EUGLOREH project
THE STATUS OF HEALTH IN THE EUROPEAN UNION:
TOWARDS A HEALTHIER EUROPE

FULL REPORT

PART III - HEALTH CAUSES, FACTORS AND DETERMINANTS

10. HEALTH DETERMINANTS

10.2. Individual characteristics

10.2.4. Genetics and genomics

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10.2.4. Genetics  and genomics

 

Acronyms

 

CoE

Council of Europe

DG SANCO

Directorate-General for Health and Consumer Protection

 

of the European Commission

DNA

Deoxyribonucleic Acid

EGAN

European Genetic AlliancesNetwork

EURORDIS

European Organisation for Rare Diseases

HiaP

Health in all Policies

ICD

International Statistical Classification of Diseases and Related

 

Health Problems

IPTS

Institute of Prospective Technology Studies (part of the EC

 

Joint Research Centre)

KBBE

Knowledge-based Bio-Economy

OECD

Organisation for Economic Co-operation and Development

Orphanet

European Database of Rare Diseases and Orphan Drugs

PHG

Public Health Genomics

PHGEN

Public Health Genomics European Network

REACH

Registration, Evaluation, Authorisation and Restriction of

 

Chemicals 

RNA

Ribonucleic Acid

TMA

Tissue Micro Arrays

UNESCO

United Nations Educational, Scientific and Cultural

 

Organization

WHO

World Health Organisation

APOE

Apolipoprotein E

MTHFR

Methylenetetrahydrofolate reductase

 

 

10.2.4.1. Introduction

 

  

Insofar, genome-based knowledge and technologies are promoting a paradigm shift in public health. The main challenges for public health in the future will be to develop new approaches of health indicators based on genotyping as well as infrastructures for the management of individual genome-based health information.

 

Clarifying the general conditions under which genome-based health information and technologies can be put to best practise in the interest of public health and particularly considering the economic, ethical, legal and social implications is presently the most pressing task of the emerging field of Public Health Genomics.

 

The next decade will provide a window of opportunity to establish infrastructures both in the health care sector and on a policy level across Europe and globally, that will enable the scientific advances to be effectively, efficiently and socially acceptable translated into evidence-based policies and interventions that improve population health.

 

The level of genome-based knowledge in certain fields like diabetes type 2 (Hoffmann et al, 2007) require an urgent shift of prevention but Public Health practitioners so far seem to be reluctant to draw conclusions from the existing evidence.

 

A comprehensive health care which regards genetic determinants, besides environmental, social and life style factors, will become essential as it creates new opportunities for target-oriented and individualised strategies in preventive medicine and early detection of illnesses due to the availability of “personal genomes” and individual genome-based health information. The integration of genome-based knowledge and technologies will change primary, secondary and tertiary prevention. alia, by applying systems-biology approaches to integrated personal data sets, disease prevention programmes and clinical interventions will be specifically targeted at susceptible individuals, families and sub-entities of populations based on their genomic risk profile (Lunshof et al., 2008).

 

The upcoming post-genomic health care system also challenges the existing concepts of surveillance and health statistics. As it  will be described later in the Chapter no indicators for the implementation of genomics information into public health exist so far. Nevertheless, indicators and statistical material are needed and have to be developed for secondary health data such as the exposure to toxic substances (toxico-genomics) or the impact of food on human health (nutria-genomics). Current health statistics and surveillance systems do not cover underlying biological factors of diseases such as genomic variants. Nonetheless, the occurrence of pleiotropic effects demonstrates already that it may not be sufficient to measure the prevalence of diseases if the surveillance is purely based on phenotypic effects. Furthermore, by considering only phenotype data instead of genotype-phenotype data, there is a systematic bias of under- and over-reporting, since currently measured prevalence data do not reflect the “realnumber of instances of a given disease or other condition in a given population at a designated time. The future use of indicators and health statistics will also depend on the level of individualisation in health care systems. Indicators and statistics can only be used if the genomic risk stratification shows outcomes which lead to the description of groups with a significant size.

