A Type 1 Diabetes Genetic Risk Score Can Aid Discrimination Between Type 1 and Type 2 Diabetes in Young Adults

Abstract Aims/hypothesis Type 1 and type 2 diabetes differ with respect to pathophysiological factors such as beta cell function, insulin resistance and phenotypic appearance, but there may be overlap between the two forms of diabetes. However, there are relatively few prospective studies that have characterised the relationship between autoimmunity and incident diabetes. We investigated associations of antibodies against the 65 kDa isoform of GAD (GAD65) with type 1 diabetes and type 2 diabetes genetic risk scores and incident diabetes in adults in European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a case-cohort study nested in the EPIC cohort. Methods GAD65 antibodies were analysed in EPIC participants (over 40 years of age and free of known diabetes at baseline) by radioligand binding assay in a random subcohort (n = 15,802) and in incident diabetes cases (n = 11,981). Type 1 diabetes and type 2 diabetes genetic risk scores were calculated. Associations between GAD65 antibodies and incident diabetes were estimated using Prentice-weighted Cox regression. Results GAD65 antibody positivity at baseline was associated with development of diabetes during a median follow-up time of 10.9 years (HR for GAD65 antibody positive vs negative 1.78; 95% CI 1.43, 2.20) after adjustment for sex, centre, physical activity, smoking status and education. The genetic risk score for type 1 diabetes but not type 2 diabetes was associated with GAD65 antibody positivity in both the subcohort (OR per SD genetic risk 1.24; 95% CI 1.03, 1.50) and incident cases (OR 1.97; 95% CI 1.72, 2.26) after adjusting for age and sex. The risk of incident diabetes in those in the top tertile of the type 1 diabetes genetic risk score who were also GAD65 antibody positive was 3.23 (95% CI 2.10, 4.97) compared with all other individuals, suggesting that 1.8% of incident diabetes in adults was attributable to this combination of risk factors. Conclusions/interpretation Our study indicates that incident diabetes in adults has an element of autoimmune aetiology. Thus, there might be a reason to re-evaluate the present subclassification of diabetes in adulthood.

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Next steps in the identification of gene targets for type 1 diabetes

Diabetologia ◽

10.1007/s00125-020-05248-8 ◽

2020 ◽

Vol 63 (11) ◽

pp. 2260-2269 ◽

Cited By ~ 1

Author(s):

Struan F. A. Grant ◽

Andrew D. Wells ◽

Stephen S. Rich

Keyword(s):

Type 2 Diabetes ◽

Type 1 Diabetes ◽

Beta Cell ◽

Genetic Risk ◽

Genetic Risk Score ◽

Cell Types ◽

Total Risk ◽

Chromosome Conformation

Abstract The purpose of this review is to provide a view of the future of genomics and other omics approaches in defining the genetic contribution to all stages of risk of type 1 diabetes and the functional impact and clinical implementations of the associated variants. From the recognition nearly 50 years ago that genetics (in the form of HLA) distinguishes risk of type 1 diabetes from type 2 diabetes, advances in technology and sample acquisition through collaboration have identified over 60 loci harbouring SNPs associated with type 1 diabetes risk. Coupled with HLA region genes, these variants account for the majority of the genetic risk (~50% of the total risk); however, relatively few variants are located in coding regions of genes exerting a predicted protein change. The vast majority of genetic risk in type 1 diabetes appears to be attributed to regions of the genome involved in gene regulation, but the target effectors of those genetic variants are not readily identifiable. Although past genetic studies clearly implicated immune-relevant cell types involved in risk, the target organ (the beta cell) was left untouched. Through emergent technologies, using combinations of genetics, gene expression, epigenetics, chromosome conformation and gene editing, novel landscapes of how SNPs regulate genes have emerged. Furthermore, both the immune system and the beta cell and their biological pathways have been implicated in a context-specific manner. The use of variants from immune and beta cell studies distinguish type 1 diabetes from type 2 diabetes and, when they are combined in a genetic risk score, open new avenues for prediction and treatment.

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No prognostic role of a GWAS-derived genetic risk score in renal outcomes for patients from French cohorts with type 1 and type 2 diabetes

Diabetes & Metabolism ◽

10.1016/j.diabet.2018.01.016 ◽

2019 ◽

Vol 45 (5) ◽

pp. 494-497

Author(s):

P. Barbieux ◽

B. György ◽

E. Gand ◽

P.-J. Saulnier ◽

G. Ducrocq ◽

...

Keyword(s):

Type 2 Diabetes ◽

Risk Score ◽

Genetic Risk ◽

Genetic Risk Score ◽

Prognostic Role ◽

Renal Outcomes

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1535-P: An Insulin Resistance Genetic Risk Score (IR_GRS) Is Associated with Mortality in Type 1 Diabetes (T1D)

Diabetes ◽

10.2337/db19-1535-p ◽

2019 ◽

Vol 68 (Supplement 1) ◽

pp. 1535-P

Author(s):

RACHEL G. MILLER ◽

TINA COSTACOU ◽

SUNA ONENGUT-GUMUSCU ◽

WEI-MIN CHEN ◽

STEPHEN S. RICH ◽

...

