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41v0RwMV8OL._SY344_BO1,204,203,200_ I have an old friend from college who I’m in touch with via Facebook. He looks great. In fact, he looks like how I’d like to look. After a year of running and lifting I’m noticeably more muscular. I’m 150-155 pounds at 5’8, and according to my Aria I’ve lost about ~3% body fat (I’m not reporting the absolute value because it’s not that accurate, though the readings seem consistent day to day). But, since I’m South Asian and tend toward a “baby face” mien I’m not where I want to be in terms of definition. In contrast my friend is very toned. I asked him how he had changed his physique so much over the years, since in college he was rather “soft” looking. His response? Gay peer pressure.

This is why articles like this in Salon drive me crazy, You should never diet again: The science and genetics of weight loss. It’s excerpted from the book Secrets From the Eating Lab: The Science of Weight Loss, the Myth of Willpower, and Why You Should Never Diet Again. The author, Traci Mann, is a professor at the University of Minnesota, as she proudly notes:

To tease apart the effects of genes from the effects of the shared environment, researchers located identical twins that were raised in separate homes without knowing each other. It may seem surprising that there are enough sets of twins that meet this criteria, but there are. This type of twin research was partly pioneered in the very psychology department in which I work, at the University of Minnesota (coincidentally located in the twin cities of Minneapolis and St. Paul). If you go up to the fifth floor, the walls are covered with photographs of identical twins that were separated at the age of five months (on average) and had been apart for about thirty years before being reunited as adults. The visible similarities are remarkable, as are the many documented behavioral similarities.

The crucial twin study of body weight (which comes from the Swedish Adoption/Twin Study of Aging) included 93 pairs of identical twins raised apart (and 154 pairs of identical twins raised together). Sure enough, the weights of identical twins, whether they were raised together or apart, were highly correlated. That study, along with several others, led scientists to conclude that genes account for 70 percent of the variation in people’s weight. Seventy percent! What is truly remarkable is that this is only slightly lower than the role genes play in height (about 80 percent of the variation). Don’t get me wrong. I’m not saying you can’t influence your weight at all, just that the amount of influence you have is fairly limited, and you’ll generally end up within your genetically determined set weight range.

41nk1RoCEWL._SY344_BO1,204,203,200_ Many readers will be familiar with twin studies. If you aren’t, read Born that Way by William Wright. The strange thing about this reference to this scientific project is that it’s incongruous to see it in a Left-wing publication like Salon. The more moderate Slate trashed twin studies about four years ago, even though cutting edge genomic methods are now validating their results. Why all the hostility? Mostly it has to do with non-trivial heritabilities for intelligence and personality which come out of this type of research, which are not congenial to a particular sort of Left-wing mentality (see Steven Pinker’s The Blank Slate). I suspect the issue here is that the political valence is not alarming to the readers of Salon, who are very open arguments about “thin privilege”, and the idea that the heavy might be considered another protected class. The analogy then in terms of heritability and a biological basis for this trait is with homosexuality, where the Left favors genetic determinism. The same studies also come with high heritabilities for traits such as weight in developed world populations. The quoted results above are correct, but the implications that the public takes from them are misleading.

I’m pretty sure that Traci Mann knows the technical definition of heritability by the way she writes. That is, the proportion of phenotypic variation that can be explained by genetic variation within the population. The problem is that the general public is going to see “70 percent heritable” and think “70 percent genetic,” when that’s not even wrong. The way the piece is written also misleads in this fashion. One thing to note is that even though height is 80 to 90 percent heritable, the correlation between full siblings for this trait is only 0.50. I suspect this would surprise people since it is such a heritable trait, but that goes to show that a population wide heritability statistic has only modest utility on the individual scale. More importantly by analogy to height the norm of reaction matters a great deal. We know empirically that genetically similar populations vary in mean and variance of weight and height over time and in different environments.

Which goes back to social context. My friend now works out a lot and watches what he eats. It’s something that he does every day, and something that is enabled by the social environment in which he is embedded (see this music video about “Mean Gays”). Weight varies in the United States by class and region, and from what I recall this remains after you control for demographic variables. What this probably means is that it takes a village to sustain weight loss. So in a way those who argue that dieting is useless are correct. But they’re being misleading when they imply that your weight is ultimately “genetic.” It’s social.

Update: A friend emailed me and pointed out figure 2 in a recent Nature paper. It gets at what’s producing the heritability statistic:

nature14177-f2 (1)

• Category: Science • Tags: Heritability 
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1280px-Galton_experimentA few weeks ago I went hiking around Lake Tahoe, and at a local coffee shop I couldn’t help overhearing a bunch of middle-aged women enthusing wildly about a new service which matches you up with someone based on your genetic profiles. They noticed my gawking and so I stopped listening, but honestly I was somewhat worried that they were so credulous. A Slate piece, Online dating sites use DNA to make perfect matches. Does it really work?, hits most of the major issues that I have with these services. As noted in the Slate review the various results attempting to correlate MHC profiles with attraction have been mixed at best (i.e., they don’t seem particularly robust). But the bigger issue to me is that even if there is a modest population-wide effect which has an underlying evolutionary basis, it is unlikely to be one of the parameters impacting relationship success. What I mean is that even if immune profile matching (or lack thereof) matters, it matters far less than other variables which are much more visible and obvious. For example, physical attraction and cultural compatibility.

Genetics is real. It’s powerful. It matters. And that means all sorts of snake-oil salesmen will start to enter the field to make money. No surprise. The reality is that for most things that matter you already know the likely genetic outcome. Look at the parents.

• Category: Science • Tags: Heritability 
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Credit: John Hawks

Credit: John Hawks

In the comments below there was a question as to why outcomes for offspring from parents can vary a great deal even without regression toward the mean. First, about regression. It’s a confusing and misunderstood concept. There is a general statistical phenomenon here, but let’s focus on genetics. Often in the comments of this weblog I’ll get the rhetorical question which has the general form of “but what about regression toward the mean?” Usually this is a good clue that the person has no idea what they are talking about. What about regression toward the mean? It’s not a magical force which shifts populations back toward a set point in an orthogenetic fashion. Basically when you select an individual based on their traits, and infer about the likely character of their offspring, you can predict the expected impact of genes on the outcome. The phenotype is an intelligible signal of the nature of genes in a heritable trait, and genes are predictably transmitted to offspring. In contrast there is an “environmental”* component which you don’t understand, can’t control, and can’t account for. This component is often not transmitted across the generations, so fluke contingencies which lead to individuals who are sharply deviated from the average of a population are not replicated in subsequent generations, and individuals are expected to be more typical. A perfectly heritable trait would not regress at all on the population level.

But you can predict only so much from heritability. The above plot is from John Hawks’ anthropology class. You see that the regression line is 0.72, so the heritability as inferred from these data is such. That means that 72% of the variance in the phenotype, height, can be accounted for by variance in genes. That’s a population wide statistic. That doesn’t mean that height is “72% genetic” on the individual level. That’s not even wrong. Since heritability is a population wide measure, so you need to be judicious when inferring toward individuals.

Yet still tall parents tend to have tall children. If two tall parents had hundreds of children, then you could make some inferences about the average height of the children using the breeder’s equation. But observe that there’s still noise in the prediction. There’s going to be a distribution of outcomes. Height in the developed world is 80 to 90 percent heritable, but the correlation in heights between siblings is on the order of 0.5. Similarly, IQ is on the order of 50 percent heritable, but the correlation between siblings is on the order of 0.5. Presumably segregation and recombination are working in a fashion to mix and match the genomes of individuals so that even heritable polygenic traits aren’t quite as predictable as you’d think.

* Before someone points it out, I am aware this component often collapses non-additive genetic variance, such as epistasis.

