1. Identification of biomarkers for glycaemic deterioration in type 2 diabetes
- Author
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Roderick C. Slieker, Louise A. Donnelly, Elina Akalestou, Livia Lopez-Noriega, Rana Melhem, Ayşim Güneş, Frederic Abou Azar, Alexander Efanov, Eleni Georgiadou, Hermine Muniangi-Muhitu, Mahsa Sheikh, Giuseppe N. Giordano, Mikael Åkerlund, Emma Ahlqvist, Ashfaq Ali, Karina Banasik, Søren Brunak, Marko Barovic, Gerard A. Bouland, Frédéric Burdet, Mickaël Canouil, Iulian Dragan, Petra J. M. Elders, Celine Fernandez, Andreas Festa, Hugo Fitipaldi, Phillippe Froguel, Valborg Gudmundsdottir, Vilmundur Gudnason, Mathias J. Gerl, Amber A. van der Heijden, Lori L. Jennings, Michael K. Hansen, Min Kim, Isabelle Leclerc, Christian Klose, Dmitry Kuznetsov, Dina Mansour Aly, Florence Mehl, Diana Marek, Olle Melander, Anne Niknejad, Filip Ottosson, Imre Pavo, Kevin Duffin, Samreen K. Syed, Janice L. Shaw, Over Cabrera, Timothy J. Pullen, Kai Simons, Michele Solimena, Tommi Suvitaival, Asger Wretlind, Peter Rossing, Valeriya Lyssenko, Cristina Legido Quigley, Leif Groop, Bernard Thorens, Paul W. Franks, Gareth E. Lim, Jennifer Estall, Mark Ibberson, Joline W. J. Beulens, Leen M ’t Hart, Ewan R. Pearson, Guy A. Rutter, Epidemiology and Data Science, APH - Aging & Later Life, APH - Health Behaviors & Chronic Diseases, General practice, ACS - Diabetes & metabolism, APH - Methodology, and ACS - Heart failure & arrhythmias
- Subjects
Male ,Multidisciplinary ,Blood Glucose/metabolism ,Insulin/metabolism ,General Physics and Astronomy ,General Chemistry ,Biomarkers/metabolism ,Diabetes Mellitus, Type 2/metabolism ,Lipids ,General Biochemistry, Genetics and Molecular Biology ,Extracellular Matrix Proteins/metabolism ,Mice ,Animals ,Islets of Langerhans/metabolism ,Cell Adhesion Molecules/metabolism - 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.
- Published
- 2023