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Gene expression signature predicts rate of type 1 diabetes progression

Year of publication

2023

Authors

INNODIA Consortium; Suomi, Tomi; Starskaia, Inna; Kalim, Ubaid Ullah; Rasool, Omid; Jaakkola, Maria K.; Grönroos, Toni; Välikangas, Tommi; Brorsson, Caroline; Mazzoni, Gianluca; Bruggraber, Sylvaine; Overbergh, Lut; Dunger, David; Peakman, Mark; Chmura, Piotr; Brunak, Seren; Schulte, Anke M.; Mathieu, Chantal; Knip, Mikael; Lahesmaa, Riitta
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Abstract

<p>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.</p>
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Organizations and authors

University of Turku

Starskaia Inna

Elo Laura

Jaakkola Maria

Rasool Omid

Lahesmaa Riitta

Suomi Tomi

Välikangas Tommi

Grönroos Toni

Kalim Ubaid

Åbo Akademi University

Lahesmaa Riitta

Publication type

Publication format

Article

Parent publication type

Journal

Article type

Original article

Audience

Scientific

Peer-reviewed

Peer-Reviewed

MINEDU's publication type classification code

A1 Journal article (refereed), original research

Publication channel information

Journal/Series

EBioMedicine

Parent publication name

EBioMedicine

Volume

92

Article number

104625

​Publication forum

82311

​Publication forum level

1

Open access

Open access in the publisher’s service

Yes

Open access of publication channel

Fully open publication channel

Self-archived

Yes

Other information

Fields of science

Biochemistry, cell and molecular biology; Biomedicine; General medicine, internal medicine and other clinical medicine; Gynaecology and paediatrics

Keywords

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Publication country

Netherlands

Internationality of the publisher

International

Language

English

International co-publication

Yes

Co-publication with a company

Yes

DOI

10.1016/j.ebiom.2023.104625

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes