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      The Fangshan/Family-based Ischemic Stroke Study In China (FISSIC) protocol

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          Abstract

          Background

          The exact etiology of ischemic stroke remains unclear, because multiple genetic predispositions and environmental risk factors may be involved, and their interactions dictate the complexity. Family-based studies provide unique features in design, while they are currently underrepresented for studies of ischemic stroke in developing countries. The Fangshan/Family-based Ischemic Stroke Study In China (FISSIC) program aims to conduct a genetic pedigree study of ischemic stroke in rural communities of China.

          Methods/Design

          The pedigrees of ischemic stroke with clear documentation are recruited by using the proband-initiated contact method, based on the stroke registry in hospital and communities. Blood samples and detailed information of pedigrees are collected through the health care network in the rural area, and prospective follow-up of the pedigrees cohort is scheduled. Complementary strategies of both family-based design and matched case-spousal control design are used, and comprehensive statistical methods will be implemented to ascertain potential complex genetic and environmental factors and their interactions as well.

          Discussion

          This study is complementary to other genetic pedigree studies of ischemic stroke, such as the Siblings With Ischemic Stroke Study (SWISS), which are established in developed countries. We describe the protocol of this family-based genetic epidemiological study that may be used as a new practical guideline and research paradigm in developing countries and facilitate initiatives of stroke study for international collaborations.

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          Most cited references32

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          Implementing a unified approach to family-based tests of association.

          We describe a broad class of family-based association tests that are adjusted for admixture; use either dichotomous or measured phenotypes; accommodate phenotype-unknown subjects; use nuclear families, sibships or a combination of the two, permit multiple nuclear families from a single pedigree; incorporate di- or multi-allelic marker data; allow additive, dominant or recessive models; and permit adjustment for covariates and gene-by-environment interactions. The test statistic is basically the covariance between a user-specified function of the genotype and a user-specified function of the trait. The distribution of the statistic is computed using the appropriate conditional distribution of offspring genotypes that adjusts for admixture.
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            The investigation of linkage between a quantitative trait and a marker locus.

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              Sample size requirements for association studies of gene-gene interaction.

              In the study of complex diseases, it may be important to test hypotheses related to gene-gene (G x G) interaction. The success of such studies depends critically on obtaining adequate sample sizes. In this paper, the author investigates sample size requirements for studies of G x G interaction, focusing on four study designs: the matched-case-control design, the case-sibling design, the case-parent design, and the case-only design. All four designs provide an estimate of interaction on a multiplicative scale, which is used as a unifying theme in the comparison of sample size requirements. Across a variety of genetic models, the case-only and case-parent designs require fewer sampling units (cases and case-parent trios, respectively) than the case-control (pairs) or case-sibling (pairs) design. For example, the author describes an asthma study of two common recessive genes for which 270 matched case-control pairs would be required to detect a G x G interaction of moderate magnitude with 80% power. By comparison, the same study would require 319 case-sibling pairs but only 146 trios in the case-parent design or 116 cases in the case-only design. A software program that computes sample size for studies of G x G interaction and for studies of gene-environment (G x E) interaction is freely available (http://hydra.usc.edu/gxe).
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                Author and article information

                Journal
                BMC Med Genet
                BMC Medical Genetics
                BioMed Central (London )
                1471-2350
                2007
                10 September 2007
                : 8
                : 60
                Affiliations
                [1 ]Department of Epidemiology & Biostatistics, Peking University School of Public Health, Beijing 100083, China
                [2 ]Key Laboratory of Epidemiology, Ministry of Education, Beijing 100083, China
                [3 ]Department of Neurology, the First Hospital of Fangshan District, Beijing 102400, China
                [4 ]Department of Clinical Laboratory Medicine, the First Hospital of Fangshan District, Beijing 102400, China
                Article
                1471-2350-8-60
                10.1186/1471-2350-8-60
                1997110
                17825112
                cf1d0c52-42f5-47c4-ac7d-f6c5521016a7
                Copyright © 2007 Tang et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 July 2007
                : 10 September 2007
                Categories
                Study Protocol

                Genetics
                Genetics

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