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logo There’s a specter haunting genetics, and that’s Gattaca. The 1997 film comes up constantly whenever someone is doing something with genetics which might be pushing the envelope. But what world do we live in? We live in a world of the Genetic Information Nondiscrimination Act. More importantly, we live in the world of the Innocence Project. This enterprise is so well known that we don’t even blink an eye, but what they’re doing is applying genetics. This came to my mind because of the most recent case of two men exonerated of rape and murder (they were on death row). And if you think being railroaded like this only happens to low IQ and socially advantaged individuals, see the Michael Morton case. Think applied genetics is scary? Imagine a world without it!

• Category: Science • Tags: Gattaca, Genetics 
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In the post below, Moderate marginal value to genomics, I left some things implicit. It turns out that this was an ill-considered decision. In reality my comments were simply more cryptic and opaque than implicit. This is pretty obvious because even those readers who are biologists didn’t seem to catch what I had assumed would be obvious in the thrust of my argument.

The point in the broadest sense is that DNA and genomics are not magical. Genetics existed before either of them. Understanding the physical basis of genetics has certainly been incredibly fruitful, and genomics has altered the playing field in many ways. But there was a broad understanding of genetics before DNA and genomics, both in a Mendelian sense and in the area of biometrics and quantitative genetics. In the earlier post I indicated that the tools for predictions of adult traits due to the effect of genes have been around for a long time: our family history. By this, I mean that a lot of traits of interest are substantially heritable. A great deal of the variation within the population can be explained by variation of genes in the population, as inferred by patterns of correlation between individuals in their traits as a function of genetic relatedness. This is genetics as a branch of applied statistics. It has great “quick & dirty” power, especially in agricultural science.

Let’s look at something simple, height. It’s a continuous trait which is rather concrete. No one argues that “height” is a social construct. In Western societies height is ~80-90% heritable. That means that most of the variation within the population of the trait can be explained by variation in one’s family background. Tall people have tall children, short people have short children, and so forth. Here’s a “toy” scatterplot which shows the relation between mid-parent heights and adult offspring heights (I made up the numbers):

The correlation isn’t perfect. But it’s pretty good. The more heritable a trait is, the more a scatterplot of this form (offspring regressed on parents) approaches tight linearity with a slope of ~1. These plots are measuring narrow sense heritability, which is the additive genetic variance over the phenotypic variance. Additive genetic variance just means the variants which have additive or subtractive values to the trait value (or, they can be transformed as such).

To make this plot in a fashion which is more than illustrative you need a lot of data on a large number of individuals and their parents. This would be tedious and require a substantial labor investment in earlier periods, but today with powerful data mining techniques I think it would be much, much, easier. In a world where the child is the father of the man these methods would have great power.

But they’re not perfect. Siblings vary in height, even though though the trait seems mostly controlled by variation in genes on the population level. What’s going on? Genetically, Mendelian segregation and genetic recombination are going to reshuffle the many alleles which control variation in height from parent to offspring in terms of what the gamete contributes. Additionally, the nature of the environmental “noise” may vary from sibling to sibling. Using population wide data you can infer the expected value of the offspring based in heritability and mid-parent value, but there’s going to be variance about the mean of the theoretical distribution. For example, the standard deviation of I.Q. within the population is 15 points, and across full-siblings it is also 15 points.

This is where genomics comes in. It does make a difference, on the margin. I suspect it would do so by removing some of the uncertainty of segregation and genetic recombination. Going back to the height example, imagine that you know of the ~1,000 genes which vary within the population to control variation in height. You sequence two parents, and so know which regions of the genomes they’re enriched for “tall” or “short” alleles. Some of the variance in the offspring is going to be due to the fact that the offspring don’t receive a perfect proportional representation of their parent’s alleles in terms of aggregate effect size. You could then remove some of the uncertainty in outcome because you can check the child’s genome against the parents’ and assess whether they received more or less of the “tall” or “short” alleles.

But there would still be environmental “noise” which you probably couldn’t account for. You can see an illustration of what I have in mind in the two normal distributions I plotted above. Both of them represent the theoretical distribution of possibilities of a child on a quantitative trait which only becomes realized in adulthood. The blue line shows what you can infer from the plain information of parental phenotypes. But what happens when you give them a genomic test? You remove some of the uncertainty from your calculus, and the variance drops. You see that in the red line.

This is what I mean when I say that genomics matters on the margin. It does have an effect. But all the tools to profile and predict are around us now. Even determined amateurs can find out quite a bit about someone’s family if they’re determined. This is no different in deep principle from the sort of techniques which large corporations are utilizing to create a “profile” of your possible future purchases by what you purchased in the past. The parents are past purchases. The adult offspring are future purchases. Knowing a lot of behavior genetic implicated genes might help the profile, but at the end of the day it’s not a deal-breaker or a game-changer.