 

The Human Genome Project, the International HapMap Project and the Personal Genome Project as well as systems-biology approaches, the development of new genetic tests, DNA chip technologies and related technologies, in particular high-throughput, low-cost sequencing, offer new opportunities for the promotion of population health which will lead to fundamental challenges in the healthcare delivery systems. Medicine and Public Health get an increasing insight into the biological factors which drive disease mechanisms, in particular in the field of cancer. Health care systems, policy makers and industries are struggling to transfer the emerging knowledge through translational research into clinical and technological applications. The emerging genome-based health information and technologies deserves new concepts in the understanding of health and diseases as well as new concepts of prevention and health service delivery and calls for a paradigm shift in Public Health; however,  all health stakeholders are not fully prepared for the conceptual change. Public Health Genomics advocates the interdisciplinary discourse on and the understanding of genomics; it fosters progress in translational research and supports the introduction of these new concepts of risk stratification and prevention.

 

10.2.4.2. Data sources

 

The role of genetics and genomics in data collection has dramatically changed in the last two decades from genetic disease and inherited genetic variation to biological markers of all types and systems biology. These advances which are primarily affected by basic research are also affecting the need for data gathering and health statistics in genomics. Up to now European health statistics cover the prevalence and incidence of diseases but they are not designed to compile information on the biological aetiology of disease. Therefore the traditional tools of monitoring and surveillance do not reflect the needs of researchers and policymakers in Public Health Genomics.

 

At present the role of genetic susceptibilities and other biomarkers in systems biology and complex diseases is discussed mainly in the clinical setting. The main burden of disease can be associated with the so-called common complex genetic disorders, often named multifactorial diseases. Still, the statistical data are unable to communicate the underlying biological factors which contribute to the occurrence and prevalence of such diseases. The Wellcome Trust Case Control Consortium has recently published the preliminary results of a genome-wide association study which highlights the manifold Public Health challenges deriving from genetic research in a journal paper which covered 14.000 cases and 3000 shared controls for seven major common diseases (Wellcome Trust 2007).

 

The advances in Public Health monitoring do not correspond yet to the emerging knowledge we have seen in genomics in the past decade. The few existing information sources provide policy makers and researchers with piecemeal information which are often both disease and mutation specific. European networks like Orphanet and EURORDIS and their respective national affiliates are collecting data on rare genetic disorders (see Chapter 7 on Rare Diseases). These diseases are monogenic and have a low frequency in European populations. Rare diseases require a specific infrastructure and a solid cooperation amongst Member States as in most cases only a few reference laboratories can perform the tests. For the multifactorial diseases which constitute the main burden of disease, we do not have monitoring and surveillance systems at present which are designed to gather information that capture genotypic and phenotypic information in a desired way. Moreover, common complex disorders require the integration of genome-based and secondary data in both the medical and Public Health setting.

 

10.2.4.3. Data description and analysis

 

In the past twenty years, the advances in genome research have revolutionized knowledge of the role of inheritance in health and disease. Nowadays, it is known that DNA determines not only the cause of single-gene disorders, which affect millions of people worldwide, but also predispositions (“susceptibilities”), which are based on genotype and haplotype variants, to common diseases. The new technologies will allow researchers to examine genetic mutations at the functional genomic unit level, and to better understand systems biology, epigenomic and pleiotropic effects, the significance of environmental factors such as chemical agents, nutrition or personal behaviour in relation to the causation of diseases like cardiovascular diseases , allergies, cancer, psychiatric disorders or infectious diseases. There are already many good examples such as the interaction of APOE polymorphisms with smoking and alcohol on the risk of cardiovascular diseases and dementia or as the interaction of MTHFR C677T polymorphism (especially in women) with smoking on the risk of multiple myeloma, coronary heart diseases, pre-menopausal breast cancer, schizophrenia and recurrent pregnancy losses..

 

Currently, the followingtrends” can be observed regarding the understanding of diseases, due to novel genome-based knowledge:

 

·          the potential of an earlier and more precise identification of risk strata in families and subgroups of the population (i.e., the identification of high, moderate and low risk groups; the stratification by “genome-based standardisation” in addition to age and sex standardisation of diseases);

·          the differentiation between several disease (sub)entities resulting in the same phenotype (e.g., breast cancer or obesity), which are either following mainly a mendelian trait (“inherited”) or mainly a genomic-environmental pattern: i.e. although having the same phenotype this phenotype subsumes totally different disease entities;

·          the concept of a genomic variant being in individuals a risk factor and a protective factor at the same time (e.g., the role of ACE insertion-deletion polymorphism in stroke (increase of risk) and Alzheimer’s disease (decrease of risk) (Lehmann et al., 2005);

·          pleiotropic effects of susceptibility genes in complex diseases being associated to more than one disease (e.g., the role of G-308A TNF alpha gene variant in obesity, asthma and non-Hodgkin lymphoma) (Sookoian et al, 2005; Gao et al, 2006; Rothman et al, 2006): by this, we see a shift from a disease-specific orientation to  “disease clusters”, “disease syndromes” and “health outcomes”;

