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Missing Heritability

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Heritability:

The heritability of a trait within a population is the proportion of observable differences in a trait between individuals within a population that is due to genetic differences. Factors including genetics, environment and random chance can all contribute to the variation between individuals in their observable characteristics (in their “phenotypes”)…Heritability thus analyzes the relative contributions of differences in genetic and non-genetic factors to the total phenotypic variance in a population. For instance, some humans in a population are taller than others; heritability attempts to identify how much genetics are playing a role in part of the population being extra tall.

Over at Haldane’s Sieve Dr. Joseph Pickrell has a commentary up on a preprint on explaining the ‘missing heritability’ using yeast genetics. All good reading. I long ago gave up on the idea that the idea of ‘heritability’ would ever be widely internalized among the educated public in any precise sense. But we muddle on. The next decade is going to be big for the genomics of complex traits. Or so people keep telling me!

But this gives me the excuse to point to a commentary which you really should read again and again. It is A commentary on ‘common SNPs explain a large proportion of the heritability for human height’ by Yang et al. (2010).:

Recently a paper authored by ourselves and a number of co-authors about the proportion of phenotypic variation in height that is explained by common SNPs was published in Nature Genetics (Yang et al., 2010). Common SNPs explain a large proportion of the heritability for human height (Yang et al.). During the refereeing process (the paper was rejected by two other journals before publication in Nature Genetics) and following the publication of Yang et al. (2010) it became clear to us that the methodology we applied, the interpretation of the results and the consequences of the findings on the genetic architecture of human height and that for other traits such as complex disease are not well understood or appreciated. Here we explain some of these issues in a style that is different from the primary publication, that is, in the form of a number of comments and questions and answers. We also report a number of additional results that show that the estimates of additive genetic variation are not driven by population structure.

Here again is an ungated PDF link. And this is the original paper which triggered this response, Common SNPs explain a large proportion of the heritability for human height.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Genetics, Genomics, Missing Heritability 
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Please see Luke Jostins’ posts at Genetic Inference and Genomes Unzipped.

Update: Steve Hsu weighs in. He read the supplements! Mad props.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Genetics, Genomics, Missing Heritability 
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The Pith: A great deal of important medical genetic differences between people may be due to the nature of interactions of genetic variants.

If you’ve been reading this blog for a while you know that there is a question in genomics right now as to “missing heritability.” The issue is basically that there are traits where patterns of inheritance within the population strongly imply that most of the variation is due to genes, but attempts to ascertain which specific genetic variants are responsible for this variation have failed to yield much. For example, with height you have a trait which is ~80-90 percent heritable in Western populations, which means that the substantial majority of the population wide variation is attributable to genes. But geneticists feel very lucky if they detect a variant which can account for 1 percent of the variance.

One simple explanation, which gains some genomic support, is that variation on these traits is due to innumerable variants widely distributed across the genome. Therefore, a variant of one percent effect may be a rather large one. There are also those who argue that it may be that there are even more very rare, but somewhat larger effect, alleles at work.


Another model is that the “missing heritability” can be solved by reconceptualizing the “genetic architecture” of the trait. This means that currently a major assumption of many models for putatively polygenic traits is that the variation is due to many genes of small effect which modify the trait value in an additive and independent manner. In other words, the genetic architecture in this sense is a linear system. A clear alternative, or complementary, possibility is that there are genetic interactions which are generating deviations from linearity. This would be epistasis, which has different implications depending on the sort of biology you’re talking about (e.g., molecular vs. evolutionary).

A new paper in PNAS makes the case that a lot of the “missing heritability” has to do with the assumption of additivity in many of the models attempting to smoke out associations. But first, let me point to a press release from from GeneWatch:

The study supports earlier findings by GeneWatch UK that much of the heritability of common diseases, calculated using twin studies, may not exist (2). Scientists have been puzzled by the failure of large genetic studies to find genes which explain the “missing heritability” of common diseases such as heart disease and cancer and traits such as height. Typically, 85 to 95 per cent of the expected heritability has not been found. Today’s new study confirms that one explanation may be that interactions between multiple genes would reduce the predicted heritability. These interactions were not properly accounted for by the eugenicist Ronald Fisher who developed the original twin studies method in 1918, and later analysis has not corrected Fisher’s error.

“Claims of a genetic revolution in healthcare have long been based on false assumptions” said Dr Helen Wallace, Director of GeneWatch UK, “If heritability is much lower than expected this means that genetic differences play only a small role in explaining why some individuals get a disease which others do not. Genetic testing can help people with rare disorders but will never be useful to predict and prevent the common diseases that most people get.”