Keyword(s):

Insulin Resistance ◽

Type 1 Diabetes ◽

Risk Score ◽

Genetic Risk ◽

Genetic Risk Score

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243-OR: Integrating Genetic Risk Score and Islet Autoantibody Characteristics in the Predictive Model for Type 1 Diabetes in the TrialNet Study

Diabetes ◽

10.2337/db21-243-or ◽

2021 ◽

Vol 70 (Supplement 1) ◽

pp. 243-OR

Author(s):

LAURIC A. FERRAT ◽

ANDREA STECK ◽

HEMANG M. PARIKH ◽

LU YOU ◽

SUNA ONENGUT-GUMUSCU ◽

...

Keyword(s):

Type 1 Diabetes ◽

Predictive Model ◽

Risk Score ◽

Genetic Risk ◽

Genetic Risk Score ◽

Islet Autoantibody

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Prediction of type 1 diabetes at birth: cord blood metabolites versus genetic risk score in the MoBa cohort

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/clinem/dgab400 ◽

2021 ◽

Author(s):

German Tapia ◽

Tommi Suvitaival ◽

Linda Ahonen ◽

Nicolai A Lund-Blix ◽

Pål R Njølstad ◽

...

Keyword(s):

Type 1 Diabetes ◽

Cord Blood ◽

Bile Acids ◽

Risk Score ◽

Genetic Risk ◽

Risk Group ◽

Genetic Risk Score ◽

Blood Concentrations ◽

Polar Metabolites

Abstract Background and aim Genetic markers are established as predictive of type 1 diabetes, but unknown early life environment is believed to be involved. Umbilical cord blood may reflect perinatal metabolism and exposures. We studied whether selected polar metabolites in cord blood contribute to prediction of type 1 diabetes. Methods Using a targeted UHPLC-QQQ-MS platform, we quantified 27 low molecular weight metabolites (including amino acids, small organic acids and bile acids) in 166 children, who later developed type 1 diabetes, and 177 random control children in the Norwegian Mother, Father and Child (MoBa) cohort. We analysed the data using logistic regression (estimating odds ratios per standard deviation [aOR]), area under the receiver operating characteristic curve (AUC) and k-means clustering. Metabolites were compared to a genetic risk score based on 51 established non-HLA SNPs, and a four-category HLA risk group. Results The strongest associations for metabolites were aminoadipic acid (aOR=1.23,95%CI:0.97–1.55), indoxyl sulfate (aOR=1.15,95%CI:0.87–1.51), and tryptophan (aOR=0.84,95%CI:0.65–1.10), with other aORs close to 1.0, and none significantly associated with type 1 diabetes. K-means clustering identified six clusters, none of which were associated with type 1 diabetes. Cross-validated AUC showed no predictive value of metabolites (AUC 0.49), while the non-HLA genetic risk score AUC was 0.56 and the HLA risk group AUC was 0.78. Conclusions In this large study, we found no support of a predictive role of cord blood concentrations of selected bile acids and other small polar metabolites in the development of type 1 diabetes.

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Progression from islet autoimmunity to clinical type 1 diabetes is influenced by genetic factors: results from the prospective TEDDY study

Journal of Medical Genetics ◽

10.1136/jmedgenet-2018-105532 ◽

2018 ◽

Vol 56 (9) ◽

pp. 602-605 ◽

Cited By ~ 4

Author(s):

Andreas Beyerlein ◽

Ezio Bonifacio ◽

Kendra Vehik ◽

Markus Hippich ◽

Christiane Winkler ◽

...

Keyword(s):

Type 1 Diabetes ◽

Risk Score ◽

Genetic Risk ◽

Genetic Factors ◽

Genetic Risk Score ◽

Risk Scores ◽

Islet Autoimmunity ◽

Islet Autoantibody ◽

Clinical Type

BackgroundProgression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown.MethodsIn 341 islet autoantibody-positive children with the human leucocyte antigen (HLA) DR3/DR4-DQ8 or the HLA DR4-DQ8/DR4-DQ8 genotype from the prospective TEDDY (The Environmental Determinants of Diabetes in the Young) study, we investigated whether a genetic risk score that had previously been shown to predict islet autoimmunity is also associated with disease progression.ResultsIslet autoantibody-positive children with a genetic risk score in the lowest quartile had a slower progression from single to multiple autoantibodies (p=0.018), from single autoantibodies to diabetes (p=0.004), and by trend from multiple islet autoantibodies to diabetes (p=0.06). In a Cox proportional hazards analysis, faster progression was associated with an increased genetic risk score independently of HLA genotype (HR for progression from multiple autoantibodies to type 1 diabetes, 1.27, 95% CI 1.02 to 1.58 per unit increase), an earlier age of islet autoantibody development (HR, 0.68, 95% CI 0.58 to 0.81 per year increase in age) and female sex (HR, 1.94, 95% CI 1.28 to 2.93).ConclusionsGenetic risk scores may be used to identify islet autoantibody-positive children with high-risk HLA genotypes who have a slow rate of progression to subsequent stages of autoimmunity and type 1 diabetes.

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