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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