Combining polygenic risk scores and human leukocyte antigen variants for personalized risk assessment of type 1 diabetes in the Taiwanese population

Aims To analyse the genome‐wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic effects on T1D risk and age at diagnosis in the Taiwanese population. Materials and Methods We selected 610 patients with T1D and 2511 health...

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Published inDiabetes, obesity & metabolism Vol. 25; no. 10; pp. 2928 - 2936
Main Authors Liao, Wen‐Ling, Huang, Yu‐Nan, Chang, Ya‐Wen, Liu, Ting‐Yuan, Lu, Hsing‐Fang, Tiao, Zih‐Yu, Su, Pen‐Hua, Wang, Chung‐Hsing, Tsai, Fuu‐Jen
Format Journal Article
LanguageEnglish
Published Oxford, UK Blackwell Publishing Ltd 01.10.2023
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Abstract Aims To analyse the genome‐wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic effects on T1D risk and age at diagnosis in the Taiwanese population. Materials and Methods We selected 610 patients with T1D and 2511 healthy individuals from an electronic medical record database of more than 300 000 individuals with genetic information, analysed their GWAS data, and developed a polygenic risk score (PRS). Results The PRS, based on 149 selected single‐nucleotide polymorphisms, could effectively predict T1D risk. A PRS increase was associated with increased T1D risk (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.72‐2.55). Moreover, a 1‐unit increase in standardized T1D PRS decreased the age at diagnosis by 0.74 years. Combined PRS and human leukocyte antigen (HLA) DQA1*03:02–DQA1*05:01 genotypes could accurately predict T1D risk. In multivariable models, HLA variants and PRS were independent risk factors for T1D risk (OR 3.76 [95% CI 1.54‐9.16] and 1.71 [95% CI 1.37‐2.13] for HLA DQA1*03:02–DQA1*05:01 and PRS, respectively). In a limited study population of those aged ≤18 years, PRS remained significantly associated with T1D risk. The association between T1D PRS and age at diagnosis was more obvious among males and patients aged ≤18 years. Conclusions Polygenic risk score and HLA variations enable personalized risk estimates, enhance newborn screening efficiency for ketoacidosis prevention, and addresses the gap in data on T1D prediction in isolated Asian populations.
AbstractList To analyse the genome-wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic effects on T1D risk and age at diagnosis in the Taiwanese population.AIMSTo analyse the genome-wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic effects on T1D risk and age at diagnosis in the Taiwanese population.We selected 610 patients with T1D and 2511 healthy individuals from an electronic medical record database of more than 300 000 individuals with genetic information, analysed their GWAS data, and developed a polygenic risk score (PRS).MATERIALS AND METHODSWe selected 610 patients with T1D and 2511 healthy individuals from an electronic medical record database of more than 300 000 individuals with genetic information, analysed their GWAS data, and developed a polygenic risk score (PRS).The PRS, based on 149 selected single-nucleotide polymorphisms, could effectively predict T1D risk. A PRS increase was associated with increased T1D risk (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.72-2.55). Moreover, a 1-unit increase in standardized T1D PRS decreased the age at diagnosis by 0.74 years. Combined PRS and human leukocyte antigen (HLA) DQA1*03:02-DQA1*05:01 genotypes could accurately predict T1D risk. In multivariable models, HLA variants and PRS were independent risk factors for T1D risk (OR 3.76 [95% CI 1.54-9.16] and 1.71 [95% CI 1.37-2.13] for HLA DQA1*03:02-DQA1*05:01 and PRS, respectively). In a limited study population of those aged ≤18 years, PRS remained significantly associated with T1D risk. The association between T1D PRS and age at diagnosis was more obvious among males and patients aged ≤18 years.RESULTSThe PRS, based on 149 selected single-nucleotide polymorphisms, could effectively predict T1D risk. A PRS increase was associated with increased T1D risk (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.72-2.55). Moreover, a 1-unit increase in standardized T1D PRS decreased the age at diagnosis by 0.74 years. Combined PRS and human leukocyte antigen (HLA) DQA1*03:02-DQA1*05:01 genotypes could accurately predict T1D risk. In multivariable models, HLA variants and PRS were independent risk factors for T1D risk (OR 3.76 [95% CI 1.54-9.16] and 1.71 [95% CI 1.37-2.13] for HLA DQA1*03:02-DQA1*05:01 and PRS, respectively). In a limited study population of those aged ≤18 years, PRS remained significantly associated with T1D risk. The association between T1D PRS and age at diagnosis was more obvious among males and patients aged ≤18 years.Polygenic risk score and HLA variations enable personalized risk estimates, enhance newborn screening efficiency for ketoacidosis prevention, and addresses the gap in data on T1D prediction in isolated Asian populations.CONCLUSIONSPolygenic risk score and HLA variations enable personalized risk estimates, enhance newborn screening efficiency for ketoacidosis prevention, and addresses the gap in data on T1D prediction in isolated Asian populations.
AimsTo analyse the genome‐wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic effects on T1D risk and age at diagnosis in the Taiwanese population.Materials and MethodsWe selected 610 patients with T1D and 2511 healthy individuals from an electronic medical record database of more than 300 000 individuals with genetic information, analysed their GWAS data, and developed a polygenic risk score (PRS).ResultsThe PRS, based on 149 selected single‐nucleotide polymorphisms, could effectively predict T1D risk. A PRS increase was associated with increased T1D risk (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.72‐2.55). Moreover, a 1‐unit increase in standardized T1D PRS decreased the age at diagnosis by 0.74 years. Combined PRS and human leukocyte antigen (HLA) DQA1*03:02–DQA1*05:01 genotypes could accurately predict T1D risk. In multivariable models, HLA variants and PRS were independent risk factors for T1D risk (OR 3.76 [95% CI 1.54‐9.16] and 1.71 [95% CI 1.37‐2.13] for HLA DQA1*03:02–DQA1*05:01 and PRS, respectively). In a limited study population of those aged ≤18 years, PRS remained significantly associated with T1D risk. The association between T1D PRS and age at diagnosis was more obvious among males and patients aged ≤18 years.ConclusionsPolygenic risk score and HLA variations enable personalized risk estimates, enhance newborn screening efficiency for ketoacidosis prevention, and addresses the gap in data on T1D prediction in isolated Asian populations.
Aims To analyse the genome‐wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic effects on T1D risk and age at diagnosis in the Taiwanese population. Materials and Methods We selected 610 patients with T1D and 2511 healthy individuals from an electronic medical record database of more than 300 000 individuals with genetic information, analysed their GWAS data, and developed a polygenic risk score (PRS). Results The PRS, based on 149 selected single‐nucleotide polymorphisms, could effectively predict T1D risk. A PRS increase was associated with increased T1D risk (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.72‐2.55). Moreover, a 1‐unit increase in standardized T1D PRS decreased the age at diagnosis by 0.74 years. Combined PRS and human leukocyte antigen (HLA) DQA1*03:02–DQA1*05:01 genotypes could accurately predict T1D risk. In multivariable models, HLA variants and PRS were independent risk factors for T1D risk (OR 3.76 [95% CI 1.54‐9.16] and 1.71 [95% CI 1.37‐2.13] for HLA DQA1*03:02–DQA1*05:01 and PRS, respectively). In a limited study population of those aged ≤18 years, PRS remained significantly associated with T1D risk. The association between T1D PRS and age at diagnosis was more obvious among males and patients aged ≤18 years. Conclusions Polygenic risk score and HLA variations enable personalized risk estimates, enhance newborn screening efficiency for ketoacidosis prevention, and addresses the gap in data on T1D prediction in isolated Asian populations.
To analyse the genome-wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic effects on T1D risk and age at diagnosis in the Taiwanese population. We selected 610 patients with T1D and 2511 healthy individuals from an electronic medical record database of more than 300 000 individuals with genetic information, analysed their GWAS data, and developed a polygenic risk score (PRS). The PRS, based on 149 selected single-nucleotide polymorphisms, could effectively predict T1D risk. A PRS increase was associated with increased T1D risk (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.72-2.55). Moreover, a 1-unit increase in standardized T1D PRS decreased the age at diagnosis by 0.74 years. Combined PRS and human leukocyte antigen (HLA) DQA1*03:02-DQA1*05:01 genotypes could accurately predict T1D risk. In multivariable models, HLA variants and PRS were independent risk factors for T1D risk (OR 3.76 [95% CI 1.54-9.16] and 1.71 [95% CI 1.37-2.13] for HLA DQA1*03:02-DQA1*05:01 and PRS, respectively). In a limited study population of those aged ≤18 years, PRS remained significantly associated with T1D risk. The association between T1D PRS and age at diagnosis was more obvious among males and patients aged ≤18 years. Polygenic risk score and HLA variations enable personalized risk estimates, enhance newborn screening efficiency for ketoacidosis prevention, and addresses the gap in data on T1D prediction in isolated Asian populations.
Author Huang, Yu‐Nan
Liu, Ting‐Yuan
Tsai, Fuu‐Jen
Liao, Wen‐Ling
Lu, Hsing‐Fang
Su, Pen‐Hua
Chang, Ya‐Wen
Tiao, Zih‐Yu
Wang, Chung‐Hsing
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Cites_doi 10.1371/journal.pgen.1002293
10.1046/j.1464‐5491.2001.00400.x
10.1056/NEJMoa1610187
10.3389/fendo.2022.842673
10.1038/ng.3245
10.1186/1471‐2350‐8‐54
10.1196/annals.1375.046
10.1016/0198‐8859(95)00108‐5
10.34172/hpp.2020.18
10.1093/gigascience/giz082
10.1210/er.2019-00088
10.1038/nrdp.2017.16
10.1016/S0140-6736(13)60591-7
10.1002/dmrr.970
10.2337/diacare.18.11.1483
10.1007/s11892‐011‐0223‐x
10.1038/s41525‐021‐00178‐9
10.1093/bfgp/elu022
10.1038/nature05911
10.1038/s41576-019-0127-1
10.1038/s43586-021-00056-9
10.1038/s41588-022-01054-7
10.1016/S0140-6736(16)30582-7
10.1038/ng.3330
10.1038/s41598-020-75690-6
10.1016/0198‐8859(93)90526‐7
10.1038/s41588‐021‐00880‐5
10.1038/s41576-018-0018-x
10.1186/s13742‐015‐0047‐8
10.1038/nrendo.2015.8
10.1111/pedi.12645
10.37796/2211‐8039.1302
10.1530/eje.1.02035
10.1016/S2213-8587(22)00159-0
10.1038/s41591-020-0930-4
10.2337/dc18-2023
10.1038/ncomms15927
10.1038/ng.2354
10.1038/ng.381
10.1038/ng2068
10.1172/JCI142242
10.1016/j.ajhg.2022.09.010
10.1038/nature06406
10.1038/995
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References 2007; 39
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2005; 153
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2016; 387
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2021; 1
2017; 376
2011; 7
2018; 19
2015; 47
2013; 15
2021; 53
1998; 19
2019; 40
2021; 11
1993; 38
2019; 42
2019; 20
1995; 44
2007; 450
2007; 8
2022; 13
2020; 26
2014; 13
2021; 131
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2022; 54
2001; 18
2006; 1079
2022; 109
2014; 383
2012; 44
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References_xml – volume: 11
  start-page: 533
  issue: 6
  year: 2011
  end-page: 542
  article-title: Genetics of the HLA region in the prediction of type 1 diabetes
  publication-title: Curr Diab Rep
– volume: 387
  start-page: 387
  year: 2016
  end-page: 2339
  article-title: Genetic risk factors for type 1 diabetes
  publication-title: Lancet
– volume: 44
  start-page: 955
  issue: 8
  year: 2012
  end-page: 959
  article-title: Fast and accurate genotype imputation in genome‐wide association studies through pre‐phasing
  publication-title: Nat Genet
– volume: 6
  start-page: 10
  issue: 1
  year: 2021
  article-title: Genetic profiles of 103,106 individuals in the Taiwan Biobank provide insights into the health and history of Han Chinese
  publication-title: NPJ Genom Med
– volume: 20
  start-page: 467
  issue: 8
  year: 2019
  end-page: 484
  article-title: Benefits and limitations of genome‐wide association studies
  publication-title: Nat Rev Genet
– volume: 11
  start-page: 289
  issue: 5
  year: 2015
  end-page: 297
  article-title: Combination immunotherapies for type 1 diabetes mellitus.
