Literature DB >> 3673476

Prospects for detecting genotype X environment interactions in twins with breast cancer.

N G Martin1, L J Eaves, A C Heath.   

Abstract

We consider a study of MZ and DZ twin pairs ascertained because one or both twins have a disease. Genotypes at a major locus are known and putative environmental risk factors have been measured for all individuals. The power of the study to estimate the effect on liability of the measured and residual genetic and environmental effects (Gm, Gr, Em, Er) and all two-way interactions between them (except Gr X Er) is estimated by simulation. If liabilities can be indexed on a continuous scale (eg, blood pressure as an index of liability to hypertension), then a study of 600 MZ and 600 DZ pairs would have sufficient power to detect quite subtle interaction effects, even if ascertainment is greatly biased toward MZ twins. If liabilities cannot be measured and only affection status is known, then the power of the study would be much lower, although not impracticably so. There appears to be no advantage in augmenting the twins with a sample of control individuals who have been drawn at random from the population regardless of disease status, at least for the case we have considered in which the disease threshold on the liability scale is assumed to be known without error. The argument is developed in terms of the utility of the design for research into breast cancer.

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Year:  1987        PMID: 3673476     DOI: 10.1017/s0001566000004542

Source DB:  PubMed          Journal:  Acta Genet Med Gemellol (Roma)        ISSN: 0001-5660


  5 in total

1.  A finite mixture model for genotype and environment interactions: detecting latent population heterogeneity.

Authors:  Nathan A Gillespie; Michael C Neale
Journal:  Twin Res Hum Genet       Date:  2006-06       Impact factor: 1.587

2.  Peer substance involvement modifies genetic influences on regular substance involvement in young women.

Authors:  Arpana Agrawal; Sumitra Balasubramanian; Emily K Smith; Pamela A F Madden; Kathleen K Bucholz; Andrew C Heath; Michael T Lynskey
Journal:  Addiction       Date:  2010-10       Impact factor: 6.526

Review 3.  How frailty models can be used for evaluating longevity limits: taking advantage of an interdisciplinary approach.

Authors:  A I Yashin; I A Iachine
Journal:  Demography       Date:  1997-02

4.  Evidence for an interaction between age at first drink and genetic influences on DSM-IV alcohol dependence symptoms.

Authors:  Arpana Agrawal; Carolyn E Sartor; Michael T Lynskey; Julia D Grant; Michele L Pergadia; Richard Grucza; Kathleen K Bucholz; Elliot C Nelson; Pamela A F Madden; Nicholas G Martin; Andrew C Heath
Journal:  Alcohol Clin Exp Res       Date:  2009-09-17       Impact factor: 3.455

5.  Comparability of surrogate and self-reported information on melanoma risk factors.

Authors:  J F Aitken; A Green; R MacLennan; L Jackman; N G Martin
Journal:  Br J Cancer       Date:  1993-05       Impact factor: 7.640

  5 in total

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