·          the potential of individual genomic profiling: i.e., the concurrent detection of multiple genomic variants that have been associated with greater risk or predisposition to a particular disease or condition as the basis for individual health information management. Here, the individual genotype status on all genomic variants increases or decreases the risk for certain diseases;

·          the shift from carrier screening to a screening based on individual genomic profiling;

·          the impact of genetic variants on the metabolism of drugs and the development of drug targets

·          the role of genomic determinants not only within a bunch of other health determinants (e.g. social, behavioural, environmental, biological) but also as a modifier and triggering factor (e.g., epigenomic effects or the triggering role of infectious diseases such as human papilloma virus in cervical cancer or adenovirus in obesity);

·          the role of genomic determinants as “necessary but not sufficientdeterminants in the development of complex diseases and health problems;

·          correlation of individual pathways in systems biology with onset, severity and prolongation of diseases as well as with response to therapies;

·          the differentiation between predictive tests (i.e., tests with 0-100% probability being a continuum and referring to monogenetic as well as to complex diseases) on the one hand and tests for diseases with high penetrance (referring to monogenetic diseases as well to complex diseases followingmendelian trait) and low or moderate penetrance (most complex diseases) on the other hand; and

·          shift in the definitions: from “genetic test” to “genomic variant” to “genome-based health informationbased on a “personal genome”.

 

Besides that novel knowledge, also accompanying novel technologies, such as high-throughput and low cost sequencing, are already triggering the shift in the comprehension of health and disease as well as in the understanding of new approaches to prevention and therapy (Khoury, 1996; Brand, 2002; French and Moore 2003). For example, high-throughput technologies such as tissue microarrays (so-called TMAs) have the potential to screen large numbers of molecular targets in tumor samples for rapid causal, prognostic, diagnostic, or therapeutic purposes (Torhorst et al., 2001). Complementary to the conventional microarray gene expression profiling, population-based TMAs can be implemented to quickly validate gene expression microarray data in a larger population of tissue samples. This will provide information at the microanatomical level by the use of immunohistochemistry for proteins and in situ hybridization for RNA (Hoos et al., 2001). Through population-based TMAs, it will be possible to assess multiple genomic and protein differences among malignancies such as colorectal cancer, breast cancer, gliomas or rhabdomyosarcoma and thus studying the molecular and cytogenetic changes associated with these malignancies, including human carcinogenic infections (Kononen et al., 1998). In pharmacogenomics new technologies are used to reduce negative side-effects of drugs as physicians and policy makers are empowered to stratify genome-based risks (Roberts et al., 2000). Still, if we look at the metabolism of drugs and the impact of the CYP system, we do not see any Public Health oriented sets of data which are available in Europe.

 

The level of genome-based knowledge in certain fields like diabetes type 2 (Hoffmann et al, 2007) require an urgent shift of prevention but Public Health practitioners so far seem to be reluctant to draw conclusions from the existing evidence. In order to make sound policy judgements, Public Health practitioners will need to integrate information deriving from statistics, genomic research, the family history, individual genomic variants and the individual exposure to exogenous risks. In the field of infectious diseases the situation is slightly different as pandemics have alerted all stakeholders that genome-based knowledge needs to be used to prevent future incidents.

 

 

 

10.2.4.4. Control tools and policies

 

The issue of genetics and genomics has been in the centre of the public debate for almost two decades. International organisations like the UNESCO, the WHO and the OECD have set up policy statements and guidelines in the field of genetics/genomics. Amongst the countless statements and recommendations, the 1997 UNESCO Declaration on the Human Genome and Human Rights (UNESCO, 1997), the 2003 UNESCO International Declaration on Human Genetic Data (UNESCO, 2003) and the 1997 Council of Europe Convention on Human Rights and Biomedicine (Council of Europe, 1997) are the most cited. None of the declarations and conventions gives significant attention to the needs of Public Health in the context of genomics. The European Union has regulated certain aspects which affect genomics, but so far there has been no coherent and comprehensive regulation or best practices which address all issues relevant to genomics and Public Heath. The Institute of Prospective Technology Studies (IPTS) of the EC-Joint Research Centre has analysed important socio-economic issues, in particular in the 2003 study “Towards quality assurance and harmonisation of genetic testing services in the EU” (Ibarreta et al, 2003) and the 2007 studyBIO4EU” (Zika et al,2007).

