Beware of scientific revolutions!

Gene ExpressionBy Razib KhanAug 28, 2011 9:15 AM


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Above is the Ngram result for paradigm shift, a ubiquitous descriptive concept which can be quite slippery when applied to contemporary science. For example, every few years there is always a new "revolution" which is going to overturn "Darwinism." Be it punctuated equilibrium, symbiogenesis, or epigenetics. But over time revolutionary fervor abates, and the orthodoxy remains standing, albeit with modifications and alterations, making it all the more robust. I thought of this when I saw Andrea Cantor's comment below in relation to twin studies:

Twin studies underestimate heritability only if you subscribe to the crude notion that the effect of genes is additive, i.e., keeping “environments” the same, the more similar two people are genetically the more alike they will be.

This ignores everything we now know about the way genes work.

Genes are not self-activating: they do not turn themselves on and produce traits. Genes do not, in fact, produce anything. Genes are turned on and off by the epigenome in response to environmental inputs. If you are inclined to doubt this, then consider: If all the cells in our body are supposed to contain identical DNA, how do you account for the existence of different tissues and cells types (

answer: the epigenome

). Twins have been shown to have significantly different epigenomes in the womb. Does this show that twin studies underestimate heritability? Of course not. It shows, rather, that these studies are out of touch with advances in molecular genetics.

You are all committed to a crude, 19th century conception of the relationship between genotype and phenotype

. Twin studies are based upon a scientific paradigm that has remained unchanged since the time of Galton. Problem is, recent advances in molecular genetics are bringing about a paradigm shift in the science of genetics. Twin studies make it seem all so easy: All you need is a large data set that has zygosity status and statistical software and any undergraduate can unravel the biomolecular basis of human behavior. Would that it were so easy.

I get comments like this frequently. Often I don't publish them (in fact, I usually ban the commenter). These contributions to the discussion exhibit internal coherency, and thankfully they're not personal attacks (though they do tend to stink of condescension). But they don't really further the discussion, and are liable to just confuse people. I let this comment through because I thought it might be interesting to respond to it, to clarify a few points. I highlighted some buzzwords and tendencies which unify a broad range of commenters/opinionators on science, from Creationists to quasi-Blank Slaters. There are general terms such as "paradigm shift." There are almost always references to how dated the science that you are alluding to is. You are "out of touch" (or being perverse). Then there are the weird "what does that even mean?" assertions which often litter this class of comments. This is probably the main reason I often don't let these comments through: they waste your time because they require a lot of interpretation. I honestly don't know what it means to assert that anyone would think that twin studies can unravel the "biomolecular basis of human behavior." I'd like to meet the person who thinks this. Finally, there are the specific buzzwords. Here you have epigenome. A reference to the mysterious connection between genotype and phenotype usually helps to impress as well. But it turns out that I didn't even need to respond. Luke Jostins is at it again, defending the honor of the twin study! Here's his comment:

@Andrea Cantor The relationship between biological interaction and genetic addativity on the variance component scale is more complex than I think you realise, and the common terms between the two (additivity, interaction, etc) seem to have thrown off your intuition. The fact is that virtually all the assumptions of twin studies have been extensively tested, and they have all been found to be relatively good approximations (statistically) the behaviour of genetic risk in populations, in certain relatively well characterised circumstances. This doesn’t mean that biological systems aren’t full of interaction, or that epigenetic effects are not important, or that genetic effects are stationary over time, or that interactions between genes and environment do not exist. It just means that your intuitive feel that these effects result in statistical non-additivity on the genetic risk scale is wrong.

In other words, Andrea Cantor doesn't know what she's talking about. That's fine. But using her comment as a prototype, I hope it will help us navigate the turbulent waters of the scientific discourse.

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