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Review article: Biomedical intelligence

Vol. 144 No. 4950 (2014)

The Lausanne Institutional Biobank: A new resource to catalyse research in personalised medicine and pharmaceutical sciences

  • Vincent Mooser
  • Christine Currat
DOI
https://doi.org/10.4414/smw.2014.14033
Cite this as:
Swiss Med Wkly. 2014;144:w14033
Published
30.11.2014

Summary

Breakthrough technologies which now enable the sequencing of individual genomes will irreversibly modify the way diseases are diagnosed, predicted, prevented and treated. For these technologies to reach their full potential requires, upstream, access to high-quality biomedical data and samples from large number of properly informed and consenting individuals and, downstream, the possibility to transform the emerging knowledge into a clinical utility.

The Lausanne Institutional Biobank was designed as an integrated, highly versatile infrastructure to harness the power of these emerging technologies and catalyse the discovery and development of innovative therapeutics and biomarkers, and advance the field of personalised medicine. Described here are its rationale, design and governance, as well as parallel initiatives which have been launched locally to address the societal, ethical and technological issues associated with this new bio-resource.

Since January 2013, inpatients admitted at Lausanne CHUV University Hospital have been systematically invited to provide a general consent for the use of their biomedical data and samples for research, to complete a standardised questionnaire, to donate a 10–ml sample of blood for future DNA extraction and to be re-contacted for future clinical trials. Over the first 18 months of operation, 14,459 patients were contacted, and 11,051 accepted to participate in the study.

This initial 18–month experience illustrates that a systematic hospital-based biobank is feasible; it shows a strong engagement in research from the patient population in this University Hospital setting, and the need for a broad, integrated approach for the future of medicine to reach its full potential.

References

  1. Visscher PM, Brown MA, McCarthy MI, Yang J. Five years of GWAS discovery. Am J Human Genet. 2012;90(1):7–24.
  2. Tennessen JA, Bigham AW, O’Connor TD, Fu W, Kenny EE, Gravel S, et al. Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science. 2012;337(6090):64–9.
  3. Nelson MR, Wegmann D, Ehm MG, Kessner D, St Jean P, Verzilli C, et al. An Abundance of Rare Functional Variants in 202 Drug Target Genes Sequenced in 14,002 People. Science. 2012.
  4. Coventry A, Bull-Otterson LM, Liu X, Clark AG, Maxwell TJ, Crosby J, et al. Deep resequencing reveals excess rare recent variants consistent with explosive population growth. Nat Commun. 2010;1(131.
  5. Bamshad MJ, Shendure JA, Valle D, Hamosh A, Lupski JR, Gibbs RA, et al. The Centers for Mendelian Genomics: a new large-scale initiative to identify the genes underlying rare Mendelian conditions. Am J Med Genet Part A. 2012;158A(7):1523–5.
  6. Ginsburg G. Medical genomics: Gather and use genetic data in health care. Nature. 2014;508(7497):451–3.
  7. Mooser V. Genomics and personalized medicine. Praxis. 2014;103(10):567–71.
  8. Denny JC, Bastarache L, Ritchie MD, Carroll RJ, Zink R, Mosley JD, et al. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat Biotechnol. 2013;31(12):1102–10.
  9. Payne DJ, Gwynn MN, Holmes DJ, Pompliano DL. Drugs for bad bugs: confronting the challenges of antibacterial discovery. Nat Rev Drug Discov. 2007;6(1):29–40.
  10. Ziegler A, Koch A, Krockenberger K, Grosshennig A. Personalized medicine using DNA biomarkers: a review. Hum Genet. 2012;131(10):1627–38.
  11. Cohen J, Pertsemlidis A, Kotowski IK, Graham R, Garcia CK, Hobbs HH. Low LDL cholesterol in individuals of African descent resulting from frequent nonsense mutations in PCSK9. Nat Genet. 2005;37(2):161–5.
  12. Weedon MN, Lango H, Lindgren CM, Wallace C, Evans DM, Mangino M, et al. Genome-wide association analysis identifies 20 loci that influence adult height. Nat Genet. 2008;40(5):575–83.
  13. Sullivan D, Olsson AG, Scott R, Kim JB, Xue A, Gebski V, et al. Effect of a Monoclonal Antibody to PCSK9 on Low-Density Lipoprotein Cholesterol Levels in Statin-Intolerant Patients: The GAUSS Randomized Trial. JAMA: the journal of the American Medical Association. 2012:1–10.
  14. Hood L, Flores M. A personal view on systems medicine and the emergence of proactive P4 medicine: predictive, preventive, personalized and participatory. New biotechnology. 2012;29(6):613–24.
  15. Elliott P, Peakman TC, Biobank UK. The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine. Int J Epidemiol. 2008;37(2):234–44.
  16. Firmann M, Mayor V, Vidal PM, Bochud M, Pecoud A, Hayoz D, et al. The CoLaus study: a population-based study to investigate the epidemiology and genetic determinants of cardiovascular risk factors and metabolic syndrome. BMC Cardiovasc Disord. 2008;8:6.
  17. Maillard PY. Sequencing the human genome and society. Praxis. 2014;103(10):551–3.
  18. Barazzetti G, Kaufmann A, and Benaroyo L. Ethical and social issues associated with genomic medicine. Praxis. 2014;103(10):573–7.
  19. Raisaro JL, Ayday E, Hubaux JP. Patient privacy in the genomic era. Praxis. 2014;103(10):579–86.
  20. Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466(7307):707–13.
  21. Windhager S, Schaschl H, Schaefer K, Mitteroecker P, Huber S, Wallner B, Fieder M. Variation at genes influencing facial morphology are not associated with developmental imprecision in human faces. PLoS One. 2014;9(6):e99009.
  22. The TG, Hdl Working Group of the Exome Sequencing Project NHL, Blood I. Loss-of-Function Mutations in APOC3, Triglycerides, and Coronary Disease. N Engl J Med. 2014;371(1):22–31.
  23. Jorgensen AB, Frikke-Schmidt R, Nordestgaard BG, Tybjaerg-Hansen A. Loss-of-Function Mutations in APOC3 and Risk of Ischemic Vascular Disease. N Engl J Med. 2014;371(1):32–41.
  24. Mabuchi H, Haba T, Tatami R, Miyamoto S, Sakai Y, Wakasugi T, et al. Effect of an inhibitor of 3–hydroxy-3–methyglutaryl coenzyme A reductase on serum lipoproteins and ubiquinone-10–levels in patients with familial hypercholesterolemia. N Engl J Med. 1981;305(9):478–82.
  25. Hu Y, Li L, Ehm MG, Bing N, Song K, Nelson MR, Talmud PJ, et al. The benefits of using genetic information to design prevention trials. Am J Hum Genet. 2013;92(4):547–57.
  26. Couch FJ, Nathanson KL, Offit K. Two decades after BRCA: setting paradigms in personalized cancer care and prevention. Science. 2014;343(6178):1466–70.

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