• Category: Science • Tags: Heritability 
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The above clip of Neil DeGrasse Tyson has been lighting up my social feeds. It’s made Upworthy. Tyson ends by stating that “Before we start talking about genetic differences [between race and gender], you gotta come up with a system where there is equal opportunity, then we can have that conversation.” The major question that immediately comes to mind with these sorts of assertions, which are quite ubiquitous, is how one determines the extent of equal opportunity if one does not have a model for the outcomes of equal opportunity. The reality is that those making such claims have a model of the outcomes, unstated because it is shared by so many. Proportionate representation, because they assume that in fact that there are no innate dispositional differences* between groups. The Left liberal version of Homo economicus. Once this model is in place then lack of proportionate representation can be taken as ipso facto evidence of lack of equal opportunity.** With this model in hand innate dispositional differences would give the same outcomes, but could be taken as evidence of lack of equal opportunity. So ultimately the “lack of interest” in these issues dovetails nicely with priors. If it turned out there were differences between the groups that the model would start to get messier.***

Since the clips such as above are shared by like minded individuals naturally there’s no strong critique. Rather, the assertions are “devastating”to the opposing view, which are almost entirely absent among like-minded individuals. Larry Summers may be a moderately liberal Democrat, but his airing of possible differences between males and females in the early aughts is now grounds for reading him out of polite company from what I can tell. A few years ago I had dinner with Chris Mooney about his contention that overall there is a greater skepticism of science among Republicans/Right than Democrats/Left. I can accede to this point as being possible. It seems unlikely skepticism of science or religion or any other cultural trait would be equally distributed across the ideological spectrum, and in our day and age in the United States natural scientists tend to align with the political Left, and the political Right has a generalized distrust for intellectuals. But I pointed out to Chris that on the modern cultural Left acknowledgement of sex differences seems to still be in bad odor. But a moderate amount of sexual dimorphism seems to be evident in the natural history of our own species, so it isn’t unreasonable to posit some differences. But many now consider it an implausible prior. Chris was skeptical, as he contended that this battle had ended long ago, and a hardcore “blank slate” position has lost. I wish it were so. I had the experience of having an exchange with a prominent science writer with a background in science who would not concede that men, on average, have stronger upper bodies than women. When push comes to shove I doubt that this person would stand by such skepticism, but it illustrates how deep the reflex is if even basic size and strength differences are now subject to interrogation.

The normative roots of skepticism in this domain become clear when one focuses on the one area where Left and Right invert when it comes to the biological basis of human behavior: homosexuality. As a moderately heritable complex trait it seems entirely likely there is a biological basis for homosexuality, at least in part. But the case has not been clinched by a “gay gene,” nor is the trait one which develops in a genetically deterministic fashion like the generation of five fingers on one’s hand. For reasons common to many complex traits it seems unlikely that there will ever be found a singular “gay gene,” and evidence from fields such as psychology and neurobiology do not offer silver bullet models for how homosexuality comes about, because its expression has environmental correlates (for example, same-sex intercourse is practiced in a facultative manner in prison in the Arab world, without being homosexual orientation, so some nuance in terminology is necessary). But the cultural Left, and now the majority of young Americans, can grasp that a complex behavioral trait does not necessarily lend itself to explanatory models as simple as Newtonian physics. The threshold of skepticism of “innate differences” seems to curiously be lower in this case for the Left, and tuned up higher on the social Right.

Motivated reasoning is powerful. This will not be answered by one blog post, or a decades’ worth of research. Because complex traits have genetic architectures which are not easily reducible to a few genes of large effect, “final answers” may be a while in coming (if ever). But the truth is what it is. Even if people in the United States “lack interest” in particular subjects, that is unlikely to stop other nations, whose economies and scientific institutions are still developing, from exploring avenues of research neglected by Americans. Obviously there are no perfectly objective humans, but one convenient fact about ideological bias is that different groups have different blind spots. The future will likely be one of scientific cooperation as a side effect of competition.

Finally, it is always useful for me to outline some of my thoughts by referring to a piece by one of the greatest population geneticists of the 20th century, James F. Crow. He writes in Unequal by nature:
a geneticist’s perspective on human differences

Two populations may have a large overlap and differ only slightly in their means. Still, the most outstanding individuals will tend to come from the population with the higher mean. The implication, I think, is clear: whenever an institution or society singles out individuals who are exceptional or outstanding in some way, racial differences will become more apparent. That fact may be uncomfortable, but there is no way around it.

The fact that racial differences exist does not, of course, explain their origin. The cause of the observed differences may be genetic. But it may also be environmental, the result of diet, or family structure, or schooling, or any number of other possible biological and social factors.

My conclusion, to repeat, is that whenever a society singles out individuals who are outstanding or unusual in any way, the statistical contrast between means and extremes comes to the fore. I think that recognizing this can eventually only help politicians and social policymakers.

The basic model is exceedingly simple. Representation of the tails of a distribution can be much more skewed than small differences in mean values might imply. Let’s give a concrete illustration. Imagine a population at the mean of the height for American males. 70 inches or 5’10). Assuming a standard deviation of 2 inches and a normal distribution 1 out of 770 males will be 76 inches or above (6’4 or greater).**** Now imagine a population where the average height for males is 71 inches. Obviously most of the distribution will overlap. But now 1 out of 161 males is 76 inches or above. For the two populations the overwhelming number of individuals are going to occupy the vast middle ground about the mean. But for particular professions great height might be indispensable, in which case the two populations may have greatly different representations in such fields.

I’m thinking in the above case American basketball. But it is key to remember that basketball requires more than great height. It requires grace and strength as well. In some domains, such as professional sports and the highest echelons of the academy, it seems likely that individuals will exhibit a combination of exceptional traits, not just one, in which case the above argument is further amplified.

None of this is difficult to understand, even if you reject any empirical basis in specific cases. But 10 years of discussing this topic has informed me that this is irrelevant, when people are highly motivated they will refuse to engage in what Ernst Mayr terms “population thinking”. Rather, they will insist on referring to typologies, rather than distributions, even if one asserts that one is discussing distributions. For one, this is comfortable as a mode of analysis for humans. Categories are clear and distinct. Second, it makes for much easier refutation of plainly incorrect categorical assertions. But despite futility some things must be said now and again.

Addendum: There are some asking how one can disentangle environmental and genetic effects. That is a large part of what fields like behavior genetics, and now much of social science, attempt to do. But that being said I have outlined a very simple design enabled by modern genomics, leveraging the imperfect correlation between genomic ancestry and physical appearance.

* These need not be heritable or genetic. So I’m being vague with the terminology.

** A second implicit assumption is a normative understanding of how humans flourish and the set of choices which they should make to self-actualize.

*** It isn’t logically impossible to contend that there are differences between populations/sexes which make proportional representation unlikely, and, that there are social impediments which might amplify or dampen skewed representation in particular fields. The former cases seem self-evident, but what would I put in the latter categories? Clearly throughout the 20th century the representation of Jews, and later Asians in the United States, in areas of higher education have been dampened by quota systems. Similarly, segregation in sports resulted in an over-representation of non-Hispanic whites in many fields in the United States. Once equality of opportunity was allowed (or in cases where it has been) one saw not a decrease, but increase, is representation in the elite levels away from population wide proportions.

**** In reality many quantitative traits exhibit “fat tails,” so there are more individuals at the extremes than one might expect. But that doesn’t alter the qualitative effect.

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Sir Francis Galton

Modern evolutionary genetics owes its origins to a series of intellectual debates around the turn of the 20th century. Much of this is outlined in Will Provines’ The Origins of Theoretical Population Genetics, though a biography of Francis Galton will do just as well. In short what happened is that during this period there were conflicts between the heirs of Charles Darwin as to the nature of inheritance (an issue Darwin left muddled from what I can tell). On the one side you had a young coterie around William Bateson, the champion of Gregor Mendel’s ideas about discrete and particulate inheritance via the abstraction of genes. Arrayed against them were the acolytes of Charles Darwin’s cousin Francis Galton, led by the mathematician Karl Pearson, and the biologist Walter Weldon. This school of “biometricians” focused on continuous characteristics and Darwinian gradualism, and are arguably the forerunners of quantitative genetics. There is some irony in their espousal of a “Galtonian” view, because Galton was himself not without sympathy for a discrete model of inheritance!

William Bateson

In the end science and truth won out. Young scholars trained in the biometric tradition repeatedly defected to the Mendelian camp (e.g. Charles Davenport). Eventually, R. A. Fisher, one of the founders of modern statistics and evolutionary biology, merged both traditions in his seminal paper The Correlation between Relatives on the Supposition of Mendelian Inheritance. The intuition for why Mendelism does not undermine classical Darwinian theory is simple (granted, some of the original Mendelians did seem to believe that it was a violation!). Many discrete genes of moderate to small effect upon a trait can produce a continuous distribution via the central limit theorem. In fact classical genetic methods often had difficulty perceiving traits with more than half dozen significant loci as anything but quantitative and continuous (consider pigmentation, which we know through genomic methods to vary across populations mostly due to half a dozen segregating genes or so).

Notice here I have not said a word about DNA. That is because 40 years before the understanding that DNA was the substrate of genetic inheritance scientists had a good grasp of the nature of inheritance through Mendelian processes. The gene is fundamentally an abstract unit, an analytic element subject to manipulation which allows us to intelligibly trace and predict patterns of variation across the generations. It so happens that the gene is instantiated in a material sense through sequences of the biomolecule DNA. This is very important. Because we know the material basis of modern genetics it is a much more fundamental science than economics (economics remains mired in its “biometric age!”).

