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Medicine

Scientists Stack Up New Genes For Height 66

An anonymous reader writes "An international team of researchers, including a number from the University of North Carolina at Chapel Hill schools of medicine and public health, have discovered hundreds of genes that influence human height. Their findings confirm that the combination of a large number of genes in any given individual, rather than a simple 'tall' gene or 'short' gene, helps to determine a person's stature. It also points the way to future studies exploring how these genes combine into biological pathways to impact human growth."
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Scientists Stack Up New Genes For Height

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  • Re:GATTACA? (Score:3, Informative)

    by 99BottlesOfBeerInMyF ( 813746 ) on Thursday September 30, 2010 @06:05PM (#33753576)

    I don't see the GATTACA connection here, other than a knee-jerk response to any DNA discoveries.

    If we know what genes encode desirable traits, that is the first step towards genetically altering offspring to have those traits... ala Gattaca. This isn't about knowing who has the genes for tallness, but about the potential of altering those genes so that people who do not have altered genes are societally disadvantaged.

  • Article link (Score:3, Informative)

    by gringer ( 252588 ) on Thursday September 30, 2010 @06:39PM (#33753902)

    Took me a bit of time to find, but here's the link to the actual research paper (requires nature subscription):
    http://www.nature.com/nature/journal/vaop/ncurrent/full/nature09410.html [nature.com]

    From the abstract:

    Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation)

    The introduction of the paper states that "80% of the variation [for height] within a given population is estimated to be attributable to additive genetic factors, but over 40 previously published variants explain less than 5% of the variance." While this paper pushes that to 16%, it's nowhere near the limit of what can be detected.

    I find it interesting that they've got a sample size of around 100,000 individuals for this study (actually a meta-analysis of summary statistics from 46 GWAS of 133,653 individuals), but still claim a need for more individuals. I suspect that'll still be said when a study is done on 10 million individuals, or a billion.

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