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3. Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank

6. Identification of biomarkers for glycaemic deterioration in type 2 diabetes

7. Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models

8. The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits

9. A saturated map of common genetic variants associated with human height

11. A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

13. The power of genetic diversity in genome-wide association studies of lipids

14. Author Correction: Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models

15. Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study

16. Circulating small non‐coding RNAs are associated with the insulin‐resistant and obesity‐related type 2 diabetes clusters.

17. Apolipoprotein-CIII O-Glycosylation Is Associated with Micro- and Macrovascular Complications of Type 2 Diabetes

18. Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project

19. An omics-based machine learning approach to predict diabetes progression: a RHAPSODY study

20. Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project

21. Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes

22. Genomics Research of Lifetime Depression in the Netherlands : The BIObanks Netherlands Internet Collaboration (BIONIC) Project

23. Integration of epidemiologic, pharmacologic, genetic and gut microbiome data in a drug–metabolite atlas

24. Apolipoprotein-CIII O-Glycosylation, a Link between GALNT2 and Plasma Lipids

25. Multi-omics subgroups associated with glycaemic deterioration in type 2 diabetes: an IMI-RHAPSODY Study.

26. IgG N‐glycans are associated with prevalent and incident complications of type 2 diabetes

28. Apolipoprotein-CIII O-Glycosylation, a Link between GALNT2 and Plasma Lipids

29. IgG N-glycans are associated with prevalent and incident complications of type 2 diabetes

30. Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models:[with Author Correction]

31. Potential Value of Identifying Type 2 Diabetes Subgroups for Guiding Intensive Treatment: A Comparison of Novel Data-Driven Clustering With Risk-Driven Subgroups

32. The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits

34. Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study

35. Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts

36. Author Correction : The power of genetic diversity in genome-wide association studies of lipids

37. Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas

38. Novel subgroups of type 2 diabetes based on multi-Omics profiling: an IMI-RHAPSODY Study

42. Additional file 1 of Diabetes risk loci-associated pathways are shared across metabolic tissues

43. Plasma protein N-glycosylation is associated with cardiovascular disease, nephropathy, and retinopathy in type 2 diabetes

44. Performance of prediction models for nephropathy in people with type 2 diabetes: systematic review and external validation study

45. The power of genetic diversity in genome-wide association studies of lipids

46. Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study

47. Long RNA Sequencing and Ribosome Profiling of Inflamed β-Cells Reveal an Extensive Translatome Landscape

48. Replication and cross-validation of type 2 diabetes subtypes based on clinical variables:an IMI-RHAPSODY study

49. Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes:An IMI-RHAPSODY Study

50. Processes Underlying Glycemic Deterioration in Type 2 Diabetes:An IMI DIRECT Study

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