Literature DB >> 11269649

The genealogic approach to human genetics of disease.

J Gulcher1, A Kong, K Stefansson.   

Abstract

The goal of modern human genetics is to correlate genes with disease or, more specifically, relate genetic variation to phenotypic variation. Although this correlation is usually straightforward in the Mendelian disorders, it has proved to be much more difficult to find in the common diseases because they appear to be more complex, likely involving an interplay among multiple genes and between genes and the environment. Although the strategy of linkage mapping of families was very successful when it was applied to the rare monogenic diseases, few common diseases have been mapped to statistical significance. Many investigators are now abandoning linkage analysis altogether and are moving to a candidate gene case-control strategy. In this article, we describe a genealogic approach to mapping human disease genes and provide three examples of how we have used it to map common diseases to statistical significance. We focus on a simple population with little historic migration and use a computerized genealogy database to increase the number of patients who can be compared with other affected relatives through high-density microsatellite genotyping. The genealogy helps determine which phenotypic classification is inherited and therefore possible to map. It may represent a more efficient strategy than candidate gene case-control studies for determination of what alleles or haplotypes are shared by patients in a population. We suggest that the genetics community not give up on linkage analysis, nor should it assume that the common diseases are too complex to map.

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Year:  2001        PMID: 11269649

Source DB:  PubMed          Journal:  Cancer J        ISSN: 1528-9117            Impact factor:   3.360


  10 in total

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2.  Increased power of mixed models facilitates association mapping of 10 loci for metabolic traits in an isolated population.

Authors:  Eimear E Kenny; Minseung Kim; Alexander Gusev; Jennifer K Lowe; Jacqueline Salit; J Gustav Smith; Sirisha Kovvali; Hyun Min Kang; Christopher Newton-Cheh; Mark J Daly; Markus Stoffel; David M Altshuler; Jeffrey M Friedman; Eleazar Eskin; Jan L Breslow; Itsik Pe'er
Journal:  Hum Mol Genet       Date:  2010-11-30       Impact factor: 6.150

3.  An evaluation of the current state of genomic data privacy protection technology and a roadmap for the future.

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Review 4.  The HapMap and genome-wide association studies in diagnosis and therapy.

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Journal:  Annu Rev Med       Date:  2009       Impact factor: 13.739

5.  The use of genealogy databases for risk assessment in genetic health service: a systematic review.

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Review 6.  Electronic health records: the next wave of complex disease genetics.

Authors:  Brooke N Wolford; Cristen J Willer; Ida Surakka
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7.  Detection of CX3CR1 single nucleotide polymorphism and expression on archived eyes with age-related macular degeneration.

Authors:  C-C Chan; J Tuo; C M Bojanowski; K G Csaky; W R Green
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8.  Genome-wide analysis of genetic susceptibility to language impairment in an isolated Chilean population.

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9.  Cancer as a complex phenotype: pattern of cancer distribution within and beyond the nuclear family.

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10.  Linkage of osteoporosis to chromosome 20p12 and association to BMP2.

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  10 in total

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