My attention was brought to this by Hellen Wallace herself, who sent a rather bombastic email stating that Eric Lander has come around to her model, where gene-gene interactions loom large. But from reading the paper I think one of the issue that the authors highlight is that there is often a conflation between heritability in the narrow sense, h2, and heritability in the broad sense, H2. h2 accounts for additive genetic variation. The authors seem to be making the case that you may have to focus on heritability in the broad sense. They state: “Broad-sense heritability H2 measures the full contribution of genes… H2 is the relevant quantity for clinical risk assessment, because it measures our ultimate ability to predict phenotype from genotype.”

I have characterized GeneWatch as “Genetic Creationists” before, and that is because of their misrepresentations and exaggerations. A close reading of this paper does not seem to align at all with their agenda, though it does imply that attempts to map genotype to phenotype are going to be hard. Let me jump to the paper’s conclusion:

Finally, notwithstanding our focus here, we believe that concerns about missing heritability should not distract from the fundamental goals of medical genetics. Human genetic studies to discover variants associated with common traits should primarily be regarded as the analog to mutant hunts in model organisms, with the primary purpose being to identify the underlying pathways and processes. The key focus should be to study the biological role of the variants discovered so far. The proportion of phenotypic variance explained by a variant in the human population is a notoriously poor predictor of the importance of the gene for biology or medicine. [A classic example is the gene encodingHMGCoA reductase, which explains only a tiny fraction of the variance in cholesterol levels but is a powerful target for cholesterol-lowering drugs (1).] Ultimately, the most important goal for biomedical research is not explaining heritability—that is, predicting personalized patient risk—but understanding pathways underlying disease and using that knowledge to develop strategies for therapy and prevention.

You can read the full paper at PNAS, it’s open access. But really you have to go through the supplements, and I’ve only read a few sections of that. Do I believe this? I think the model works out. Frankly, I wanted to check the acknowledgments, and the people listed there give me confidence that the theory here is legitimate, even if you don’t work out the equations yourself. But is this empirically the case? That’s a different issue altogether. The authors note that there will be follow up papers soon. What I will be curious about is the extent of differences in interaction effects by trait. A supplementary table gives us a taste. You see correlations for monozygotic and dizygotic twins. In an additive model the third row should be ~ 0. Look at birth weight and voting behavior, and contrast it with height and IQ.


Citaion: The mystery of missing heritability: Genetic interactions create phantom heritability, doi:10.1073/pnas.1119675109

(Republished from Discover/GNXP by permission of author or representative)
 
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Aka Pygmies

The Pith: There has been a long running argument whether Pygmies in Africa are short due to “nurture” or “nature.” It turns out that non-Pygmies with more Pygmy ancestry are shorter and Pygmies with more non-Pygmy ancestry are taller. That points to nature.

In terms of how one conceptualizes the relationship of variation in genes to variation in a trait one can frame it as a spectrum with two extremes. One the one hand you have monogenic traits where the variation is controlled by differences on just one locus. Many recessively expressed diseases fit this patter (e.g., cystic fibrosis). Because you have one gene with only a few variants of note it is easy to capture in one’s mind’s eye the pattern of Mendelian inheritance for these traits in a gestalt fashion. Monogenic traits are highly amenable to a priori logic because their atomic units are so simple and tractable. At the other extreme you have quantitative polygenic traits, where the variation of the trait is controlled by variation on many, many, genes. This may seem a simple formulation, but to try and understand how thousands of genes may act in concert to modulate variation on a trait is often a more difficult task to grokk (yes, you can appeal to the central limit theorem, but that means little to most intuitively). This is probably why heritability is such a knotty issue in terms of public understanding of science, as it concerns the component of variation in quantitative continuous traits which is dispersed across the genome. The traits where there is no “gene for X.” Additionally, quantitative traits are likely to have a substantial environmental component of variation, confounding a simple genotype to phenotype mapping.

ResearchBlogging.org Arguably the classic quantitative trait is height. It is clear and distinct (there aren’t arguments about the validity of measurement as occurs in psychometrics), and, it is substantially heritable. In Western societies with a surfeit of nutrition height is ~80-90% heritable. What this means is that ~80-90% of the variance of the trait value within the population is due to variance of the genes within the population. Concretely, there will be a very strong correspondence between the heights of offspring and the average height of the two parents (controlled for sex, so you’re thinking standard deviation units, not absolute units). And yet height is at the heart of the question of the “missing heriability” in genetics. By this, I mean the fact that so few genes have been associated with variation in height, despite the reality that who your parents are is the predominant determination of height in developed societies.