The “post-genomic era” is predicated on industrial scale analysis of the material basis of genetics in the form of DNA sequence and structure. But we shouldn’t confuse DNA, concrete bases, with classical Mendelism. A focus on the material and concrete is not limited to genetics. In the mid-2000s there was a fad for cognitive neuroscience fMRI studies, which were perceived to be more scientific and convincing than classical cognitive scientific understandings of “how the mind works.” In the wake of the recession of fMRI “science” due to serious methodological problems we’re left to fall back on less sexy psychological abstractions, which may not be as simply reduced to material comprehension, but which have the redeeming quality of being informative nonetheless.

This brings me to the recent paper on SNPs associated with education in a massive cohort, GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment. You should also read the accompanying FAQ. The bottom line is that the authors have convincingly identified three SNPs to explain 0.02% of the variation in educational attainment across their massive data set. Pooling all of the SNPs with some association they get ~2% of the variation explained. This is not particularly surprising. A few years back one of the authors on this paper wrote Most Reported Genetic Associations with General Intelligence Are Probably False Positives. Those with longer memories in human genetics warned me of this issue in the early 2000s. More statistically savvy friends began to warn me in 2007. At that point I began to caution people who assumed that genomics would reveal the variants which are responsible for normal variation on intelligence, because it seemed likely that we might have to wait a lot longer than I had anticipated. As suggested in the paper above previous work strongly implied that the genetic architecture of intelligence is one where the variation on the trait in the normal range is controlled by innumerable alleles of small effect segregating in the population. Otherwise classical genetic techniques may have been able to detect the number of loci with more surety. If you read Genetics of Human Populations you will note that using classical crossing techniques and pedigrees geneticists did in fact converge upon approximately the right number of loci segregating to explain the variation between European and African pigmentation 60 years ago!

Some of my friends have been arguing that the small effect sizes here validate the position that intelligence variation is mostly a function of environment. This is a complicated issue, and first I want to constrain the discussion to developed Western nations. It is an ironic aspect that arguably intelligence is most heritable among the most privileged. By heritable I mean the component of variation of the trait controlled by genes. When you remove environmental variation (i.e. deprivation) you are left with genetic variation. Within families there is a great deal of I.Q. difference across siblings. The correlation is about 0.5. Not bad, but not that high. Of course some of you may think that I’m going to talk about twin studies now. Not at all! Though contrary to what science journalists who seem to enjoy engaging in malpractice like Brian Palmer of Slate seem to think classical techniques have been to a great extent validated by genomics, it is by looking at unrelated individuals that some of the most persuasive evidence for the heritability of intelligence has been established. It is no coincidence that one of the major authors of the above study also is an author on the previous link. There is no contradiction in acknowledging difficulties of assessing the concrete material loci of a trait’s variation even if one can confidently infer that association. There was genetics before DNA. And there is heritability even without specific SNPs.

Additionally, I want to add one caveat into the “environmental” component of variation. For technical reasons this environmental component may actually include relatively fixed biological variables. Gene-gene interactions, or developmental stochasticity come to mind. Though these are difficult or impossible to predict from parent to offspring correlations they are not as simple as removing lead from the environment of deprived children. My own suspicion is that the large variation in intelligence across full siblings tell us a lot about the difficult to control and channel nature of “environmental” variation.

Finally, I want to point out that even small effect loci are not trivial. The authors mention this in their FAQ, but I want to be more clear, Small genetic effects do not preclude drug development:

Consider a trait like, say, cholesterol levels. Massive genome-wide association studies have been performed on this trait, identifying a large number of loci of small effect. One of these loci is HMGCR, coding for HMG-CoA reductase, an important molecule in cholesterol synthesis. The allele identified increases cholesterol levels by 0.1 standard deviations, meaning a genetic test would have essentially no ability to predict cholesterol levels. By the logic of the Newsweek piece, any drug targeted at HMGCR would have no chance of becoming a blockbuster.

Any doctor knows where I’m going with this: one of the best-selling groups of drugs in the world currently are statins, which inhibit the activity of (the gene product of) HMGCR. Of course, statins have already been invented, so this is something of a cherry-picked example, but my guess is that there are tens of additional examples like this waiting to be discovered in the wealth of genome-wide association study data. Figuring out which GWAS hits are promising drug targets will take time, effort, and a good deal of luck; in my opinion, this is the major lesson from Decode (which is not all that surprising a lesson)–drug development is really hard

Addendum: Most of my friends, who have undergraduate backgrounds in biology, and have taken at some quantitative genetics, seem to guess the heritability of I.Q. to be 0.0 to 0.20. This is just way too low. But is it even important to know this? I happen to think an accurate picture of genetic inheritance is probably useful when assessing prospects of mates….

Citation: Rietveld, Cornelius A., et al. “GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment.” Science (New York, NY) (2013).

(Republished from Discover/GNXP by permission of author or representative)
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Recently I was at the dentist and I was told that because I did not have any caries at this age, I would probably not have to worry about that in the future (in contrast, I do have some issues with gingivitis). I wasn’t surprised that I didn’t have caries, I have no great love of sweet confections. I had chalked up my evasion of this dental ailment to my behavior. To make a long story short my dentist disabused me of the notion that dental pathologies are purely a function of dental hygiene and diet. Rather, he explained that many of these ailments exhibit strong family and ethnic patterns, and are substantially heritable. My mother did suffer from periodontal disease a few years back, and that has made me much more proactive of my own dental health.

As someone who is quite conscious of the power of genetics, I was quite taken aback by this blind spot. I realized that not only did I attribute my own rather fortunate dental health (so far) to my personal behaviors, but, I had long suspected those with dental issues of less than optimal habits. Obviously environment (e.g., high sugar diet) does matter. But apparently a great deal of the variation in the trait is heritable. If you are still curious, here’s a paper which might interest you, Heritable patterns of tooth decay in the permanent dentition: principal components and factor analyses.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Health, Heritability 
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One of the more fascinating things about getting much of your child’s pedigree genotyped is that one can ascertain true relatedness to various relatives, rather than just expected relatedness. For example, 28% of her genome is identical by descent from my father, while 22% is from my mother. She is 26% identical by descent with one uncle, and 24% with another. More practically, the understanding of patterns realized and concrete genetic relatedness within families allows us another avenue into teasing apart heritability. Though this method has been around for more than half-a-decade, I find it curious that when I post on it some commenters immediately make objections to twin studies. Why? Because they assume that the analysis had to be a twin study because they don’t know of the genomic methodology!

But on a broader evolutionary scale, does this matter? Two of my siblings have a relatedness of 41%. In other words, as you can see in the histogram there is a wide variation in relatedness. Might this perhaps impact social relations? One can imagine genetically more similar siblings aligning against those who are dissimilar. Or not. I am skeptical that this would apply to humans, but I do wonder about organisms with larger broods. If we don’t find much variation on the scale of siblings, despite genetic variation (and therefore, likely phenotypic tells of similarity), then I would hazard to suggest that inclusive fitness is not quite the razor sharp discerning tool that some posit it is. Rather, it is part of the broader swiss army knife of behavioral ecology.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Genetics, Heritability 
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According to the reader survey 88 percent said they understood what heritability was. But only 34 percent understood the concept of additive genetic variance. For the purposes of this weblog it highlights that most people don’t understand heritability, but rather heritability. The former is the technical definition of heritability which I use on this weblog, the latter is heritability in the colloquial sense of a synonym for inheritance, biological and cultural. Almost everyone who understands the technical definition of heritability will know what heritability in the ‘narrow sense’ is, often just informally termed heritability itself. It is the proportion of phenotype variability that can be attributed to additive genetic variation. Those who understand additive genetic variance and heritability in the survey were 32 percent of readers. If you understand heritability in the technical manner you have to understand additive genetic variance. This sets the floor for the number who truly understand the concept in the way I use on this weblog (I suspect some people who were exceedingly modest who basically understand the concept for ‘government purposes’ put themselves in the ‘maybe’ category’). After nearly 10 years of blogging (the first year or so of which I myself wasn’t totally clear on the issue!) that’s actually a pretty impressive proportion. You take what you can get.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Heritability, Quantitative Genetics 
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Tim Pawlenty debates Lady Gaga’s ‘Born This Way’ idea:

Gregory pressed, asking “Is being gay a choice?”

Pawlenty ultimately said, “I defer to the scientists in that regard.”

Again, Gregory pressed: “So you, you think it’s not a choice. … That you are, as Lady Gaga says, you’re born that way.”

Said Pawlenty: “There’s no scientific conclusion that it’s genetic. We don’t know that. So we don’t know to what extent, you know, it’s behavioral, and that’s something that’s been debated by scientists for a long time. But as I understand the science, there’s no current conclusion that it’s genetic.”

This is one issue where the American Left has a tendency to be on the side of the hereditarians. In contrast, the American Right emphasizes the plasticity of human behavior, and its amenability to cultural pressures and individual will and contingency. Transpose the structure of the arguments to male-female sex differences, and many of the basic elements would be preserved, but those espousing them would invert politically.