 

Some Member States of the EU have developed their own sector-specific legislative framework in the 1990's. Austria was the first country with its Gentechnikgesetz from 1991 and countries like France and Estonia have followed the Austrian example. In recent years the process has slowed down and more normative competence has been handed over to professional bodies and associations. The existing regulatory framework is focusing on the DNA/RNA analysis technology rather than on the use of genome-based health information and the societal impact of genome-based knowledge in general. Research in the different areas of genomics has shown that the initial genetic exceptionalism and determinism which fuelled the new sector-specific laws in the 1990's are unjustified. Only in the field of rare diseases most of the arguments of exceptionalism and determinism are well grounded. Several European initiatives such as EGAN, EURORDIS and Orphanet are addressing the special policy needs of rare diseases; further legislative work may be needed as more knowledge is emerging.

 

The DG SANCO fundedPublic Health Genomics European Network (PHGEN)” is currently drafting a European policy perspective which addresses the needs of Public Health in the EU (www.phgen.eu). PHGEN follows the internationally acknowledged Bellagio Statement of Public Health Genomics (www.graphint.org). The network takes into account the two main policy frames in the field. The DG SANCO is also running several working parties and networks of National Competent Authorities. Amongst them there are groups working specifically on health monitoring and data collections.

 

The “Health in all Policies” (“HiaP”) approach was developed under the Finnish presidency and has been further promoted by the Ministerial Conference organized by the Italian Ministry of Health, in collaboration with EC and WHO/EURO, in Rome on 18 December 2007. This concept is also rooted in Art 152 of the revised EC Treaty. The Commission and the European Parliament are obliged to strive for a high level of health protection in all their policies. In various regulatory areas such as food labelling, smoking, advertisement, toxic products (“REACH”), workplace regulations, pharmaceuticals and health services the “Health in all Policiesdoctrine calls for the integration of genome-based knowledge. In fact, the “Health in all Policiesapproach can only be successful if genome-based knowledge is integrated into political decision making processes. The new mode of health regulation depends on a sound evidence base and this evidence base would be incomplete and misleading if genomic knowledge is excluded.

 

The German presidency put the “Knowledge-based Bio-Economy” (“KBBE”) forward which aims to integrate both the “Health in all Policiesidea and the Lisbon Strategy for more growth. Biotechnology is seen as one of the key industries for the economic future of Europe and genomics enables researchers and the industry to understand the biological factors which determine the future perspectives of the markets.

 

10.2.4.5. Future developments

 

Insofar, genome-based knowledge and technologies are promoting a paradigm shift in public health. In the past we started our public health tasks by looking at the population first, identified high risk groups and implemented interventions for subgroups of the population (e.g. newborn screening, breast cancer screening, HIV screening, specific screening options for migrants, carrier screening). At present we already start our public health tasks by looking at family histories first, identify high risk families based on “disease syndromes” and implement family-oriented preventive interventions. In the future we may start our public health tasks by looking at the individual first, identify individual risks based on individual genomic profiling and may then implement personalized preventive strategies.

 

The trends, which have been briefly described here, show that the integration of genome-based knowledge into health reporting will be one of the most important challenges that our health care systems will face (Collins et al, 1998; Childs and Valle, 2000; Collins and McKusick, 2001; Burke, 2003Ellsworth and O'Donnell, 2004): in the future it will be almost impossible not only to group diseases according to ICD10, but also to use the traditional and well established health indicators for health reporting and health planning, since they refer to the phenotype and not to the genotype. Thus, it will be questionable whether the traditional concepts of health indicators still apply. All health indicators, which have been developed so far, will have to be reanalysed in the realm of genomics. Also, it remains to be seen whether it will be possible to develop new approaches of health indicators. The implementation of long running cohort studies starting as early as possible in life and including nested case-control studies at various ages and at various occasions as well as the implementation of case-control studies in the very old population may help to generate hypotheses on genomic-environmental associations as well as on “disease clustersbased on pleiotropic effects and to develop such new health indicators. In addition to these large-scale population-based biobank approaches, the application of systems biology approaches to integrated personal data sets may already contribute in the near future to the development of such new indicators

 

Thus, the main challenges for public health in the future will be to develop new approaches of health indicators based on genotyping as well as infrastructures for the management of individual genome-based health information. At the same time, the traditional separation in public health reporting between communicable and non-communicable diseases and also between rare and common diseases may  no longer be valid: non-communicable diseases are triggered by communicable diseases (e.g. obesity by adenoviruses) and one phenotype (e.g. obesity) can be rare in the one case (e.g., due to MC4R mutant and being resistant to any diet or physical activity) or common in the other case (due to environmental factors).

