Skip directly to search Skip directly to A to Z list Skip directly to navigation Skip directly to page options Skip directly to site content

The Path from Genome-based Research to Population Health: Development of an International Public Health Genomics Network

This website is archived for historical purposes and is no longer being maintained or updated.

Burke, Wylie MD, PhD1; Khoury, Muin J. MD, PhD2; Stewart, Alison PhD3; Zimmern, Ronald L. MA, FFPHM4; for the Bellagio Group

Genetics in Medicine 2006; 8(7):451-58

From the 1Department of Medical History and Ethics, University of Washington, Seattle, WA; the 2Office of Public Health Genomics, Coordinating Center for Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA; the 3Public Health Genetics Unit, Strangeways Research Laboratory, Cambridge, UK; and the Public Health Genetics Unit, Strangeways Research Laboratory, Cambridge, UK; 4Members of the Bellagio Group are listed in the Acknowledgments.

Correspondence to Wylie Burke, MD, PhD, Department of Medical History and Ethics, University of Washington, Box 357120, 1959 Northeast Pacific, Room A204, Seattle, WA 98195-7120.

Received for publication: January 22, 2006
Accepted for publication: April 6, 2006

 

The health benefits of the Human Genome Project have been widely anticipated. Experts predict a new era of individualized disease prevention based on testing for genetic susceptibilities,(1) and safer, more effective use of drugs based on pharmacogenomic testing.(2) Genomic research is also predicted to improve disease classification and generate innovative therapies, targeted more precisely to the molecular mechanisms of disease.(3)

Early breakthroughs support this promise. Genetic testing can identify women at high risk for breast and ovarian cancer who may benefit from interventions such as breast screening by MRI and prophylactic oophorectomy.(4) Pharmacogenomic testing offers a potential means to increase the safety of drugs with narrow therapeutic indices, such as mercapotopurines(5) and warfarin.(6,7) Genetic analysis of disease processes such as cancer has also provided benefit: Overexpression of the HER2/neu gene provides an important prognostic indicator in breast cancer, and identifies patients most likely to benefit from the groundbreaking drug herceptin.(8) Similarly, imatinib mesylate, a novel cancer therapy, was developed as a result of analysis of the genetic changes in a specific type of leukemia.(9)

Despite these impressive early advances, serious reservations have been voiced about the occurrence and timing of a genomics revolution in medicine.(10) The relationship between DNA sequence and phenotype is far from simple, even for highly penetrant single gene conditions.(11,12) Most individual gene variants associated with common diseases will have low positive predictive value and associated attributable risk, raising questions about their clinical utility.(10,13,14) Also, an overemphasis on genetic contributors to disease may result in neglect of other factors, such as environmental exposures, social structure and lifestyle.(10)

Which vision of the future should the prudent clinician believe: A cornucopia of healthcare innovations based on genomic research, or a stream of genetically-based interventions that fail to deliver value to the public? We argue that both visions are correct; that genome-based research will offer unprecedented opportunities for improved disease prevention and therapy, but will also generate many promising ideas that do not ultimately provide a health benefit.

As with other emerging technologies, the pressing challenge is to devise an efficient strategy to distinguish innovative advances from false leads. The stakes are high, as healthcare systems face increasing strains with growing elderly populations and chronic disease burdens.(15) The potential benefits offered by the Human Genome Project and advances in related technologies need to be weighed against the resources required to implement them and the potential harms.

In this paper, we review the challenges in using genome-based research for the benefit of population health, make the case for an interdisciplinary knowledge integration process under the rubric of a field variously dubbed public health genetics or public health genomics, which is poised to address these challenges, and discuss the development of an international initiative to promote a collaborative approach to harness genome-based knowledge for the benefit of worldwide population health.

Using Genome-Based Research to Improve Health

Limitations in genetic prediction

Diseases due to single gene mutations are generally rare; for example, BRCA1 and BRCA2 mutations account for only 3-10% of breast cancer cases overall.(16) A somewhat larger proportion of diseases can be considered oligogenic, with disease risk due to the effects of a relatively small number of gene variants. For most diseases, however, etiology is multifactorial, with numerous genetic influences interacting with many different social and environmental factors. The specific gene variants contributing to disease, and the relative importance of genetic and nongenetic factors, may vary considerably among different people with a given disease. Because of the complexity of multifactorial disease etiology, there are inherent limitations in the potential for genetics to predict health status.