The issue gets even more thorny when you talk about variation across societies. This is a simple and yet complex issue. On the one hand we know that over time people across the world have gotten taller as nutrition has gotten better. What is less well known is that human populations have been shrinking until the past few centuries since the the Last Glacial Maximum ~20,000 years ago. Why? One can posit many reasons, both genetic and environmental, but it does point us to the reality that the story of height is not monotonic. That is, it doesn’t go in one direction, and has no simple one size fits all answer.

But that’s just the dimension of time. How about space? The question of whether different populations have final different genetic potentials for height is a disputed one. And yet it seems plausible that at the extremes there are genuine differences in the gene frequencies across populations which will speak to their different distributions in trait values. This is particularly interesting in the case of very populations characterized by low median adult heights, often termed “pygmies.” Of particular note are the Pygmies of Central Africa, who exist in a state of cultural symbiosis with their Bantu and Nilotic neighbors, adopting their languages, but remaining distinct.

These populations have very low median heights, but they are clearly not dwarfs (they are proportionate). Thankfully at least the population genetics of the Pygmies of Africa are now relatively well understood. It seems that the Western and Eastern Pygmy populations are very distinct clusters, with a common ancestry perhaps on the order of tens of thousands of years in the past. And not surprisingly the genetic distance between the Pygmy groups and their non-Pygmy neighbors is very large. The Western Pygmies tend to show more evidence of admixture with their Bantu neighbors than the Eastern ones (I suspect this is due to the longer residence of Bantus in this region). But for me the hardest issue to grapple with is the reality that the Pygmies of Central Africa seem to be genetically closer to the Khoisan people of Southern Africa than their Bantu or Nilotic neighbors! I believe this is evidence of an ancient hunter-gatherer continuum within Africa which has been marginalized and overlain by the recent expansion of Bantu farmers and Nilotic pastoralists.

In any case, what does all this have to do with the genetics of height? A new paper in the American Journal of Physical Anthropology synthesizes the inferences generated from population genetics with the basic logical assumptions of quantitative genetics to adduce that the difference between Pygmies and non-Pygmies in height is actually likely to be due to heritable differences. Indirect evidence for the genetic determination of short stature in African Pygmies:

Central African Pygmy populations are known to be the shortest human populations worldwide. Many evolutionary hypotheses have been proposed to explain this short stature: adaptation to food limitations, climate, forest density, or high mortality rates. However, such hypotheses are difficult to test given the lack of long-term surveys and demographic data. Whether the short stature observed nowadays in African Pygmy populations as compared to their Non-Pygmy neighbors is determined by genetic factors remains widely unknown. Here, we study a uniquely large new anthropometrical dataset comprising more than 1,000 individuals from 10 Central African Pygmy and neighboring Non-Pygmy populations, categorized as such based on cultural criteria rather than height. We show that climate, or forest density may not play a major role in the difference in adult stature between existing Pygmies and Non-Pygmies, without ruling out the hypothesis that such factors played an important evolutionary role in the past. Furthermore, we analyzed the relationship between stature and neutral genetic variation in a subset of 213 individuals and found that the Pygmy individuals’ stature was significantly positively correlated with levels of genetic similarity with the Non-Pygmy gene-pool for both men and women. Overall, we show that a Pygmy individual exhibiting a high level of genetic admixture with the neighboring Non-Pygmies is likely to be taller. These results show for the first time that the major morphological difference in stature found between Central African Pygmy and Non-Pygmy populations is likely determined by genetic factors.

First, is there a plausible physiological reason for the difference in adult height between Pygmies and non-Pygmies? The authors review the relevant evidence:

Endocrinologists have described the physiological determination of the African Pygmies’ short stature: serum levels of Insulin-Like Growth Factor 1 (IGF1) and of Growth Hormone Binding Protein (GHBP) are abnormally low, whereas the levels of Growth Hormone (GH) and IGF2 do not differ from Non-Pygmy controls…In this context, Merimee…proposed that the short stature of African Pygmies could be attributed to the absence of a growth spurt during puberty and that the genetic factor(s) implicated in the Pygmy stature were to be found in the GH-IGF1 axis…A recent gene-expression study further showed a slight (1.8-fold) under-expression of GH and a more dramatic (8-fold) under-expression of the GH receptor in adult African Pygmies, which was not found in Non-Pygmy Bantu speakers…However, the only genetic study focusing specifically on Pygmies’ stature, failed to find allele frequency differences in the promoter region of the gene encoding IGF1 between two African Pygmy populations and Non-Pygmy controls…In this context, whether the Pygmy populations’ short stature is solely due to environmental pressures experienced by individuals during growth (i.e., phenotypic plasticity), or to a complex genetic mechanism, remains to be demonstrated.

