Multiple SNP testing improves risk prediction of first venous thrombosis

Author:

de Haan Hugoline G.1,Bezemer Irene D.1,Doggen Carine J. M.12,Le Cessie Saskia13,Reitsma Pieter H.45,Arellano Andre R.6,Tong Carmen H.6,Devlin James J.6,Bare Lance A.6,Rosendaal Frits R.145,Vossen Carla Y.17

Affiliation:

1. Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands;

2. Department of Health Technology & Services Research, MIRA Institute for Biomedical Technology and Technical Medicine, Enschede, The Netherlands;

3. Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands;

4. Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands;

5. Department of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, The Netherlands;

6. Celera, Alameda, CA; and

7. Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands

Abstract

Abstract There are no risk models available yet that accurately predict a person's risk for developing venous thrombosis. Our aim was therefore to explore whether inclusion of established thrombosis-associated single nucleotide polymorphisms (SNPs) in a venous thrombosis risk model improves the risk prediction. We calculated genetic risk scores by counting risk-increasing alleles from 31 venous thrombosis-associated SNPs for subjects of a large case-control study, including 2712 patients and 4634 controls (Multiple Environmental and Genetic Assessment). Genetic risk scores based on all 31 SNPs or on the 5 most strongly associated SNPs performed similarly (areas under receiver-operating characteristic curves [AUCs] of 0.70 and 0.69, respectively). For the 5-SNP risk score, the odds ratios for venous thrombosis ranged from 0.37 (95% confidence interval [CI], 0.25-0.53) for persons with 0 risk alleles to 7.48 (95% CI, 4.49-12.46) for persons with more than or equal to 6 risk alleles. The AUC of a risk model based on known nongenetic risk factors was 0.77 (95% CI, 0.76-0.78). Combining the nongenetic and genetic risk models improved the AUC to 0.82 (95% CI, 0.81-0.83), indicating good diagnostic accuracy. To become clinically useful, subgroups of high-risk persons must be identified in whom genetic profiling will also be cost-effective.

Publisher

American Society of Hematology

Subject

Cell Biology,Hematology,Immunology,Biochemistry

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