The key role of interventions

In addition, even when a genetic risk is substantial, knowledge of the risk contributes to improved health outcomes only if effective measures are available for preventive or early treatment. For example, APOE genotyping can identify an increased risk for Alzheimer Disease (AD),(17) but does not provide a health benefit because no preventive interventions are known. Moreover, despite the increased risk, a positive result is of relatively low predictive value; many people without the APOE4 allele associated with AD risk will also develop the disease. However, some people are likely to seek this risk information,(18) and it may provide some benefit by allowing people to make personal and family decisions based on risk knowledge. From a public health perspective, use of genetic tests for this purpose requires rigorous and systematic evaluation, to determine whether the benefits justify the potential harms and opportunity costs.

Similarly, genetic testing is of uncertain value when the available interventions are not genotype-specific. For example, people with factor V Leiden or the prothrombin variant G20210A have an increased risk for venous thrombosis (VT).(19) However, current data suggest that their recurrence risk for VT is not significantly elevated compared to other patients with VT.(20) As a result, genetic testing is not needed for clinical management.

Genetic testing will have its greatest public health value when it identifies individuals who would benefit from specific interventions based on their risk. This paradigm is the basis for newborn screening, and for the use of a small number of genetic tests, such as BRCA testing, which have become a part of clinical practice. By this reasoning, the public health value of APOE genotyping would increase if a specific therapy were identified to reduce AD risk in people with the APOE4 allele.

Could genetic risk be a motivator for behavioral change?

Even without genotype-specific interventions, some experts propose that knowledge of genetic risk can inform individuals about the lifestyle changes most beneficial for them, letting them know what health risks to worry about. This intuitively appealing argument is a hypothesis that remains to be tested.(21) The limited available data offer mixed results. Genetic tests identifying an increased risk for lung cancer do not appear to result in increased smoking cessation.(22,23) Conversely, genetic risk information may motivate participation in preventive screening: several studies have shown that the likelihood of participating in colorectal cancer screening is positively associated with having a family history of the disease.(24-28)

False reassurance is a risk of this approach. When genetic risk is emphasized, a test showing the absence of genetic risk for a condition such as cardiovascular disease, diabetes or cancer could send the message that there is no need to worry about that particular risk, yet the negative predictive value of such tests is likely to be very low.

Clearly, further research is needed. With the right combination of risk information and behavioral interventions, progress in lifestyle change might be possible. An important question from the population perspective will be the feasibility of using genetics to subcategorize populations, in order to achieve greater efficiency by directing appropriate interventions to those subpopulations rather than to the whole population.

Other uses of genetic information to improve health outcome

In addition to information about individual susceptibilities, genome-based research is generating knowledge about somatic genetic changes including somatic mutations occurring during carcinogenesis and profiles of gene expression that characterize specific disease states. This research may provide the basis for innovative drug development and for diagnostic and prognostic tests that guide clinical management. As with genetic susceptibility testing, careful evaluation of the predictive value of such tests and the effectiveness of related therapeutics or other interventions will be needed.

Genetic exceptionalism and the isolation of ELSI research

One of the challenges in the evaluation of genomic applications to healthcare is the integration of studies of the ethical, legal and social implications (ELSI) with those of clinical outcomes. The Human Genome Project allocated funds toward ELSI research and a vast amount of literature has resulted, but the separation of ELSI research from other scientific and clinical spheres has hampered a constructive contribution of ELSI research to the goal of improving population health. An example is the ACCE framework proposed for evaluation of genetic tests,(29) in which the scientific and clinical evaluation are considered separately from the ethical, legal and social consequences of a test, without guidance as to how these different spheres should inform each other.

This separation may be an outcome of genetic exceptionalism,(30) the concept that genetic information is uniquely powerful, and also uniquely dangerous and frightening, resulting in the need for special protections. This concept appears to result from the considerable hype, both positive and negative, that has surrounded the human genome project. Exaggerated claims about the predictive power of genetic information have been met by equally exaggerated warnings about the consequences of its misuse.

