TY - JOUR

T1 - Genetic Risk Score Modelling for Disease Progression in New-Onset Type 1 Diabetes Patients

T2 - Increased Genetic Load of Islet-Expressed and Cytokine-Regulated Candidate Genes Predicts Poorer Glycemic Control

AU - Brorsson, Caroline A

AU - Nielsen, Lotte B

AU - Andersen, Marie-Louise

AU - Kaur, Simranjeet

AU - Bergholdt, Regine

AU - Hansen, Lars

AU - Mortensen, Henrik B.

AU - Pociot, Flemming

AU - Størling, Joachim

AU - Hvidoere Study Group On Childhood Diabetes

PY - 2016

Y1 - 2016

N2 - Genome-wide association studies (GWAS) have identified over 40 type 1 diabetes risk loci. The clinical impact of these loci on β-cell function during disease progression is unknown. We aimed at testing whether a genetic risk score could predict glycemic control and residual β-cell function in type 1 diabetes (T1D). As gene expression may represent an intermediate phenotype between genetic variation and disease, we hypothesized that genes within T1D loci which are expressed in islets and transcriptionally regulated by proinflammatory cytokines would be the best predictors of disease progression. Two-thirds of 46 GWAS candidate genes examined were expressed in human islets, and 11 of these significantly changed expression levels following exposure to proinflammatory cytokines (IL-1β + IFNγ + TNFα) for 48 h. Using the GWAS single nucleotide polymorphisms (SNPs) from each locus, we constructed a genetic risk score based on the cumulative number of risk alleles carried in children with newly diagnosed T1D. With each additional risk allele carried, HbA1c levels increased significantly within first year after diagnosis. Network and gene ontology (GO) analyses revealed that several of the 11 candidate genes have overlapping biological functions and interact in a common network. Our results may help predict disease progression in newly diagnosed children with T1D which can be exploited for optimizing treatment.

AB - Genome-wide association studies (GWAS) have identified over 40 type 1 diabetes risk loci. The clinical impact of these loci on β-cell function during disease progression is unknown. We aimed at testing whether a genetic risk score could predict glycemic control and residual β-cell function in type 1 diabetes (T1D). As gene expression may represent an intermediate phenotype between genetic variation and disease, we hypothesized that genes within T1D loci which are expressed in islets and transcriptionally regulated by proinflammatory cytokines would be the best predictors of disease progression. Two-thirds of 46 GWAS candidate genes examined were expressed in human islets, and 11 of these significantly changed expression levels following exposure to proinflammatory cytokines (IL-1β + IFNγ + TNFα) for 48 h. Using the GWAS single nucleotide polymorphisms (SNPs) from each locus, we constructed a genetic risk score based on the cumulative number of risk alleles carried in children with newly diagnosed T1D. With each additional risk allele carried, HbA1c levels increased significantly within first year after diagnosis. Network and gene ontology (GO) analyses revealed that several of the 11 candidate genes have overlapping biological functions and interact in a common network. Our results may help predict disease progression in newly diagnosed children with T1D which can be exploited for optimizing treatment.

KW - Adolescent

KW - Adult

KW - Alleles

KW - Child

KW - Cohort Studies

KW - Cytokines

KW - Diabetes Mellitus, Type 1

KW - Disease Progression

KW - Female

KW - Gene Expression Profiling

KW - Genetic Load

KW - Genetic Predisposition to Disease

KW - Genome-Wide Association Study

KW - Genotype

KW - Hemoglobin A, Glycosylated

KW - Humans

KW - Hyperglycemia

KW - Insulin-Secreting Cells

KW - Interferon-gamma

KW - Interleukin-1beta

KW - Islets of Langerhans

KW - Male

KW - Middle Aged

KW - Polymorphism, Single Nucleotide

KW - Risk

KW - Tumor Necrosis Factor-alpha

KW - Young Adult

KW - Journal Article

KW - Research Support, N.I.H., Extramural

KW - Research Support, Non-U.S. Gov't

U2 - 10.1155/2016/9570424

DO - 10.1155/2016/9570424

M3 - Journal article

C2 - 26904692

VL - 2016

JO - Journal of Diabetes Research

JF - Journal of Diabetes Research

SN - 2314-6745

M1 - 9570424

ER -