Download Commentary: From phenotype, to genotype, to gene–environment

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DeBaun JR, Miller EC, Miller JA. N-hydroxy-2-acetyl-aminofluorene
sulfotransferase: Its probable role in carcinogenesis and in protein(methion-5-yl) binding in rat liver. Cancer Res 1970;30:577.
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Kellermann G, Shaw CR, Kellermann ML. Aryl hydrocarbon
hydroxylase inducibility and bronchogenic carcinoma. New Engl J Med
1973;289:934.
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N-2-fluorenylhydroxylamine. Reaction with nucleic acids and with
guanosine 5-monophosphate. Biochemistry 1970;9:2471.
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Kellermann G, Kellermann ML, Jett JR, Moses HL, Fontana RS. Aryl
hydrocarbon hydroxylase in man and lung cancer. Human Genetics
1978;(Suppl. 1):161.
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Cardona RA, King CM. Activation of the o-glucuronide of
the carcinogen N-hydroxy-FAA by enzymatic deacetylation in vitro:
Formation of FA-tRNA adducts. Biochem Pharmacol 1976;25:1051.
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Higginson J. The role of the pathologist in environmental medicine
and public health. Am J Pathol 1967;86:460.
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Kadlubar FF, Miller JA, Miller EC. Hepatic microsomal
N-glucuronidation and nucleic acid binding of N-hydroxy arylamines
in relation to urinary bladder carcinogenesis. Cancer Res 1977;37:805.
Brody H. The systems view of man: implications for medicine, science
and ethics. Perspect Biol Med 1973;17:71.
Published by Oxford University Press on behalf of the International Epidemiological Association
ß The Author 2007; all rights reserved.
International Journal of Epidemiology 2007;36:18–20
doi:10.1093/ije/dyl292
Commentary: From phenotype, to genotype,
to gene–environment interaction and risk for
complex diseases
Kenneth Olden
‘No one supposes that all the individuals of the same species
are cast in the same actual mould. These individual differences
are of the highest importance to us, for they are often
inherited.’ (The Origin of Species, Charles Darwin, 1859)
The 1979 publication of the article by Lower et al.1 on
‘N-acetyltransferase phenotype and risk in urinary bladder
cancer: approaches in molecular epidemiology’ generated
considerable interest and enthusiasm for research to understand gene–gene and gene–environment interactions in human
health and disease. This seminal publication in the
Environmental Health Perspectives transformed population
health research and provided the foundation for the massive
sequencing efforts to identify genetic variations involved in
modulating human response to drugs and other environmental
xenobiotics.2–4 The study of Lower et al.1 was prompted by
their interest in understanding the relationship between
N-acetyltransferase phenotype and susceptibility to the development of bladder cancer from human exposure to arylamines,
as a result of cigarette smoking or working in the chemical dye
industry. Previous studies had suggested that (i) a significant
portion of bladder cancer could be attributed to such exposures,
(ii) the distribution of N-acetyltransferase activity in the liver
was highly variable among individuals and (iii) that individuals
with low enzyme activity (the so-called ‘slow acetylator
Laboratory of Molecular Carcinogenesis, National Institute of Environmental
Health Sciences, National Institutes of Health, DHHS, RTP, NC 27709, USA.
E-mail: [email protected]
phenotype’) were most susceptible to the development of
bladder cancer.
Based on these observations, Lower et al.1 hypothesized that
the slow acetylator phenotype would be over-represented in a
population of bladder cancer patients occupationally exposed to
arylamines. Their finding of an excess of individuals of the slow
acetylator phenotype, within such a population from Denmark,
confirmed both the earlier suggestion that arylamines play a
role in bladder carcinogenesis and their hypothesis that slow
acetylators are at increased risk. Also, this landmark study
demonstrated the power of hypothesis-driven, population-based
studies for assessing disease risk associated with specific
interactions between genes and the environment. Because of
this pioneering publication, epidemiological research is now
being pursued to validate the biological significance of human
genetic variants by correlating polymorphisms, affecting various
metabolic pathways to disease risk. In some cases, populationbased studies can provide mechanistic insight before functional
genomics is informative. The extent of genetic polymorphism in
the human genome is becoming increasingly clear with the
advent of molecular cloning and gene sequencing, and this
clarity has enhanced understanding of their involvement in
disease susceptibility.
Over the past 27 years, numerous genetically determined
phenotypes have been convincingly associated with change in
susceptibility to various diseases. However, the fact that most are
only weakly associated with risk suggests that multiple, rather
than single, phenotypes contribute to increased or decreased risk.
In fact, most associations are not strong enough to be by
themselves diagnostic or predictive, and interactions between
N-ACETYLTRANSFERASE PHENOTYPE AND RISK IN URINARY BLADDER CANCER
genes and metabolic pathways may obscure functional relationships, making association studies difficult to replicate or validate.