Need for an Evaluation Strategy

As genome-based research generates new ideas for healthcare innovation, there is a critical need for an evaluation process, based in ongoing integration of knowledge within and across multiple disciplines (including ELSI) to determine the outcomes, both health-related and social, of new genome-based applications. In the absence of a robust evaluation strategy, a trial-and-error process of innovation occurs. Resulting commercial incentives tend to promote the value of genetic tests based on the intuitive appeal of risk knowledge in the absence of proven benefit. This approach is already evident in direct-to-consumer and -physician marketing of genetic tests,(31,32) and represents a potential drain on healthcare resources. There is also a risk that effective innovations will not be implemented, or implemented haphazardly.(33,34)

The Public Health Genomics Enterprise

With these challenges in mind, an international expert workshop was convened in April, 2005, in Bellagio, Italy. The workshop was attended by a multidisciplinary group of 18 experts from Canada, France, Germany, the United Kingdom and the United States. A full report of the discussions and conclusions of the Bellagio workshop is available.(35) Participants at the meeting developed a consensus on the structure needed for effective translation of genome-based science and technology into improved population health. Figure 1 shows this concept in visual form.

The central role of knowledge integration

Knowledge integration, both within and across disciplines, is the driving force of the public health genomics enterprise. It is defined as the process of selecting, storing, collating, analyzing, integrating and disseminating information both within and across disciplines for the benefit of population health. It includes methodological development, and is the means by which information is transformed into useful knowledge.

Integration of knowledge within a discipline: HuGENet™ as a model

Genetic epidemiology offers an example of knowledge integration. This field has been dominated over the past 10-15 years by the search for associations between specific genetic variants and disease. The experience to date indicates that many initial reports of gene-disease associations are false-positive findings. Thus, before clinical applications can be considered, all the accumulated knowledge about a set of gene variants must be carefully assessed, including prevalence in different populations, the strength of the association with different disease endpoints, and interactions between gene variants and social and environmental determinants of risk. HuGENet™ (Human Genome Epidemiology Network), an initiative of the Office for Genomics and Disease Prevention (ODGP) at the US Centers for Disease Control and Prevention in Atlanta, GA, provides the basis for a constructive approach to this problem, and also represents a model for international collaborative efforts in other research areas.

HuGENet™ is now an international network comprising nearly 800 collaborators in 43 countries, with core activities consisting of information exchange through its Web site,(36) training and technical assistance, knowledge base development and information dissemination. As of December, 2005, 42 HuGE reviews have been published, each providing a structured and systematic summary of human genetic variation and its health implications at one or more gene loci.(36) In addition, more than 286 systematic reviews – including meta-analysis or pooled analyses – of gene-disease associations have been published since 2001.(36) An important function of these reviews is to identify gaps in existing epidemiological and clinical knowledge, informing the future research agenda. The structure of HuGENet™ is currently being revised along the lines of the highly successful international Cochrane Collaboration. Several HuGENet™ coordinating centers are being developed including Cambridge, Ottawa and Ioannina. Projects are underway to develop new systems for capturing and storing relevant data in an appropriate format for use in meta-analyses and systematic reviews.(37,38)

A related initiative, the Public Population Project in Genomics (P3G), has recently been launched.(39) This project has the goal of providing the international population genomics community with the resources, tools and know-how to facilitate data management for improved methods of knowledge transfer and sharing. Regular members are international, national or regional not-for-profit organizations that are or will be conducting a large population (N > 10,000 samples) genomics projects. Not-for-profit organizations and individuals committed to population genomics research genomics can join as Associate or Individual members.

Other disciplines might benefit from taking this coordinated approach. Genetic test evaluation is being approached piecemeal throughout the world, with initiatives using varying methodologies now underway under the auspices of both the European Union and the Organization for Economic Cooperation and Development, as well as in many individual countries including Canada, the UK and the US. Coordinating these activities through international networks like HuGENet™ and P3G would allow sharing of expertise and avoid wasteful duplication. Similarly, a joint approach to sustainable integration of genetics into existing mainstream medical specialties may be helpful.(40-42)

Integration of knowledge across disciplines

Creating productive collaboration in a single discipline is only the first step in knowledge integration. Knowledge and insight from many disciplines will be needed to fully evaluate the potential for genome-based research to improve population health. (Figure 1 ). Both medical and social outcomes of test use must be considered, and appropriate procedures must be implemented for practice guideline development, decision-making by healthcare payers, and population-based consultation and education. In addition, current ethical and regulatory frameworks need to be assessed for their appropriateness to new conceptual and technologic approaches based on genomic research.

