Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Tytuł pozycji:

Development and Standardization of an Improved Type 1 Diabetes Genetic Risk Score for Use in Newborn Screening and Incident Diagnosis.

Tytuł :
Development and Standardization of an Improved Type 1 Diabetes Genetic Risk Score for Use in Newborn Screening and Incident Diagnosis.
Autorzy :
Sharp SA; Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.
Rich SS; Center for Public Health Genomics, University of Virginia, Charlottesville, VA.
Wood AR; Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.
Jones SE; Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.
Beaumont RN; Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.
Harrison JW; Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.
Schneider DA; Pacific Northwest Diabetes Research Institute, Seattle, WA.; Department of Medicine, University of Washington, Seattle, WA.
Locke JM; Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.
Tyrrell J; Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.
Weedon MN; Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.
Hagopian WA; Pacific Northwest Diabetes Research Institute, Seattle, WA .
Oram RA; Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K. .; Academic Renal Unit, Royal Devon and Exeter NHS Foundation Trust, Exeter, U.K.
Pokaż więcej
Źródło :
Diabetes Care [Diabetes Care] 2019 Feb; Vol. 42 (2), pp. 200-207.
Typ publikacji :
Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Validation Study
Język :
English
Journal Info :
Publisher: American Diabetes Association Country of Publication: United States NLM ID: 7805975 Publication Model: Print Cited Medium: Internet ISSN: 1935-5548 (Electronic) Linking ISSN: 01495992 NLM ISO Abbreviation: Diabetes Care
Imprint Name(s) :
Publication: Alexandria Va : American Diabetes Association
Original Publication: New York, American Diabetes Assn.
MeSH Terms :
Genetic Testing*/methods
Genetic Testing*/standards
Diabetes Mellitus, Type 1/*diagnosis
Diabetes Mellitus, Type 1/*genetics
Neonatal Screening/*methods
Neonatal Screening/*standards
Alleles ; Case-Control Studies ; Diabetes Mellitus, Type 1/epidemiology ; Female ; Genetic Predisposition to Disease ; HLA Antigens/genetics ; Haplotypes ; Humans ; Incidence ; Infant, Newborn ; Male ; Polymorphism, Single Nucleotide ; Quality Improvement ; Reference Standards ; Research Design/standards ; Risk Factors ; United Kingdom
Grant Information :
T32 DK007247 United States DK NIDDK NIH HHS; U01 DK063829 United States DK NIDDK NIH HHS; R01 DK096926 United States DK NIDDK NIH HHS; United Kingdom WT_ Wellcome Trust; P30 DK017047 United States DK NIDDK NIH HHS; WT097835MF United Kingdom WT_ Wellcome Trust; MC_PC_15047 United Kingdom MRC_ Medical Research Council
Substance Nomenclature :
0 (HLA Antigens)
Entry Date(s) :
Date Created: 20190119 Date Completed: 20190724 Latest Revision: 20200202
Update Code :
20200202
DOI :
10.2337/dc18-1785
PMID :
30655379
Czasopismo naukowe
Objective: Previously generated genetic risk scores (GRSs) for type 1 diabetes (T1D) have not captured all known information at non-HLA loci or, particularly, at HLA risk loci. We aimed to more completely incorporate HLA alleles, their interactions, and recently discovered non-HLA loci into an improved T1D GRS (termed the "T1D GRS2") to better discriminate diabetes subtypes and to predict T1D in newborn screening studies.
Research Design and Methods: In 6,481 case and 9,247 control subjects from the Type 1 Diabetes Genetics Consortium, we analyzed variants associated with T1D both in the HLA region and across the genome. We modeled interactions between variants marking strongly associated HLA haplotypes and generated odds ratios to create the improved GRS, the T1D GRS2. We validated our findings in UK Biobank. We assessed the impact of the T1D GRS2 in newborn screening and diabetes classification and sought to provide a framework for comparison with previous scores.
Results: The T1D GRS2 used 67 single nucleotide polymorphisms (SNPs) and accounted for interactions between 18 HLA DR-DQ haplotype combinations. The T1D GRS2 was highly discriminative for all T1D (area under the curve [AUC] 0.92; P < 0.0001 vs. older scores) and even more discriminative for early-onset T1D (AUC 0.96). In simulated newborn screening, the T1D GRS2 was nearly twice as efficient as HLA genotyping alone and 50% better than current genetic scores in general population T1D prediction.
Conclusions: An improved T1D GRS, the T1D GRS2, is highly useful for classifying adult incident diabetes type and improving newborn screening. Given the cost-effectiveness of SNP genotyping, this approach has great clinical and research potential in T1D.
(© 2019 by the American Diabetes Association.)

Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies