Embracing Complexity: Searching for Gene-Gene and Gene Environment Interactions in Genetic Epidemiology

Information generated by genetic epidemiology and genomics studies has been accumulating at fast pace, and this knowledge opens new vistas in public health, allowing for the understanding of gene–environment interactions. However, the translation of genome-based knowledge and technologies to the practice of healthcare, and especially of public health, is challenging. Because health impact assessment (HIA) proved to be an effective tool to assist consideration of health issues is sectoral policymaking, this study aimed at exploring its role in the translational process by a systematic literature review on the use of genetic information provided by genetic epidemiology and genomics studies in HIA. PubMed, Scopus, and Web of Science electronic databases were searched and the findings systematically reviewed and reported by the PRISMA guidelines. The review found eight studies that met the inclusion criteria, most of them theoretically discussing the use of HIA for introducing genome-based technologies in healthcare practice, and only two articles considered, in short, the possibility for a generic application of genomic information in HIA. The findings indicate that HIA should be more extensively utilized in the translation of genome-based knowledge to public health practice, and the use of genomic information should be facilitated in the HIA process.

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Epidemiology of psychiatric disorder in childhood and adolescence

New Oxford Textbook of Psychiatry ◽

10.1093/med/9780199696758.003.0209 ◽

2012 ◽

pp. 1594-1600

Author(s):

E. Jane Costello ◽

Adrian Angold

Keyword(s):

Psychiatric Disorder ◽

Psychiatric Disorders ◽

Molecular Genetics ◽

Clinical Psychiatry ◽

Genetic Epidemiology ◽

Developmental Psychopathology ◽

Childhood And Adolescence ◽

Common Language ◽

Services Research ◽

Gene Environment

This chapter has covered a lot of ground; from the first stirrings of understanding about childhood psychiatric disorders to the possibility of using molecular genetics to identify gene–environment interactions that can generate psychiatric disorder. There are fuzzy boundaries between epidemiology and developmental psychopathology, life course epidemiology, genetic epidemiology, services research, and clinical psychiatry. It will be important to keep these boundaries pervious, to share a common language where possible, and to learn and use one another's methods.

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Genetic Epidemiology and Molecular Genetics

10.1093/oxfordhb/9780199381678.013.002 ◽

2014 ◽

Author(s):

Michael C. Stallings ◽

Ian R. Gizer ◽

Kelly C. Young-Wolff

Keyword(s):

Substance Use ◽

Environmental Factors ◽

Genetic Epidemiology ◽

Twin Studies ◽

Joint Effect ◽

Gene Environment ◽

Genetic Mechanisms ◽

Or Gene ◽

Pathway Analyses ◽

Use Behavior

The tools of genetic epidemiology—family, adoption, and twin studies—show convincingly that substance use behavior and substance use disorders are influenced by both genetic and familial and extrafamilial environmental factors. Environmental factors appear to play a more influential role in the early stages of substance use, whereas genetic factors become more important in the development of problem use and substance use disorder. Moreover, some genetic effects are likely conditional on conducive environments; research employing both behavior genetic approaches and measured genes point to important gene–environment interactions that promote substance use and dependence. Consequently, a full understanding of the addiction process requires investigating substance use behavior within its comorbid context. The identification of specific genetic mechanisms underlying these heritable influences is elusive. These findings have prompted the development of new strategies for testing the joint effect of multiple genetic variants in gene-based or gene pathway analyses.

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Gene-Environment Interaction: A Genetic-Epidemiological Approach

Journal of Medical Biochemistry ◽

10.2478/v10011-010-0021-z ◽

2010 ◽

Vol 29 (3) ◽

pp. 131-134 ◽

Cited By ~ 4

Author(s):

Tatjana Pekmezović

Keyword(s):

Environmental Factors ◽

Genetic Epidemiology ◽

Disease Risk ◽

Environmental Exposures ◽

Molecular Medicine ◽

Environment Interaction ◽

Gene Environment Interaction ◽

Gene Environment ◽

Genetic And Environmental Factors ◽

Epidemiological Approach

Gene-Environment Interaction: A Genetic-Epidemiological ApproachClassical epidemiology addresses the distribution and determinants of diseases in populations, and the factors associated with disease causation, with the aim of preventing disease. Both genetic and environmental factors may contribute to susceptibility, and it is still unclear how these factors interact in their influence on risk. Genetic epidemiology is the field which incorporates concepts and methods from different disciplines including epidemiology, genetics, biostatistics, clinical and molecular medicine, and their interaction is crucial to understanding the role of genetic and environmental factors in disease processes. The study of gene-environment interaction is central in the field of genetic epidemiology. Gene-environment interaction is defined as »a different effect of an environmental exposure on disease risk in persons with different genotypes,« or, alternatively, »a different effect of a genotype on disease risk in persons with different environmental exposures.« Five biologically plausible models are described for the relations between genotypes and environmental exposures, in terms of their effects on disease risk. Therefore, the study of gene-environment interaction is important for improving accuracy and precision in the assessment of both genetic and environmental factors, especially in disorders of less defined etiology. Genetic epidemiology is also applied at the various levels of disease prevention.

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Information Metrics in Genetic Epidemiology

Statistical Applications in Genetics and Molecular Biology ◽

10.2202/1544-6115.1569 ◽

2011 ◽

Vol 10 (1) ◽

Cited By ~ 1

Author(s):

David L Tritchler ◽

Lara Sucheston ◽

Pritam Chanda ◽

Murali Ramanathan

Keyword(s):

Genetic Epidemiology ◽

Linear Models ◽

Probability Models ◽

Information Theoretic ◽

Multinomial Data ◽

Model Search ◽

Gene Environment ◽

Correct Usage ◽

Log Linear ◽

Information Metrics

Information-theoretic metrics have been proposed for studying gene-gene and gene-environment interactions in genetic epidemiology. Although these metrics have proven very promising, they are typically interpreted in the context of communications and information transmission, diminishing their tangibility for epidemiologists and statisticians.In this paper, we clarify the interpretation of information-theoretic metrics. In particular, we develop the methods so that their relation to the global properties of probability models is made clear and contrast them with log-linear models for multinomial data. Hopefully, a better understanding of their properties and probabilistic implications will promote their acceptance and correct usage in genetic epidemiology. Our novel development also suggests new approaches to model search and computation.

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