Achieving knowledge integration across disciplines is not easy, but is essential to the tasks of public health genomics. Each discipline has its own language and means of communication, its own standards for success, and its own methods for sharing and discussing ideas and concepts. In addressing this problem, the Bellagio workshop participants found it helpful to define and distinguish two concepts: multidisciplinarity and interdisciplinarity. In a multidisciplinary collaboration, different professionals work on a common problem, interacting with each other but each contributing from within a defined disciplinary framework. The convening power of public health, in bringing people together and developing a shared sense of purpose and ownership, can be very fruitful in a multidisciplinary project. An example is the joint effort to identify and implement of a research agenda related to the discovery of the HFE gene and to develop education and guidelines for clinicians related to diagnosis of HFE-associated hemochromatosis (Appendix 1.2).

To achieve the novel integration or synthesis required in public health genomics, however, Bellagio participants identified the need to move further, toward an interdisciplinary collaboration, in which questions are framed and addressed jointly by persons trained in the different component disciplines. The need for such integration is apparent in debates about the contributions of ELSI research.

Integrating ELSI into the evaluation process
Workshop participants considered many issues evaluated in ELSI research as relevant to public health genomics, including the privacy of genetic information, the potential for genetic discrimination, both positive and negative, stigmatization and negative psychological consequences potentially arising from some genetic tests, the regulation of genetic tests, the governance of genomic research involving human subjects and/or human tissue (for example, population and patient-based biobank projects), the relationship between genetics and the concept of race, justice and equity in access to the benefits of genome-based research, and the use of genetic testing in the context of reproductive choice.

Participants concluded, however, that research addressing these issues often has little impact on efforts to improve population health. One problem is the tendency for the research to occur in isolation, because of the absence of an effective relationship between academic ELSI research and policy-makers and the separation of ELSI research from other scientific and clinical spheres. The promotion of interdisciplinarity would increases the potential for ELSI research to make constructive contributions.

Another problem is the frequent use of genetic exceptionalism as a frame for issues related to genetics and genomics. Bellagio workshop participants, in accord with a multidisciplinary group convened by the European Commission,(4)3 favored moving away from genetic exceptionalism. Genetic determinants should be neither privileged nor unreasonably demonized.(30) As an example, the widespread use of Huntington’s disease – a highly-penetrant and fatal late-onset condition for which no effective treatment exists – as a paradigm for predictive genetic testing should be actively discouraged, as it gives a highly misleading idea of the predictive power of genetic information for most people. Examples drawn from common diseases, such as the genetic contributors to venous thrombosis,(19,20) Alzheimer Disease,(17) and other common disorders of public health significance (10,14) are more readily generalizable.

Normalizing genetics as a contributor to risk, and as a result, achieving more balanced public dialogue, will enable a more rational approach to the use of genetics to benefit population health. At the same time, some of the debate surrounding genetics has pointed to the need for more adequate regulation and protection in other areas of biomedical research and clinical practice.

Making Use of Knowledge Integration

The integrated multidisciplinary knowledge generated from an effective public health genomics enterprise supports four core activities (Figure 1 ):

  • Informing public policy: Included in this activity are legal, philosophical and social analyses, development of regulatory frameworks, engagement in the policy-making process, promoting relevant research, seeking international comparisons, and working with governments and relevant public institutions.
  • Developing and evaluating preventive and clinical health services: This activity includes strategic planning; service organization, manpower planning and capacity building; service review, assessment and evaluation; and guideline development.
  • Communication and stakeholder engagement: Relevant activities include promoting general genetic literacy in society, public dialogue, and engaging with industry, which is seen as a key player in the development of new genomics-based clinical interventions.
  • Education and training: This will involve promoting genetic literacy for health professionals, specific training for public health genetics specialists, and development of educational materials, courses, workshops and seminars.

Educational programs in public health genetics/genomics are already underway at some centers (Appendix 1.3). These efforts provide essential preparation for the multidisciplinary work envisaged for the translation of genome-based research into actions for population health, and serve as another important area for collaboration. There is a need to develop and disseminate competencies for public health genomics, which will differ substantially from competencies already developed, by NCHPEG and others, for genetics education in specific clinical fields.