 

The integration of genomics into Public Health research, policy and practice will be one of the most important future challenges for all health care systems. Clarifying the general conditions under which genome-based health information and technologies can be put to best practise in the field of Public Health and particularly considering the economic, ethical, legal and social implications is presently the most pressing task of the emerging field of Public Health Genomics (PHG), defined as the application of genetic and molecular science to the promotion of health and prevention of disease through the organised efforts of society (Brand, 2005). Policymakers now have the opportunity to protect consumers, to monitor the implications of genomics for health, social, and environmental policy goals, and to assure that genomics advances will be taped not only to treat medical conditions, but also to prevent disease and improve health (Brand et al., 2006). Policy must find an acceptable balance between providing strong protection for individualsinterests while enabling society to benefit from genomics (Schulte in den Bäumen, 2006). In the field of indicators, health statistics and surveillance, the upcoming genomic knowledge may require fundamental changes and a new infrastructure. The more individual prevention and therapy develop the more the use of the traditional tools will become difficult. Thus, European and global initiatives are setting up new biobanking and surveillance projects which are designed to complement the current actions. For the Public Health community the paradigm shift associated with genomics has implications on the training of professionals, the understanding of the causes of disease, the organisation of services and the communications with stakeholders. In genomics it is no longer possible to work with “simplemessages which are targeted at whole populations. The current research in genomics more than indicates that we see an increasing individualisation of prevention. Thus, Public Health will come under pressure to follow this approach by redefining the methods and concepts developed in the “oldphenotypic and socio-economic period. Genomics adds a new dimension to these concepts as it calls for an integration of knowledge deriving from diverse sources such as social epidemiology, systems biology, genetic epidemiology, toxico-genomics, nutria-genomics and genetics to name only a few.

 

The next decade will provide a window of opportunity to establish infrastructures both in the health care sector and on a policy level across Europe and globally, that will enable the scientific advances to be effectively, efficiently and socially acceptable translated into evidence-based policies and interventions that improve population health.

 

10.2.4.6. References

 

Brand A (2002): Prädiktive GentestsParadigmenwechsel für Prävention und Gesundheitsversorgung? Gesundheitswesen, 64: 224-229.

 

Brand A (2005): Public health and genetics—a dangerous combination? European Journal of Public Health15(2):114-116.

 

Brand A, Schröder P, Brand H, Zimmern R (2006): Getting Ready for the Future: Integration of Genomics into Public Health Research, Policy and Practices in Europe and Globally. Community Genetics, 9:67-71.

 

Burke W (2003): Genomics as a Probe for Disease Biology. New England J of Medicine, 349: 969-974.

 

Childs B, Valle D (2000): Genetics, Biology and Disease. Ann Rev Gen Hum Genet, 1: 1-19.

 

Collins FS, Patrinos A, Jordan E, Chakravarti A., Gesteland R, Walters L (1998): New Goals for the U.S. Genome Project: 1998-2003. Science, 282: 682-689.

 

Collins FS, McKusick VA (2001): Implications of the Human Genome Project for Medical Science. J Am Med Ass, 285: 540-544.

 

Council of Europe (1997): Convention for the protection of Human Rights and dignity of the human being with regard to the application of biology and medicine: Convention on Human Rights and Biomedicine
CETS No.: 164

(available at: http://conventions.coe.int/Treaty/Commun/QueVoulezVous.asp?NT=164&CL=ENG)

 

Ellsworth DL, ODonnell CJ (2004): Emerging Genomic Technologies and Analytic Methods for Population- and Clinic-Based Research; in Khoury MJ, Little J, Burke W (eds.). Human Genome Epidemiology. A Scientific Foundation for Using Genetic Information to Improve Health and Prevent Disease. Oxford New York Tokyo, Oxford University Press, pp 17-37.

 

French ME, Moore JB (2003): Harnessing Genetics to Prevent Disease and Promote Health. Partnership for Prevention. Washington

 

Gao J, Shan G, Sun B, Thompson PJ, Gao X (2006): Association between polymorphism of tumour necrosis factor alpha-308 gene promoter and asthma: a meta-analysis. Thorax, 61:466-471.

