Gene expression signature predicts rate of type 1 diabetes progression
Tomi Suomi, Inna Starskaia, Ubaid Ullah, Omid Rasool, Maria K. Jaakkola, Toni Grönroos, Tommi Välikangas, Caroline Brorsson, Gianluca Mazzoni, Sylvaine F. A. Bruggraber, Lut Overbergh, David B. Dunger, Mark Peakman, Piotr Jaroslaw Chmura, Søren Brunak, Anke M. Schulte, Chantal Mathieu, Mikael Knip, Riitta Lahesmaa, Laura L. Elo, Chantal Mathieu, Pieter Gillard, Kristina Casteels, Lutgart Overbergh, David B. Dunger, Chris Wallace, Mark L. Evans, Ajay Thankamony, Emile Hendriks, Sylvaine Bruggraber, Loredana Marcoveccchio, Mark Peakman, Timothy Tree, Noel G. Morgan, Sarah J. Richardson, John A. Todd, Linda S. Wicker, Adrian Mander, Colin Dayan, Mohammad Alhadj Ali, Thomas R. Pieber, Décio L. Eizirik, Myriam Cnop, Søren Brunak, Flemming Pociot, Jesper Johannesen, Peter Rossing, Cristina Legido‐Quigley, Roberto Mallone, Raphaël Scharfmann, Christian Boîtard, Mikael Knip, Timo Otonkoski, Riitta Veijola, Riitta Lahesmaa, Matej Orešič, Jorma Toppari, Thomas Danne, Anette G. Ziegler, Peter Achenbach, Teresa Rodríguez-Calvo, Michele Solimena, Ezio Bonifacio, Stephan Speier, Reinhard W. Holl, Francesco Dotta, Francesco Chiarelli, Piero Marchetti, Emanuele Bosi, Stefano Cianfarani, Paolo Ciampalini, Carine de Beaufort, Knut Dahl‐Jørgensen, Torild Skrivarhaug, Geir Joner, Lars Krogvold, Przemka Jarosz-Chobot, Tadej Battelino, Bernard Thorens, Martin Gotthardt, Bart O. Roep, Tanja Nikolic, Arnaud Zaldumbide, Åke Lernmark, Marcus Lundgren, Guillaume Costacalde, Thorsten Strube, Anke M. Schulte, Almut Nitsche, Mark Peakman, José Luis Vela, Matthias von Herrath, Johnna D. Wesley, Antonella Napolitano-Rosen, Mélissa Thomas, Nanette C. Schloot, Allison B. Goldfine, Frank Waldron-Lynch, Jill Kompa, Aruna Vedala
Abstract
BACKGROUND: Type 1 diabetes is a complex heterogenous autoimmune disease without therapeutic interventions available to prevent or reverse the disease. This study aimed to identify transcriptional changes associated with the disease progression in patients with recent-onset type 1 diabetes. METHODS: Whole-blood samples were collected as part of the INNODIA study at baseline and 12 months after diagnosis of type 1 diabetes. We used linear mixed-effects modelling on RNA-seq data to identify genes associated with age, sex, or disease progression. Cell-type proportions were estimated from the RNA-seq data using computational deconvolution. Associations to clinical variables were estimated using Pearson's or point-biserial correlation for continuous and dichotomous variables, respectively, using only complete pairs of observations. FINDINGS: We found that genes and pathways related to innate immunity were downregulated during the first year after diagnosis. Significant associations of the gene expression changes were found with ZnT8A autoantibody positivity. Rate of change in the expression of 16 genes between baseline and 12 months was found to predict the decline in C-peptide at 24 months. Interestingly and consistent with earlier reports, increased B cell levels and decreased neutrophil levels were associated with the rapid progression. INTERPRETATION: There is considerable individual variation in the rate of progression from appearance of type 1 diabetes-specific autoantibodies to clinical disease. Patient stratification and prediction of disease progression can help in developing more personalised therapeutic strategies for different disease endotypes. FUNDING: A full list of funding bodies can be found under Acknowledgments.