Gene expression signature predicts rate of type 1 diabetes progression
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Gene expression signature predicts rate of type 1 diabetes progression. / Suomi, Tomi; Starskaia, Inna; Kalim, Ubaid Ullah; Rasool, Omid; Jaakkola, Maria K.; Grönroos, Toni; Välikangas, Tommi; Brorsson, Caroline; Mazzoni, Gianluca; Bruggraber, Sylvaine; Overbergh, Lutgart; Dunger, David; Peakman, Mark; Chmura, Piotr; Brunak, Søren; Schulte, Anke M.; Mathieu, Chantal; Knip, Mikael; Lahesmaa, Riitta; Elo, Laura L.; Pociot, Flemming (Member of author collaboration); Johannesen, Jesper (Member of author collaboration); Rossing, Peter (Member of author collaboration); INNODIA consortium.
In: EBioMedicine, Vol. 92, 104625, 2023.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Gene expression signature predicts rate of type 1 diabetes progression
AU - Suomi, Tomi
AU - Starskaia, Inna
AU - Kalim, Ubaid Ullah
AU - Rasool, Omid
AU - Jaakkola, Maria K.
AU - Grönroos, Toni
AU - Välikangas, Tommi
AU - Brorsson, Caroline
AU - Mazzoni, Gianluca
AU - Bruggraber, Sylvaine
AU - Overbergh, Lutgart
AU - Dunger, David
AU - Peakman, Mark
AU - Chmura, Piotr
AU - Brunak, Søren
AU - Schulte, Anke M.
AU - Mathieu, Chantal
AU - Knip, Mikael
AU - Lahesmaa, Riitta
AU - Elo, Laura L.
AU - INNODIA consortium
A2 - Pociot, Flemming
A2 - Johannesen, Jesper
A2 - Rossing, Peter
N1 - Publisher Copyright: © 2023 The Authors
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Autoantibodies
KW - Gene expression signature
KW - Predictive model
KW - RNA-seq
KW - Type 1 diabetes
U2 - 10.1016/j.ebiom.2023.104625
DO - 10.1016/j.ebiom.2023.104625
M3 - Journal article
C2 - 37224769
AN - SCOPUS:85159802766
VL - 92
JO - EBioMedicine
JF - EBioMedicine
SN - 2352-3964
M1 - 104625
ER -
ID: 357651850