 

Hoffmann K., Mattheisen M, Dahm S, Nürnberg P, Roe C, Johnson J, Cox N J, Wichmann H E, Wienker T F, Schulze J, Schwarz P E, Lindner T H (2007): A German genome-wide linkage scan for type 2 diabetes supports the existence of a metabolic syndrome locus on chromosome 1p36.13 and a type 2 diabetes locus on chromosome 16p12.2. Diabetologia, 50:1418-1422.

 

Hoos A, Urist MJ, Stojadinovic A, Mastorides S, Dudas ME, Leung DHY, Kuo D, Brennan MF, Lewis JJ, Cordon-Cardo C (2001): Validation of tissue microarrays for immunohistochemical profiling of cancer specimens using the example of human fibroplastic tumors. Am J Pathol, 158:1245-1251.

 

Ibarreta D, Bock, A.K., Klein C, Rodriguez-Cerezo E (2003): Institute of Prospective Technology Studies, EC-Joint Research. Towards quality assurance and harmonisation of genetic testing services in the EU, www.jrc.es

 

Khoury MJ (1996): From Genes to Public Health: The Applications of Genetic Technology in Disease Prevention. Am J Public Health, 86(12): 1717-1722.

 

Kononen J, Bubendorf L, Kallioniemi A, Barlund M, Schraml P, Leighton S, Torhorst J, Mihatsch MJ, Sauter G, Kallioniemi OP (1998): Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat Med4:844-847.

 

Lehmann DJ, Cortina-Borja M, Warden DR, Smith D, Sleegens K, Prince JA, van Duijn CM, Kehoe PG (2005): Large meta-analysis establishes the ACE insertion-deletion polymorphism as a marker of Alzheimer’s disease. AM J Epidemiol, 162:305-317.

 

Lunshof JE, Chadwik R, Vorhaus DB, Church GM (2008): From genetic privacy to open consent. Nature Reviews Genetics, AOP, published online 1 April 2008; doi:10.1038/nrg2360: 2-7.

 

Roberts, R, Sullivan P, Joyce P, Kennedy M (2000):, Rapid and comprehensive determination of cytochrome P450 CYP2D6 poor metabolizer genotypes by multiplex polymerase chain reaction, Human Mutation, 16 (1): 7785.

 

Rothman N, Skibola CF, Wang SS, Morgan G, Lan Q, Smith MT, Spinelli JJ, Willett E, De Sanjose S, Cocco P, Berndt SI, Brennan P, Brooks-Wilson A, Wacholder S, Becker N, Hartge P, Zheng T, Roman E, Holly EA, Boffetta P, Armstrong B, Cozen W, Linet M, Bosch FX, Ennas MG, Holford TR, Gallagher RP, Rollinson S, Bracci PM, Cerhan JR, Whitby D, Moore PS, Leaderer B, Lai A, Spink C, Davis S, Bosch R, Scarpa A, Zhang Y, Severson RK, Yeager M, Chanock S, Nieters A (2006): Genetic variation in TNF and IL10 and risk of non-Hodgkin lymphoma: a report from the InterLymph Consortium. Lancet Oncol, 7(1):27-38.

 

Schulte in den Bäumen T (2006): Governance in genomics: a conceptual challenge for public health genomics law. Italian Journal of Public Health, 4(3): 4652.

 

Sookoian SC, Gonzalez C, Pirola CJ (2005): Meta-analysis on the G-308A tumor necrosis factor alpha gene variant and phenotypes associated with the metabolic syndrome. Obes Res, 13:2122-2131.

 

Torhorst J, Bucher C, Kononen J, Haas P, Zuber M, Köchli OR, Mross F, Dieterich H, Moch H, Mihatsch M, Kallioniemi OP, Sauter G (2001): Tissue microarrays for rapid linking of molecular changes to clinical endpoints. Am J Pathol, 159:2249-2256.

 

UNESCO (1997): Universal Declaration on the Human Genome and Human Rights, 1997, www.unesco.org

 

UNESCO (2003):  International Declaration on Human Genetic Data, 2003, www.unesco.org

 

Wellcome Trust Case Control Consortium (2007): Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, Vol 447:661-678

 

Zika E, Papatryfon I, Wolf O, Gómez-Barbero M, Stein A J, Bock A K (2007): Consequences, Opportunities and Challenges of Modern Biotechnology for Europe, EC - Joint Research Centre, Institute of Prospective Technology Studies, EC-Joint Research. Bio4EU, www.jrc.es