Identification of biomarkers for glycaemic deterioration in type 2 diabetes
Nature Communications, 2023
Slieker R., Donnelly L., Akalestou E., Lopez-Noriega L., Melhem R., Güneş A., Abou Azar F., Efanov A., Georgiadou E., Muniangi-Muhitu H., Sheikh M., Giordano G., Åkerlund M., Ahlqvist E., Ali A., Banasik K., Brunak S., Barovic M., Bouland G., Burdet F., Canouil M., Dragan I., Elders P., Fernandez C., Festa A., Fitipaldi H., Froguel P., Gudmundsdottir V., Gudnason V., Gerl M., van der Heijden A., Jennings L., Hansen M., Kim M., Leclerc I., Klose C., Kuznetsov D., Mansour Aly D., Mehl F., Marek D., Melander O., Niknejad A., Ottosson F., Pavo I., Duffin K., Syed S., Shaw J., Cabrera O., Pullen T., Simons K., Solimena M., Suvitaival T., Wretlind A., Rossing P., Lyssenko V., Legido Quigley C., Groop L., Thorens B., Franks P., Lim G., Estall J., Ibberson M., Beulens J., ’t Hart L., Pearson E., Rutter G.
| Disease area | Application area | Sample type | Products |
|---|---|---|---|
Metabolic Diseases | Patient Stratification | Plasma |  Olink Target 96 |
Abstract
We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.