One issue which needs to be clarified is the distinction between something which is explainable by genetics, and something which is not explainable by genetics but may still have a biological basis. It does seem that homosexuality is only modestly heritable. That means that genetic variation can not explain all the population wide variation in sexual orientation. The correlation between identical twins on height is much tighter than when it comes to homosexuality.

Does that mean then that since so much of the variation in homosexuality is “environmental” it is amenable to change? Let’s focus on male homosexuals, as the heritability estimates for female homosexuals are so much lower. “Environment” in these heritability estimates means a lot of different things. It can include what we normally think of environment, socialization. But it can also include pre-natal and post-natal developmental randomness which induces unpredictable biological variability. Then there are the mysterious changes wrought by infection. Finally, even non-linear gene-gene interactions are often included in the “environmental” component. In other words, even if most of the variance in homosexual behavior can’t be explained by variance in genes, that doesn’t imply that a male who has a homosexual orientation at the age of 12 is going to be able to change that through behavioral therapy with any ease.

At the end of the day I doubt we’ll fine a “gay gene” in the near future. And without that, people like Tim Pawlenty will continue to take the stand they’re taking now. Revised upward heritability estimates wouldn’t change anything either, if people don’t want to believe that a behavior has a strong biological basis for ideological reasons, unless you can offer up a robust concrete genetic association they’ll keep denying in my experience.

But a bigger meta issue has to be “so what?” If homosexuality has a biological basis, then in the long term one can imagine that someone could devise a “cure” for it, just as they have claimed with today with talk therapy and what not. But that’s the long term. In the short run it does seem that if something is biological the naturalistic fallacy will loom large in our political debates.

(Republished from Discover/GNXP by permission of author or representative)
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On several occasions I’ve gotten into discussions with geneticists about the possibility of reconstructing someone’s facial structure by genes alone. Combined with advances in pigmentation prediction by genetics, this could put the sketch artist out of business! But all that begs the question: how heritable are facial features anyhow? Impressionistically we know that feature are broadly heritable. This isn’t a tenuous supposition, you see the resemblance over and over across families. All that being said, what are the specific quantitative heritability estimates? How do they relate to other traits we’re interested in? This review from the early 1990s seems to have what I’m looking for, The Role of Genetics in Craniofacial Morphology and Growth. Below is a table which shows averaged heritabilities for a range of facial quantitative traits from a large number of studies:

h2 is the narrow-sense heritability. Also, in care you are curious cephalometry seems to be utilizing imaging of some sort. Anthropmetry refers to the more conventional measuring techniques (get out the calipers!). These results suggest that facial features are typically more heritable than behavioral traits (usually < 0.50), but less heritable than height (0.8-0.9). This seems plausible to me.

These results came to my attention because of a paper in the European Journal of Human Genetics, Genetic determination of human facial morphology: links between cleft-lips and normal variation:

Recent genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with non-syndromic cleft lip with or without cleft palate (NSCL/P), and other previous studies showed distinctly differing facial distance measurements when comparing unaffected relatives of NSCL/P patients with normal controls. Here, we test the hypothesis that genetic loci involved in NSCL/P also influence normal variation in facial morphology. We tested 11 SNPs from 10 genomic regions previously showing replicated evidence of association with NSCL/P for association with normal variation of nose width and bizygomatic distance in two cohorts from Germany (N=529) and the Netherlands (N=2497). The two most significant associations found were between nose width and SNP rs1258763 near the GREM1 gene in the German cohort (P=6 × 10−4), and between bizygomatic distance and SNP rs987525 at 8q24.21 near the CCDC26 gene (P=0.017) in the Dutch sample. A genetic prediction model explained 2% of phenotype variation in nose width in the German and 0.5% of bizygomatic distance variation in the Dutch cohort. Although preliminary, our data provide a first link between genetic loci involved in a pathological facial trait such as NSCL/P and variation of normal facial morphology. Moreover, we present a first approach for understanding the genetic basis of human facial appearance, a highly intriguing trait with implications on clinical practice, clinical genetics, forensic intelligence, social interactions and personal identity.

The authors get to the point at the very end of the discussion:

In conclusion, we have demonstrated that association with one marker could explain ca. 2% of nose width variation, and a tentative association between bizygomatic distance and other markers could account for about 0.5% of variation. Finally, our study represents the first approach to understanding genetic control of facial morphology, demonstrating that predicting facial distance traits from genetic markers is not nearly as straightforward as it is for human eye…and hair color…and that further genetic research will be needed to identify predictive genetic markers, which could achieve the accuracy needed for practical applications such as future forensics.

In other words, the genetic architecture of the traits which govern facial features are going to be more like height than pigmentation. That means forensic facial reconstruction will be a way off in the distance. But how far in the distance? A friend pointed out recently if that full genome sequences were ever associated with Facebook profiles that might be a data miner’s dream come true. The way is already out there, the key is the will, ethical and computational.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Genetics, Genomics, Heritability, Human Genetics 
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Epigenetics is making it “big time,” Slate has a review up of the new book Epigenetics: The Ultimate Mystery of Inheritance. In case you don’t know epigenetics in terms of “what it means/why it matters” holds out the promise to break out of the genes → trait conveyor belt. Instead positing genes → trait → experience → genes, and so forth. Or perhaps more accurately genes → trait × experience → genes. Epigenetics has obviously long been overlooked as a biological phenomenon. But, I think the same could be said for the ubiquity of asexual reproduction and unicellularity! Life science exhibits anthropocentrism. That’s why there’s human genetics, and biological anthropology. My own concern is that epigenetics will give some a license to posit that the old models have been overthrown, when in fact in many cases they have been modified on the margin. Especially at the level of organisms which we’re concerned about; human-scaled eukaryotes. Humans most of all.

The last paragraph in the review highlights the hope, promise, and perils of epigenetics in regards to social relevance:

It’s almost enough to make one nostalgic for the simplicity of old-style genetic determinism, which at least offered the sense that the genetic hand you were dealt at birth was the same one you would play your whole life—except that epigeneticists hold out the promise that the blessings of a single life, too, can be passed on. Disease researchers, Francis reports, have hopes that the effects of abnormal epigenesis may be reversed. For example, it’s possible that the damage caused by many cancers is epigenetic. If those epigenetic attachments can be altered, then it’s possible the cancer can be stopped. Still, even if we are discovering that an extraordinary range of conditions may be epigenetic, not all of them are. There are still specific diseases that follow a deterministic path. If you are unlucky enough to draw the Huntington’s mutation in the genetic shuffle, you will develop the disease. Francis rightly emphasizes the wonder of epigenetics and the molecular rigor it brings to the idea that life is a creative process not preordained by our genome any more than it is preordained by God. Yet even as epigenetic research invites dreams of mastery—self-creation through environmental manipulation—it also underscores our malleability. There is no easy metaphor for this combination. But if we must have one, we should at least start with the cell, not the gene. The genome is no blueprint, but maybe the cell is a construction site, dynamic, changeable, and complicated. Genes are building materials that are shaped by the cell, and they in turn create materials used in the cell. Because the action at the site is ongoing, a small aberration can have a small effect, or it can cascade through the system, which may get stuck. Recall that your body is a moving collection of these building sites, piled in a relatively orderly way on top of another. Malleability? It’s an ongoing dance with chaos, but, incredibly, it works.

If people have a hard enough time with the concept of heritability, I have no idea how they’ll deal with heritability of epigenetic modifications! In science itself epigenetics has really come to the fore over the last 10 years. Here’s a plot which shows the change over time in the scientific literature:

And here’s the Google Trends results:

Either the media only discovered epigenetics in 2008, or Google’s index wasn’t very good. I suspect the former, as I started being asked about the term by intellectual non-science types circa 2008. For Google Correlate “epigenetic” and “subjective” have a correlation of 0.91, and “epigenetics” and “we create” have a correlation of 0.89. These are a little disturbing, and I hope epigenetics doesn’t go the way of quantum theory and general relativity and become abused in other disciplines. For example, “epigenetics means that genetic inheritance is a subjective fiction!”

(Republished from Discover/GNXP by permission of author or representative)
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At The Intersection Chris Mooney points to new research which reiterates that 1) political ideology exhibits some heritability, 2) and, there are associations between political ideology and specific genes. I’ll set #2 aside for now, because this is a classic “more research needed” area at this point. But as I mentioned in the comments the heritability of political ideology is well known and robust. From what I can gather most people assume it’s mediated through personality traits. In the comments Chris asks:

That sounds sensible. What i find amazing is that if the heritability of politics is so robust–and I agree, it would happen via personality–why is this so widely ignored?