This conceptual framework for public health genomics recognizes the importance of applied and translational research in achieving the goal of improving population health. Research activities inevitably identify gaps in the knowledge base that need to be addressed by further basic research (Figure 1 ). The boundaries between basic and applied research are indistinct, and the continuum from research to practice may be better represented by the term frontier research proposed in a recent European public report.(44) The dynamic and interactive nature of the enterprise is represented by double-headed arrows (Figure 1 ): It is informed by societal priorities,(45) generates knowledge as well as using it, and is modulated by the effects of its own outputs and activities. Thus, public health genomics incorporates a cycle of analysis-strategy-action (implementation)-evaluation, a widely recognized approach in public health practice. This cycle, which is equivalent to the US Institute of Medicine’s cycle of assessment-policy development-assurance,(46) describes how the enterprise carries out its activities.

An International Public Health Genomics Network

After laying the groundwork describing the components of the public health genomics enterprise, the Bellagio workshop participants unanimously agreed to establish an international forum to address the global challenge for integrating and using genome-based knowledge and technologies for the benefit of population health. The forum will be known as the Genome-based Research and Population Health International Network or GRAPH Int. The use of the term Int signifies that the collaboration is not only international but also interdisciplinary and integrated. GRAPH Int is an international collaboration that facilitates the responsible and effective translation of genome-based knowledge and technologies into public policies, programs and services for the benefit of population health. Membership of GRAPH Int is open to all individuals and organizations that have an interest in this mission. Six initial goals for GRAPH Int were defined:

  1. To provide an international forum for dialogue and collaboration
  2. To promote relevant research
  3. To support the development of an integrated knowledge base
  4. To promote education and training
  5. To encourage communication and engagement with the public and other stakeholders
  6. To inform public policy

GRAPH Int will provide a concerted global approach to build the infrastructure that will be needed for the translation of developments in genome-based research into effective interventions to improve population health. International consensus has been reached on the scope and strategy for this enterprise. GRAPH Int, a new international forum and network, welcomes all those who wish to participate in this enterprise and invites them to work together to achieve its goals. A coordination and communication hub will be provided by the Public Health Agency of Canada.(47) The first meeting of this international forum occurred at the International Genomics and Public Health meeting in Montreal, Canada, June 4-7, 2006.(48)

In summary, while the Human Genome Project and advances in molecular biology have forever changed the face of science, application of these scientific discoveries for the benefit of population health is a major challenge worldwide. We hope that the implementation of the public health genomics enterprise around the world facilitated by the newly formed international network could over time begin to harness genome-based sciences and technologies for the benefit of population health in the 21st century.

Acknowledgements

We gratefully acknowledge the support of the Rockefeller Foundation and the help of the staff at the Rockefeller Foundation Study and Conference Center in Bellagio, Italy.

We also acknowledge the invaluable contributions of the participants in the Bellagio meeting, who included: Judith Allanson, MD, Chief of the Department of Genetics, Children’s Hospital of Eastern Ontario and Professor of Pediatrics, University of Ottawa; Angela Brand, MD, PhD, MPH, Professor for Social Medicine & Public Health, German Centre for Public Health Genomics, University of Applied Sciences, Bielefeld; Hilary Burton, MA, BM, BCh, FFPHM, Consultant in Public Health Medicine, Public Health Genetics Unit, Cambridge; Anne Cambon-Thomsen, MD, Director of Research, National Centre for Scientific Research, National Institute for Health and Medical Research Inserm U 558, Toulouse Cedex; Sian Griffiths, MA, MB BChir, FFPHM, Professor of Public Health, The Chinese University of Hong Kong; Mohamed Karmali, MD, Director-General, Laboratory for Foodborne Zoonoses, Public Health Agency of Canada, Ontario, Canada; Elena Khlinovskaya Rockhill, PhD, Research Associate, Department of Social Anthropology, University of Cambridge; Bartha Knoppers, JD, PhD, Canada Research Chair in Law & Medicine, University of Montreal; Julian Little, PhD, Canada Research Chair in Human Genome Epidemiology, University of Ottawa; Teri Manolio, MD, PhD, Director of Epidemiology & Biometry, National Heart, Lung & Blood Institute; Theresa Marteau, PhD, Professor of Health Psychology, Psychology & Genetics Research Group, King’s College London; Thomas Murray, PhD, President, The Hastings Center; Linda Rosenstock, MD, MPH, Dean of School of Public Health, University of California, Los Angeles; Julian Sampson, DM, Professor of Medical Genetics, Cardiff University.

