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Genetics/Genomes/Proteomics/Metabolomics

Epigenome-Wide Association Study of Incident Type 2 Diabetes in a British Population: EPIC-Norfolk Study

  1. Alexia Cardona1,2⇑,
  2. Felix R. Day1,
  3. John R.B. Perry1,
  4. Marie Loh3,4,5,
  5. Audrey Y. Chu6,
  6. Benjamin Lehne3,
  7. Dirk S. Paul7,
  8. Luca A. Lotta1,
  9. Isobel D. Stewart1,
  10. Nicola D. Kerrison1,
  11. Robert A. Scott1,
  12. Kay-Tee Khaw8,
  13. Nita G. Forouhi1,
  14. Claudia Langenberg1,
  15. Chunyu Liu6,9,
  16. Michael M. Mendelson6,9,10,
  17. Daniel Levy6,
  18. Stephan Beck11,
  19. R. David Leslie12,
  20. Josée Dupuis9,
  21. James B. Meigs13,14,15,
  22. Jaspal S. Kooner16,17,18,19,
  23. Jussi Pihlajamäki20,21,
  24. Allan Vaag22,
  25. Alexander Perfilyev23,
  26. Charlotte Ling23,
  27. Marie-France Hivert24,25,
  28. John C. Chambers3,16,17,18,26,
  29. Nicholas J. Wareham1 and
  30. Ken K. Ong1⇑
  1. 1MRC Epidemiology Unit, Institute of Metabolic Science, School of Clinical Medicine, University of Cambridge, Cambridge, U.K.
  2. 2Department of Genetics, University of Cambridge, Cambridge, U.K.
  3. 3Department of Epidemiology and Biostatistics, Imperial College London, London, U.K.
  4. 4Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research, Singapore
  5. 5Department of Biochemistry, National University of Singapore, Singapore
  6. 6Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
  7. 7MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, U.K.
  8. 8Department of Public Health and Primary Care, University of Cambridge, Cambridge, U.K.
  9. 9Department of Biostatistics, School of Public Health, Boston University, Boston, MA
  10. 10Department of Cardiology, Boston Children's Hospital, Boston, MA
  11. 11Medical Genomics, UCL Cancer Institute, University College London, London, U.K.
  12. 12The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, U.K.
  13. 13Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
  14. 14Harvard Medical School, Boston, MA
  15. 15Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, MA
  16. 16Department of Cardiology, Ealing Hospital, Middlesex, U.K.
  17. 17Imperial College Healthcare NHS Trust, London, U.K.
  18. 18MRC-PHE Centre for Environment and Health, Imperial College London, London, U.K.
  19. 19National Heart and Lung Institute, Imperial College London, London, U.K.
  20. 20Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Joensuu, Finland
  21. 21Clinical Nutrition and Obesity Center, Kuopio University Hospital, Kuopio, Finland
  22. 22Cardiovascular and Metabolic Disease Translational Medicine Unit, Early Clinical Development, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
  23. 23Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Scania University Hospital, Malmö, Sweden
  24. 24Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA
  25. 25Massachusetts General Hospital, Boston, MA
  26. 26Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
  1. Corresponding authors: Alexia Cardona, alexia.cardona{at}mrc-epid.cam.ac.uk, and Ken K. Ong, ken.ong{at}mrc-epid.cam.ac.uk
Diabetes 2019 Dec; 68(12): 2315-2326. https://doi.org/10.2337/db18-0290
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    Figure 1

    Predicted causal effects of DNAm on T2DM. The scatterplot shows the genetic-predicted effects of DNAm intensity on risk for T2DM (y-axis) plotted against observed effect estimates (from the LOLIPOP confirmation phase [x-axis]) at each of 16 top-hit MVPs (see Supplementary Table 7). Effect sizes are log–odds ratios per 1-unit change in normalized methylation intensity aligned to higher observed odds of T2DM.

Tables

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  • Table 1

    Baseline characteristics of participants in the EPIC-Norfolk, LOLIPOP, and FHS study samples

    EPIC-Norfolk, discovery phaseLOLIPOP, confirmation phaseFHS, confirmation phase
    Incident T2DMNoncaseIncident T2DMNoncasePrevalent T2DMNoncase
    N5637011,0741,5904032,204
    Female sex, n (%)474 (84)407 (58)352 (36.3)507 (31.8)173 (43.0)1,245 (56.5)
    Age (years)61.6 (8.1)59.1 (9.2)52.5 (10.2)49.9 (9.8)69.3 (8.4)65.8 (8.9)
    EthnicityEuropeanEuropeanIndian AsianIndian AsianEuropeanEuropean
    HbA1c (%)6.5 (1.3)5.5 (0.33)5.77 (0.49)5.37 (0.48)6.67 (1.15)5.55 (0.27)
    HbA1c (mmol/mol)47.4 (14.2)36.2 (3.6)40 (5.4)35 (5.2)49 (12.6)37 (3)
    BMI (kg/m2)29.2 (4.5)25.6 (3.6)28.9 (4.6)26.7 (3.9)31.6 (6.2)27.7 (5.0)
    • Data are means (SD) unless otherwise indicated.

