Accelerating Medicines Partnership in Type 2 Diabetes and Common Metabolic Diseases: Collaborating to Maximize the Value of Genetic and Genomic Data

Abstract

In the last two decades, significant progress has been made toward understanding the genetic basis of type 2 diabetes. An important supporter of this research has been the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), most recently through the Accelerating Medicines Partnership Program for Type 2 Diabetes (AMP T2D) and Accelerating Medicines Partnership Program for Common Metabolic Diseases (AMP CMD). These public-private partnerships of the National Institutes of Health, multiple biopharmaceutical and life sciences companies, and nonprofit organizations, facilitated and managed by the Foundation for the National Institutes of Health, were designed to improve understanding of therapeutically relevant biological pathways for type 2 diabetes. On the occasion of NIDDK's 75th anniversary, we review the history of NIDDK support for these partnerships, which saw the convergence of research directions prioritized by academic consortia, the pharmaceutical industry, and government funders. Although the NIDDK was not the sole originator or funder of these efforts, its support and leadership have been pivotal to the partnerships' success and have enabled their research to be broadly accessible through the AMP Common Metabolic Diseases Knowledge Portal (CMDKP) and the AMP Common Metabolic Diseases Genome Atlas (CMDGA). Findings from AMP CMD align with NIDDK's mission to conduct research and share results with the goal of improving health and quality of life.

Article highlights: The Accelerating Medicines Partnership Program for Type 2 Diabetes (AMP T2D) and Accelerating Medicines Partnership Program for Common Metabolic Diseases (AMP CMD) were created to accelerate the translation of genetic and genomic data into knowledge about the biology of disease. Their goal was to gain a better understanding of the mechanisms underlying types 1 and 2 diabetes and prediabetes, obesity, cardiovascular disease, kidney disease, and nonalcoholic steatohepatitis. This work identified multiple genes and pathways underlying these diseases. The findings of AMP T2D and AMP CMD have implications for drug development and improved risk prediction, diagnosis, and treatment for common metabolic diseases.

Figure 1

Organization of the AMP T2D Consortium. Work on AMP T2D occurred across 30 institutions and was funded by NIDDK and five major pharmaceutical companies via the FNIH. Overall guidance was provided by a steering committee that included representatives from industry, academia, and funding agencies. EBI, European Bioinformatics Institute; EMBL-EBI, European Molecular Biology Laboratory European Bioinformatics Institute.

Figure 2

Growth of the T2DKP and CMDKP from the inception of the T2DKP in October 2015. The vertical dashed line in 2020 marks the advent of AMP CMD and the CMDKP. Numbers in red indicate the average number of users per month at those time points. Arrows at the bottom indicate selected highlights in development of the portals (see text for further description). The x-axis labels show month and year abbreviations where, for example, Oct-15 is October 2015.

Figure 3

A variety of variant-to-function and gene-to-function strategies are in use to progressively narrow down the list of potential cardiometabolic disease effector genes for detailed experimental validation.

Figure 4

The Variant Sifter tool of the CMDKP can suggest hypotheses about potential effector genes. Note that for clarity, selected portions of the interface are shown here. The workflow begins with the selection of a phenotype and a genomic region by the user. A: Genetic associations across the region are displayed in the top panel. Here the user has chosen to view genetic associations for type 2 diabetes in the region of the ADCY5 gene and has selected a variant of interest, converting its symbol from a dot to a star. This creates a vertical line (augmented for visibility in the figure) that marks the position of the variant across all other panels. B: Available credible sets, either curated from the literature or computed at the CMDKP, may be selected and displayed. Here the user has displayed a credible set from Mahajan et al. (23), 2022. C: The user has the ability to select 1 or more of 4 annotation types and nearly 50 tissue categories (not shown), after which the coordinates of the selected annotations are displayed within specific tissue and cell types for each tissue category chosen. The interface shows that the variant of interest is located within regions annotated as enhancers in pancreatic islets and pancreas tissue. D: Variant-to-gene connections generated using five different methods are displayed, allowing the user to determine whether a variant of interest is located within a genomic region that is predicted to contact the promoter of a gene of interest. Here, two of three methods (Cicero co-accessibility and Activity-by-Contact, each displayed in a horizontal track) predict that the marked variant is within a region that contacts the ADCY5 promoter. The example shown in the figure suggests that the index variant affects type 2 diabetes risk by impacting regulation of ADCY5 expression, recapitulating the results of Roman et al. (58), 2017.