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Genetics/Genomes/Proteomics/Metabolomics

Genetic Contribution to the Divergence in Type 1 Diabetes Risk Between Children From the General Population and Children From Affected Families

  1. Markus Hippich1,
  2. Andreas Beyerlein1,2,
  3. William A. Hagopian3,
  4. Jeffrey P. Krischer4,
  5. Kendra Vehik4,
  6. Jan Knoop1,
  7. Christiane Winker1,5,
  8. Jorma Toppari6,
  9. Åke Lernmark7,
  10. Marian J. Rewers8,
  11. Andrea K. Steck8,
  12. Jin-Xiong She9,
  13. Beena Akolkar10,
  14. Catherine C. Robertson11,
  15. Suna Onengut-Gumuscu11,
  16. Stephen S. Rich11,
  17. Ezio Bonifacio5,12⇑,
  18. Anette-G. Ziegler1,2,5⇑,
  19. the TEDDY Study Group*
  1. 1Institute of Diabetes Research, Helmholtz Zentrum München (German Research Center for Environmental Health), Munich-Neuherberg, Germany
  2. 2Forschergruppe Diabetes, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
  3. 3Pacific Northwest Research Institute, Seattle, WA
  4. 4Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL
  5. 5Forschergruppe Diabetes e.V., Helmholtz Zentrum München (German Research Center for Environmental Health), Munich-Neuherberg, Germany
  6. 6Department of Pediatrics, Turku University Hospital, and Research Centre for Integrative Physiology and Pharmacology, Institute of Biomedicine, University of Turku, Turku, Finland
  7. 7Department of Clinical Sciences, Lund University/CRC, Skåne University Hospital SUS, Malmo, Sweden
  8. 8Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, CO
  9. 9Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA
  10. 10National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD
  11. 11Center for Public Health Genomics, University of Virginia, Charlottesville, VA
  12. 12DFG Center for Regenerative Therapies Dresden, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
  1. Corresponding authors: Anette-G. Ziegler, anette-g.ziegler{at}helmholtz-muenchen.de, and Ezio Bonifacio, ezio.bonifacio{at}tu-dresden.de
    Diabetes 2019 Apr; 68(4): 847-857. https://doi.org/10.2337/db18-0882
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    • Figure 1
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      Figure 1

      Cumulative risks of islet autoantibodies and diabetes. Kaplan-Meier curves for the risk of one or more islet autoantibodies (A and B), multiple islet autoantibodies (C and D), and diabetes (E and F) in FDR children (red) and in GP children (blue), stratified into children with the HLA DR3/DR4-DQ8 (A, C, and E) or HLA DR4-DQ8/DR4-DQ8 (B, D, and F) genotypes. Shaded areas represent the 95% CI. Numbers represent children at risk. P values were calculated using log-rank tests.

    • Figure 2
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      Figure 2

      A: Distribution of non-HLA DR-DQ genetic risk scores in all 4,414 DR3/DR4-DQ8 or DR4-DQ8/DR4-DQ8 children stratified into FDR children (red) and GP children (blue). B: Distribution of non-HLA DR-DQ genetic risk scores in 317 DR3/DR4-DQ8 or DR4-DQ8/DR4-DQ8 children who developed multiple islet autoantibodies. P values were calculated using the two-sided Mann-Whitney U test.

    • Figure 3
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      Figure 3

      The modification of risk by the BTNL2 SNP rs3763305 on the development of one or more islet autoantibodies (A), multiple islet autoantibodies (B), and diabetes (C) in children with the DR3/DRB1*04:04-DQ8 or DRB1*04:04-DQ8/DRB1*04:04-DQ8 genotypes. Risks are shown for the GG genotype versus the GA or AA genotypes at rs3763305. P values were calculated using log-rank tests.