  • Table 2

    MVPs associated with incident T2DM at P < 1.0E-07 in EPIC-Norfolk (N = 1,264)

    CpG identifierChrPositionOR95% CIPFDRGene nameGene position
    cg1969303111441529090.520.46–0.62.7E-211.3E-15TXNIP3′ UTR
    cg0650016121425296561.651.45–1.896.4E-141.5E-08ABCG1Body
    cg1447610111200575150.670.59–0.762.8E-103.9E-05PHGDHBody
    cg1402017617702765801.631.4–1.93.3E-103.9E-05SLC9A3R13′ UTR
    cg1102468217176708191.561.35–1.796.0E-105.7E-05SREBF1Body
    cg0639716122380900051.511.32–1.734.5E-093.3E-04SYNGR1Body; TSS200
    cg0057495811683641980.690.61–0.785.2E-093.3E-04CPT1A5′ UTR
    cg0623542911671296901.491.3–1.75.5E-093.3E-04NDUFV1TSS1500
    cg0577842417525245071.691.42–2.027.4E-093.9E-04AKAP15′ UTR
    cg1137614711570177740.680.59–0.771.3E-086.0E-04SLC43A1Body
    cg04816311710331761.511.31–1.751.7E-087.2E-04C7orf50Body
    cg0271160819519798040.690.6–0.794.5E-081.5E-03SLC1A51st exon; 5′ UTR
    cg0830968721342424660.680.6–0.784.5E-081.5E-03
    cg13514042711587281.421.25–1.614.5E-081.5E-03
    cg089940601062540320.650.55–0.765.2E-081.6E-03PFKFB3Body
    cg016767957754242841.561.33–1.846.5E-081.8E-03PORBody
    cg251303811273133081.491.29–1.736.7E-081.8E-03SLC9A1Body
    cg1118322715892564111.491.29–1.727.0E-081.8E-03MAN2A2Body
    • Position: by HapMap build 37. OR: odds ratio per 1 SD in methylation intensity. Genes: gene names in which the CpG falls from 1,500 bp upstream of the transcriptional start site to the end of the 3′ UTR as in Illumina’s Infinium Human Methylation 450K BeadChip manifest file. Chr, chromosome; FDR, false discovery rate.

  • Table 3

    Confirmation of the top 18 T2DM-associated MVPs in LOLIPOP and FHS

    CpG identifierChrGeneDiscovery, incident T2DMLOLIPOP, incident T2DMFHS, prevalent T2DM*
    OR95% CIOR95% CIPβSEP
    cg196930311TXNIP0.520.46–0.60.680.62–0.751.2E-14−2.6E-022.7E-031.6E-21
    cg0650016121ABCG11.651.45–1.891.441.31–1.582.6E-141.5E-021.8E-037.1E-17
    cg144761011PHGDH0.670.59–0.760.810.75–0.893.0E-06−1.6E-023.6E-031.5E-05
    cg1402017617SLC9A3R11.631.4–1.91.141–1.294.3E-025.4E-031.5E-033.9E-04
    cg1102468217SREBF11.561.35–1.791.401.26–1.572.2E-098.6E-031.6E-035.4E-08
    cg0639716122SYNGR11.511.32–1.731.171.06–1.281.1E-039.6E-032.2E-031.6E-05
    cg0057495811CPT1A0.690.61–0.780.800.74–0.881.1E-06−6.7E-037.9E-044.8E-17
    cg0623542911NDUFV11.491.3–1.71.111–1.245.8E-022.4E-031.3E-036.5E-02
    cg0577842417AKAP11.691.42–2.021.441.21–1.713.5E-054.9E-031.6E-032.5E-03
    cg1137614711SLC43A10.680.59–0.770.850.74–0.971.5E-02−3.2E-031.2E-038.4E-03
    cg048163117C7orf501.511.31–1.751.131–1.274.4E-022.0E-023.2E-038.4E-10
    cg0271160819SLC1A50.690.6–0.790.840.76–0.939.7E-04−7.9E-031.7E-032.0E-06
    cg0830968721—0.680.6–0.780.820.74–0.911.9E-04−7.8E-033.0E-031.0E-02
    cg135140427—1.421.25–1.611.040.94–1.154.4E-011.8E-041.4E-039.0E-01
    cg0899406010PFKFB30.650.55–0.760.810.72–0.926.6E-04−1.6E-022.5E-038.5E-10
    cg016767957POR1.561.33–1.841.090.95–1.262.2E-019.2E-032.4E-031.2E-04
    cg251303811SLC9A11.491.29–1.731.231.09–1.391.2E-036.5E-031.7E-031.7E-04
    cg1118322715MAN2A21.491.29–1.721.080.97–1.21.9E-014.6E-032.0E-032.2E-02
    • MVPs and individual cells with confirmed association P < 0.05 appear in boldface type. FHS: 403 case and 2,204 control subjects). LOLIPOP: 1,074 case and 1,590 control subjects. OR: odds ratio for T2DM per 1 SD in methylation intensity. Chr, chromosome.

