Diabetologia

, Volume 56, Issue 12, pp 2556–2563 | Cite as

Prediction of type 2 diabetes in women with a history of gestational diabetes using a genetic risk score

  • Soo Heon Kwak
  • Sung Hee Choi
  • Kyunga Kim
  • Hye Seung Jung
  • Young Min Cho
  • Soo Lim
  • Nam H. Cho
  • Seong Yeon Kim
  • Kyong Soo Park
  • Hak C. Jang
Article

Abstract

Aims/hypothesis

Women with a history of gestational diabetes mellitus (GDM) are at increased risk of future development of type 2 diabetes. Recently, over 65 genetic variants have been confirmed to be associated with diabetes. We investigated whether this genetic information could improve the prediction of future diabetes in women with GDM.

Methods

This was a prospective cohort study consisting of 395 women with GDM who were followed annually with an OGTT. A weighted genetic risk score (wGRS), consisting of 48 variants, was assessed for improving discrimination (C statistic) and risk reclassification (continuous net reclassification improvement [NRI] index) when added to clinical risk factors.

Results

Among the 395 women with GDM, 116 (29.4%) developed diabetes during a median follow-up period of 45 months. Women with GDM who went on to develop diabetes had a significantly higher wGRS than those who did not (9.36 ± 0.92 vs 8.78 ± 1.07; p < 1.56 × 10−7). In a complex clinical model adjusted for age, prepregnancy BMI, family history of diabetes, blood pressure, fasting glucose and fasting insulin concentration, the C statistic marginally improved from 0.741 without the wGRS to 0.775 with the wGRS (p = 0.015). The addition of the wGRS to the clinical model resulted in a modest improvement in reclassification (continuous NRI 0.430 [95% CI 0.218, 0.642]; p = 7.0 × 10−5).

Conclusions/interpretation

In women with GDM, who are at high risk of diabetes, the wGRS was significantly associated with the future development of diabetes. Furthermore, it improved prediction over clinical risk factors.

Keywords

Genetic risk score Gestational diabetes Risk prediction Type 2 diabetes 

Abbreviations

GDM

Gestational diabetes mellitus

GRS

Genetic risk score

GWA

Genome-wide association

IGT

Impaired glucose tolerance

IQR

Interquartile range

IR

Insulin resistance

IS

Insulin secretion

NGT

Normal glucose tolerance

NRI

Net reclassification improvement

SNP

Single nucleotide polymorphism

uGRS

Unweighted genetic risk score

wGRS

Weighted genetic risk score

Notes

Acknowledgements

This work was supported by the Korea Healthcare Technology R & D Project, Ministry of Health and Welfare (grant no. A111362), and by a grant from the National Project for Personalized Genomic Medicine, Ministry for Health and Welfare (grant no. A111218-GM09), Republic of Korea.

Funding

This work was funded by the National Project for Personalized Genomic Medicine and Korea Healthcare Technology R & D Project, Ministry for Health and Welfare, Republic of Korea.

Duality of interest

The authors declare that there is no duality of interest associated with this study.

Contribution statement

SHK contributed substantially to the conception and design, acquisition, analysis and interpretation of data and drafting and revising the manuscript. SHC, KK, HSJ, YMC, SL and SYK contributed substantially to the conception and design, interpretation of data and revising the manuscript. NHC contributed substantially to the conception and design, acquisition and interpretation of data and revising the manuscript. KSP and HCJ contributed substantially to the conception and design, acquisition, analysis and interpretation of data and revising the manuscript. All authors approved the final version to be published.

