Identification of biomarkers for glycaemic deterioration in type 2 diabetes.
Roderick C SliekerLouise A DonnellyElina AkalestouLivia Lopez-NoriegaRana MelhemAyşim GüneşFrederic Abou AzarAlexander EfanovEleni GeorgiadouHermine Muniangi-MuhituMahsa SheikhGiuseppe N GiordanoMikael ÅkerlundEmma AhlqvistAshfaq AliKarina BanasikSoren BrunakMarko BarovicGerard A BoulandFrédéric BurdetMickaël CanouilIulian DraganPetra J M EldersCéline FernandezAndreas FestaHugo FitipaldiPhillippe FroguelValborg GudmundsdottirVilmundur G GudnasonMathias J GerlAmber A van der HeijdenLori L JenningsMichael K HansenMin KimIsabelle LeclercChristian KloseDmitry KuznetsovDina Mansour AlyFlorence MehlDiana MarekOlle MelanderAnne NiknejadFilip OttossonImre PavoKevin DuffinSamreen K SyedJanice L ShawOver CabreraTimothy J PullenKai SimonsMichele SolimenaTommi SuvitaivalAsger WretlindEllen BurgessValeriya LyssenkoCristina Legido QuigleyLeif C GroopBernard ThorensPaul W FranksGareth E LimJennifer L EstallMark IbbersonJoline Wilhelma Johanna BeulensLeendert M 't HartEwan R PearsonGuy A RutterPublished in: Nature communications (2023)
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.