An analogy to current market research and prediction algorithms is particularly apropos I think. They creep people out. So I naturally expect people to be creeped out if the state or insurance company has detailed fleshed out acturial tables based on genetics and genomics. But genetics or genomics don’t make it any more or less scary on a deep level. Nor do they make the techniques qualitatively more effective. And the policy questions and responses are going to be the same no matter what.

(Republished from Discover/GNXP by permission of author or representative)
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In the comments below when it comes to genomic privacy I expressed a rather carefree attitude toward the future possibilities of dark prediction. Over at the comments were rather uniformly alarmed, and influenced by Gattaca. For example: “It’s really kind of shocking how accurate Gattaca is turning out to be.”

Unfortunately I haven’t watched Gattaca. I read a negative a review when the film came out, and since I don’t watch many movies in any case I passed. This I’ve come to regret because of the influence of the film, whether it was great as a work of art or not, is strong enough today to routinely be referenced. It seems to have pretty good reviews on Rotten Tomatoes, and it’s got some staying power on Google Trends. I keep meaning to watch it on Amazon Instant Video, but then there’s the opportunity cost of time. So I did the second best thing, I read the plot summary on Wikipedia.

The main thing I took away from reading the plot summary of the world of Gattaca is that the power of genetics to predict the future is far greater in that world than it will likely ever be in our own world. Not only that, but the marginal value of genomics in terms of the behavioral predictions which people fear in particular is not going to be that great. By marginal value, I’m alluding to the fact that one of the best guides to how you will turn out is how your parents turn out. We know that much of the variation of many traits like I.Q., height, and personality is heritable variation, in that variation in genes controls much of the variation in the trait in the population. But because much of that variation is dispersed across a wide range of genes simply finding a specific gene is likely to be of little added value. The most efficacious way to be “Gattacaed” is to be profiled by the behavior and morbidity of your family! Genome adds some juice on top of this, but not nearly as much as people fear.*

A secondary issue is that this focus on genes neglects the reality of stochastic variation. As long time reader “biologist” likes to point out even inbred C. elegans lines exhibit a lot of variation in trait outcome because you can’t just squeeze randomness out of the equation. That’s part of the reason biological processes and science is so sloppy in comparison to more deterministic fields like physics. So if you combine the fact that a substantial proportion of behavioral variation is just going to be due to random events because of the nature of the universe (e.g., the sensitivity of biological development to fluctuations in environment), along with the fact that a lot of the predictive value is already there in parental information, then any government or society which fixates on genes to the exclusion of all else is as “reality based” as Soviet Communism. It’s going to collapse, or it’s already totally crazy and the fixation on genomics is your last worry.

I expressed my amusement, frustration, and confusion, at this whole situation to David Dobbs yesterday on twitter. You see, I’ve been pegged as a “genetic determinist” since the beginning of my blogging. I regularly get caught in the “glass-half-empty” trap which Steven Pinker outlined in the early 2000s whereby asserting that ~50% of the variation of a trait might be controlled by genes gets you tagged as a genetic determinist, even if you are explicit in acknowledging that ~50% of the variation is obviously not controlled by variation of genes. I’m way more open than most people to the importance of biological factors in differences between sexes, and differences between populations and across the populations, as well as biologically encoded “human universals.” I really don’t stress too much about the fact that people disagree, I suspect I’m right and that we’ll know whether I’m right or wrong within the next decade or so because of the likely crystallization of much more expansive data sets of all sorts (genomic, behavioral, social, etc.) which will be mined by powerful analytic tools.

But with all that in the rear-view mirror it is really bizarre that I have to keep screaming that you don’t need to stress out about genomics as such. It’s part & parcel of the broader rise of information technology and self-awareness. It’s also part of the seamless whole of nature, a portion of which we’ve always been aware of. Everyone knows parents resemble offspring on a host of traits, even if they unlearn this truth later on. And whether a government believes that genes or a “frigid mother” “determines” outcomes, whether they do good or bad is independent of these sorts of details.

P.S. Only two people have offered to put their genotype into the public domain in the past week. If you want to do so, please email me at contactgnxp -at- gmail -com. Here is my genotype.

* Eventually though perhaps you could ascertain where you rank within the sibling pecking order in terms of mutational load, which would be informative.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Behavior Genetics, Gattaca, Genetics, Genomics 
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Razib Khan
About Razib Khan

"I have degrees in biology and biochemistry, a passion for genetics, history, and philosophy, and shrimp is my favorite food. If you want to know more, see the links at"