Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes
(2021) In Scientific Reports 11. p.1-13- Abstract
Significant progress has been made in elucidating genetic risk factors influencing Type 1 diabetes (T1D); however, features other than genetic variants that initiate and/or accelerate islet autoimmunity that lead to the development of clinical T1D remain largely unknown. We hypothesized that genetic and environmental risk factors can both contribute to T1D through dynamic alterations of molecular interactions in physiologic networks. To test this hypothesis, we utilized longitudinal blood transcriptomic profiles in The Environmental Determinants of Diabetes in the Young (TEDDY) study to generate gene co-expression networks. In network modules that contain immune response genes associated with T1D, we observed highly dynamic differences... (More)
Significant progress has been made in elucidating genetic risk factors influencing Type 1 diabetes (T1D); however, features other than genetic variants that initiate and/or accelerate islet autoimmunity that lead to the development of clinical T1D remain largely unknown. We hypothesized that genetic and environmental risk factors can both contribute to T1D through dynamic alterations of molecular interactions in physiologic networks. To test this hypothesis, we utilized longitudinal blood transcriptomic profiles in The Environmental Determinants of Diabetes in the Young (TEDDY) study to generate gene co-expression networks. In network modules that contain immune response genes associated with T1D, we observed highly dynamic differences in module connectivity in the 600 days (~ 2 years) preceding clinical diagnosis of T1D. Our results suggest that gene co-expression is highly plastic and that connectivity differences in T1D-associated immune system genes influence the timing and development of clinical disease.
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- author
- Brænne, Ingrid ; Onengut-Gumuscu, Suna ; Chen, Ruoxi ; Manichaikul, Ani ; Rich, Stephen ; Chen, Wei-Min and Farber, Charles
- contributor
- Lernmark, Åke
LU
; Agardh, Daniel
LU
; Aronsson, Carin Andrén
LU
; Ask, Maria
LU
; Bennet, Rasmus
LU
; Cilio, Corrado
LU
; Engqvist, Helene
LU
; Ericson-Hallström, Emelie
LU
; Fransson, Lina
LU
; Gard, Thomas
LU
; Hansen, Monika
LU
; Jisser, Hanna
LU
; Johansen, Fredrik
LU
; Jonsdottir, Berglind
LU
; Jovic, Silvija
LU
; Larsson, Helena Elding
LU
; Lindström, Marielle
LU
; Lundgren, Markus
LU
; Maziarz, Marlena
LU
; Månsson-Martinez, Maria
LU
; Markan, Maria
LU
; Mestan, Zeliha
LU
; Ottosson, Karin
LU
; Rahmati, Kobra
LU
; Ramelius, Anita
LU
; Salami, Falastin
LU
; Sjöberg, Anette
LU
; Sjöberg, Birgitta
LU
; Svensson, Malin
LU
; Törn, Carina
LU
; Wallin, Anne
LU
; Wimar, Åsa
LU
and Åberg, Sofie
LU
- author collaboration
- organization
- publishing date
- 2021-12
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Scientific Reports
- volume
- 11
- article number
- 22651
- pages
- 1 - 13
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85122116230
- pmid:34811390
- ISSN
- 2045-2322
- DOI
- 10.1038/s41598-021-01840-z
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2021, The Author(s).
- id
- 5af76cc3-936a-4b05-a328-a3c95768a419
- date added to LUP
- 2024-09-05 16:28:02
- date last changed
- 2025-10-14 10:03:55
@article{5af76cc3-936a-4b05-a328-a3c95768a419,
abstract = {{<p>Significant progress has been made in elucidating genetic risk factors influencing Type 1 diabetes (T1D); however, features other than genetic variants that initiate and/or accelerate islet autoimmunity that lead to the development of clinical T1D remain largely unknown. We hypothesized that genetic and environmental risk factors can both contribute to T1D through dynamic alterations of molecular interactions in physiologic networks. To test this hypothesis, we utilized longitudinal blood transcriptomic profiles in The Environmental Determinants of Diabetes in the Young (TEDDY) study to generate gene co-expression networks. In network modules that contain immune response genes associated with T1D, we observed highly dynamic differences in module connectivity in the 600 days (~ 2 years) preceding clinical diagnosis of T1D. Our results suggest that gene co-expression is highly plastic and that connectivity differences in T1D-associated immune system genes influence the timing and development of clinical disease.</p>}},
author = {{Brænne, Ingrid and Onengut-Gumuscu, Suna and Chen, Ruoxi and Manichaikul, Ani and Rich, Stephen and Chen, Wei-Min and Farber, Charles}},
issn = {{2045-2322}},
language = {{eng}},
pages = {{1--13}},
publisher = {{Nature Publishing Group}},
series = {{Scientific Reports}},
title = {{Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes}},
url = {{http://dx.doi.org/10.1038/s41598-021-01840-z}},
doi = {{10.1038/s41598-021-01840-z}},
volume = {{11}},
year = {{2021}},
}