Supplementary material

125_2013_3059_MOESM1_ESM.pdf (170 kb)
ESM Table 1 (PDF 170 kb)
125_2013_3059_MOESM2_ESM.pdf (127 kb)
ESM Table 2 (PDF 126 kb)
125_2013_3059_MOESM3_ESM.pdf (116 kb)
ESM Table 3 (PDF 116 kb)
125_2013_3059_MOESM4_ESM.pdf (117 kb)
ESM Table 4 (PDF 117 kb)
125_2013_3059_MOESM5_ESM.pdf (28 kb)
ESM Fig. 1 (PDF 27 kb)
125_2013_3059_MOESM6_ESM.pdf (30 kb)
ESM Fig. 2 (PDF 30 kb)

References

  1. 1.
    Bellamy L, Casas JP, Hingorani AD, Williams D (2009) Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet 373:1773–1779PubMedCrossRefGoogle Scholar
  2. 2.
    Kwak SH, Choi SH, Jung HS et al (2013) Clinical and genetic risk factors for type 2 diabetes at early or late post partum after gestational diabetes mellitus. J Clin Endocrinol Metab 98:E744–E752PubMedCrossRefGoogle Scholar
  3. 3.
    Buchanan TA, Xiang A, Kjos SL et al (1998) Gestational diabetes: antepartum characteristics that predict postpartum glucose intolerance and type 2 diabetes in Latino women. Diabetes 47:1302–1310PubMedGoogle Scholar
  4. 4.
    Metzger BE, Cho NH, Roston SM, Radvany R (1993) Prepregnancy weight and antepartum insulin secretion predict glucose tolerance five years after gestational diabetes mellitus. Diabetes Care 16:1598–1605PubMedCrossRefGoogle Scholar
  5. 5.
    Jang HC (2011) Gestational diabetes in Korea: incidence and risk factors of diabetes in women with previous gestational diabetes. Diabetes Metab J 35:1–7PubMedCrossRefGoogle Scholar
  6. 6.
    Kwak SH, Jang HC, Park KS (2012) Finding genetic risk factors of gestational diabetes. Genomics Inform 10:239–243PubMedCrossRefGoogle Scholar
  7. 7.
    Buchanan TA, Xiang AH, Peters RK et al (2002) Preservation of pancreatic beta-cell function and prevention of type 2 diabetes by pharmacological treatment of insulin resistance in high-risk Hispanic women. Diabetes 51:2796–2803PubMedCrossRefGoogle Scholar
  8. 8.
    Ratner RE, Christophi CA, Metzger BE et al (2008) Prevention of diabetes in women with a history of gestational diabetes: effects of metformin and lifestyle interventions. J Clin Endocrinol Metab 93:4774–4779PubMedCrossRefGoogle Scholar
  9. 9.
    Morris AP, Voight BF, Teslovich TM et al (2012) Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet 44:981–990PubMedCrossRefGoogle Scholar
  10. 10.
    Manolio TA, Collins FS, Cox NJ et al (2009) Finding the missing heritability of complex diseases. Nature 461:747–753PubMedCrossRefGoogle Scholar
  11. 11.
    Meigs JB, Shrader P, Sullivan LM et al (2008) Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med 359:2208–2219PubMedCrossRefGoogle Scholar
  12. 12.
    Lyssenko V, Jonsson A, Almgren P et al (2008) Clinical risk factors, DNA variants, and the development of type 2 diabetes. N Engl J Med 359:2220–2232PubMedCrossRefGoogle Scholar
  13. 13.
    Talmud PJ, Hingorani AD, Cooper JA et al (2010) Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II Prospective Cohort Study. BMJ 340:b4838PubMedCrossRefGoogle Scholar
  14. 14.
    Vassy JL, Durant NH, Kabagambe EK et al (2012) A genotype risk score predicts type 2 diabetes from young adulthood: the CARDIA study. Diabetologia 55:2604–2612PubMedCrossRefGoogle Scholar
  15. 15.
    Kwak SH, Kim SH, Cho YM et al (2012) A genome-wide association study of gestational diabetes mellitus in Korean women. Diabetes 61:531–541PubMedCrossRefGoogle Scholar
  16. 16.
