Rare and common variants: twenty arguments G.Gibson Homework 3 Mylène Champs Marine Flechet Mathieu Stifkens 1 Bioinformatics - GBIO0009-1 - K.Van Steen

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Rare and common variants: twenty arguments G.Gibson

Homework 3

Mylène ChampsMarine Flechet

Mathieu Stifkens

Bioinformatics - GBIO0009-1 - K.Van Steen University of Liège

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Content : Rare and common variants

IntroductionSummary

◦Rare allele model◦Infinitesimal model

Conclusion


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IntroductionSummary


Conclusion


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Introduction: Rare and common variants

◦Genome-wide association studies (GWASs) identify genetic factors that influence health and disease.

◦First model used : CDCV (Common disease Common variant) = a small number of common variants can explain the percentage of disease risk.

◦This model is not used anymore because of the “missing heritability problem”. A few loci with moderate effect cannot explain several percent of disease susceptibility.


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IntroductionSummary


Conclusion


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Summary : Rare and common variants

Rare allele model◦Presentation of the model◦Arguments « in favour »◦Arguments « against »


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Rare allele model – Presentation ◦Model known as « many rare alleles of large

effect ».

◦The variance for a disease is due to rare variants (allele frequency<1%) which are highly penetrant (large effect).

◦Example: Schizophrenia = collection of many similar conditions that are attributable to rare variants.


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Rare allele model – Presentation

Causal variant effects (yellow dots) may be large in a few individuals but are not common enough to represent a “hit” in a GWAS.


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Rare allele model – « In favour »◦ Evolutionnary theory predicts that disease alleles should be

rare[1] ;

◦ Empirical population genetic data shows that deleterious variants are rare[1] ;

◦ Rare copy number variants contribute to several complex psychological disorders[1] ;

◦ Many rare familial disorders are due to rare alleles of large effects[1];

◦ Synthetic association may explain common variants effects[1] .


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Rare allele model – « In favour »◦ Evolutionnary theory predicts that disease alleles should

be rare[1] ;

◦ Empirical population genetic data shows that deleterious variants are rare[1] ;

◦ Rare copy number variants contribute to several complex psychological disorders[1] ;

◦ Many rare familial disorders are due to rare alleles of large effects[1];

◦ Synthetic association may explain common variants effects[1] .


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Evolutionnary theory predicts that disease alleles should be rare[1] :

◦Deleterious alleles are created by mutation; removed by purifying selection.

◦Rate(creation) > rate (removal)


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Rare copy number variants contribute to several complex psychological disorders[1] :

◦CNVs : hemizygous deletion – local duplication;

◦Promote disease such as schyzophrenia and autism and modify its severity .


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Synthetic association may explain common variants effects[1] :


LD Data [2]

For common variants which do not explain much percentage of the disease susceptibility Rare variants increase this case risk.

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Rare allele model – « Against »◦ Analysis of GWAS data is not consistent with rare variants

explanations[1] ;

◦ Sibling recurrence rates are greater than would be expected by the postulated effect sizes of rare variants[1] ;

◦ Rare variants do not obviously have additive effects[1] ;

◦ Epidemiological transitions cannot be attributed to rare variants[1] ;

◦ GWAS associations are consistent across populations[1] ;


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Rare allele model – « Against »◦ Analysis of GWAS data is not consistent with rare

variants explanations[1] ;

◦ Sibling recurrence rates are greater than would be expected by the postulated effect sizes of rare variants[1] ;

◦ Rare variants do not obviously have additive effects[1] ;

◦ Epidemiological transitions cannot be attributed to rare variants[1] ;

◦ GWAS associations are consistent across populations[1] ;


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Analysis of GWAS data is not consistent with rare variants explanations[1]

◦ Rare variants cannot be the predominant source of heritabilily;

◦ There should be many of them with large size and effect.


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Rare variants do not obviously have additive effects[1]

◦ Genetic associations are known to be additive whereas rare variants interact multiplicatively and they have dominant effect;

◦ However on the statistical side rare variants induce additivity effects.


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Epidemiological transitions cannot be attributed to rare variants[1]

◦ The change of prevalence of some diseases is too fast;

◦ The model can not explain the influence of environmental variable.


