Common versus rare variants, again

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A commentary published this week in the prestigious journal Cell is the latest salvo in the rare variants versus common variants “debate” (see my overall thoughts on this topic here). The commentary contains a number of false claims (ie. many SNP-disease associations found to date are false positives due to population structure) and non sequiturs (ie. the inability to find a known function for polymorphisms associated with disease means those polymorphisms have no effect on disease), which I’ll skip over in the interest of getting to the main point.

The conclusion of the authors, of course, is that the community should be doing full-genome resequencing of cases and controls to identify rare variants that cause disease. The more I see the argument presented as a bold “paradigm shift” (yes, believe it or not, the authors use this term), the more it makes me smile. It’s sort of like, back when the telescope was invented, someone writing a passionate essay saying, “Hey! You know where we should point this thing? The sky, you bloody idiots!”. The same people who have been very successful with genome-wide association studies using common SNPs have already begun to publish targeted resequencing studies (for example), and there’s no one in the field who hasn’t salivated over the prospect of dirt-cheap resequencing.

In any case, the authors of this essay have blinders on regarding the potential problems with this approach. As they say, the problem is in the biology. If the truth is that many common variants of extremely weak effect account for the majority of the variance in disease risk for many diseases, such is life, and resequencing studies simply won’t get around it. The authors cite a paper that argues this is exactly the case for schizophrenia, but of course don’t mention this conclusion, and seem oblivious to the problem it presents to their discussion. A prediction: after the first rounds of resequencing studies don’t account for all the so-called “missing heritability” of common diseases, the herd will come stampeding back to common variants (just as nonsensically as they seem to be stampeding away now).

6 Comments

  1. The paper by McClellan and King in Cell actually provides extremely strong arguments that rare variants explain the bulk of the genetic variance for many so-called “complex” traits and, conversely, that an important role for common variants in contributing to phenotypic variance is neither expected nor supported by any evidence. Common variants are common because they are almost invariably neutral.

    Along with David Porteous, I have recently written a review of this topic in reference to schizophrenia in particular, which comes to much the same conclusion:

    Mitchell, K., & Porteous, D. (2010). Rethinking the genetic architecture of schizophrenia Psychological Medicine DOI: 10.1017/S003329171000070X

  2. >Common variants are common because they are almost invariably neutral.

    right. and a polymorphism with a slight effect on disease risk is essentially neutral. neutral != no phenotypic effect.

  3. Neutral = no phenotypic effect of an allele, on average across all genotypes. If there is a detectable increase in risk, on average, associated with an allele, which is what GWAS look for, then it is by definition not neutral.

    As it happens, very few such associations have emerged from GWAS for psychiatric disorders, indicating a small contribution of common variants to overall phenotypic variance.

    On the other hand, an increasing number of very rare mutations with large effects have been and continue to be discovered. i.e., normal genetics applies – no need for new mechanisms based on polygenic models.

  4. strictly speaking, every allele has some selection coefficient. the number of alleles with selection coefficient X at some frequency Y depends on the population size, the mutation rate, blah, blah…i’m sure you’re familiar with this. alleles with a small effect on risk are nearly neutral.

    >As it happens, very few such associations have emerged from GWAS for psychiatric disorders, indicating a small contribution of common variants to overall phenotypic variance

    again, this is a non sequitur–an alternative is that common variants have very small effects.

    >On the other hand, an increasing number of very rare mutations with large effects have been and continue to be discovered

    this is certainly true. but rare mutation, by definition, contribute very little to the overall phenotypic variance. let’s say we do full genome resequencing from 500 schizophrenia cases and 500 controls (presumably this will happen in the next few years). A number of interesting things will be identified, without a doubt. What fraction of the phenotypic variance do you predict these things will explain?

  5. > What fraction of the phenotypic variance do you predict these things will explain?

    I don’t think that we have any good with which to make such estimates.

    I agree with you that resequencing to identify variants that were missed in earlier studies is an obvious idea, and I’m happy that the community is doing this.

    One quick question – assume that pter is correct in saying people will stampede back and forth between common and rare variants after the next few years of (relatively) cheap resequencing fails to explain all heritable disease risk. If that’s true will we eventually find the missing signal for heritable disease risk?

  6. The penetrance of rare variants must be between common variants and Mendelian variants. Their penetrance are intermediate and can not be test by functional assay because the penetrance is too low to observe Mendelian segregation (lost 1:1 ratio between genotype and phenotype). I did not agree with rare variants with high penetrance (how much) because we can not observe clear linkage or pedigree in family with common disease. High locus heterogeneity of rare variants imply that there could be some additive effect between different loci to explain phenotypic variance. My question is if we sequence 1000 person genome, how can we test rare variants related common disease. Just see odd ratio rare variants from 1000 sequence?

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