Gene expression signature predicts rate of type 1 diabetes progression

被引:9
|
作者
Suomi, Tomi [1 ,2 ,3 ]
Starskaia, Inna [1 ,2 ,3 ,4 ]
Kalim, Ubaid Ullah [1 ,2 ,3 ]
Rasool, Omid [1 ,2 ,3 ]
Jaakkola, Maria K. [1 ,2 ,3 ]
Gronroos, Toni [1 ,2 ,3 ]
Valikangas, Tommi [1 ,2 ,3 ]
Brorsson, Caroline [5 ]
Mazzoni, Gianluca [5 ]
Bruggraber, Sylvaine [6 ]
Overbergh, Lut [7 ,8 ]
Dunger, David [5 ,6 ]
Peakman, Mark [9 ]
Chmura, Piotr [5 ]
Brunak, Seren [5 ]
Schulte, Anke M. [10 ]
Mathieu, Chantal [7 ,8 ]
Knip, Mikael [11 ,12 ,13 ,14 ]
Lahesmaa, Riitta [1 ,2 ,3 ,15 ]
Elo, Laura L. [1 ,2 ,3 ,15 ]
机构
[1] Univ Turku, Turku Biosci Ctr, Turku 20520, Finland
[2] Abo Akad Univ, FI-20520 Turku, Finland
[3] Univ Turku, InFLAMES Res Flagship Ctr, Turku, Finland
[4] Univ Turku, Turku Doctoral Programme Mol Med, Turku, Finland
[5] Univ Copenhagen, Novo Nord Fdn Ctr Prot Res, Fac Hlth & Med Sci, Copenhagen, Denmark
[6] Univ Cambridge, Dept Paediat, Cambridge, England
[7] Katholieke Univ Leuven, Leuven, Belgium
[8] Univ Ziekenhuizen, Leuven, Belgium
[9] Immunol & flammat Res Therapeut Area, Sanofi, MA USA
[10] Sanofi Aventis Deutschland GmbH, Frankfurt, Germany
[11] Univ Helsinki, Paediat Res Ctr, Helsinki, Finland
[12] Helsinki Univ Hosp, Helsinki, Finland
[13] Univ Helsinki, Fac Med, Res Program Clin & Mol Metab, Helsinki, Finland
[14] Tampere Univ Hosp, Tampere Ctr Child Hlth Res, Tampere, Finland
[15] Univ Turku, Inst Biomed, Turku 20520, Finland
来源
EBIOMEDICINE | 2023年 / 92卷
基金
欧洲研究理事会; 芬兰科学院;
关键词
Type; 1; diabetes; Autoantibodies; RNA-seq; Gene expression signature; Predictive model; BETA-CELL FUNCTION; RISK; DIAGNOSIS; CHILDREN; AUTOANTIBODIES; NEUTROPHILS; PRECEDES; HISTORY;
D O I
10.1016/j.ebiom.2023.104625
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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 diag-nosis 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.
引用
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页数:12
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