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IntroductionSummary


Conclusion


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Infinitesimal model◦Presentation of the model◦Arguments « in favour »◦Arguments « against »


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Infinitesimal model – Presentation◦ Known as « common » model or many common variants of small

effects.

◦ This is the model used in GWASs.

◦ Common variants are the major source of genetic variance for disease susceptibility.

◦ Hundreds or thousands of loci of small effect contribute in each case.

◦ Example : Height or BMI studies, hundred of loci have been found but they don’t explain all of the genetic variance. This problem is called the « missing heritability problem ».


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Infinitesimal model – Presentation


Significant “hits” of common variants with small effects. Several SNPs within a linkage disequilibrium (LD) block are associated with the trait [1].

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Infinitesimal model – « In favour »◦ The infinitesimal model underpins standard quantitative genetic

theory[1] ;

◦ Common variants collectively capture the majority of the genetic variance in GWASs[1] ;

◦ Variation in endophenotypes is almost certainly due to common variants[1] ;

◦ Model organism research supports common variants contributions to complex phenotypes[1] ;

◦ GWASs have successfully identified thousands of common variants[1] .


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Infinitesimal model – « In favour »◦ The infinitesimal model underpins standard quantitative

genetic theory[1] ;

◦ Common variants collectively capture the majority of the genetic variance in GWASs[1] ;

◦ Variation in endophenotypes is almost certainly due to common variants[1] ;

◦ Model organism research supports common variants contributions to complex phenotypes[1] ;

◦ GWASs have successfully identified thousands of common variants[1] .


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The infinitesimal model underpins standard quantitative genetic theory[1] :

◦ High heritability ;

◦ No results were against the infinitesimal model.


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Common variants collectively capture the majority of the genetic variance in GWASs[1]:

Capture more of the genetic variance by using all significant SNPs;

Variance is attributed to hundreds of loci.


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GWASs have successfully identified thousands of common variants[1] :

◦ Unrealistic assumptions of the effect size ;

◦ Increasing samples allows to determine more loci.


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Infinitesimal model – « Against »◦ The QTL paradox[1] ;

◦ The abscence of blending inheritence[1] ;

◦ Demographic phenomena suggest more than one simple common-variant model[1] ;

◦ Very few common variants for disease have been functionnaly validated[1] ;

◦ What accounts for the missing heritability[1] ?


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Infinitesimal model – « Against »◦ The QTL paradox[1] ;

◦ The abscence of blending inheritence[1] ;

◦ Demographic phenomena suggest more than one simple common-variant model[1] ;

◦ Very few common variants for disease have been functionnaly validated[1] ;

◦ What accounts for the missing heritability[1] ?


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The QTL paradox[1]

◦ We cannot find QTLs detected in pedigrees and in experimental crosses;

◦ Explanations:-> QTLs are rare variants that only contribute in that cross.-> Each cross captures only a small fraction of genetic variance in a population.


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The abscence of blending inheritence[1]

◦ The granularity in the distribution of risks and phenotypic trait variation should decrease with the crossing of two unrelated poeple;

◦ However we observe higher risks than the model predicted;

◦ For example : We can observe that in some family complex phenotype

traits are recurrent.


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What accounts for the missing heritability[1] ?

◦ The model does not take into account the missing heritability problem;

◦ But the problem really exists !


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IntroductionSummary


Conclusion


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Conclusion : Rare and common variants

Which model would you choose ?


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Which model would you choose ?

◦ Both !

◦ We should learn how to use the two models together because they both have their place in the current research.

◦ Idea : Integrate rare and common variants effects together.


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The common variants establish the background liability to a disease and this liability can be modified by the rare variants with large effects [1].

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Thank you for your attention !


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References :


[1] G. GIBSON : Rare and common variants: twenty arguments. Nat. Rev. Genet., 13(2):135145, Feb 2012.[2] Bioinformatics course – GWAS studies, K. VAN STEEN

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Rare and common variants: twenty arguments G.Gibson Homework 3 Mylène Champs Marine Flechet Mathieu Stifkens 1 Bioinformatics - GBIO0009-1 - K.Van Steen