Improved Genetic Risk Scoring Algorithm ( GRS2 ’) for Type 1 Diabetes Prediction

2022 ◽  
Author(s):  
Hui‐Qi Qu ◽  
Jingchun Qu ◽  
Joseph Glessner ◽  
Yichuan Liu ◽  
Frank Mentch ◽  
...  
2017 ◽  
Vol 17 (12) ◽  
Author(s):  
Maria J. Redondo ◽  
Richard A. Oram ◽  
Andrea K. Steck

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 209-LB ◽  
Author(s):  
JORDAN RUSSELL ◽  
LUIZ ROESCH ◽  
MARK A. ATKINSON ◽  
DESMOND SCHATZ ◽  
ERIC W. TRIPLETT ◽  
...  

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1535-P
Author(s):  
RACHEL G. MILLER ◽  
TINA COSTACOU ◽  
SUNA ONENGUT-GUMUSCU ◽  
WEI-MIN CHEN ◽  
STEPHEN S. RICH ◽  
...  

Author(s):  
Melanie R Shapiro ◽  
Puchong Thirawatananond ◽  
Leeana Peters ◽  
Robert C Sharp ◽  
Similoluwa Ogundare ◽  
...  

2011 ◽  
Vol 412 (23-24) ◽  
pp. 2128-2131 ◽  
Author(s):  
Jeffrey L. Mahon ◽  
Craig A. Beam ◽  
Santica M. Marcovina ◽  
David C. Boulware ◽  
Jerry P. Palmer ◽  
...  

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 243-OR
Author(s):  
LAURIC A. FERRAT ◽  
ANDREA STECK ◽  
HEMANG M. PARIKH ◽  
LU YOU ◽  
SUNA ONENGUT-GUMUSCU ◽  
...  

Author(s):  
German Tapia ◽  
Tommi Suvitaival ◽  
Linda Ahonen ◽  
Nicolai A Lund-Blix ◽  
Pål R Njølstad ◽  
...  

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.


2018 ◽  
Vol 56 (9) ◽  
pp. 602-605 ◽  
Author(s):  
Andreas Beyerlein ◽  
Ezio Bonifacio ◽  
Kendra Vehik ◽  
Markus Hippich ◽  
Christiane Winkler ◽  
...  

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.


Diabetes Care ◽  
2021 ◽  
pp. dc202388
Author(s):  
Ionut Bebu ◽  
Sareh Keshavarzi ◽  
Xiaoyu Gao ◽  
Barbara H. Braffett ◽  
Angelo J. Canty ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document