10.2.4. Genetics
and genomics
Acronyms
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. Inter
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 “real” number 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 following “trends” 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 sufficient” determinants 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 following a mendelian 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 information” based 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 study “BIO4EU” (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 funded “Public 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 Policies” doctrine calls for the
integration of genome-based knowledge. In fact, the “Health in all Policies”
approach 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
Policies” idea 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, 2003; Ellsworth 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 clusters” based 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 individuals’
interests 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 “simple” messages 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 “old” phenotypic 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.
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