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Genetic Effects on Environmental Vulnerability to Disease. Novartis Foundation Symposia

  • ID: 2171209
  • Book
  • 232 Pages
  • John Wiley and Sons Ltd
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While much research has attempted to show direct linear relations between genes and disorder, scientists have been discouraged by inconsistent findings based on this simple gene–phenotype approach. An alternative approach is to incorporate information about the environment. The gene–environment interaction approach focuses on the circumstances in which there is an environmental determinant of disease but where genes influence susceptibility to that environmental factor.

Genetic Effects on Environmental Vulnerability to Disease is based on the final meeting of the Novartis Foundation Symposium Series (#293 Understanding How Gene Environment Interactions Work to Predict Disorder). Contributions from geneticists, physicians, oncologists, biologists, statisticians, epidemiologists, psychiatrists and psychologists address:

- how physiological (mechanistic) measures can be better integrated into epidemiological cohort studies

- how best to characterise subjects vulnerability versus resilience by moving beyond genetic main effects

- how gene hunters can benefit from recruiting samples selected for known exposures

- how environmental pathogens can be used as tools for gene hunting

- how to deal with potential spurious (statistical) interactions, and

- how genes can help explain fundamental demographic properties of disorders such as sex distribution or age effects.

Interwoven with transcripts of the lively discussions among researchers, the contents of the book offer a cutting–edge review of the methodological issues prevailing in this complex, multi–disciplinary field.

A glossary of technical terms helps facilitate understanding across the different disciplines involved, and Sir Michael Rutter s introduction and concluding remarks contribute to presenting scientific issues in an interesting, easily accessible manner.

This book will be of interest to epidemiologist, geneticists, developmental biologists, and researchers in psychiatric disorders, obesity, diabetes, cancer, respiratory diseases and cardiovascular disease

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1. Michael Rutter

Introduction: whither gene environment interactions?

2. Rudolf Uher

Gene environment interaction: overcoming methodological challenges


3. Marco Battaglia, Cecilia Marino, Michel Maziade, Massimo Molteni and Francesca D Amato

Gene environment interaction and behavioural disorders: a developmental perspective based on endophenotypes


4. Naomi R. Wray, William L. Coventry, Michael R. James, Grant W. Montgomery, Lindon J. Eaves and Nicholas G. Martin

Use of monozygotic twins to investigate the relationship between 5HTTLPR genotype, depression and stressful life events: an application of Item Response Theory



General discussion I

5. Harold Snieder, Xiaoling Wang, Vasiliki Lagou, Brenda W. J. H. Penninx, Harriëtte Riese and Catharina A. Hartman

Role of gene stress interactions in gene–finding studies


6. Kenneth A. Dodge

Practice and public policy in the era of gene environment interactions


7. Kristi B. Adamo and Frédérique Tesson

Gene environment interaction and the metabolic syndrome


General discussion II

8. Stephen P. Robertson and Richie Poulton

Longitudinal studies of gene environment interaction in common diseases good value for money?


9. Kee–Seng Chia

Gene environment interactions in breast cancer


10. Malak Kotb, Nourtan Abdeltawab, Ramy Aziz, Sarah Rowe, Robert W. Williams and Lu Lu

Unbiased forward genetics and systems biology approaches to understanding how gene environment interactions work to predict susceptibility and outcomes of infections


11. Steven R. Kleeberger and Hye–Youn Cho

Gene environment interactions in environmental lung diseases


General discussion III

12. Fernando D. Martinez

Gene environment interaction in complex diseases: asthma as an illustrative case


13. Michael Rutter

Conclusions: taking stock and looking ahead


Index of contributors

Subject index

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Sir Michael J. Rutter
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