There are I think several issues at work. First, many people are not comfortable within imagining that beliefs which they attribute to their conscious rational choice are not only subject to social inculcation, but that may also have an element of genetic disposition. Second, most people have a poor grasp of what heritability implies. Take a look at some of Chris’ commenters. The response is generally in the “not even wrong” class. Finally, what’s the actionable component to this? In other words, what are people going to do with this sort of information?

I think there is a possible way in which heritability information might be used: you could consciously try to reshape the environmental context in which it is expressed so that the norm of reaction is recentered. This is related to the concept of the “Overton window”. Gay rights in the United States is the best illustration of that. Today a moderate conservative position is to favor civil unions. Yet in the year 2000 the very socially liberal state of Vermont was riven by conflict over the very possibility of civil unions. The “center” has moved, and so has the “right” and “left.”

The disposition toward conservatism and liberalism does not manifest in absolute tendencies, but attitudes and actions comprehensible only against a reference which allows for one’s own bias to come to the fore. This is why heritabilities of being conservative and liberal can remain the same over time and across cultures, even though conservative and liberal can mean very different things in different contexts. Some natural genetic variance in the traits which allow for political ideological difference may also suggest to us there is little possibility of a “end of politics,” where there is total unanimity on all topics. When consensus is achieved, there will presumably always be some who wish to push the boundaries of innovation further, and those who resist just as fiercely. Just as there will always be a minority who may pine for the days of yore, while everyone else looks at them as if they’re loony.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Ideology, Science • Tags: Behavior Genetics, Heritability, Politics 
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I’m going to promote a comment:

…would knowing the root biological cause for differences which are already apparent to us change anything?

It’s obvious to you that there’s a contradiction here, but to the average educated person this makes total sense.

The proximal reason seems to be that in thinking about “genetic” and “environmental” factors, the average educated person still fundamentally views “genetics” as equivalent to genetic determinism and “environmental” factors as equivalent to social norms or parenting tactics. In this black-and-white view of human development, quantitative distinctions and complex causal models have no place. Genetic causes are irremediable and ever-lasting, whereas environmental causes are a generation-away from disappearing with the right appropriations to social programs. That’s why an environmental cause for phenotypic differences doesn’t “count” but a genetic one is game changing.

It seems as if the nature-nurture world view painted in the 1970s by the anti-heredity crowd has remained largely intact with only minor modifications in the mind of the average educated person. Since the 1970s, they now know to respond to questions about nature-vs-nurture by saying “both”, but their understanding goes no deeper than that. As best as I can tell, “both” to them just means genetic-determinism in some cases and environmental effects in other cases. When pressed, they also seem to believe that the environment ultimately determines which matters when — “genetics” matters only because we are nurturing enough.

With this in mind, imagine their confusion and horror at being told about non-zero heritability. It’s as if a person who believes the world is flat is told that someone can sail westward from Europe to Asia. Because they can’t imagine a round world, they have to instead imagine that there’s a portal on the edge of the world that takes you from one side to the other. Granted that’s a limited analogy, but I think that’s what you’re seeing here — total confusion. Importantly, this is basically what everyone believes.

Alas, I’m not a good communicator. At least not to my satisfaction. Long time readers still speak about “nature” and “nurture” in a colloquial manner which makes it clear that they haven’t internalized what heritability implies about the irrelevance of the structure of their argument. Almost all of the discourse about genetics, and quantitative traits, whether it be behavioral or physical (e.g., obesity in the latter case), in the public domain is basically in a “not-even-wrong” category of incoherence. But we must muddle on. What else can we do? I wish David Dobbs the best of luck with his new enterprise.

(Republished from Discover/GNXP by permission of author or representative)
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The Pith: In this post I examine how looking at genomic data can clarify exactly how closely related siblings really are, instead of just assuming that they’re about 50% similar. I contrast this randomness among siblings to the hard & fast deterministic nature of of parent-child inheritance. Additionally, I detail how the idealized spare concepts of genetics from 100 years ago are modified by what we now know about how genes are physically organized, and, reorganized. Finally, I explain how this clarification allows us to potentially understand with greater precision the nature of inheritance of complex traits which vary within families, and across the whole population.

Humans are diploid organisms. We have two copies of each gene, inherited from each parent (the exception here is for males, who have only one X chromosome inherited from the mother, and lack many compensatory genes on the Y chromosome inherited from the father). Our own parents have two copies of each gene, one inherited from each of their parents. Therefore, one can model a grandchild from two pairs of grandparents as a mosaic of the genes of the four ancestral grandparents. But, the relationship between grandparent and grandchild is not deterministic at any given locus. Rather, it is defined by a probability. To give a concrete example, consider an individual who has four grandparents, three of whom are Chinese, one of whom is Swedish. Imagine that the Swedish individual has blue eyes. One can assume reasonably then on the locus which controls blue vs. non-blue eye color difference one of the grandparents is homozygous for the “blue eye” allele, while the other grandparents are homozygous for the “brown eye” alleles. What is the probability that any given grandchild will carry a “blue eye” allele, and so be a heterozygote? Each individual has two “slots” at a given locus. We know that on one of those slots the individual has only the possibility of having a brown eye allele. Their probability of variation then is operative only on the other slot, inherited from the parent whom we know is a heterozygote. That parent in their turn may contribute to their offspring a blue eye allele, or a brown eye allele. So there is a 50% probability that any given grandchild will be a heterozygote, and a 50% probability that they will be a homozygote. The above “toy” example on one locus is to illustrate that the variation that one sees among individuals is in part due to the fact that we are not a “blend” of our ancestors, but a combination of various discrete genetic elements which are recombined and synthesized from generation to generation. Each sibling then can be conceptualized as a different “experiment” or “trial,” and their differences are a function of the fact that they are distinctive and unique combinations of their ancestors’ genetic variants. That is the most general theory, without any direct reference to proximate biophysical details of inheritance. Pure Mendelian abstraction as a formal model tells us that reproductive events are discrete sampling processes. But we live in the genomic age, and as you can see above we can measure the variation in genetic relationships among siblings today in an empirical sense. The expectation, as we would expect, is 0.50, but there is variance around that expectation. It is not likely that all of your siblings are “created equal” in reference to their coefficient of genetic relationship to you.

We know now that the human genome consists of about ~3 billion base pairs of A, G, C, and T. In the oldest classical evolutionary genetic models each of these base pairs can be conceived to be inherited independently from the other. In other words, evolution is a game of independent probabilities. But this idealization is not the concrete reality. To the left is a visualization of a human male karyotype, the set of 23 chromosomal pairs which the human genome (excluding the mtDNA) manifests as. Because the ~3 billion aforementioned base pairs have a physical position within these chromosomes the reality is that some are inherited together. That is, their inheritance patterns are associated due to their physical linkage. The karytope you see is clearly diploid. Each chromosome is divided into two symmetrical homologs, inherited from each parent (except 23, the sex chromosomes). The chromosomal numbers also correspond roughly to a rank order of size. To give you a sense of the gap, chromosome 1 has 250,000,000 bases and 4,200 genes, while chromosome 22 has 1,100 genes and 50,000,000 bases (the Y chromosome has a paltry 450 genes, as opposed to the 1,800 on the X).

In the toy example above the eye color locus is on a chromosome. Specifically, chromosome 15. Each individual will inherit one copy of 15 from their parents. But, there is no guarantee that each sibling will inherit the same copy from the generation of the grandparents. Let’s illustrate this schematically. Below you see the four combinations possible in relation to the chromosomes inherited by an individual’s parents from their own parents. So “paternal” and “maternal” here is in reference from the parental generation, so there are two of each. The ones inherited from the parental mother I’ve italicized.

Possible outcomes of combinations from grandparents
Paternal Maternal
Father Paternal Paternal Paternal Paternal Maternal
Maternal Maternal Paternal Maternal Maternal

The outcome are as follows:

Top-left cell: paternal grandfather’s chromosome + maternal grandfather’s chromosome
Top-right cell: paternal grandfather’s chromosome + maternal grandmother’s chromosome
Bottom-left cell: paternal grandmother’s chromosome + maternal grandfather’s chromosome
Bottom-right cell: paternal grandmother’s chromosome + maternal grandfather’s chromosome

As an example, if on chromosome 15 two siblings were characterized by the top-left cell, we might say that they were 100% “identical-by-descent” (IBD). This just means that their genes came down from the exact same ancestors. On the other hand, if one sibling was characterized by the top-left cell, and another the bottom-right, then they would be 0% IBD! In other words, in theory with this model siblings could be 0% IBD on the autosomal chromosomes if they kept inheriting different homologs from their grandparents, chromosome by chromosome (This would not be possible for chromosome 23. Males by necessity inherit the same Y from their father. While two females must share the same X from their father).