References

  1. Collins FS. Shattuck lecture-medical and societal consequences of the Human Genome Project. N Engl J Med 1999;341:28-37.
  2. Roses AD. Pharmacogenetics and drug development: the path to safer and more effective drugs. Nat Rev Genet 2004;5:645-656.
  3. Austin CP. The impact of the completed human genome sequence on the development of novel therapeutics for human disease. Annu Rev Med 2004;55:1-13.
  4. Nelson HD, Huffman LH, Fu R, Harris EL. Genetic Risk Assessment and BRCA Mutation Testing for Breast and Ovarian Cancer Susceptibility: Systematic Evidence Review for the U.S. Preventive Services Task Force. Ann Intern Med 2005;143:362-379.
  5. Weinshilboum R. Thiopurine pharmacogenetics: clinical and molecular studies of thiopurine methyltransferase. Drug Metab Disp 2001;29:601-605.
  6. Higashi MK, Veenstra DL, Kondo LM, Wittkowsky AK, et al. Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy. JAMA 2002;287:1690-1698.
  7. Rieder MJ, Reiner AP, Gage BF, Nickerson DA, et al. Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N Engl J Med 2005;352:2285-2293.
  8. Emens LA. Trastuzumab: targeted therapy for the management of HER-2/neu-overexpressing metastatic breast cancer. Am J Ther 2005;12:243-253.
  9. Krause DE, Van Etten RA. Tyrosine kinases as targets for cancer therapy. N Engl J Med 2005;353:172-187.
  10. Holtzman NA, Marteau TM. Will genetics revolutionize medicine? N Engl J Med 2000;343:141-144.
  11. Dipple KM, McCabe ER. Modifier genes convert simple Mendelian disorders to complex traits. Mol Genet Metab 2000;71:43-50.
  12. Beutler E. Discrepancies between genotype and phenotype in hematology: an important frontier. Blood 2001;98:2597-2602.
  13. Hubbard R, Lewontin RC. Pitfalls of genetic testing. N Engl J Med 1996;334:1192-1194.
  14. Vineis P, Schulte P, McMichael AJ. Misconceptions about the use of genetic tests in populations. Lancet 2001;357:709-712.
  15. World Health Organization. The world health report 2003 – shaping the future. Available at: http://www.who.int/whr/2003/en/index.html.
  16. Neuhausen SL. Ethnic differences in cancer risk resulting from genetic variation. Cancer 1999;86:2575-2582.
  17. Mayeux R, Schupf N. Apolipoprotein E and Alzheimer’s disease: the implications of progress in molecular medicine. Am J Public Health 1995;85:1280-1284.
  18. Roberts JS, Barber M, Brown TM, Cupples LA, et al. Who seeks genetic susceptibility testing for Alzheimer’s disease? Findings from a multisite, randomized clinical trial. Genet Med 2004;6:197-203.
  19. Reich LM, Bower M, Keys NS. Role of the geneticist in testing and counseling for inherited thrombophilia. Genet Med 2003;5:133-143.
  20. Christiansen SC, Cannegieter SC, Koster T, Vandenbroucke JP, et al. Thrombophilia, clinical factors, and recurrent venous thrombotic events. JAMA 2005;293:2352-2361.
  21. Marteau TM, Lerman C. Genetic risk and behavioural change. BMJ 2001;322:1056-1059.
  22. Audrain J, Boyd NR, Roth J, Main D, et al. Genetic susceptibility testing in smoking-cessation treatment: one-year outcomes of a randomized trial. Addict Behav 1997;22:741-751.
  23. McBride CM, Bepler G, Lipkus IM, Lyna P, et al. Incorporating genetic susceptibility feedback into a smoking cessation program for African-American smokers with low income. Cancer Epidemiol Biomarkers Prev 2002;11:521-528.
  24. Slattery ML, Edwards SL, Ma KN, Friedman GD. Colon cancer screening, lifestyle, and risk of colon cancer. Cancer Cause Control 2000;11:555-563.
  25. Mandelson MT, Curry SJ, Anderson LA, Nadel MR, et al. Colorectal cancer screening participation by older women. Am J Prev Med 2000;19:149-154.
