This page lists datasets whose summary statistic files are hosted at the T2DKP.
| Dataset name in T2DKP | Publication (ordered by publication date, most recent first) | Phenotypes | Downloads |
|---|---|---|---|
| Chronic kidney disease progression 2023 GWAS: trans-ancestry, African American, and European ancestries | Genome-Wide Association Study of CKD Progression. Robinson-Cohen C, et al. J Am Soc Nephrol. 2023 Jun 1. doi: 10.1681/ASN.0000000000000170. PMID: 37261792 |
Renal |
Summary statistics: trans-ancestry, eGFR decline with diabetes Summary statistics: trans-ancestry, eGFR decline without diabetes Summary statistics: African American ancestry, eGFR decline with diabetes Summary statistics: African American ancestry, eGFR decline without diabetes Summary statistics: European ancestry, eGFR decline with diabetes Summary statistics: European ancestry, eGFR decline without diabetes |
| SUGAR-MGH 2023 sulfonylurea and metformin response GWAS: trans-ancestry | Genome-wide association analysis identifies ancestry-specific genetic variation associated with acute response to metformin and glipizide in SUGAR-MGH. Li JH, Brenner LN, Kaur V, et al. Diabetologia. 2023 May 26. doi: 10.1007/s00125-023-05922-7. PMID: 37233759 |
Pharmacogenomic | |
| Dietary intake 2022 GWAS: European ancestry | Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits. Merino J, Dashti HS, Sarnowski C, et al. Nat Hum Behav. 2022 Jan;6(1):155-163. doi: 10.1038/s41562-021-01182-w. PMID: 34426670 |
Nutritional | |
| Fasting proinsulin 2023 GWAS: European ancestry | Loci for insulin processing and secretion provide insight into type 2 diabetes risk. Broadaway KA, et al. Am J Hum Genet. 2023 Jan 18;S0002-9297(23)00002-2. doi: 10.1016/j.ajhg.2023.01.002. PMID: 36693378 |
Glycemic | |
| Triglyceride levels in T2D 2022 GWAS: European ancestry; Triglyceride levels in non-T2D 2022 GWAS: European ancestry | Genome-wide discovery for diabetes-dependent triglycerides-associated loci. Selvaraj MS, et al. PMID: 36269708 |
Diabetic complications | |
| Type 2 diabetes TOPMed imputed 2023 GWAS: Hispanic ancestry | The power of TOPMed imputation for the discovery of Latino enriched rare variants associated with type 2 diabetes. Huerta-Chagoya A, et al. Diabetologia. 2023 May 6. doi: 10.1007/s00125-023-05912-9. PMID: 37148359 |
Glycemic | |
| DIAMANTE T2D 2022 GWAS | Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. Mahajan A, Spracklen CN, Zhang W, Ng MCY, Petty LE, Kitajima H, Yu GZ, Rüeger S, Speidel L, et al. Nat Genet. 2022 May 12. doi: 10.1038/s41588-022-01058-3.. PMID: 35551307 |
Glycemic |
Download GWAS summary statistics (trans-ancestry; East Asian, European, and South Asian ancestries) |
| GENIE 2022 DKD GWAS | Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease. Sandholm N, Cole JB, et al., Diabetologia. 2022 Jun 28. doi: 10.1007/s00125-022-05735-0. PMID: 35763030 |
Diabetic complications |
CKD |
| MRI-based organ age 2022 GWAS: European ancestry | Using deep learning to predict abdominal age from liver and pancreas magnetic resonance images. Le Goallec A, et al. Nat Commun. 2022 Apr 13;13(1):1979. doi: 10.1038/s41467-022-29525-9. PMID:35418184 |
Predicted abdominal age | |
| Additive model 2022 T2D GWAS: European ancestry | Recessive Genome-Wide Meta-analysis Illuminates Genetic Architecture of Type 2 Diabetes. O'Connor MJ, et al. Diabetes. 2022 Mar 1;71(3):554-565. doi: 10.2337/db21-0545.. PMID:34862199 |
Glycemic | |
| ProDiGY 2021 GWAS | The First Genome-Wide Association Study for Type 2 Diabetes in Youth: The Progress in Diabetes Genetics in Youth (ProDiGY) Consortium. Srinivasan S, et al. Diabetes. 2021 Apr;70(4):996-1005. doi: 10.2337/db20-0443. PMID:33479058 |
Glycemic | |
| (Dataset not integrated into CMDKP) | Genome-wide gene-diet interaction analysis in the UK Biobank identifies novel effects on Hemoglobin A1c. Westerman K, et al. Hum Mol Genet. 2021 Aug 28;30(18):1773-1783. doi: 10.1093/hmg/ddab109. PMID:33864366 |
