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

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

in 631/337/2019 / 631/553 / 692/699/2743/137/1418 / Autoimmunity / Case-Control Studies / Child / Child, Preschool / Clinical Medicine / Computational Biology / Diabetes / Diabetes mellitus (insulin dependent) / Diabetes Mellitus, Type 1 - genetics / Endocrinology and Diabetes / Endokrinologi och diabetes / Environmental risk / Female / Gene Expression Profiling / Gene Expression Regulation / Gene Regulatory Networks / Genes / Genetic diversity / Genetic variance / Genome-Wide Association Study / Humanities and Social Sciences / Humans / Immune response / Immune system / Klinisk medicin / Male / Medical and Health Sciences / Medicin och hälsovetenskap / Models, Statistical / multidisciplinary / Prospective Studies / Risk factors / Science / Science (multidisciplinary) / Systems Biology / Transcriptome / Transcriptomics

2021

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

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

2021

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

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

2021

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Journal Article

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

Chen, Ruoxi,

Chen, Wei-Min,

Rich, Stephen S.,

Onengut-Gumuscu, Suna,

Manichaikul, Ani W.,

Brænne, Ingrid,

Farber, Charles R.

2021

Overview

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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Publisher

Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio

Subject

631/337/2019

/ 631/553

/ 692/699/2743/137/1418

/ Autoimmunity

/ Case-Control Studies

/ Child

/ Child, Preschool