If you have a background in biology, you know this is wrong, because there’s more to the story. Recombination means that in fact you don’t invariably inherit intact copies of your grandparent’s chromosome. Rather, during meoisis, an individual’s chromosomes often “mix & match” their strands so that new mosaics are formed. So instead of inheriting homologous chromosomes which resemble exactly those carried by their grandparents, individuals often have chromosomes which are a mosaic of maternal and paternal due to the two meoisis events which intervened (one during the formation of the gametes which led to one’s parents, and another during the formation of the gametes of their parents’). If you are still confused, the following 3 minute instructional video may help. The narration has information, so if you can’t listen, the blue = paternal chromosomal segments, and the red = maternal chromosomal segments. Focus especially on recombination, about half way through the video.

This process works in contradiction to conditional dependence of inheritance of variants due to physical linkage on the same chromosomal regions. In other words, though still theoretically possible with no recombination for siblings to be very different, realistically recombination breaks apart many of the associations and reduces the realized variance. In the figure above the the low bound outliers in terms of genetic distance across sibling pairs are about mid-way between the coefficient of relatedness of half-siblings (0.25) and full-siblings (0.50), and fulling-sibling ~0.35 or so (the high bounds are 0.65).

Any any given locus the variance of IBD for siblings is 1/8. Since expectation is ~0.50, you can infer from this that on a specific gene there’s a lot of deviation across a cohort of siblings. This makes sense when you consider that siblings differ a great deal on single gene Mendelian traits. But what about the whole genome? Because now you have many more “draws” the “law of large nummbers” tends to reduce the variance. The figure to the right shows the standard deviation of IBD by chromosome. Remember that expectation is ~0.50. Observe that longer chromosomes have lower deviations. This is due to the variation of rates of recombination across the genome. We’ve come a long way from an abstract Mendelian model, to the point where one can integrate in an understanding of differences of rates of recombination across regions of the genome into the model. The total genome standard deviation of IBD turns out to be 0.036, which is close to older theoretical models which predicted ~0.04. This means that if you randomly drew two full-siblings and compared the extent of total genome IBD, the highest likelihood would be that they differed from 0.50 by 0.036. Assuming a normal distribution that means that 70% of siblings would fall within the interval 0.536 and 0.464 coefficient of relatedness. About 95% would fall with two standard deviations, 0.428 and 572. About 99.8% would fall within three standard deviations, 39.2 to 61.8.

The paper from which I’m drawing the figures and statistics is Assumption-Free Estimation of Heritability from Genome-Wide Identity-by-Descent Sharing between Full Siblings. The citations, as well as follow-up papers are very interesting. It shows how modern genomics is literally swallowing whole the insights of classical quantitative genetics. Nature is one, and abstractions ultimately map onto the concrete. I’d long thought I should review this paper and its insights, as comparisons across siblings are likely going to be a future avenue of understanding the genetic basis of many traits. But I have a more personal reason for looking into this issue.

This week many of my family members came “online” to the 23andMe system. To review:

RF = Father
RM = Mother
RS1 = Sibling 1 (female)
RS2 = Sibling 2 (male)

Later to come will be RS3, another male. But his data has not loaded….

23andMe has many features related to disease risk and ancestry information. The former was not of great interest to me, as my family is large enough that I had a good sense of what we were at risk for. 23andMe told me that I was at more risk for various ailments which are common across my extended pedigree. It also told me I was at more risk for ailments which are not known in my family. And, it told me I was at less risk for ailments common across my extended pedigree. Finally, it told me I was at less risk for ailments not common across my pedigree. You get the picture. For most people there isn’t much value-add here. I haven’t even touched the issue of “odds ratios”.

In regards to ancestry, I have received some value. I suspect I’m near the end of the line in this area, unless I get into some serious DYI genetics. My involvement in the Harappa Ancestry Project is more about understanding regional patterns of variation, than that of my own family.

So we’re at the next stage: looking at patterns in my own family. The screenshot you see above is from the ‘family inheritance’, and shows the IBD between RS2 and RF chromosome by chromosome. My male sibling and my father. As you can see they are “half-identical” across the whole genome, as they should be. Of each gene my father contributes one copy on the autosome. There’s no variance here. The total 2.86 GB value is also what you’d expect, there are ~3 billion base pairs, and you’re excluding the X and Y, as well as “no calls.” I can tell you that I exhibit the exact same relationship to my father as my brother. In contrast, my sister has more segments shared. That’s because she has an X chromosome from my father. The relationship to our mother is also as expected. We’re all equally related to our parents, once you account for sex differences on chromosome 23.

Below are the screenshots from family inheritance comparing the three siblings in terms of our genomes. Remember that half-identical (light blue) has half the weight as full-identical (dark blue).

[nggallery id=30]

Here’s the top-line. I share about the same length of segments that are half-identical to both RS1 and RS2, 2.26 and 2.27 GB. But, while I have 0.60 full-identical with RS1, I have 0.86 full-identical with RS2. And here’s the even more surprising part: RS1 and RS2 have much less in common than I do with either of them. 2.09 GB half-identical, and 0.5 full-identical.

But that’s not all. 23andMe has a “relative finder” feature. It’s main goal is to find relatives you don’t know about. I don’t have any non-close relative so far, in contrast to most others from what I have heard. It may be that most of the Bangladeshis in the database are from my own immediate family! (though there are some Indian Bengalis, I’ve found only one other Bangladeshi in the database to “share” genes with) You can though include your own family in the mix. You get two different values, % of DNA shared, and # of shared segments. The former basically seems to be a proxy for IBD. I have a person of European American ancestry on my account, and they have many “relatives” matched with whom they share 0.1-1% of their genome. One individual who asked for a contact did turn out to be a very distant cousin (his surname was the same as that of a grandparent). In any case, the matrix above shows the results so far for my family. My parents are not related; they share no segments or DNA IBD. In contrast, we are all about ~50% IBD with our parents (remember that father contributes no X chromosome to sons). But look at the sibling comparisons. In particular, RS1 & RS2 share only42% of their DNA! This aligns with the earlier results. RS1 and I are a bit closer than expectation. RS2 and I are a bit more distinct. Interestingly, while RS2 and I have 49 segments in common, RS1 and RS2 have 55 in common. Why the discrepancy? Presumably RS1 and RS2 load up on the number of segments on smaller chromosomes. This seems clear in the images above.

Where does this leave us? We know intuitively that siblings differ, and cluster, in their traits. These data and methods illustrate how in the near future how parents be able to determine which siblings cluster on the total genome content level! As I have stated before, RS2 and I in particular resemble each other physically, far more than either of us resemble RS1. Could this relate to what we’ve found genomically? I believe so. Physical appearance is controlled by many different variants across many different genes, so the phenotype may be a good reflection of the character of the total genome. This can be generalized to other quantitative traits.

Finally, this has clear implications for our study of genetic inheritance within families. Classical genetic techniques had to assume that the coefficient of relatedness between siblings was 0.50. The deviation from this expectation would have introduced errors into estimates of heritability and possibly masked the understanding of the genetic architecture of a trait. But now we can correct for deviations from the 0.50 value, and so better understand the genetic basis of complex traits such as behavior.

Citation: Visscher, P., Medland, S., Ferreira, M., Morley, K., Zhu, G., Cornes, B., Montgomery, G., & Martin, N. (2006). Assumption-Free Estimation of Heritability from Genome-Wide Identity-by-Descent Sharing between Full Siblings PLoS Genetics, 2 (3) DOI: 10.1371/journal.pgen.0020041

(Republished from Discover/GNXP by permission of author or representative)
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Image credit: Aleksandra Pospiech

One of the interesting and robust nuggets from behavior genetics is that heritability of psychological traits increases as one ages. Imagine for example you have a cohort of individuals you follow over their lives. At the age of 1 the heritability of I.Q. may be ~20%. This means that ~20% of the variation in the population of I.Q. explained by variation in the genes of the population. More concretely, you would only expect a weak parent-offspring correlation in I.Q. in this sample. At the age of 10 the heritability of I.Q. in the same sample may be ~40%, and in mature adulthood it may rise to ~80% (those are real numbers which I’ve borrowed from Robert Plomin). Many people find this result rather counterintuitive. How can a trait like intelligence become “more genetic”?

Remember that I’m talking about heritability here, not an ineffable “more” or “less” quantum of “genetic” aspect of a trait. In other words: does variation in genes due to different parental backgrounds matter for a trait? Second, the nature of psychological traits is somewhat slippery and plastic. As I’ve noted before the correlation between a score on a 10-world vocabulary test and general intelligence is pretty good. You can expect people with high scores on the vocabulary test to have higher I.Q.’s than those who have low scores. But if you take an individual and lock them in a room without human contact for their first 15 years, they are unlikely to exhibit any such correspondence. You don’t have to be a rocket scientist to understand why. Quantitative behavior genetic traits are complex and are subject to a host of background conditions, and express themselves in an environmental context.