  publication-title: Endocrinology
– volume: 376
  start-page: 1419
  issue: 15
  year: 2017
  end-page: 1429
  article-title: Incidence trends of type 1 and type 2 diabetes among youths, 2002‐2012
  publication-title: N Engl J Med
– volume: 11
  start-page: 57
  issue: 4
  year: 2021
  end-page: 65
  article-title: Comparison of multiple imputation algorithms and verification using whole‐genome sequencing in the CMUH genetic biobank
  publication-title: Biomedicine (Taipei)
– volume: 42
  start-page: 1414
  issue: 8
  year: 2019
  end-page: 1421
  article-title: Identification of novel T1D risk loci and their association with age and islet function at diagnosis in autoantibody‐positive T1D individuals: based on a two‐stage genome‐wide association study
  publication-title: Diabetes Care
– volume: 3
  year: 2017
  article-title: Type 1 diabetes mellitus
  publication-title: Nat Rev Dis Primers
– volume: 47
  start-page: 381
  issue: 4
  year: 2015
  end-page: 386
  article-title: Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers
  publication-title: Nat Genet
– volume: 10
  issue: 1
  year: 2020
  article-title: Novel genetic risk factors influence progression of islet autoimmunity to type 1 diabetes
  publication-title: Sci Rep
– volume: 4
  start-page: 7
  year: 2015
  article-title: Second‐generation PLINK: rising to the challenge of larger and richer datasets
  publication-title: GigaScience
– volume: 1079
  start-page: 305
  year: 2006
  end-page: 309
  article-title: Is HLA class II profile relevant for the study of large‐scale differentially expressed genes in type 1 diabetes mellitus patients?
  publication-title: Ann N Y Acad Sci
– volume: 8
  year: 2017
  article-title: Enrichment of low‐frequency functional variants revealed by whole‐genome sequencing of multiple isolated European populations
  publication-title: Nat Commun
– volume: 10
  start-page: 597
  issue: 8
  year: 2022
  end-page: 608
  article-title: Type 1 diabetes in diverse ancestries and the use of genetic risk scores
  publication-title: Lancet Diabetes Endocrinol
– volume: 44
  start-page: 210
  issue: 4
  year: 1995
  end-page: 219
  article-title: HLA‐encoded susceptibility to insulin‐dependent diabetes mellitus is determined by DR and DQ genes as well as their linkage disequilibria in a Chinese population
  publication-title: Hum Immunol
– volume: 40
  start-page: 1500
  issue: 6
  year: 2019
  end-page: 1520
  article-title: Genetic risk scores for diabetes diagnosis and precision medicine
  publication-title: Endocr Rev
– volume: 10
  start-page: 98
  issue: 2
  year: 2020
  end-page: 115
  article-title: Prevalence and incidence of type 1 diabetes in the world: a systematic review and meta‐analysis
  publication-title: Health Promot Perspect
– volume: 53
  start-page: 962
  issue: 7
  year: 2021
  end-page: 971
  article-title: Fine‐mapping, trans‐ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes
  publication-title: Nat Genet
– volume: 25
  start-page: 299
  issue: 4
  year: 2009
  end-page: 301
  article-title: New prospects for immunotherapy at diagnosis of type 1 diabetes
  publication-title: Diabetes Metab Res Rev
– volume: 153
  start-page: 895
  issue: 6
  year: 2005
  end-page: 899
  article-title: Sex‐specific association of PTPN22 1858T with type 1 diabetes but not with Hashimoto's thyroiditis or Addison's disease in the German population
  publication-title: Eur J Endocrinol
– volume: 7
  issue: 9
  year: 2011
  article-title: A genome‐wide meta‐analysis of six type 1 diabetes cohorts identifies multiple associated loci
  publication-title: PLoS Genet
– volume: 15
  start-page: 108
  issue: 2
  year: 2013
  end-page: 115
  article-title: Investigation the role of gender on the HLA‐DRB1 and DQB1 association with type 1 diabetes mellitus in Iranian patients
  publication-title: Cell J Summer
– volume: 18
  start-page: 1483
  issue: 11
  year: 1995