    • Figure 4
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      Figure 4

      Risk of developing islet autoantibodies and diabetes in FDR children (B, D, and F) and in GP children (A, B, and C) according to genetic susceptibility strata based on HLA DRB1*04 subtype and genetic risk score. Risks are shown for the development of one or more islet autoantibodies (A and B), multiple islet autoantibodies (C and D), and diabetes (E and F). All of the children had the DR3/DR4-DQ8 or DR4-DQ8/DR4-DQ8 genotype. Genetic susceptibility strata were defined as 1) high-risk DRB1*04 subtype (DR3/DRB1*04:01 or DRB1*04:01-DQ8/DR4 without 04:04 or 04:07) and GRS in the upper quartile (gray), 2) high-risk DRB1*04 subtype and GRS in the second quartile or lower-risk DRB1*04 subtype and GRS in the upper quartile (pink), 3) high-risk DRB1*04 subtype and GRS in the lower 50th centile or lower-risk DRB1*04 subtype and GRS in the second quartile (light blue), and 4) lower-risk DRB1*04 subtype and GRS in the lower 50th centile (green). The strata appear in this order from top to bottom in the risk tables. P values were calculated across all strata using log-rank tests.

    Tables

    • Figures
    • Table 1

      Study characteristics by first-degree relative status

      VariableFDR children (n = 423)GP children (n = 4,149)
      Males200 (47.3)2,082 (50.2)
      HLA genotype
       DR3/4-DQ8280 (66.2)2,755 (66.4)
       DR4-DQ8/DR4-DQ8143 (33.8)1,394 (33.6)
      Country
       U.S.194 (45.9)1,750 (42.2)
       Finland51 (12.1)792 (19.1)
       Germany92 (21.7)209 (5.0)
       Sweden86 (20.3)1,398 (33.7)
      First-degree relative with T1D
       None0 (0.0)4,149 (100.0)
       Mother146 (34.5)0 (0.0)
       Father180 (42.6)0 (0.0)
       Sibling79 (18.7)0 (0.0)
       Multiplex18 (4.3)0 (0.0)
      Outcome events
       One or more islet  autoantibodies85 (20.1)415 (10.0)
       Multiple islet autoantibodies69 (16.3)255 (6.1)
       First-appearing IAA51 (12.1)227 (5.5)
       First-appearing GADA46 (10.9)250 (6.0)
       Diabetes47 (11.1)145 (3.5)
      Genetic risk score available408 (96.5)4,006 (96.6)
      • Data are n (%).

    • Table 2

      Allelic enrichment of DRB1*04 subtypes in FDR children

      DR4 subtypeFDR children (alleles, n = 535)GP children (alleles, n = 5,415)P*
      DRB1*04:01329 (60.15)2,788 (51.49)<0.0001
      DRB1*04:0233 (6.03)291 (5.37)0.42
      DRB1*04:04137 (25.05)1,928 (35.60)<0.0001
      DRB1*04:0523 (4.20)226 (4.17)0.91
      DRB1*04:061 (0.18)1 (0.02)0.17
      DRB1*04:077 (1.28)153 (2.83)0.035
      DRB1*04:084 (0.73)25 (0.46)0.33
      DRB1*04:100 (0.00)1 (0.02)1
      DRB1*04:111 (0.18)1 (0.02)0.17
      DRB1*04:130 (0.00)1 (0.02)1
      • Data are n (%). Each DRB*04 allele was counted separately (once for children with the DR3/DR4-DQ8 genotype and twice for children with the DR4-DQ8/DR4-DQ8 genotype). DRB*04 subtype information was missing in 77 DR3/DR4-DQ8 and 35 DR4-DQ8/DR4-DQ8 children. Children with the nonrisk DRB1*04:03 allele were excluded a priori from the TEDDY study unless they had a first-degree relative with type 1 diabetes, and the 12 occurrences of this allele in FDR children were therefore not considered.

      • *P values were calculated using Fisher test.