    Metzger BE (1991) Summary and recommendations of the Third International Workshop-Conference on Gestational Diabetes Mellitus. Diabetes 40(Suppl 2):197–201PubMedCrossRefGoogle Scholar
  17. 17.
    American Diabetes Association (2013) Diagnosis and classification of diabetes mellitus. Diabetes Care 36(Suppl 1):S67–S74CrossRefGoogle Scholar
  18. 18.
    Matsuda M, DeFronzo RA (1999) Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care 22:1462–1470PubMedCrossRefGoogle Scholar
  19. 19.
    Kanat M, Winnier D, Norton L et al (2011) The relationship between β-cell function and glycated hemoglobin: results from the Veterans Administration Genetic Epidemiology Study. Diabetes Care 34:1006–1010PubMedCrossRefGoogle Scholar
  20. 20.
    Li Y, Willer C, Sanna S, Abecasis G (2009) Genotype imputation. Annu Rev Genomics Hum Genet 10:387–406PubMedCrossRefGoogle Scholar
  21. 21.
    Hosmer DW, Lemeshow S (1989) Applied logistic regression. Wiley, New YorkGoogle Scholar
  22. 22.
    Pencina MJ, D’Agostino RB Sr, D’Agostino RB Jr, Vasan RS (2008) Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 27:157–172, discussion 207-112PubMedCrossRefGoogle Scholar
  23. 23.
    Purcell S, Neale B, Todd-Brown K et al (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575PubMedCrossRefGoogle Scholar
  24. 24.
    Kundu S, Aulchenko YS, van Duijn CM, Janssens AC (2011) PredictABEL: an R package for the assessment of risk prediction models. Eur J Epidemiol 26:261–264PubMedCrossRefGoogle Scholar
  25. 25.
    de Miguel-Yanes JM, Shrader P, Pencina MJ et al (2011) Genetic risk reclassification for type 2 diabetes by age below or above 50 years using 40 type 2 diabetes risk single nucleotide polymorphisms. Diabetes Care 34:121–125PubMedCrossRefGoogle Scholar
  26. 26.
    Vassy JL, Meigs JB (2012) Is genetic testing useful to predict type 2 diabetes? Best Pract Res Clin Endocrinol Metab 26:189–201PubMedCrossRefGoogle Scholar
  27. 27.
    Vassy JL, Dasmahapatra P, Meigs JB et al (2012) Genotype prediction of adult type 2 diabetes from adolescence in a multiracial population. Pediatrics 130:e1235–e1242PubMedCrossRefGoogle Scholar
  28. 28.
    Buchanan TA (2001) Pancreatic B cell defects in gestational diabetes: implications for the pathogenesis and prevention of type 2 diabetes. J Clin Endocrinol Metab 86:989–993PubMedCrossRefGoogle Scholar
  29. 29.
    Kwak SH, Park KS (2013) Genetics of type 2 diabetes and potential clinical implications. Arch Pharm Res 36:167–177PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Soo Heon Kwak
    • 1
  • Sung Hee Choi
    • 2
    • 3
  • Kyunga Kim
    • 4
  • Hye Seung Jung
    • 1
  • Young Min Cho
    • 1
    • 2
  • Soo Lim
    • 3
  • Nam H. Cho
    • 5
  • Seong Yeon Kim
    • 1
    • 2
  • Kyong Soo Park
    • 1
    • 2
    • 6
  • Hak C. Jang
    • 2
    • 3
  1. 1.Department of Internal MedicineSeoul National University HospitalSeoulSouth Korea
  2. 2.Department of Internal MedicineSeoul National University College of MedicineSeoulSouth Korea
  3. 3.Department of Internal MedicineSeoul National University Bundang HospitalSeongnam-SiSouth Korea
  4. 4.Department of StatisticsSookmyung Women’s UniversitySeoulSouth Korea
  5. 5.Department of Preventive MedicineAjou University School of MedicineSuwonSouth Korea
  6. 6.World Class University Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and TechnologySeoul National UniversitySeoulSouth Korea

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