The Genius in All of Us: New Insights Into Genetics, Talent, and IQ by David Shenk Read Free Book Online

heights predictably decreased: Union soldiers dropped from sixty-eight to sixty-seven inches in the mid-eighteen-hundreds, and similar patterns held for West Point cadets, Amherst students, and free blacks in Maryland and Virginia. By the end of the nineteenth century, however, the country seemed set to regain its eminence. The economy was expanding at a dramatic rate, and public-hygiene campaigns were sweeping the cities clean at last: for the first time in American history, urbanites began to outgrow farmers.
    In personal correspondence, Patrick Bateson warns: “[Don’t] overstate your case. Differences in genes can be correlated with a difference in behaviour or morphology. Not everyone will reach the same height if they are all given a superb diet. Pygmies, for example, produce less growth hormone or, in the case of other populations (the phenotype seems to have evolved at least five times in different parts of the world), are less receptive to growth hormone.”
         “Maze-dull” rats, which had consistently tested poorly in those same mazes, making an average of 40 percent more mistakes .
       This second group consistently stumbled through the same maze over and over again without remembering or learning, making an average of 40 percent more mistakes than the smarter group. They seemed obviously dumber than the Maze-bright strain, possessing an apparently inferior set of intelligence genes.
         “a classic example of gene-environment interaction ”: McClearn, “Genetics, Behavior and Aging,” p. 11.
         temperature surrounding turtle and crocodile eggs determined their gender : Bateson, “Behavioral Development and Darwinian Evolution,” p. 52.
         In 1972, Harvard biologist Richard Lewontin supplied a critical clarification that helped his colleagues understand GxE .
    Paolo Vineis, chair of Environmental Epidemiology, Imperial College, London, explains:
    This issue was clarified in an important paper by Richard Lewontin many years ago, but it is still a matter of confusion. The main idea of Lewontin’s paper is that when we evaluate gene-environment interactions we use the “analysis of variance” paradigm, that is, we try to combine the two main effects (genes versus environment), plus their interactive term, in a linear model. Causal models presuppose a linear combination of factors as the base line, variances are then computed and the role of the two main effects (or their interaction) is apportioned accordingly. But, Lewontin argues, the analysis-of-variance approach is misleading. There is no theoretical justification for the presumption of a linear explanation (this is done for the sake of simplicity but does not correspond to any reasonable biological reason). By contrast, all the experiments done with, for example, Arabidopsis (a plant) or Drosophila (based for example on radiation-induced mutations) show that mutations cause a change in what is called the “norm of reaction,” that is, the ability of the organism to react to different environmental conditions. The way in which the mutant strain will react, say, to different temperatures, is not predictable if the environmental conditions are not specified. Usually what happens is “canalization,” that is, under “normal” conditions there is a certain norm of reaction that is the same for the wild type and the mutants, whereas in changing environments the wild type andthe mutant differ in the norm of reaction. What this suggests is that in at least some cases a nonlinear explanation is going to be required. In practical terms, it means that all attempts to explain disease on the basis of either the environment or genes (or their interaction) are in fact doomed to fail, because two organisms with different gene variants will have exactly the same response in a normal environment, and a totally different response in an abnormal environment . (Italics mine.) (Vineis, “Misuse of genetic data in environmental