    • Table 3

      Cox proportional hazards models for developing islet autoantibodies and diabetes in FDR children compared with GP children (reference)

      One or more islet autoantibodiesMultiple islet autoantibodiesDiabetes
      Model 1*Model 2*Model 1*Model 2*Model 1*Model 2*
      HR (95% CI)PHR (95% CI)PHR (95% CI)PHR (95% CI)PHR (95% CI)PHR (95% CI)P
      FDR child2.12 (1.65–2.72)<0.00011.82 (1.42–2.35)<0.00012.77 (2.09–3.68)<0.00012.26 (1.70–3.02)<0.00013.69 (2.60–5.23)<0.00012.92 (2.05–4.16)<0.0001
      DRB1*04:01/x†1.42 (1.10–1.83)0.00751.48 (1.08–2.01)0.0141.38 (0.93–2.04)0.1052
      Genetic risk score‡1.48 (1.34–1.64)<0.00011.66 (1.47–1.88)<0.00011.67 (1.42–1.96)<0.0001
      BTNL2 rs3763305 GG§1.05 (0.79–1.40)0.731.39 (0.96–2.00)0.0801.80 (1.11–2.93)0.0175
      ITGA1 rs7735139 GG§1.18 (0.86–1.63)0.301.06 (0.70–1.60)0.771.11 (0.67–1.87)0.6776
      • *Model 1 and 2 are adjusted for sex, country (reference: U.S.), and HLA genotype (reference: DR4-DQ8/DR4-DQ8).

      • †Reference: DRB1 without 04:01 or 04:01/04:04 and 04:01/04:07.

      • ‡Per unit increase.

      • §Reference: GA/AA genotype.

    • Table 4

      BTNL2 SNP genotype frequencies in relation to the development of islet autoantibodies and diabetes among TEDDY children with HLA DR3/DR4-DQ8 or DR4-DQ8/DR4-DQ8 and available genotype information

      Islet autoantibody negativeOne or more islet autoantibodiesMultiple islet autoantibodiesDiabetes
      HLA DR3/4-DQ8 (n = 3,024), BTNL2 SNP rs3763305
       GG1,839 (69.1)272 (75.3)190 (79.8)120 (82.8)
       GA823 (30.9)89 (24.7)48 (20.2)25 (17.2)
       AA1 (0.0)0 (0.0)0 (0.0)0 (0.0)
       P*0.0300.00070.0007
      HLA DR4-DQ8/DR4-DQ8 (n = 1,532), BTNL2 SNP rs3763305
       GG692 (49.7)89 (64.0)63 (73.3)36 (76.6)
       GA571 (41.0)44 (31.7)21 (24.4)10 (21.3)
       AA130 (9.3)6 (4.3)2 (2.3)1 (2.1)
       P*0.0033<0.00010.0010
      • Data are n (%).

      • *Children who remained islet autoantibody negative were compared with children who developed one or more islet autoantibodies, multiple islet autoantibodies, and diabetes using Fisher test.

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    Genetic Contribution to the Divergence in Type 1 Diabetes Risk Between Children From the General Population and Children From Affected Families
    Markus Hippich, Andreas Beyerlein, William A. Hagopian, Jeffrey P. Krischer, Kendra Vehik, Jan Knoop, Christiane Winker, Jorma Toppari, Åke Lernmark, Marian J. Rewers, Andrea K. Steck, Jin-Xiong She, Beena Akolkar, Catherine C. Robertson, Suna Onengut-Gumuscu, Stephen S. Rich, Ezio Bonifacio, Anette-G. Ziegler, the TEDDY Study Group
    Diabetes Apr 2019, 68 (4) 847-857; DOI: 10.2337/db18-0882

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    Genetic Contribution to the Divergence in Type 1 Diabetes Risk Between Children From the General Population and Children From Affected Families
    Markus Hippich, Andreas Beyerlein, William A. Hagopian, Jeffrey P. Krischer, Kendra Vehik, Jan Knoop, Christiane Winker, Jorma Toppari, Åke Lernmark, Marian J. Rewers, Andrea K. Steck, Jin-Xiong She, Beena Akolkar, Catherine C. Robertson, Suna Onengut-Gumuscu, Stephen S. Rich, Ezio Bonifacio, Anette-G. Ziegler, the TEDDY Study Group
    Diabetes Apr 2019, 68 (4) 847-857; DOI: 10.2337/db18-0882
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