Literature DB >> 29702327

Clinical and research uses of genetic risk scores in type 1 diabetes.

Seth A Sharp1, Michael N Weedon1, William A Hagopian2, Richard A Oram3.   

Abstract

Type 1 diabetes (T1D) is a chronic disease of high blood glucose caused by autoimmune destruction of pancreatic beta cells eventually resulting in severe insulin deficiency. T1D has a significant heritable risk. Genetic associations found are particularly strong in the HLA class II region but T1D is a polygenic disease associated with over 60 loci across the genome. Polygenic risk scores are one method of summing these genetic risk elements as a single continuous variable. This review discusses the clinical and research utility of genetic risk scores in T1D particularly in disease prediction and progression. We also explore creative uses of genetic risk scores in big data and the limitations of using a genetic risk score. The increase in publically available genetic data and rapid fall in costs of genotyping mean that a T1D genetic risk score (T1D GRS) is likely to prove useful for disease prediction, discrimination, investigation of unusual cohorts, and investigation of biology in large datasets where genetic data are available.
Copyright © 2018 Elsevier Ltd. All rights reserved.

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Year:  2018        PMID: 29702327      PMCID: PMC6089633          DOI: 10.1016/j.gde.2018.03.009

Source DB:  PubMed          Journal:  Curr Opin Genet Dev        ISSN: 0959-437X            Impact factor:   5.578


  55 in total

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2.  Found in Translation: A Type 1 Diabetes Genetic Risk Score Applied to Clinical Diagnosis.

Authors:  Jose C Florez
Journal:  Diabetes Care       Date:  2016-03       Impact factor: 19.112

3.  Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1 diabetes.

Authors:  Christiane Winkler; Jan Krumsiek; Florian Buettner; Christof Angermüller; Eleni Z Giannopoulou; Fabian J Theis; Anette-Gabriele Ziegler; Ezio Bonifacio
Journal:  Diabetologia       Date:  2014-09-04       Impact factor: 10.122

4.  Extreme genetic risk for type 1A diabetes.

Authors:  Theresa A Aly; Akane Ide; Mohamed M Jahromi; Jennifer M Barker; Maria S Fernando; Sunanda R Babu; Liping Yu; Dongmei Miao; Henry A Erlich; Pamela R Fain; Katherine J Barriga; Jill M Norris; Marian J Rewers; George S Eisenbarth
Journal:  Proc Natl Acad Sci U S A       Date:  2006-09-11       Impact factor: 11.205

5.  Newborn screening for HLA markers associated with IDDM: diabetes autoimmunity study in the young (DAISY).

Authors:  M Rewers; T L Bugawan; J M Norris; A Blair; B Beaty; M Hoffman; R S McDuffie; R F Hamman; G Klingensmith; G S Eisenbarth; H A Erlich
Journal:  Diabetologia       Date:  1996-07       Impact factor: 10.122

6.  The genetic interpretation of area under the ROC curve in genomic profiling.

Authors:  Naomi R Wray; Jian Yang; Michael E Goddard; Peter M Visscher
Journal:  PLoS Genet       Date:  2010-02-26       Impact factor: 5.917

7.  Improving prediction of type 1 diabetes by testing non-HLA genetic variants in addition to HLA markers.

Authors:  Andrea K Steck; Fran Dong; Randall Wong; Alexandra Fouts; Edwin Liu; Jihane Romanos; Cisca Wijmenga; Jill M Norris; Marian J Rewers
Journal:  Pediatr Diabetes       Date:  2013-11-08       Impact factor: 4.866

8.  Type 1 Diabetes Genetic Risk Score: A Novel Tool to Discriminate Monogenic and Type 1 Diabetes.

Authors:  M N Weedon; A T Hattersley; K A Patel; R A Oram; S E Flanagan; E De Franco; K Colclough; M Shepherd; S Ellard
Journal:  Diabetes       Date:  2016-04-05       Impact factor: 9.461

9.  Definition of high-risk type 1 diabetes HLA-DR and HLA-DQ types using only three single nucleotide polymorphisms.

Authors:  Cao Nguyen; Michael D Varney; Leonard C Harrison; Grant Morahan
Journal:  Diabetes       Date:  2013-02-01       Impact factor: 9.461

10.  Frequency and phenotype of type 1 diabetes in the first six decades of life: a cross-sectional, genetically stratified survival analysis from UK Biobank.

Authors:  Nicholas J Thomas; Samuel E Jones; Michael N Weedon; Beverley M Shields; Richard A Oram; Andrew T Hattersley
Journal:  Lancet Diabetes Endocrinol       Date:  2017-11-30       Impact factor: 44.867

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Authors:  Qinghong Shi; Hanxin Yao
Journal:  BMC Med Genomics       Date:  2021-05-18       Impact factor: 3.063

3.  Genetic aspects of type 1 diabetes.

Authors:  Hae Sang Lee; Jin Soon Hwang
Journal:  Ann Pediatr Endocrinol Metab       Date:  2019-09-30

4.  Parental autoimmune and autoinflammatory disorders as multiple risk factors for common neurodevelopmental disorders in offspring: a systematic review and meta-analysis.

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Journal:  Transl Psychiatry       Date:  2022-03-18       Impact factor: 7.989

5.  Application of a Blockchain Platform to Manage and Secure Personal Genomic Data: A Case Study of LifeCODE.ai in China.

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Journal:  J Med Internet Res       Date:  2019-09-10       Impact factor: 5.428

Review 6.  Epigenetic Regulation in Etiology of Type 1 Diabetes Mellitus.

Authors:  Marie Cerna
Journal:  Int J Mol Sci       Date:  2019-12-19       Impact factor: 5.923

  6 in total

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