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Holzinger ER, Verma SS, Moore CB, et al. Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min. 2017;10:25doi: 10.1186/s13040-017-0145-5.
Holzinger, E. R., Verma, S. S., Moore, C. B., Hall, M., De, R., Gilbert-Diamond, D., Lanktree, M. B., Pankratz, N., Amuzu, A., Burt, A., Dale, C., Dudek, S., Furlong, C. E., Gaunt, T. R., Kim, D. S., Riess, H., Sivapalaratnam, S., Tragante, V., van Iperen, E. P. A., Brautbar, A., Carrell, D. S., Crosslin, D. R., Jarvik, G. P., Kuivaniemi, H., Kullo, I. J., Larson, E. B., Rasmussen-Torvik, L. J., Tromp, G., Baumert, J., Cruickshanks, K. J., Farrall, M., Hingorani, A. D., Hovingh, G. K., Kleber, M. E., Klein, B. E., Klein, R., Koenig, W., Lange, L. A., Mӓrz, W., North, K. E., Charlotte Onland-Moret, N., Reiner, A. P., Talmud, P. J., van der Schouw, Y. T., Wilson, J. G., Kivimaki, M., Kumari, M., Moore, J. H., Drenos, F., Asselbergs, F. W., Keating, B. J., & Ritchie, M. D. (2017). Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData mining, 1025. https://doi.org/10.1186/s13040-017-0145-5
Holzinger, Emily R, et al. "Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals." BioData mining vol. 10 (2017): 25. doi: https://doi.org/10.1186/s13040-017-0145-5
Holzinger ER, Verma SS, Moore CB, Hall M, De R, Gilbert-Diamond D, Lanktree MB, Pankratz N, Amuzu A, Burt A, Dale C, Dudek S, Furlong CE, Gaunt TR, Kim DS, Riess H, Sivapalaratnam S, Tragante V, van Iperen EPA, Brautbar A, Carrell DS, Crosslin DR, Jarvik GP, Kuivaniemi H, Kullo IJ, Larson EB, Rasmussen-Torvik LJ, Tromp G, Baumert J, Cruickshanks KJ, Farrall M, Hingorani AD, Hovingh GK, Kleber ME, Klein BE, Klein R, Koenig W, Lange LA, Mӓrz W, North KE, Charlotte Onland-Moret N, Reiner AP, Talmud PJ, van der Schouw YT, Wilson JG, Kivimaki M, Kumari M, Moore JH, Drenos F, Asselbergs FW, Keating BJ, Ritchie MD. Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min. 2017 Jul 24;10:25. doi: 10.1186/s13040-017-0145-5. eCollection 2017. PMID: 28770004; PMCID: PMC5525436.
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BioData Min. 2017 Jul 24;10:25. doi: 10.1186/s13040-017-0145-5. eCollection 2017.

Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals.

BioData mining

Emily R Holzinger, Shefali S Verma, Carrie B Moore, Molly Hall, Rishika De, Diane Gilbert-Diamond, Matthew B Lanktree, Nathan Pankratz, Antoinette Amuzu, Amber Burt, Caroline Dale, Scott Dudek, Clement E Furlong, Tom R Gaunt, Daniel Seung Kim, Helene Riess, Suthesh Sivapalaratnam, Vinicius Tragante, Erik P A van Iperen, Ariel Brautbar, David S Carrell, David R Crosslin, Gail P Jarvik, Helena Kuivaniemi, Iftikhar J Kullo, Eric B Larson, Laura J Rasmussen-Torvik, Gerard Tromp, Jens Baumert, Karen J Cruickshanks, Martin Farrall, Aroon D Hingorani, G K Hovingh, Marcus E Kleber, Barbara E Klein, Ronald Klein, Wolfgang Koenig, Leslie A Lange, Winfried Mӓrz, Kari E North, N Charlotte Onland-Moret, Alex P Reiner, Philippa J Talmud, Yvonne T van der Schouw, James G Wilson, Mika Kivimaki, Meena Kumari, Jason H Moore, Fotios Drenos, Folkert W Asselbergs, Brendan J Keating, Marylyn D Ritchie

Affiliations

  1. Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute for General Medical Sciences, National Institutes of Health, Baltimore, MD USA.
  2. The Center for Systems Genomics, The Pennsylvania State University, University Park, State College, PA USA.
  3. Department of Surgery, Duke University, Durham, NC USA.
  4. Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH USA.
  5. Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH USA.
  6. Department of Medicine, McMaster University, Hamilton, ON Canada.
  7. Department of Lab Medicine and Pathology, University of Minnesota, Minneapolis, MN USA.
  8. London School of Hygiene and Tropical Medicine, London, UK.
  9. Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA USA.
  10. MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
  11. Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  12. Department of Vascular Medicine, Academic Medical Center, Amsterdam, The Netherlands.
  13. Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands.
  14. Department of Medical Genetics, Biomedical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands.
  15. Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands.
  16. Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, Amsterdam, The Netherlands.
  17. Department of Medical Genetics, Marshfield Clinic, Marshfield, WI USA.
  18. Group Health Research Institute, Group Health Cooperative, Seattle, WA USA.
  19. Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Tygerberg, South Africa.
  20. Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN USA.
  21. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL USA.
  22. Department of Population Health Sciences, Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, WI USA.
  23. Department of Cardiovascular Medicine, The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
  24. Department of Epidemiology and Public Health, UCL Institute of Epidemiology & Health Care, University College London, London, UK.
  25. Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany.
  26. Department of Internal Medicine II - Cardiology, University of Ulm Medical Centre, Ulm, Germany.
  27. Department of Genetics, University of North Carolina School of Medicine at Chapel Hill, Chapel Hill, NC USA.
  28. Synlab Academy, Synlab Services GmbH, Mannheim, Germany.
  29. Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC USA.
  30. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
  31. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA USA.
  32. MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK.
  33. Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS USA.
  34. ISER, University of Essex, Essex, UK.
  35. Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA.
  36. Centre of Cardiovascular Genetics, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK.
  37. Division of Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA USA.
  38. Division of Transplantation, Department of Surgery, University of Pennsylvania, Philadelphia, PA USA.
  39. Biomedical and Translational Informatics, Geisinger Clinic, Danville, PA USA.

PMID: 28770004 PMCID: PMC5525436 DOI: 10.1186/s13040-017-0145-5

Abstract

BACKGROUND: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG).

RESULTS: Our analysis consisted of a discovery phase using a merged dataset of five different cohorts (

CONCLUSIONS: These results may reveal novel insights into the genetic etiology of lipid levels. Furthermore, we developed a pipeline to perform a computationally efficient interaction analysis with multi-cohort replication.

Keywords: Computational genetics; Genetic epidemiology; Genetics; Interactions; Lipids

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