    • * In FHS, β indicates difference in percentage DNAm intensity between case and control subjects, with adjustment for age, sex, principal components 1–3 (calculated from methylation data), batch, and family structure.

  • Table 4

    Analysis of the top 18 T2DM-associated MVPs in nonblood tissues

    CpG identifierChrGeneBlood, T2DM-CONLiver, T2DM-CONFatMuscle
    T2DMCONT2DM-CONT2DM-CON PT2DM-CON, consistentT2DMCONT2DM-CONT2DM-CON PT2DM-CON, consistent
    ORPT2DM-CONPConsistent
    cg196930311TXNIP0.522.7E-21−0.0410.65True0.5010.4990.0020.71False0.5940.634-0.0400.02True
    cg0650016121ABCG11.656.4E-140.0350.64True0.4770.4390.0380.02True0.3600.3490.0110.75True
    cg144761011PHGDH0.672.8E-100.0800.14False0.5650.5610.0040.86False0.4830.484−0.0010.85True
    cg1402017617SLC9A3R11.633.3E-100.0650.26True0.6780.686−0.0080.36False0.7410.748−0.0070.52False
    cg1102468217SREBF11.566.0E-100.0810.24True0.6460.6400.0070.58True0.4060.3910.0160.96True
    cg0639716122SYNGR11.514.5E-09−0.1450.07False0.5010.516−0.0150.09False0.5620.566−0.0050.78False
    cg0057495811CPT1A0.695.2E-090.0590.42FALSE0.0910.096−0.0050.22True0.0970.103−0.0060.33True
    cg0623542911NDUFV11.495.5E-09−0.0370.60False0.7930.7930.0010.43True0.7640.765−0.0010.82False
    cg0577842417AKAP11.697.4E-090.0190.75True0.5830.594−0.0110.36False0.6440.648−0.0050.64False
    cg1137614711SLC43A10.681.3E-080.0760.15False0.3010.305−0.0050.54True0.2820.285−0.0030.64True
    cg048163117C7orf501.511.7E-080.0260.63True0.8530.861−0.0080.81False0.8790.885−0.0060.35False
    cg0271160819SLC1A50.694.5E-080.0180.72False0.2450.256−0.0110.06True0.3560.376−0.0200.06True
    cg08309687210.684.5E-080.0170.85False0.6340.653−0.0190.12True0.4460.4450.0010.85False
    cg1351404271.424.5E-080.1300.09True0.7100.7060.0030.71True0.7320.7240.0070.55True
    cg0899406010PFKFB30.655.2E-08−0.0950.17True0.1700.175−0.0050.86True0.1540.1430.0110.55False
    cg016767957POR1.566.5E-08−0.0900.47False0.8510.852−0.0010.86False0.8900.892−0.0020.85False
    cg251303811SLC9A11.496.7E-08−0.0690.14False0.6210.6100.0110.19True0.7640.776−0.0110.40False
    cg1118322715MAN2A21.497.0E-08−0.1050.19False0.9450.946−0.0010.63False0.9060.910−0.0040.40False
    • Data are mean β unless otherwise indicated. CON, control subjects.

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Epigenome-Wide Association Study of Incident Type 2 Diabetes in a British Population: EPIC-Norfolk Study
Alexia Cardona, Felix R. Day, John R.B. Perry, Marie Loh, Audrey Y. Chu, Benjamin Lehne, Dirk S. Paul, Luca A. Lotta, Isobel D. Stewart, Nicola D. Kerrison, Robert A. Scott, Kay-Tee Khaw, Nita G. Forouhi, Claudia Langenberg, Chunyu Liu, Michael M. Mendelson, Daniel Levy, Stephan Beck, R. David Leslie, Josée Dupuis, James B. Meigs, Jaspal S. Kooner, Jussi Pihlajamäki, Allan Vaag, Alexander Perfilyev, Charlotte Ling, Marie-France Hivert, John C. Chambers, Nicholas J. Wareham, Ken K. Ong
Diabetes Dec 2019, 68 (12) 2315-2326; DOI: 10.2337/db18-0290

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Epigenome-Wide Association Study of Incident Type 2 Diabetes in a British Population: EPIC-Norfolk Study
Alexia Cardona, Felix R. Day, John R.B. Perry, Marie Loh, Audrey Y. Chu, Benjamin Lehne, Dirk S. Paul, Luca A. Lotta, Isobel D. Stewart, Nicola D. Kerrison, Robert A. Scott, Kay-Tee Khaw, Nita G. Forouhi, Claudia Langenberg, Chunyu Liu, Michael M. Mendelson, Daniel Levy, Stephan Beck, R. David Leslie, Josée Dupuis, James B. Meigs, Jaspal S. Kooner, Jussi Pihlajamäki, Allan Vaag, Alexander Perfilyev, Charlotte Ling, Marie-France Hivert, John C. Chambers, Nicholas J. Wareham, Ken K. Ong
Diabetes Dec 2019, 68 (12) 2315-2326; DOI: 10.2337/db18-0290
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