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Future needs in exploration of gene-environment interactions

Hamet, Pavel

doi: 10.1097/HJH.0b013e328358f6b3
EDITORIAL COMMENTARIES
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Centre hospitalier de l’Université de Montréal, Montréal, Québec, Canada

Correspondence to Pavel Hamet, O.Q., MD, Ph.D, FRCPC, Centre hospitalier de l’Université de Montréal, Montréal, Québec, Canada. E-mail: pavel.hamet@umontreal.ca

The past debate on the relative importance of nature vs. nurture in shaping human development is nowadays understood as gene-environment interactions. Although still not fully accepted, it is now evident that a more relevant question is not to know which one is the most important, but how these two determinants of life can and do interact. In diseases such as hypertension, it is evident that a better understanding of the mechanisms of interaction between a variety of environmental factors that include stress, sodium intake and other nutritional factors, physical activity or antihypertensive medications with specific genetic polymorphisms, copy number variants and other genetic variants is of utmost importance [1]. There are several examples in literature demonstrating the impact of a single allelic variant not only on a specific phenotype but also on its modulation by the environment. An example is the fat mass and obesity-associated gene, FTO. Its single nucleotide polymorphism (SNP) rs9939609 has been widely described to be associated with obesity and other metabolic syndrome components but recent evidence is also pointing to a specific impact of the environment, in the form of high dietary saturated fat that accentuates the risk of obesity in carriers of a specific allele of that SNP [2]. We have observed that FTO gene is particularly susceptible to environmental modulation in our studies of obesity and hypertension [3] in which we showed that the association of the FTO gene with blood pressure was apparent only after withdrawal of the antihypertensive medication, which overshadowed its relationship with blood pressure without affecting its relation with obesity [4]. It has also been demonstrated that the genetic risk, confined by an aggregate of most of the known risk alleles of obesity discovered in recent Genome Wide Associations Studies (GWAS) may be attenuated by as much as 40% with physical exercise [5]. Most of phenotypes in cardiometabolic regulation are polygenic in nature, including hypertension and its cardiovascular outcomes, best demonstrated by a multistage study of GWAS performed in 200 000 individuals of European descent, which identified 29 SNP as previously known and new variants influencing blood pressure in pathways leading to hypertension and its outcomes, including stroke and coronary heart disease [6]. We have shown a similar polygenic contribution in the French-Canadian founder population, pointing to synaptic plasticity pathways as a crossroad between hypertension, habitual substance use, obesity and mental and physical stress [7] as a paradigm of gene–environment interactions.

A large number of recent studies have addressed the environmental influence in the context of specific genetic background in behavioural research such as the one on childhood stress in relation to serotonin transporter gene and issuing depressive disorder in adulthood [8]. This type of research is an example of discordant results found in the literature, which merits a comment on methodology in this area [9]. Although genotyping is usually highly accurate and reproducible, and so is the determination of the resulting disease, the accurate determination of the initial phenotypes or environmental influences is much more difficult to achieve. An example is childhood experience with consequences in late adulthood that is recorded by a questionnaire in which length of exposure, dose effect and confounders remain undesirably vague.

In this issue of Journal of Hypertension, Mbewe-Campbell et al.[10] from Daniel O’Connor's group is proposing new tools for observation of gene and environment interactions. After initially identifying novel polymorphisms within the Cathepsin L gene, they discovered a novel genetic variant in the Cathepsin L promoter (CTSL1) with functional consequences on disruption of a xenobiotic response element (XRE) as demonstrated by both exogenous end endogenous modifications in gene expression. These elegant functional genomic studies were then translated to humans by studying individuals at the extremes of the blood pressure distribution revealing association of C171A (rs3118869) variant in CTSL promoter with both SBP and DBP significantly higher (10 and 8 mmHg, respectively) in CC homozygotes contrasting with lowest BP in AA homozygotes, and with heterozygotes in between. These data were validated in an independent population. They demonstrated potential functional consequences of this polymorphism that may clearly lead to abnormalities in xenobiotic metabolism but also to abnormal levels of endogenous neurotransmitters including neuropeptide Y.

This observation led the authors to suggest a potential for transcriptional strategy as a tool in exploration of gene–environment interactions. This is novel and useful information yet, as the authors acknowledge themselves, further studies are required such as the ethnic differences in response to xenobiotics, the type of xenobiotics implicated in this effect in the context of hypertension or other disorders. In addition, the impact of CTSL promoter variance will need to be evaluated in the context of polygenic mosaic responding to environmental influences. This has been demonstrated for example in genomic response to caloric restriction, resulting in prolonged survival. In this situation, CTSL transcription increase is among the most prominent modifications, but only in the context of a large number of metabolic, signal transduction and stress gene transcriptional modifications [11].

One of the most convincing examples of gene–environment interactions is the well known case of the epithelial growth factor receptor EGFR gene and the impact of its gene variants on radiation effects on lung cancer incidence in atomic bomb survivors [12]. The quality of the input data was assured by the accuracy in radiation dose received and exact exposure time. Since then, several modulating factors have been identified such as smoking and sex. Even with very accurate environmental data, the difficulty in risk evaluation is hampered by the fact that the number of cancer cases is relatively low compared to the size of the cohort, which is frequently the case. Based on this example, novel epidemiological statistics have been developed as recently summarized by Cologne et al.[13]. This research suggests that the case–cohort study with stratified or random subcohorts selections is the most recommendable design for studies of gene–environment interactions, which usually lack statistical power. The authors recommend the method based on score-unbiased exact pseudolikelihood. Statistical packages exist in the literature allowing this methodology to be readily applied.

In conclusion, more has to be understood before concluding on the presence or absence of gene–environment interactions and their importance. Assessment of exposure, its duration, dosage and other confounders need to be carefully determined before embarking on a necessary clinical study prospective validation. A careful approach to the subject is essential in our advancement to assess accurately the clinical utility of genetic studies in their overwhelming context of gene–environment interactions.

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ACKNOWLEDGEMENTS

The author thanks Dr Johanne Tremblay for comments and discussions.

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Conflicts of interest

There are no conflicts of interest.

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REFERENCES

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