Interindividual pharmacokinetic variation in rates of drug
elimination can vary dramatically. Multinational twin studies
were conducted on the kinetics of several drugs to compare
relative contribution of genetics and environmental factors with
respect to interindividual variations.5 Results were remarkably
similar for the various populations, and pharmacokinetic
variation virtually disappeared within monozygotic twins, but
was preserved within most dizygotic twins; meaning that
variation in drug metabolism is primarily under genetic
control. Altering the environment of the monozygotic twin
had no effect on kinetics. If reported pharmacogenetic
differences of 10- to 200-fold can be extrapolated directly to
risk of human diseases, one could conclude that an individual
can be 10–200-fold more sensitive to a given drug or
environmental chemical due to differences in expression and
activity of metabolic enzymes.
While Lower et al.1 did not coin the phrase ‘molecular
epidemiology’, the application of such a molecular level
approach to examine causality and relative risk in the human
population had a significant impact on the development
of environmental genomics. Furthermore, such studies
resulted in increased awareness of the role of genetics as a
factor that can drastically alter susceptibility to most
chronic diseases, especially those triggered by environmental
exposures.
Using many of the tools developed over the past 50 years
(e.g. polymerase chain reaction techniques, high-throughput
DNA -sequencing and oligonucleotide arrays), environmental health researchers are poised to make remarkable
advances in identifying functional polymorphisms that increase
or decrease risk from exposure to environmental xenobiotics.
To promote research in this field, the National Institute
of Environmental Health Sciences of the National Institutes
of Health initiated the Environmental Genome Project in
1997.2,3,6,7 It is a comprehensive effort to re-sequence 544
candidate genes to identify polymorphisms that influence
susceptibility to environmental exposures. In addition to
polymorphisms discovery and characterization, the initiative
supports population-based epidemiological and clinical
studies, technology development and efforts to understand
the social, legal and ethical implications of such research. The
epidemiological and clinical-based population studies builds on
the work of Lower et al.,1 using more accurate measures of
exposure and gene sequencing technologies to correlate single
nucleotide polymorphisms (SNPs) or haplotype with disease
risk. Because the candidate genes have been characterized with
respect to function, elucidating their role in disease development has a high probability of immediate success.
It has become clear that addressing the role of
gene–environment interactions in the aetiology of complex
diseases will require the development of a robust framework to
account for ‘the environment’. In spite of current understanding of the multifactoral nature of the aetiological
mechanisms of chronic diseases, biomedical researchers still
tend to focus on limited or circumscribed components of
disease. While the various disciplinary approaches have led to
new insights into disease causation, they are unlikely to be able
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to provide a coherent explanation for disease aetiology. Progress
will require large-scale, multi-institutional collaboration and
interdisciplinary expertise to design, collect and analyse the
appropriate experiments.
Epidemiologists have made significant contributions to
our understanding of gene–environment interactions.8,9
However, the Achilles’ heel in the conduct of such studies
is the lack of accurate measures of exposure. The most
common approaches of estimating exposure using indirect
surrogates such as questionnaires, toxic release and production
inventories, and environmental monitoring do not take into
account individual differences in uptake, excretion and
metabolism of environmental xenobiotics and dose–response
relationships. Not only is it difficult to measure exposure
accurately, but also the available metrics are too costly for use
in large-scale cohort studies required to detect significant
associations between genes, environment and specific health
outcomes.
In addition to impediments imposed by sample size and
exposure assessment tools, population-based studies are fraught
with other challenges related to the need for better statistical
models. To define complex exposure–disease relations on a high
variable genetic background, a comprehensive portrait of
biological response to a specific exposure is needed. The
achievement of this goal will require improved modelling
capabilities to explain how multiple interactive components of
the disease process respond when perturbed by exposure to
environmental factors. I am hopeful that the newly emerging
field of toxicogenomics10 will provide the critical databases on
gene, protein and metabolite expression profiles necessary to
sort out the respective roles of genes, physical environment and
behaviour in the aetiology of chronic diseases that plague
mankind.
In conclusion, the relationship between the environment and
human illness has been well-established. The strength of these
associations indicates that a large portion of the variation in
disease incidence is due to genetic variation and differences in
environmental exposures. However, despite several decades of
experimental and epidemiological studies, the specific interactions that contribute to disease pathogenesis have been difficult
to decipher. Current efforts to collect environmental data and
analyse polymorphisms in genes that control xenobiotic
metabolism and cell growth and repair mechanisms will be
useful in achieving this objective.
References
1
2
Lower GM, Nilsson T, Nelson CE, Wolf H, Gamsky TE, Bryan GT.