Glycemic | |
| GERA age-related GWAS | The impact of non-additive genetic associations on age-related complex diseases. Guindo-Martínez M, et al. Nat Commun. 2021 Apr 23;12(1):2436. doi: 10.1038/s41467-021-21952-4. PMID:33893285 |
Multiple age-related diseases | |
| Smoking-Genotype Interaction for T2D and FG | Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose. Wu P, et al. PLoS One 2020 May 7;15(5):e0230815. doi: 10.1371/journal.pone.0230815. PMID:32379818 |
Glycemic | |
| PR interval 1000G GWAS | Multi-ancestry GWAS of the electrocardiographic PR interval identifies 210 loci underlying cardiac conduction. Ntalla I, Weng L-C, et al.. Nature Communications (2020) 11:2542 doi:10.1038/s41467-020-15706-x |
ECG Traits | |
| UK Biobank Cardiac MRI LV GWAS | Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy. Pirruccello J, et al. Nat Commun. 2020 May 7;11(1):2254. doi: 10.1038/s41467-020-15823-7. PMID:32382064 |
Cardiovascular | Summary statistics for: Left ventricular end-diastolic volume | Left ventricular end-diastolic volume (BSA-indexed) | Left ventricular ejection fraction | Left ventricular end-systolic volume | Left ventricular end-systolic volume (BSA-indexed) | Stroke volume | Stroke volume (BSA-indexed) | README |
| AGEN and DIAMANTE T2D GWAS | Identification of type 2 diabetes loci in 433,540 East Asian individuals. Spracklen C, Horikoshi M, Kim YJ, Lin K, et al. Nature 2020. https://doi.org/10.1038/s41586-020-2263-3 |
Type 2 diabetes | |
| UK Biobank dietary habit GWAS | Comprehensive genomic analysis of dietary habits in UK Biobank identifies hundreds of genetic associations. Cole JB, Florez JC, Hirschhorn JN. Nat Commun. 2020; 11: 1467. doi: 10.1038/s41467-020-15193-0. PMID:32193382 |
Dietary habits | |
| UK Biobank atrial fibrillation exome sequence analysis | Monogenic and Polygenic Contributions to Atrial Fibrillation Risk: Results From a National Biobank. Choi SH, Jurgens SJ, et al. Circ Res, 126 (2), 200-209 2020 Jan 17. doi: 10.1161/CIRCRESAHA.119.315686. PMID:31691645 |
Atrial fibrillation | Gene-level association scores | README |
| HERMES Heart Failure GWAS | Genome-wide association study provides new insights into the genetic architecture and pathogenesis of heart failure. Shah S, Henry A, et al. Nat Commun. 2020 Jan 9;11(1):163. doi: 10.1038/s41467-019-13690-5. PMID:31919418 |
Cardiovascular | |
| JDRF Diabetic Nephropathy Collaborative Research Initiative GWAS | Genome-Wide Association Study of Diabetic Kidney Disease Highlights Biology Involved in Glomerular Basement Membrane Collagen. Salem, R.M., et al. J Am Soc Nephrol. 2019 Oct;30(10):2000-2016. doi: 10.1681/ASN.2019030218. PMID:31537649 |
Renal | Download files |
| Diabetic retinopathy GWAS | Multiethnic Genome-Wide Association Study of Diabetic Retinopathy Using Liability Threshold Modeling of Duration of Diabetes and Glycemic Control. Pollack S, et al. Diabetes. 2019 Feb; 68(2): 441–456. doi: 10.2337/db18-0567. PMID:30487263 | Ocular | Download African American ancestry files Download European ancestry files README |
| SIGMA exome chip analysis | A Loss-of-Function Splice Acceptor Variant in IGF2 Is Protective for Type 2 Diabetes. Mercader M, et al., Diabetes 2017 Nov;66(11):2903-2914. doi: 10.2337/db17-0187. PMID:28838971 | Glycemic | Download files README |
| GWAS SIGMA | Sequence variants in SLC16A11 are a common risk factor for type 2 diabetes in Mexico. SIGMA Type 2 Diabetes Consortium, et al., Nature. 2014 Feb 6;506(7486):97-101. doi: 10.1038/nature12828. PMID:24390345 | Glycemic | Download files README |
| AMP T2D-GENES exome sequence analysis: SIGMA cohorts | Association of a low-frequency variant in HNF1A with type 2 diabetes in a Latino population. SIGMA Type 2 Diabetes Consortium, et al., JAMA 2014 Jun 11;311(22):2305-14. doi: 10.1001/jama.2014.6511. PMID:24915262 | Glycemic | Download files README |