So why can you explain more of the variance of a psychological trait like I.Q. at age 40 than at age 5 with genes? It has to do with environment. Specifically, intelligence isn’t something you’re born with, it’s something that you develop over time, through a complex confluence between biology and environment. The developmental process exhibits a level of contingency as well. Decision A redounds to the choice between B and C, which redounds between a further set of choices. Small initial differences in disposition and talent can compound over time through positive feedback loops. Practice may make perfect, but perfection may be a goal to which you aspire only if you have initial talent or inclination.

In other words, your genetic disposition can shape the environment you select, which can then serve to express your genetic potential in a specific manner. Children have less power in selection of their environment than adults. Over time the model is that environmental variables which differentiate children diminish in importance as they select contexts and situations which express their own preference sets as adults. This dynamic can be illustrated with a rather strange example. Consider two siblings who are pressured to be academic by their parents. One has a natural disposition toward scholarly activities, while the other does not. Their realized performance difference in youth may be small. People can respond to incentives! But at 18 the two siblings become adults, and begin to make their own decisions. At 25 one sibling may be a university drop out, and the other a graduate student. The modest differences in adolescence may start amplifying due to the positive feedback loops which consist of a set of choices which exhibit dependencies. Of course siblings would tend to be more similar than two random individuals off the street. But even within families there is genetic variance and so innate differences of disposition (the average difference in I.Q. between siblings is about the same as the average difference in I.Q. between two random people off the street, one standard deviation, or 15 points). Modeling behavior genetic phenomena in a rough & ready fashion is then a matter of keeping dynamic networks of parameters in your head. Traits aren’t constructed about of static blocks; they’re the outcomes of a set of parameters at a given moment, as well as a developmental arc shaped by a previous set of parameters (some of them the same, some of them new). Thinking like this gives you a method by which to analyze phenomena, it does not tell you in a clear and general manner how a whole range of phenomena emerged down to the last detail.

The analysis doesn’t just apply to populations over time. You can also look to different groups which are contemporary. In 2003 a paper was published, Socioeconomic Status Modifies Heritability of IQ in Young Children. The major findings are illustrated by this figure (I’ve added some clarifying labels):

On the x-axis you see socioeconomic status (SES). This variable is a compound of traits which reflect’s one’s position in the social status hierarchy. Income and wealth are clearly important, but a salesman for a fertilizer company could presumably be more economically well off than a physics professor. So other variables such as education also matter. It is clear then that as SES increases genetic variation explains much more of the variation in I.Q., while environment explains less and less. The shared environment is rather straightforward: your family. The non-shared environment is more vague, and to some extent is just the remainder from the model which predicts I.Q. In The Nurture Assumption Judith Rich Harris posited that non-shared environment was mostly peer group effects. Interestingly, by adulthood non-shared environment tends to be a more important variable than shared environment for most psychological traits.

Any guess for why genetic variance is more efficacious in prediction of I.Q. among the high status than the low status? Here’s a clue: heritability of height is much higher in developed nations than in developing nations. In other words, environment explains more of the variance in height in developing nations, while it explains almost none of the height in developed nations. There’s only so much you can eat, and there are diminishing returns on nutritional inputs. In developed nations most of the environmental variance has been removed due to adequate nutrition. When you remove the environmental variance, the genetic variance remains. Heritability is roughly the ratio of the additive genetic variance over the total variance, so its value gets larger.

The analogy to I.Q. should be relatively easy. Don’t tell Amy Chua, but there are probably diminishing marginal returns on “nurturing” environments for a child when it comes to their intellectual development. You have only a maximum of 24 hours in the day you can study and drill, and a personal library of 10,000 is probably not very different from 1,000, if all the books fall within the purview of your interest. Even in well off suburban communities there are differences of wealth and income, but on the margin vast increases in wealth and income do not allow one’s child to develop their mental faculties proportionality greater. What there remains in well off suburban communities are differences of genetic disposition and aptitude. Bill Gates’ children are probably good candidates for the Ivy League. Not because he is worth billions of dollars in relation to a professional whose net assets barely break a million. Gates got into Harvard, and reputedly did well before dropping out to pursue his business. His wife is also an overachiever.

This is I believe a fascinating topic, and needs to be explored in more detail. Some members of the same group now have a study out which shows that differences in socioeconomic status matter differently for infants at 10 months and tots are 2 years. Emergence of a Gene × Socioeconomic Status Interaction on Infant Mental Ability Between 10 Months and 2 Years:

Recent research in behavioral genetics has found evidence for a Gene × Environment interaction on cognitive ability: Individual differences in cognitive ability among children raised in socioeconomically advantaged homes are primarily due to genes, whereas environmental factors are more influential for children from disadvantaged homes. We investigated the developmental origins of this interaction in a sample of 750 pairs of twins measured on the Bayley Short Form test of infant mental ability, once at age 10 months and again at age 2 years. A Gene × Environment interaction was evident on the longitudinal change in mental ability over the study period. At age 10 months, genes accounted for negligible variation in mental ability across all levels of socioeconomic status (SES). However, genetic influences emerged over the course of development, with larger genetic influences emerging for infants raised in higher-SES homes. At age 2 years, genes accounted for nearly 50% of the variation in mental ability of children raised in high-SES homes, but genes continued to account for negligible variation in mental ability of children raised in low-SES homes.

They used a standard SEM model. I’m not going to go over that in detail, but suffice it to say that they related a set of variables to the outputs which they wanted to predict, performance on I.Q. tests for very young children. If you are curious, the demographic sample was rather diverse, and controlling for race did not impact their outcomes. So let’s outline what’s going on here.

First, predicted:

- Performance at 10 months
- Performance at 2 years

Second, putative predictors:

- Genes (A). Specifically, additive genetic variance
- Shared environment (C)
- Non-shared environment (E)

I’ve reedited some of the main results. On the Y axis you see the % of variance explainable by A, C, and E. The variance components are broken down into two levels: SES, and age. 2 SD means 2 standard deviations. In a normal distribution that’s the ~2% tail at the ends.

What you see are two trends with age and SES:

- For infants at the age of 10 months parents matter. Genes do not. SES is not a major issue.

- For tots at the age of 2 years, SES matters quite a bit. You see a recapitulation with the earlier data, where higher SES parents seem to be providing environments which probably exhibit diminishing marginal returns (environmental variance doesn’t have much of an effect on the margin), so that genetic variance is much more important by default. The trend is clear as you move in a step-wise fashio up the class ladder. Though I have to say, the top ~2% in SES is an elite group already, so I wonder what sort of environmental variance could be found there.

The figure to the left shows the same outcome out of their model, only now the curves illustartes the variation of the effects as you modify SES in a continuous fashion. These are estimates generated out of their model, so that probably explains the > 100% values you see on the margins. The key is to focus on the broad qualitative trends. Even at 2 years of age genes start to trump shared environment ~1 standard deviation above the norm (though not aggregate “environment”). If the earlier data is correct, the heritability will continue to increase over time for higher SES individuals, as their affluent backgrounds will give them perfect freedom to take them where their dispositions lead them.

Why does all this matter? There are practical outcomes to this sort of research. I’ll quite from the paper:

These findings build on a growing body of literature that highlights the importance of early life experiences for cognitive development…Current evidence suggests that, although children maintain a great deal of neurobiological and behavioral plasticity well past infancy…the predictive validity of infant mental ability for later cognitive ability is moderate…We agree with Bornstein and Sigman…who have strongly argued against the perspective “that infancy might play little or no role in determining the eventual cognitive performance of the child and, therefore, that individuals could sustain neglect in infancy if remediation were later made available”…Heckman…has recently taken an economic perspective on this topic. He argued that prophylactic interventions for disadvantaged younger children produce much higher rates of return on what he termed “human skill formation” than later remedial interventions for older children and adults do. On the basis of this perspective, Heckman concluded that “at current levels of funding, we overinvest in most schooling and post-schooling programs and underinvest in preschool programs for disadvantaged persons”….

My understanding is that the long-term effectiveness of even Head Start is non-existent, so I don’t know what proposals could be made based on this. Preschool for 1-2 years? I find it broadly plausible that high SES parents do provide more enriching environments, but I don’t see the detailed understanding necessary for genuinely effective prescriptions. Rather, we’re doing conventional trial & error when it comes to policy.

Additionally, the authors also admit that the high and low SES populations may have been stratified for genes. That’s just a way of saying that it isn’t as if genetic variance for things like intelligence are necessarily equally distributed across the social classes. If a genuine meritocracy exists what one should rapidly see is a crystallization of hereditary class castes, as individuals marry and associate assortatively on a meritocratic basis. Remember, assortative mating should increase heritability estimates (Quantitative Genetics says so!). This is part of the irony of some peoples’ conception of how genes relate to outcomes. Equality of opportunity will almost certainly lead to a cleaner separation of outcomes by genetic variation. In a chaotic world defined by random acts many people will find themselves in positions at variance with their aptitudes or dispositions. Once you remove the environmental randomness, then from each according to their capabilities should be the outcome.