N-acetyltransferase phenotype and risk in urinary bladder cancer:
approaches in molecular epidemiology. Preliminary results in Sweden
and Denmark. Environl Health Perspect 1979;29:71–79. (Reprinted Int J
Epidemiol 2007;36:11–18.)
Kaiser J. Environmental institute lays plan for gene hunt. Science
1997;298:569–70.
3
Brown PO, Hartwell L. Genomics and human diseases-variations on
variation. Nat Genet 1998;18:91093.
4
Olden K, Wilson SH. Environmental health and genomics: visions
and implications. Nat Rev Genet 2000;1:149–53.
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INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
5
Vessel ES. Genetic and environmental factors causing variation in
drug response. Mutat Res 1991;247:241–57.
8
Hunter D. Gene–environment interactions in human diseases. Nat Rev
Genet 2005;6:287–98.
6
Wilson SH, Olden K. The environmental genome project, phase I and
beyond. Molecular Prevention 2004;4:147–56.
9
7
Olden K. Use of omic approaches in unraveling mechanisms
of
gene–environment
interactions.
Curr
Genomics
2004;5:1–6.
Olden K. Gene–gene and gene–environment interactions. In:
Ginsburg G and Willard H (eds). Handbook on Genomic Medicine.
New York: Elsevier (In press).
10
Kaiser J. Tying genetics to the risk of environmental diseasse. Science
2003;300:563.
Published by Oxford University Press on behalf of the International Epidemiological Association
ß The Author 2007; all rights reserved. Advance Access publication 2 March 2007
International Journal of Epidemiology 2007;36:20–22
doi:10.1093/ije/dyl291
Commentary: First steps in molecular
epidemiology: Lower et al. 1979
Paolo Vineis
Accepted
1 December 2006
It is usually believed that the expression ‘molecular epidemiology’ was first introduced (at least for chronic diseases) in
the seminal paper by Perera and Weinstein in 1982.1 It should
not be forgotten, however, that the expression appeared already
in the title of the paper by Lower et al. published in 1979.2
Terminology apart, the paper we submit to the attention
of the readers as a historical reprint raises a number of interesting
issues.
A priori hypothesis
The paper is rather surprising because about half of it is
taken by a long introduction on the biological premises of the
work. This would probably not be accepted by the editor of
an epidemiological journal today. Most papers nowadays are
brief, factual and convey a simple, short, ‘take-home’ message.
Also, in the era of high-throughput technologies, rather
than putting forward sound hypotheses that justify the
choice of particular genes or exposures for investigation, we
see the burgeoning of genome-wide, proteome-wide and other –
ome-wide scanning, that apparently does not need the long
and tedious work of thinking in terms of models of causation.
The paper by Lower and colleagues is particularly well-written
because it exposes very elegantly a theory of bladder carcinogenesis, from which a study design, with specific hypotheses
to be tested, ensues. Since bladder cancer was known to be
mainly due to exposure to aromatic amines (as occupational
carcinogens or in tobacco smoke), the authors chose correctly
to investigate the role of N-acetyltransferase 2 (NAT2)
in modulating the risk of cancer. Very clear graphical
representations in the paper show the metabolic pathways
Imperial College London and University of Torino.
E-mail [email protected]
that aromatic amines undergo and the role played by NAT2.
At that time it was not possible yet to genotype subjects
in the context of an epidemiological investigation, therefore
cases and controls were phenotyped with a biochemical
method that separated very clearly the rapid from the slow
metabolizers. The study shows a difference in the distribution
of the acetylator phenotype among the cases and the
controls (as expected a priori, with more slow acetylators
among the former), but only in (urban) Denmark and not in
(rural) Sweden. The authors attribute the difference between
rural Sweden and urban Denmark to the different levels of
exposure to aromatic amines in the two study locations, from
occupational or environmental (air pollution) sources.
This interpretation is plausible but uncertain, since studies
have generally failed in showing a clear association between air
pollution and bladder cancer, and occupational exposures to
aromatic amines are rare. The reasoning is nevertheless
interesting because, correctly, it stresses the crucial role
played by the environment when genetic susceptibility is
investigated.
The association between bladder cancer and the NAT2
genotype is probably one of the best investigated in the history
of the genetics of cancer, and one of the few—concerning lowpenetrant genes—that have been replicated several times.3,4
Usually the association with NAT2 has been found in particular
in the exposed groups, such as industrial workers or smokers,
suggesting that Lower’s idea that the discrepancy between
Sweden and Denmark could be due to exposures was
essentially correct. In fact, this intuition has a more general
implication that I will address in the following.
Still some notations on the study design and analysis.
The study—which is clearly interesting and generally wellconducted—reflects however, the limitations of several similar
studies conducted in the early times of ‘molecular epidemiology’,