  26. Madlensky L, Esplen MJ, Gallinger S, McLaughlin JR, et al. Relatives of colorectal cancer patients: factors associated with screening behavior. Am J Prev Med 2003;25:187-194.
  27. Ramji F, Cotterchio M, Manno M, Rabeneck L, et al. Association between subject factors and colorectal cancer screening participation in Ontario, Canada. Cancer Detect Prev 2005;29:221-226.
  28. Slattery ML, Kinney AY, Levin TR. Factors associated with colorectal cancer screening in a population-based study: the impact of gender, healthcare source, and time. Prev Med 2004;38:276-283.
  29. Office of Genomics and Disease Prevention, Centers for Disease Control and Prevention. ACCE model system for collecting, analyzing, and disseiminating information on genetic tests. Available at: https://www.cdc.gov/genomics/gtesting/ACCE/fbr/.
  30. Murray TH. Genetic exceptionalism and future diaries – is genetic information different from other medical information? In Rothstien M ed., Genetic Secrets: Protecting Privacy and Confidentiality in the Genetic Era. New Haven, Yale University Press, 1997.
  31. Gollust SE, Wilfond BS, Hull SC. Direct-to-consumer sales of genetic services on the Internet. Genet Med 2003;5:332-337.
  32. Williams-Jones B, Corrigan OP. Rhetoric and hype: where’s the ‘ethics’ in pharmacogenomics? Am J Pharmacogenomics 2003;3:375-383.
  33. Berwick DM. Disseminating innovations in healthcare. JAMA 2003;289:1969-1975.
  34. Greenhalgh T, Robert G, MacFarlane F, Bate P, et al. Diffusion of innovations in service organizations: systematic review and recommendations. Milbank Quarterly 2004;82:581-629.
  35. Genome-based Research and Population Health. Report of an expert workshop held at the Rockefeller Foundation Study and Conference Center, Bellagio, Italy, 14-20 April, 2005.
  36. Centers for Disease Control and Prevention. Human Genetic Epidemiolgy Network. Available at: https://www.cdc.gov/genomics/hugenet/.
  37. Derré M, Gourraud P-A, Larré J-M, Barnetche T, et al. Towards a meta-analysis of HLA region microsatellites, the MAMSat project. Tissue Antigens 2005;66:562.
  38. Gourraud PA, Mano S, Barnetche T, Carrington M, et al. A Integration of microsatellite characteristics in the MHC region: a literature and sequence based analysis. Tissue Antigens 2004;64:543-555.
  39. Public Population Project in Genomics (P3G). Available at: http://www.p3g.org.
  40. Bell J. The new genetics in clinical practice. BMJ 1998;316:618-620.
  41. Fears R, Roberts D, Poste G. Rational or rationed medicine? The promise of genetics for improved clinical practice. BMJ 2000;320:933-935.
  42. Day IN, Wilson DI. Science, medicine, and the future: Genetics and cardiovascular risk. BMJ 2001;323:1409-1412.
  43. McNally E, Cambon-Thomsen A, Brazell C, Cassiman JJ, et al. The 25 recommendations on the ethical, legal and social implications of genetic testing. European Commission. EUR 21120 – Luxembourg: Office for Official Publications of the European Communities 2004.
  44. Harris WC, Martin B, Bonaccorsi A, Flensted-Jensen M, et al. Frontier research: a European challenge. European Commission. EUR 21619 Luxembourg: Office for Official Publications of the European Communities 2005.
  45. Knoppers BM. Of genomics and public health: building public goods? CMAJ 2005;173:1185-1186.
  46. Beskow L, Khoury MJ, Baker T, Thrasher J. The integration of genetics into public health research, policy and practice: a blueprint for action. Community Genet 2001;4:2-11.
  47. GRAPH Int. Genome-based Research and Population Health.
    Available at: http://www.graphint.org/ver2/
  48. International Genomics and Public Health. 4th Annual DNA Sampling Conference.
Format:
TOP