One of the main resources to the LUDC-IRC is the access to large well-phenotyped cohorts, which can be linked to information from the public health care system. Central to the LUDC-IRC work is the exploitation of the more refined diabetes classification, which will help us more systematically search for pathogenic mechanisms underlying each of the new diabetes subgroups.

Central to this work-package is the LUDC-IRC Bioinformatics Unit, which provides bioinformatics, biostatistics and computational support, as well as access to a high-performance computing environment. 

Objectives

• To harmonise available cohort information and sample management.
• To develop a data management system to support joint analysis of distributed data.
• To explore the influence of disease heterogeneity on disease outcome.
• To integrate data on candidate biomarkers and drug targets using systems biology approaches.
• To access and integrate additional data that supports the further validation and refinement of candidate
• biomarkers and drug targets for diabetes and its complications.
• To generate refined lists of high-quality validated prognostic/predictive biomarkers or biomarker panels and drug targets that can be prepared for qualification.

Selected publications

• Title: Subgroups of patients with young-onset type 2 diabetes in India reveal insulin deficiency as a major driver
  Reference: Diabetologia, 65, 65–78 (2022)
• Title: Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes
  Reference: Nature Genetics, 53, 1534-1542 (2021)
• Title: Novel Reclassification of Adult Diabetes Is Useful to Distinguish Stages of β-Cell Function Linked to the Risk of Vascular Complications: The DOLCE Study From Northern Ukraine
  Reference: Frontiers in Genetics, 12, 637945 (2021)
• Title: Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study
  Reference: Diabetologia, 64, 1982–1989 (2021)
• Title: Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study
  Reference: Diabetes, 70, 2683–2693 (2021)