  end-page: 1486
  article-title: Transcomplementation of HLA DQA1‐DQB1 in DR3/DR4 and DR3/DR9 heterozygotes and IDDM in Taiwanese families
  publication-title: Diabetes Care
– volume: 19
  start-page: 581
  issue: 9
  year: 2018
  end-page: 590
  article-title: The personal and clinical utility of polygenic risk scores
  publication-title: Nat Rev Genet
– volume: 450
  start-page: 887
  issue: 7171
  year: 2007
  end-page: 892
  article-title: Localization of type 1 diabetes susceptibility to the MHC class I genes HLA‐B and HLA‐A
  publication-title: Nature
– volume: 109
  start-page: 1998
  issue: 11
  year: 2022
  end-page: 2008
  article-title: The construction of cross‐population polygenic risk scores using transfer learning
  publication-title: Am J Hum Genet
– volume: 1
  year: 2021
  article-title: Genome‐wide association studies
  publication-title: Nature Reviews Methods Primers
– volume: 19
  start-page: 699
  issue: 4
  year: 2018
  end-page: 706
  article-title: Comprehensive human leukocyte antigen genotyping of patients with type 1 diabetes mellitus in Taiwan
  publication-title: Pediatr Diabetes
– volume: 447
  start-page: 661
  issue: 7145
  year: 2007
  end-page: 678
  article-title: Genome‐wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
  publication-title: Nature
– volume: 41
  start-page: 703
  issue: 6
  year: 2009
  end-page: 707
  article-title: Genome‐wide association study and meta‐analysis find that over 40 loci affect risk of type 1 diabetes
  publication-title: Nat Genet
– volume: 8
  start-page: 54
  issue: 1
  year: 2007
  article-title: Susceptibility to type 1 diabetes conferred by the PTPN22 C1858T polymorphism in the Spanish population
  publication-title: BMC Med Genet
– volume: 38
  start-page: 105
  issue: 2
  year: 1993
  end-page: 114
  article-title: Association of insulin‐dependent diabetes mellitus in Taiwan with HLA class II DQB1 and DRB1 alleles
  publication-title: Hum Immunol
– volume: 19
  start-page: 301
  issue: 3
  year: 1998
  end-page: 302
  article-title: A male‐female bias in type 1 diabetes and linkage to chromosome Xp in MHC HLA‐DR3‐positive patients
  publication-title: Nat Genet
– volume: 13
  start-page: 371
  issue: 5
  year: 2014
  end-page: 377
  article-title: Using population isolates in genetic association studies
  publication-title: Brief Funct Genomics
– volume: 131
  issue: 8
  year: 2021
  article-title: Type 1 diabetes mellitus: much progress, many opportunities
  publication-title: J Clin Invest
– volume: 47
  start-page: 839
  issue: 7
  year: 2015
  end-page: 846
  article-title: Statistical colocalization of genetic risk variants for related autoimmune diseases in the context of common controls
  publication-title: Nat Genet
– volume: 18
  start-page: 22
  issue: 1
  year: 2001
  end-page: 28
  article-title: HLA typing and immunological characterization of young‐onset diabetes mellitus in a Hong Kong Chinese population
  publication-title: Diabet Med
– volume: 8
  issue: 7
  year: 2019
  article-title: PRSice‐2: polygenic risk score software for biobank‐scale data
  publication-title: GigaScience
– volume: 39
  start-page: 857
  issue: 7
  year: 2007
  end-page: 864
  article-title: Robust associations of four new chromosome regions from genome‐wide analyses of type 1 diabetes
  publication-title: Nat Genet
– volume: 54
  start-page: 573
  issue: 5
  year: 2022
  end-page: 580
  article-title: Improving polygenic prediction in ancestrally diverse populations
  publication-title: Nat Genet
– volume: 383
  start-page: 69
  issue: 9911
  year: 2014
  end-page: 82
  article-title: Type 1 diabetes
  publication-title: Lancet
– volume: 13
  year: 2022
  article-title: Analysis of HLA variants and Graves' disease and its comorbidities using a high resolution imputation system to examine electronic medical health records
  publication-title: Front Endocrinol
– volume: 26
