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Optimising diabetes management with better diagnostics

Diabetes is a chronic disease causing widespread complications ranging from kidney and eye problems to cardiovascular disorders and with treatment response depending on disease sub-type. Techniques to differentiate between sub-types of the disease are needed.
Optimising diabetes management with better diagnostics
European leaders in beta cell biology, genetics and clinical diabetes joined forces in the EU-supported 'Collaborative European effort to develop diabetes diagnostics' (CEED3) project to address this critical need. Researchers used human samples, in silico modelling, cell lines and animal models to develop accurate diagnostic methods and validate biomarkers.

CEED3 members made several breakthroughs with regard to young (MODY), often misdiagnosed as type 1 or type 2 diabetes (T1D or T2D). Comprehensive research confirmed that C-reactive protein (CRP) was significantly lower in HNF1A-MODY than in T1D or T2D patients. Also, biomarkers such as beta cell antibodies and C-peptide measurement were useful in differentiating between MODY and T1D. Although other useful markers such as proteoglycans were also identified, difficulties with developing suitable assays limited their utility. An online MODY probability calculator was developed to predict which patients need to be genetically tested for MODY. Researchers are currently working on integrating biomarker information to increase prediction accuracy.

Loss of or dysfunction in beta cells of the islets of Langerhans in the pancreas lowers insulin production and affects blood–sugar levels causing diabetes. Considerable efforts were therefore concentrated on the development and validation of biomarkers for beta cell dysfunction and loss. The first ever genome-wide analysis was carried out inT2D patients to study DNA methylation changes in human islets. Bioinformatics, genome sequencing and exome sequencing studies helped identify several DNA-based variants in genes of interest such as secreted frizzled-related protein 4 (SFRP4).

Researchers also attempted to find genetic and non-genetic biomarkers for complications arising from diabetes, such as liver disease, kidney disease, retinopathy and cardiovascular disease. Metabolomics on T1D patients revealed that serum sphingomyelin was associated with advanced kidney disease and metabolic disorders.

Successful outcomes have resulted in the selection of the CEED3 group for development of guidelines to diagnose and manage monogenic diabetes (e.g. MODY). Research has been disseminated via 107 publications in peer-reviewed journals, over 90 talks, outreach programmes, YouTube videos and the project website.

Diabetes management based on the disease sub-type will significantly reduce health care costs, improve patient outcomes and provide novel avenues for therapy.

Related information

Subjects

Biotechnology
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