Skip to main navigation menu Skip to main content Skip to site footer

Original article

Vol. 147 No. 4142 (2017)

High participation rate among 25 721 patients with broad age range in a hospital-based research project involving whole-genome sequencing – the Lausanne Institutional Biobank

  • Murielle Bochud
  • Christine Currat
  • Laurence Chapatte
  • Cindy Roth
  • Vincent Mooser
Cite this as:
Swiss Med Wkly. 2017;147:w14528



We aimed to evaluate the interest of adult inpatients and selected outpatients in engaging in a large, real-life, hospital-based, genomic medicine research project and in receiving clinically actionable incidental findings.


Within the framework of the cross-sectional Institutional Biobank of Lausanne, Switzerland, a total of 25 721 patients of the CHUV University Hospital were systematically invited to grant researchers access to their biomedical data and to donate blood for future analyses, including whole-genome sequencing. Multivariable logistic regression analysis was used to identify personal factors, including age, gender, religion, ethnicity, citizenship, education level and mode of admission, associated with willingness to participate in this genomic research project and with interest in receiving clinically actionable incidental findings.


The overall participation rate was 79% (20 343/25 721). Participation rate declined progressively with age, averaging 83%, 75%, 67% and 62% in patients aged <64 years (n = 13 108), ≥64 years (n = 12 613), ≥80 years (n = 4557) and ≥90 years (n = 1050), respectively. Factors associated with participation substantially differed between age strata. Patients less likely to participate included women (odds ratio 0.86, [95% confidence interval 0.79–0.95] and 0.78 [0.71–0.85] before and after age 64, respectively), non-Swiss (0.81 [0.74–0.90] and 0.58 [0.52–0.65]) and those admitted through the emergency ward (0.88 [0.79–0.98] and 0.66 [0.60–0.73]). Religion and marital status were associated with participation among patients aged <64 years. A total of 19 018 (93%) participants were willing to be re-contacted for incidental findings. A high education level was associated with higher participation rate, but not with higher willingness to receive incidental findings within the population who had agreed to participate.


A large proportion of adult patients, even among the elderly, are willing to actively participate and receive incidental findings in this systematic hospital-based precision and genomic medicine research program with broad consent.