I believe that IGF can be found in meat and milk, so there are plausible dietary reasons that one could imagine this difference. As far as looking at differences between the genes which are known to impact height within populations across populations, there simply aren’t that many genes known which could account for the large between population differences. Not to mention that many of the current studies have used European populations, and so would likely have an ascertainment bias which might miss a lot of variance which is common within African populations.

The basic method in this paper is not too difficult to understand:

1) Use STRUCTURE, a program which assigns different ancestral quanta to individuals.

2) And compare the variation in a particular Pygmy-modal quantum across the population with variation in height.

If there are many genetic variants of small effect within the Pygmy genome which are resulting in their relatively low adult median height then dollops of Pygmy genome through admixture will reduce the height of non-Pygmies and dollops of non-Pygmy admixture in Pygmies will increase their height. The presumption is that if there are strong environmental impacts on height due to social differences then the disjunction between genetic identity and anthropological identity will be informative. For example, if Pygmies are put under particular stress or deprived specific nutritional intake because of their communal identity as marginalized Pygmies then different admixture levels with non-Pygmies should not matter much (and vice versa).

There’s a lot of statistics toward the aim of achieving significance in this paper (p-value > 0.05). And I really don’t understand the point of disaggregating males and females, for example. Just convert them to standard deviation units deviated from sex median! But in any case the major correlation is well illustrated by the two panels below. Pygmies are in red and non-Pygmies are in blue:

The y-axis is straightforward, height. You can see the Pygmies in their sample are shorter, on average. The x-axis is an ancestral component inferred from STRUCTURE which is generally found in non-Pygmies. You can see that as expected non-Pygmies have more of this than the Pygmies, but the descriptive statistic of a correlation between the non-Pygmy ancestry and height in Pygmies is evident even in this plot. Conversely, the Pygmy ancestry is correlated with lower adult height in non-Pygmies.

As a single result this particular finding isn’t too earth-shaking. If there was one population which was short due to genetic factors, I suspect that one would have to bet on the Pygmies of Central Africa. And as noted in the paper Pygmoid morphology is found among other hunter-gatherer tropical populations. This may not be a human ancestral type, but it is a type which has emerged repeatedly in our history, whether due to genetic or environmental factors. The big picture is that this same general procedure can be used to explore the differences in genetic dispositions across groups for many quantitative traits. With the coming era of cheap genotyping and sequencing I’m sure it will be done. A intrepid researcher has plenty of admixed populations in the New World to select from. There are in Brazil people who are socially identified and self-identify as white who have less European ancestry than those who are socially identified and self-identify as non-white. To compare the the social and genetic valences of African and European ancestral contributions for medical and psychological quantitative traits these sorts of populations will be of great future interest.

Link credit: Dienekes

Citation: Becker NS, Verdu P, Froment A, Le Bomin S, Pagezy H, Bahuchet S, & Heyer E (2011). Indirect evidence for the genetic determination of short stature in African Pygmies. American journal of physical anthropology PMID: 21541921

(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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Excellent post from Dr. Daniel MacArthur, Common copy number variation doesn’t explain much complex disease risk – but why not?:

The Wellcome Trust Case Control Consortium has just published the results of a massive survey of common, large DNA duplications and deletions (collectively termed copy number variation, or CNVs) in 16,000 patients suffering from complex diseases and 3,000 controls. The results come as no surprise, but are nonetheless disappointing: the study identified absolutely no novel CNVs associated with complex disease. Although three such variants were found to alter disease susceptibility, all three had been identified from previous studies.

The study’s findings suggests that – despite their size – common CNVs play very little role in the etiology of common, complex diseases like rheumatoid arthritis and type 2 diabetes, and researchers will have to look elsewhere to uncover the notorious “missing heritability” for these diseases.

Where to next? The field has already moved on with a new focus on rare variants, which (given the selection-based argument above) seem far more likely to yield useful findings. This year will see the launch of several very large studies taking a variety of approaches to dig into the lower end of the frequency spectrum: imputation using existing data-sets; new genome-wide association chips containing larger numbers of rare SNPs; and large-scale sequencing of candidate genes, whole exomes and even entire genomes. Rare variant discovery has already proved successful in the CNV field, and it seems likely that the next round of CNV association studies will prove enormously more fruitful than this study.

Missing heritability is a major issue. Though I guess it does science some good to have white whales to chase….

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Biology, Genetics, Genomics, Missing 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 http://www.razib.com"