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Brænne I, Onengut-Gumuscu S, Chen R, et al. Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes. Sci Rep. 2021;11(1):22651doi: 10.1038/s41598-021-01840-z.
Brænne, I., Onengut-Gumuscu, S., Chen, R., Manichaikul, A. W., Rich, S. S., Chen, W. M., Farber, C. R. (2021). Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes. Scientific reports, 11(1), 22651. https://doi.org/10.1038/s41598-021-01840-z
Brænne, Ingrid, et al. "Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes." Scientific reports vol. 11,1 (2021): 22651. doi: https://doi.org/10.1038/s41598-021-01840-z
Brænne I, Onengut-Gumuscu S, Chen R, Manichaikul AW, Rich SS, Chen WM, Farber CR. Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes. Sci Rep. 2021 Nov 22;11(1):22651. doi: 10.1038/s41598-021-01840-z. PMID: 34811390; PMCID: PMC8609030.
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Sci Rep. 2021 Nov 22;11(1):22651. doi: 10.1038/s41598-021-01840-z.

Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes.

Scientific reports

Ingrid Brænne, Suna Onengut-Gumuscu, Ruoxi Chen, Ani W Manichaikul, Stephen S Rich, Wei-Min Chen, Charles R Farber,

Affiliations

  1. Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA.
  2. Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA.
  3. Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA.
  4. Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA. [email protected].
  5. Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA. [email protected].
  6. Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA. [email protected].

PMID: 34811390 PMCID: PMC8609030 DOI: 10.1038/s41598-021-01840-z

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 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.

© 2021. The Author(s).

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