Utility of genetic risk scores in type 1 diabetes

被引:29
作者
Luckett, Amber M. M. [1 ]
Weedon, Michael N. N. [1 ]
Hawkes, Gareth [1 ]
Leslie, R. David [2 ]
Oram, Richard A. A. [1 ,3 ]
Grant, Struan F. A. [4 ,5 ,6 ,7 ,8 ,9 ]
机构
[1] Univ Exeter, Coll Med & Hlth, Exeter, England
[2] Queen Mary Univ London, Blizard Inst, London, England
[3] Royal Devon Univ Healthcare NHS Fdn Trust, Exeter, England
[4] Childrens Hosp Philadelphia, Div Human Genet, Philadelphia, PA 19104 USA
[5] Childrens Hosp Philadelphia, Div Diabet & Endocrinol, Philadelphia, PA 19104 USA
[6] Childrens Hosp Philadelphia, Ctr Spatial & Funct Genom, Philadelphia, PA 19104 USA
[7] Univ Penn, Perelman Sch Med, Dept Genet, Philadelphia, PA 19104 USA
[8] Univ Penn, Inst Diabet Obes & Metab, Perelman Sch Med, Philadelphia, PA 19104 USA
[9] Univ Penn, Perelman Sch Med, Dept Pediat, Philadelphia, PA 19104 USA
基金
美国国家卫生研究院;
关键词
Autoimmune disorders; Diabetes; Genetic risk score; Genetics; Review; Type; 1; diabetes; GENOME-WIDE ASSOCIATION; SUSCEPTIBILITY LOCI; ISLET AUTOANTIBODIES; HLA; PREDICTION; FREQUENCY; DISCRIMINATION; ARCHITECTURE; STANDARDS; VARIANTS;
D O I
10.1007/s00125-023-05955-y
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Iterative advances in understanding of the genetics of type 1 diabetes have identified >70 genetic regions associated with risk of the disease, including strong associations across the HLA class II region that account for >50% of heritability. The increased availability of genetic data combined with the decreased costs of generating these data, have facilitated the development of polygenic scores that aggregate risk variants from associated loci into a single number: either a genetic risk score (GRS) or a polygenic risk score (PRS). PRSs incorporate the risk of many possibly correlated variants from across the genome, even if they do not reach genome-wide significance, whereas GRSs estimate the cumulative contribution of a smaller subset of genetic variants that reach genome-wide significance. Type 1 diabetes GRSs have utility in diabetes classification, aiding discrimination between type 1 diabetes, type 2 diabetes and MODY. Type 1 diabetes GRSs are also being used in newborn screening studies to identify infants at risk of future presentation of the disease. Most early studies of type 1 diabetes genetics have been conducted in European ancestry populations, but, to develop accurate GRSs across diverse ancestries, large case-control cohorts from non-European populations are still needed. The current barriers to GRS implementation within healthcare are mainly related to a lack of guidance and knowledge on integration with other biomarkers and clinical variables. Once these limitations are addressed, there is huge potential for 'test and treat' approaches to be used to tailor care for individuals with type 1 diabetes.
引用
收藏
页码:1589 / 1600
页数:12
相关论文
共 82 条
[1]   Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps [J].
Adeyemo, Adebowale ;
Balaconis, Mary K. ;
Darnes, Deanna R. ;
Fatumo, Segun ;
Granados Moreno, Palmira ;
Hodonsky, Chani J. ;
Inouye, Michael ;
Kanai, Masahiro ;
Kato, Kazuto ;
Knoppers, Bartha M. ;
Lewis, Anna C. F. ;
Martin, Alicia R. ;
McCarthy, Mark I. ;
Meyer, Michelle N. ;
Okada, Yukinori ;
Richards, J. Brent ;
Richter, Lucas ;
Ripatti, Samuli ;
Rotimi, Charles N. ;
Sanderson, Saskia C. ;
Sturm, Amy C. ;
Verdugo, Ricardo A. ;
Widen, Elisabeth ;
Willer, Cristen J. ;
Wojcik, Genevieve L. ;
Zhou, Alicia .
