DIAGRAM Consortium

DIAGRAM Consortium
Name	DIAGRAM Consortium
Type	Research consortium
Founded	2006
Headquarters	London
Fields	Genomics, Epidemiology, Bioinformatics

DIAGRAM Consortium

The DIAGRAM Consortium is an international research collaboration focused on the genetics of type 2 diabetes and related metabolic traits. It convenes researchers from institutions such as Wellcome Trust Centre for Human Genetics, Harvard Medical School, Broad Institute, University of Oxford, and Imperial College London to perform large-scale genome-wide association studies, meta-analyses, and integrative genomics projects involving cohorts from United Kingdom Biobank, Framingham Heart Study, EPIC-Norfolk, and other population resources.

Overview

The consortium brings together expertise from groups including Wellcome Trust Sanger Institute, European Bioinformatics Institute, Max Planck Institute for Molecular Genetics, Karolinska Institutet, and University of Cambridge to study genetic architecture of metabolic diseases. DIAGRAM aggregates data from cohorts such as Atherosclerosis Risk in Communities Study, Multi-Ethnic Study of Atherosclerosis, Jackson Heart Study, Nurses' Health Study, and Health and Retirement Study to increase power for discovery and replication. Its work interfaces with projects like 1000 Genomes Project, HapMap Project, GTEx Consortium, ENCODE Project, and UK10K to annotate functional consequences of associated variants.

History and Development

DIAGRAM originated from collaborations among groups at Imperial College London, University of Oxford, Broad Institute, and Harvard Medical School following early GWAS efforts exemplified by studies at Wellcome Trust Case Control Consortium and publications from teams at Stanford University School of Medicine and Massachusetts General Hospital. Major consortium milestones align with landmark projects such as the release of data from the International HapMap Project and analytical advances from groups at University of Michigan and University of Chicago that applied meta-analysis methods developed in parallel with work at Columbia University and Johns Hopkins University. Over successive phases the consortium expanded membership to include investigators from University of Helsinki, Karolinska Institutet, University of Tartu, and Monash University, reflecting growing international participation mirrored by consortia like GIANT Consortium and CARDIoGRAM.

Research Goals and Methods

Primary goals include identifying common and low-frequency variants influencing type 2 diabetes risk and glycaemic traits, mapping loci to genes, and integrating results with functional genomics from GTEx Consortium and ENCODE Project. Methods leverage genome-wide association studies as practiced at Broad Institute, imputation with reference panels from the 1000 Genomes Project and UK10K, meta-analysis pipelines inspired by work at University of Oxford and Harvard School of Public Health, and fine-mapping approaches developed at Wellcome Trust Sanger Institute and Erasmus Medical Center. Analyses often incorporate statistical genetics tools from teams at University of Michigan (e.g., imputation servers), causal inference methods advanced by researchers at University of California, Berkeley and University of Chicago, and functional follow-up performed in laboratories associated with Massachusetts Institute of Technology and Cold Spring Harbor Laboratory.

Major Studies and Findings

Consortium publications have reported numerous loci associated with type 2 diabetes, glycaemic traits, and insulin secretion, paralleling findings from the GIANT Consortium and informing mechanistic work in model systems used by groups at Salk Institute and University of California, San Francisco. Key results include discovery of novel risk loci that implicate genes studied at University of Cambridge and Harvard Medical School, fine-mapping of signals with methods developed at Wellcome Trust Sanger Institute and Broad Institute, and integration with expression quantitative trait loci from GTEx Consortium and chromatin maps from ENCODE Project. These findings have influenced translational initiatives at GlaxoSmithKline, Novo Nordisk, AstraZeneca, and academic translational centers such as Karolinska Institutet Translational Medicine Center.

Collaborations and Membership

DIAGRAM’s membership spans academic institutions, public biobanks, and consortia including Wellcome Trust, National Institutes of Health, European Commission Horizon 2020, and disease-focused groups like Diabetes UK and American Diabetes Association. Academic collaborators include University of Oxford, Imperial College London, Harvard Medical School, Broad Institute, University of Cambridge, University of Michigan, Columbia University, Johns Hopkins University, Karolinska Institutet, University of Helsinki, and Monash University. The consortium coordinates with other large-scale efforts such as GIANT Consortium, CARDIoGRAMplusC4D Consortium, Psychiatric Genomics Consortium, and public resources including UK Biobank and 1000 Genomes Project to harmonize phenotypes and share summary statistics.

Data Access and Resources

DIAGRAM distributes summary-level association results to the research community via repositories and portals analogous to those maintained by European Genome-phenome Archive, dbGaP, NHGRI-EBI GWAS Catalog, and institutional servers at Wellcome Trust Sanger Institute and Broad Institute. Investigators seeking individual-level data typically request access through cohort platforms such as UK Biobank, Framingham Heart Study, EPIC-Norfolk, and dbGaP governed by data access committees like those at National Institutes of Health. The consortium’s resources are used by researchers at Stanford University, Massachusetts General Hospital, University of Chicago, and industry groups at GlaxoSmithKline and AstraZeneca for downstream functional studies and drug target prioritization.

Category:Genetic epidemiology consortia