For future investigation: the hypothesis that Goldman Sachs partners are precursors to Guild Navigators!

Citation: Tucker-Drob EM, Rhemtulla M, Harden KP, Turkheimer E, & Fask D (2010). Emergence of a Gene x Socioeconomic Status Interaction on Infant Mental Ability Between 10 Months and 2 Years. Psychological science : a journal of the American Psychological Society / APS PMID: 21169524

(Republished from Discover/GNXP by permission of author or representative)
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Since the beginning of this weblog (I’ve been writing for eight years) heritability has been a major confusion. Even long time readers misunderstand what I’m trying to get at when I talk about heritability. That’s why posts such as Mr. Luke Jostins‘ are so helpful. I had seen references to a piece online, The Causes of Common Diseases are Not Genetic Concludes a New Analysis, but I hadn’t given it much thought. Until Ms. Mary Carmichael’s post DNA, Denial, and the Rise of “Environmental Determinism”. She begins:

Michael Pollan, the well-known writer on food and agriculture, is a smart guy. His arguments tend to be nuanced and grounded in common sense. I like his basic maxim on nutrition – “Eat food. Not too much. Mostly plants” – so much that I recently promoted it in a Newsweek cover story. He’s the last person I’d suspect of reactionary thinking, which is why I wish I didn’t have to say this: Michael Pollan has made a deeply unfortunate mistake.

A few days ago, speaking to his 43,000 followers on Twitter, Pollan linked to an essay written by an environmental advocacy group that spends much of its time fighting the depradations of Big Agriculture. Curiously, the essay wasn’t about ecological destruction or even about agriculture. It was about human genetics. It argued that since genetics currently can’t explain everything about inheritance, genes must not influence the development of disease, and thus the causes of illness must be overwhelmingly environmental (meaning “uninherited” as opposed to “caused by pollution,” though the latter category of factors is part of the former one). This was a little like arguing that your engine doesn’t power your car because sometimes it breaks down in a way that confuses your mechanic — and concluding that gasoline alone is sufficient to make a car with no engine run. But Pollan took the argument at face value. He said it showed “how the gene-disease paradigm appears to be collapsing.” He was troubled that its contentions apparently had gone unnoticed: “Why aren’t we hearing about this?!”

Of course I had seen Dr. Daniel MacArthur’s post Bioscience Resource Project critique of modern genomics: a missed opportunity in my RSS, but when I started reading the rebuttal I immediately thought “Dr. Dan’s interlocutors sound kind of dumb,” and I stopped reading. After reading the post I don’t think they’re dumb, I think they’re being lawyerly. Much of the piece is a rhetorical tour de force in leveraging the prejudices and biases of the intended readership . This is the Intelligent Design version of Left-wing “Blank Slate” Creationism.* They smoothly manipulate real findings in a deceptive shell game intended to convince the public, and shape public policy. Their success is evident in Pollan’s response. “X paradigm appears to be collapsing.” “Why aren’t we hearing about this?” Does this sound familiar? Like Dr. MacArthur I think some of the criticisms within the piece are valid. Despite not being hostile to the maxim “better living through chemistry,” I do think that there has been an excessive trend toward pharmaceutical or surgical “cures” in relation to diseases of lifestyle (anti-depressants, gastric bypass, etc.). But we go down a very dangerous path when we make recourse to shoddy means toward ostensibly admirable ends. This sort of discourse is not sustainable! (just used a buzzword intended to appeal right there!)

I honestly can’t be bothered to say much more when so many others already have. This is a boat I missed. But if some of what I say above isn’t clear, I recommend you read the original essay. Then read Dr. MacArthur and Ms. Carmichael. If you’re hungry for more, Ms. Carmichael has a helpful list of links.

* Left Creationism had its most negative manifestation as Lysenkoism, but it suffuses the outlook of many who fear the emergence of a new Nazi abomination. Leon Kamin in the 1970s even claimed that IQ was not heritable at all! Though he backed off such an extreme position, it shows how confident he was that could claim such a thing.

(Republished from Discover/GNXP by permission of author or representative)
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I recall projections in the early 2000s that 25% of the American population would be employed as systems administrators circa 2020 if rates of employment growth at that time were extrapolated. Obviously the projections weren’t taken too seriously, and the pieces were generally making fun of the idea that IT would reduce labor inputs and increase productivity. I thought back to those earlier articles when I saw a new letter in Nature in my RSS feed this morning, Hundreds of variants clustered in genomic loci and biological pathways affect human height:

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2, 3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. 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). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

The supplements run to nearly 100 pages, and the author list is enormous. But at least the supplements are free to all, so you should check them out. There are a few sections of the paper proper that are worth passing on though if you can’t get beyond the paywall.

fig1bIn this study they pooled together several studies into a meta-analysis. One thing not mentioned in the abstract: they checked their GWAS SNPs against a family based study. This was important because in the latter population stratification isn’t an issue. Family members naturally overlap a great deal in their genetic background. Also, if I read it correctly they’re focusing on populations of European origin, so this might not capture larger effect alleles which impact between population variance in height but don’t vary within a given population (note that if you explored pigmentation genetics just through Europeans you would miss the most important variable on the world wide scale, SLC24A5, because it’s fixed in Europeans). In any case, as you can see what they did was extrapolate out the number of loci which their methods could capture to explain variation with the predictor being the sample size. At 500,000 individuals they’re at ~700 loci, and around 20% of the heritable variation. My initial thought is that I’m not seeing diminishing returns here, but since I haven’t read the supplements I’ll let that pass since I don’t know the guts of this anyhow. They do assert that they are likely underestimating the power of these methods because there may be be smaller effect common variants which can top off the fraction.

But even they admit that they can go only so far. Here are some sections from the conclusion that lays it out pretty clearly:

By increasing our sample size to more than 100,000 individuals, we identified common variants that account for approximately 10% of phenotypic variation. Although larger than predicted by some models26, this figure suggests that GWA studies, as currently implemented, will not explain most of the estimated 80% contribution of genetic factors to variation in height. This conclusion supports the idea that biological insights, rather than predictive power, will be the main outcome of this initial wave of GWA studies, and that new approaches, which could include sequencing studies or GWA studies targeting variants of lower frequency, will be needed to account for more of the ‘missing’ heritability. Our finding that many loci exhibit allelic heterogeneity suggests that many as yet unidentified causal variants, including common variants, will map to the loci already identified in GWA studies, and that the fraction of causal loci that have been identified could be substantially greater than the fraction of causal variants that have been identified.

In our study, many associated variants are tightly correlated with common nsSNPs, which would not be expected if these associated common variants were proxies for collections of rare causal variants, as has been proposed27. Although a substantial contribution to heritability by less common and/or quite rare variants may be more plausible, our data are not inconsistent with the recent suggestion28 that many common variants of very small effect mostly explain the regulation of height.

In summary, our findings indicate that additional approaches, including those aimed at less common variants, will likely be needed to dissect more completely the genetic component of complex human traits. Our results also strongly demonstrate that GWA studies can identify many loci that together implicate biologically relevant pathways and mechanisms. We envisage that thorough exploration of the genes at associated loci through additional genetic, functional and computational studies will lead to novel insights into human height and other polygenic traits and diseases.

The second to last paragraph takes a shot at David Goldstein’s idea of synthetic associations.

We’re still where we were a a few years back though, old fashioned Galtonian quantitative genetics, a branch of statistics, is the best bet to predict the heights of your offspring. As with intelligence, “height genes”, are not improvements upon common sense. But if you’re going into the 10-20% range of variation explained it’s certainly not trivial, and the biological details are going to be of interest.

(Republished from Discover/GNXP by permission of author or representative)
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Since we’re talking about athletics & heritability, California School Has a Montana and a Gretzky at Quarterback. Unfortunately regression toward the mean implies you’d have to bet against the sons of some of the greatest players in professional sports having anything close to the same impact. On the other hand, having a professional athlete parent is going to increase your odds of being a successful athlete in the pros by orders of magnitude I suspect. The expectation is that children of professional athletes, who are many standard deviations above the norm, will regress back toward the mean as a function of heritability. But the expectation of their athleticism is going to be far higher than the norm, and because there is going be variance around that expectation it also increases the probability that those children will match their parent, or even outperform them. The Manning brothers and Barry Bonds are cases where the offspring are more exceptional than their parent.

(Republished from by permission of author or representative)
• Category: Science • Tags: Heritability 
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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"