Literature DB >> 9271710

Population-based family study designs: an interdisciplinary research framework for genetic epidemiology.

L P Zhao1, L Hsu, O Davidov, J Potter, R C Elston, R L Prentice.   

Abstract

Most complex traits such as cancer and coronary heart diseases are attributed either to heritable factors or to environmental factors or to both. Dissecting the genetic and environmental etiology of complex traits thus requires an interdisciplinary research strategy. Genetic studies generally involve families and investigate familial aggregations of traits, segregation of major disease genes, and locations of disease genes on the human genome, the latter of which can be identified via linkage analysis. Epidemiologic studies often use population-based case-control studies to establish the role of specific environmental factors. Integrating both objectives, genetic epidemiology is to assess the associations of environmental factors with disease status, to quantify the aggregation of cases within families, to characterize putative disease genes via segregation analysis, and to localize disease genes via linkage analysis with genetic markers. To accomplish these objectives through designed studies, we propose a class of population-based family study designs, which are formed by choosing among sampling designs at three stages. The objectives of sampling at these three stages are 1) combined aggregation and association analysis, 2) combined segregation, aggregation, and association analysis, and 3) combined linkage, segregation, aggregation, and association analysis. These designs form an interdisciplinary research framework for genetic epidemiology. Our preliminary exploration of this framework and related analytic methods indicates that population-based family study designs retain the efficiency of linkage analysis for localizing disease genes without losing the property of being population-based, and they will therefore allow an assessment of a joint contribution of genetic and environmental factors to complex traits.

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Year:  1997        PMID: 9271710     DOI: 10.1002/(SICI)1098-2272(1997)14:4<365::AID-GEPI3>3.0.CO;2-2

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  3 in total

1.  Familial aggregation of food allergy and sensitization to food allergens: a family-based study.

Authors:  H-J Tsai; R Kumar; J Pongracic; X Liu; R Story; Y Yu; D Caruso; J Costello; A Schroeder; Y Fang; H Demirtas; K E Meyer; M R G O'Gorman; X Wang
Journal:  Clin Exp Allergy       Date:  2008-10-30       Impact factor: 5.018

2.  Aging syndrome genes and premature coronary artery disease.

Authors:  Adrian F Low; Christopher J O'Donnell; Sekar Kathiresan; Brendan Everett; Claudia U Chae; Stanley Y Shaw; Patrick T Ellinor; Calum A MacRae
Journal:  BMC Med Genet       Date:  2005-10-31       Impact factor: 2.103

Review 3.  Genetic approaches toward understanding the individual variation in cardiac structure, function and responses to exercise training.

Authors:  Minsun Kim; Seung Kyum Kim
Journal:  Korean J Physiol Pharmacol       Date:  2021-01-01       Impact factor: 2.016

  3 in total

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