NATURE MEDICINE, 2021, 27 (11) :1876-1884
[2]   Diabetic Ketoacidosis at Diagnosis of Type 1 Diabetes in Colorado Children, 2010-2017 [J].
Alonso, G. Todd ;
Coakley, Alex ;
Pyle, Laura ;
Manseau, Katherine ;
Thomas, Sarah ;
Rewers, Arleta .
DIABETES CARE, 2020, 43 (01) :117-121
[3]  
Atkinson MA, 2014, LANCET, V383, P69, DOI [10.1016/S0140-6736(13)60591-7, 10.1016/S0140-6736(18)31320-5]
[4]   Two Single Nucleotide Polymorphisms Identify the Highest-Risk Diabetes HLA Genotype Potential for Rapid Screening [J].
Barker, Jennifer M. ;
Triolo, Taylor M. ;
Aly, Theresa A. ;
Baschal, Erin E. ;
Babu, Sunanda R. ;
Kretowski, Adam ;
Rewers, Marian J. ;
Eisenbarth, George S. .
DIABETES, 2008, 57 (11) :3152-3155
[5]   Clinical characteristics of children diagnosed with type 1 diabetes through intensive screening and follow-up [J].
Barker, JM ;
Goehrig, SH ;
Barriga, K ;
Hoffman, M ;
Slover, R ;
Eisenbarth, GS ;
Norris, JM ;
Klingensmith, GJ ;
Rewers, M .
DIABETES CARE, 2004, 27 (06) :1399-1404
[6]   Understanding and preventing type 1 diabetes through the unique working model of TrialNet [J].
Battaglia, Manuela ;
Anderson, Mark S. ;
Buckner, Jane H. ;
Geyer, Susan M. ;
Gottlieb, Peter A. ;
Kay, Thomas W. H. ;
Lernmark, Ake ;
Muller, Sarah ;
Pugliese, Alberto ;
Roep, Bart O. ;
Greenbaum, Carla J. ;
Peakman, Mark .
DIABETOLOGIA, 2017, 60 (11) :2139-2147
[7]   Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes: A prospective study in children [J].
Bonifacio, Ezio ;
Beyerlein, Andreas ;
Hippich, Markus ;
Winkler, Christiane ;
Vehik, Kendra ;
Weedon, Michael N. ;
Laimighofer, Michael ;
Hattersley, Andrew T. ;
Krumsiek, Jan ;
Frohnert, Brigitte I. ;
Steck, Andrea K. ;
Hagopian, William A. ;
Krischer, Jeffrey P. ;
Lernmark, Ake ;
Rewers, Marian J. ;
She, Jin-Xiong ;
Toppari, Jorma ;
Akolkar, Beena ;
Oram, Richard A. ;
Rich, Stephen S. ;
Ziegler, Anette-G. .
PLOS MEDICINE, 2018, 15 (04)
[8]  
Buzzetti R, 2022, NAT REV DIS PRIMERS, V8, DOI 10.1038/s41572-022-00390-6
[9]   Histological validation of a type 1 diabetes clinical diagnostic model for classification of diabetes [J].
Carr, A. L. J. ;
Perry, D. J. ;
Lynam, A. L. ;
Chamala, S. ;
Flaxman, C. S. ;
Sharp, S. A. ;
Ferrat, L. A. ;
Jones, A. G. ;
Beery, M. L. ;
Jacobsen, L. M. ;
Wasserfall, C. H. ;
Campbell-Thompson, M. L. ;
Kusmartseva, I. ;
Posgai, A. ;
Schatz, D. A. ;
Atkinson, M. A. ;
Brusko, T. M. ;
Richardson, S. J. ;
Shields, B. M. ;
Oram, R. A. .
DIABETIC MEDICINE, 2020, 37 (12) :2160-2168
[10]  
Chen S, 2022, bioRxiv, P2022, DOI 10.1101/2022.03.20.485034