  start-page: 1247
  issue: 8
  year: 2020
  end-page: 1255
  article-title: A combined risk score enhances prediction of type 1 diabetes among susceptible children
  publication-title: Nat Med
– ident: e_1_2_8_14_1
  doi: 10.1371/journal.pgen.1002293
– ident: e_1_2_8_21_1
  doi: 10.1046/j.1464‐5491.2001.00400.x
– ident: e_1_2_8_7_1
  doi: 10.1056/NEJMoa1610187
– ident: e_1_2_8_27_1
  doi: 10.3389/fendo.2022.842673
– ident: e_1_2_8_9_1
  doi: 10.1038/ng.3245
– ident: e_1_2_8_36_1
  doi: 10.1186/1471‐2350‐8‐54
– ident: e_1_2_8_38_1
  doi: 10.1196/annals.1375.046
– ident: e_1_2_8_41_1
  doi: 10.1016/0198‐8859(95)00108‐5
– ident: e_1_2_8_8_1
  doi: 10.34172/hpp.2020.18
– ident: e_1_2_8_32_1
  doi: 10.1093/gigascience/giz082
– ident: e_1_2_8_26_1
  doi: 10.1210/er.2019-00088
– ident: e_1_2_8_2_1
  doi: 10.1038/nrdp.2017.16
– ident: e_1_2_8_3_1
  doi: 10.1016/S0140-6736(13)60591-7
– ident: e_1_2_8_6_1
  doi: 10.1002/dmrr.970
– ident: e_1_2_8_40_1
  doi: 10.2337/diacare.18.11.1483
– ident: e_1_2_8_39_1
  doi: 10.1007/s11892‐011‐0223‐x
– ident: e_1_2_8_30_1
  doi: 10.1038/s41525‐021‐00178‐9
– ident: e_1_2_8_43_1
  doi: 10.1093/bfgp/elu022
– ident: e_1_2_8_13_1
  doi: 10.1038/nature05911
– ident: e_1_2_8_19_1
  doi: 10.1038/s41576-019-0127-1
– ident: e_1_2_8_20_1
  doi: 10.1038/s43586-021-00056-9
– ident: e_1_2_8_46_1
  doi: 10.1038/s41588-022-01054-7
– ident: e_1_2_8_11_1
  doi: 10.1016/S0140-6736(16)30582-7
– ident: e_1_2_8_15_1
  doi: 10.1038/ng.3330
– ident: e_1_2_8_33_1
  doi: 10.1038/s41598-020-75690-6
– ident: e_1_2_8_42_1
  doi: 10.1016/0198‐8859(93)90526‐7
– volume: 15
  start-page: 108
  issue: 2
  year: 2013
  ident: e_1_2_8_34_1
  article-title: Investigation the role of gender on the HLA‐DRB1 and DQB1 association with type 1 diabetes mellitus in Iranian patients
  publication-title: Cell J Summer
– ident: e_1_2_8_16_1
  doi: 10.1038/s41588‐021‐00880‐5
– ident: e_1_2_8_23_1
  doi: 10.1038/s41576-018-0018-x
– ident: e_1_2_8_31_1
  doi: 10.1186/s13742‐015‐0047‐8
– ident: e_1_2_8_4_1
  doi: 10.1038/nrendo.2015.8
– ident: e_1_2_8_22_1
  doi: 10.1111/pedi.12645
– ident: e_1_2_8_28_1
  doi: 10.37796/2211‐8039.1302
– ident: e_1_2_8_37_1
  doi: 10.1530/eje.1.02035
– ident: e_1_2_8_25_1
  doi: 10.1016/S2213-8587(22)00159-0
– ident: e_1_2_8_24_1
  doi: 10.1038/s41591-020-0930-4
– ident: e_1_2_8_17_1
  doi: 10.2337/dc18-2023
– ident: e_1_2_8_44_1
  doi: 10.1038/ncomms15927
– ident: e_1_2_8_29_1
  doi: 10.1038/ng.2354
– ident: e_1_2_8_10_1
  doi: 10.1038/ng.381
– ident: e_1_2_8_12_1
  doi: 10.1038/ng2068
– ident: e_1_2_8_5_1
  doi: 10.1172/JCI142242
– ident: e_1_2_8_45_1
  doi: 10.1016/j.ajhg.2022.09.010
– ident: e_1_2_8_18_1
  doi: 10.1038/nature06406
– ident: e_1_2_8_35_1
  doi: 10.1038/995
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Snippet Aims To analyse the genome‐wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic...
To analyse the genome-wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic...
AimsTo analyse the genome‐wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic...
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SubjectTerms Age
Antigens
clinical event
Diabetes
Diabetes mellitus (insulin dependent)
Diagnosis
DQA1 protein
electronic medical record
Electronic medical records
Genetic analysis
Genomes
genome‐wide association studies
Histocompatibility antigen HLA
human leukocyte antigen
Ketoacidosis
Leukocytes
Medical screening
polygenic risk scores
Population studies
Risk assessment
Risk factors
type 1 diabetes
Title Combining polygenic risk scores and human leukocyte antigen variants for personalized risk assessment of type 1 diabetes in the Taiwanese population
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fdom.15187
https://www.ncbi.nlm.nih.gov/pubmed/37455666
https://www.proquest.com/docview/2860207417
https://www.proquest.com/docview/2838645203
Volume 25
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