannick, J.* et al.: Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls. Nature 570, 71-76 (2019)
2.
Flannick, J.* et al.: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls. Sci. Data 5:180002 (2018)
3.
Flannick, J.* et al.: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls. Sci. Data 4:170179 (2017)
4.
Manning, A.* et al.: A low-frequency inactivating Akt2 variant enriched in the Finnish population is associated with fasting insulin levels and type 2 diabetes risk. Diabetes 66, 2019-2032 (2017)
5.
Scott, R.A.* et al.: An expanded genome-wide association study of type 2 diabetes in Europeans. Diabetes 66, 2888-2902 (2017)
6.
Fuchsberger, C.* et al.: The genetic architecture of type 2 diabetes. Nature 536, 41-47 (2016)
7.
McCarthy, S.* et al.: A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279-1283 (2016)
8.
Gaulton, K.J.* et al.: Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci. Nat. Genet. 47, 1415-1425 (2015)
9.
Mahajan, A.* et al.: Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus. PLoS Genet. 11:e1004876 (2015)
10.
Moutsianas, L.* et al.: The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease. PLoS Genet. 11:e1005165 (2015)
11.
Flannick, J.* et al.: Loss-of-function mutations in SLC30A8 protect against type 2 diabetes. Nat. Genet. 46, 357-363 (2014)
12.
Lange, L.A.* et al.: Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol. Am. J. Hum. Genet. 94, 233-245 (2014)
13.
Majithia, A.R.* et al.: Rare variants in PPARG with decreased activity in adipocyte differentiation are associated with increased risk of type 2 diabetes. Proc. Natl. Acad. Sci. U.S.A. 111, 13127-13132 (2014)
14.
Stitziel, N.O.* et al.: Inactivating mutations in NPC1L1 and protection from coronary heart disease. N. Engl. J. Med. 371, 2072-2082 (2014)
15.
Wang, S.R.* et al.: Simulation of finnish population history, guided by empirical genetic data, to assess power of rare-variant tests in Finland. Am. J. Hum. Genet. 94, 710-720 (2014)
16.
Agarwala, V.* ; Flannick, J.* ; Sunyaev, S.R.* ; GoT2D Consortium (Gieger, C. ; Grallert, H. ; Hrabě de Angelis, M. ; Huth, C. ; Kriebel, J. ; Meisinger, C. ; Meitinger, T. ; Müller-Nurasyid, M. ; Peters, A. ; Rathmann, W. ; Ried, J.S. ; Strauch, K. ; Strom, T.M.) & Altshuler, D.*: Evaluating empirical bounds on complex disease genetic architecture. Nat. Genet. 45, 1418-1427 (2013)
17.
Albrechtsen, A.* et al.: Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes. Diabetologia 56, 298-310 (2013)
18.
Deloukas, P.* et al.: Large-scale association analysis identifies new risk loci for coronary artery disease. Nat. Genet. 45, 25-35 (2013)
19.
Do, R.* et al.: Common variants associated with plasma triglycerides and risk for coronary artery disease. Nat. Genet. 45, 1345-1352 (2013)
20.
Morris, A.P.* et al.: Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat. Genet. 44, 981-990 (2012)