  1. Collins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015;372(9):793–5. doi:.
  2. Muñoz M, Pong-Wong R, Canela-Xandri O, Rawlik K, Haley CS, Tenesa A. Evaluating the contribution of genetics and familial shared environment to common disease using the UK Biobank. Nat Genet. 2016;48(9):980–3. doi:.
  3. Leitsalu L, Alavere H, Tammesoo ML, Leego E, Metspalu A. Linking a population biobank with national health registries-the estonian experience. J Pers Med. 2015;5(2):96–106. doi:.
  4. Ashley EA. The precision medicine initiative: a new national effort. JAMA. 2015;313(21):2119–20. doi:.
  5. Kaiser J. NIH plots million-person megastudy. Science. 2015;347(6224):817. doi:.
  6. Mosley JD, Van Driest SL, Weeke PE, Delaney JT, Wells QS, Bastarache L, et al. Integrating EMR-linked and in vivo functional genetic data to identify new genotype-phenotype associations. PLoS One. 2014;9(6):e100322. doi:.
  7. Relling MV, Evans WE. Pharmacogenomics in the clinic. Nature. 2015;526(7573):343–50. doi:.
  8. Green RC, Berg JS, Grody WW, Kalia SS, Korf BR, Martin CL, et al.; American College of Medical Genetics and Genomics. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. 2013;15(7):565–74. doi:.
  9. Dewey FE, Murray MF, Overton JD, Habegger L, Leader JB, Fetterolf SN, et al. Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study. Science. 2016;354(6319):aaf6814. doi:.
  10. Hu Y, Li L, Ehm MG, Bing N, Song K, Nelson MR, et al. The benefits of using genetic information to design prevention trials. Am J Hum Genet. 2013;92(4):547–57. doi:.
  11. Bush WS, Oetjens MT, Crawford DC. Unravelling the human genome-phenome relationship using phenome-wide association studies. Nat Rev Genet. 2016;17(3):129–45. doi:.
  12. Storr CL, Or F, Eaton WW, Ialongo N. Genetic research participation in a young adult community sample. J Community Genet. 2014;5(4):363–75. doi:.
  13. McVeigh TP, Sweeney KJ, Kerin MJ, Gallagher DJ. A qualitative analysis of the attitudes of Irish patients towards participation in genetic-based research. Ir J Med Sci. 2016;185(4):825–31. doi:.
  14. Groth SW, Dozier A, Demment M, Li D, Fernandez ID, Chang J, et al. Participation in Genetic Research: Amazon’s Mechanical Turk Workforce in the United States and India. Public Health Genomics. 2016;19(6):325–35. doi:.
  15. Critchley C, Nicol D, Otlowski M. The impact of commercialisation and genetic data sharing arrangements on public trust and the intention to participate in biobank research. Public Health Genomics. 2015;18(3):160–72. doi:.
  16. Porteri C, Pasqualetti P, Togni E, Parker M. Public’s attitudes on participation in a biobank for research: an Italian survey. BMC Med Ethics. 2014;15(1):81. doi:.
  17. Platt T, Platt J, Thiel DB, Fisher N, Kardia SL. ‘Cool! and creepy’: engaging with college student stakeholders in Michigan’s biobank. J Community Genet. 2014;5(4):349–62. doi:.
  18. Murphy Bollinger J, Bridges JF, Mohamed A, Kaufman D. Public preferences for the return of research results in genetic research: a conjoint analysis. Genet Med. 2014;16(12):932–9. doi:.
  19. Mählmann L, Röcke C, Brand A, Hafen E, Vayena E. Attitudes towards personal genomics among older Swiss adults: An exploratory study. Appl Transl Genomics. 2016;8:9–15. doi:.
  20. Amiri L, Cassidy-Bushrow AE, Dakki H, Li J, Wells K, Oliveria SA, et al. Patient characteristics and participation in a genetic study: a type 2 diabetes cohort. J Investig Med. 2014;62(1):26–32. doi:.
  21. Freeman BD, Butler K, Bolcic-Jankovic D, Clarridge BR, Kennedy CR, LeBlanc J, et al. Surrogate receptivity to participation in critical illness genetic research: aligning research oversight and stakeholder concerns. Chest. 2015;147(4):979–88. doi:.
  22. Richards JE, Bane E, Fullerton SM, Ludman EJ, Jarvik G. Allocation of Resources to Communication of Research Result Summaries: Biobank Participant Perspectives. J Empir Res Hum Res Ethics. 2016;11(4):364–9. doi:.
  23. Middleton A, Morley KI, Bragin E, Firth HV, Hurles ME, Wright CF, et al.; DDD study. Attitudes of nearly 7000 health professionals, genomic researchers and publics toward the return of incidental results from sequencing research. Eur J Hum Genet. 2016;24(1):21–9. doi:.
  24. Allen NL, Karlson EW, Malspeis S, Lu B, Seidman CE, Lehmann LS. Biobank participants’ preferences for disclosure of genetic research results: perspectives from the OurGenes, OurHealth, OurCommunity project. Mayo Clin Proc. 2014;89(6):738–46. doi:.
  25. Ahram M, Othman A, Shahrouri M, Mustafa E. Factors influencing public participation in biobanking. Eur J Hum Genet. 2014;22(4):445–51. doi:.
  26. Bollinger JM, Scott J, Dvoskin R, Kaufman D. Public preferences regarding the return of individual genetic research results: findings from a qualitative focus group study. Genet Med. 2012;14(4):451–7. doi:.
  27. Dye T, Li D, Demment M, Groth S, Fernandez D, Dozier A, et al. Sociocultural variation in attitudes toward use of genetic information and participation in genetic research by race in the United States: implications for precision medicine. J Am Med Inform Assoc. 2016;23(4):782–6. doi:.
  28. Mooser V, Currat C. The Lausanne Institutional Biobank: a new resource to catalyse research in personalised medicine and pharmaceutical sciences. Swiss Med Wkly. 2014;144:w14033.
  29. Maurer F, Pradervand S, Guilleret I, Nanchen D, Maghraoui A, Chapatte L, et al. Identification and molecular characterisation of Lausanne Institutional Biobank participants with familial hypercholesterolaemia - a proof-of-concept study. Swiss Med Wkly. 2016;146:w14326.
  30. Maggo SD, Savage RL, Kennedy MA. Impact of New Genomic Technologies on Understanding Adverse Drug Reactions. Clin Pharmacokinet. 2016;55(4):419–36. doi:. Correction in: Clin Pharmacokinet. 2016;55(4):437.
  31. Trevisan C, Veronese N, Maggi S, Baggio G, Toffanello ED, Zambon S, et al. Factors Influencing Transitions Between Frailty States in Elderly Adults: The Progetto Veneto Anziani Longitudinal Study. J Am Geriatr Soc. 2017;65(1):179–84. doi:.
  32. Bledsoe MJ, Clayton EW, McGuire AL, Grizzle WE, O’Rourke PP, Zeps N. Return of research results from genomic biobanks: cost matters. Genet Med. 2013;15(2):103–5. doi:.
  33. Burke W, Evans BJ, Jarvik GP. Return of results: ethical and legal distinctions between research and clinical care. Am J Med Genet C Semin Med Genet. 2014;166(1):105–11. doi:.
  34. Jarvik GP, Amendola LM, Berg JS, Brothers K, Clayton EW, Chung W, et al.; eMERGE Act-ROR Committee and CERC Committee; CSER Act-ROR Working Group. Return of genomic results to research participants: the floor, the ceiling, and the choices in between. Am J Hum Genet. 2014;94(6):818–26. doi:.
  35. Shkedi-Rafid S, Dheensa S, Crawford G, Fenwick A, Lucassen A. Defining and managing incidental findings in genetic and genomic practice. J Med Genet. 2014;51(11):715–23. doi:.

Most read articles by the same author(s)