Clan Genomics and the Complex Architecture of Human Disease

Lupski, James R.; Belmont, John W.; Boerwinkle, Eric; Gibbs, Richard A.

doi:10.1016/j.cell.2011.09.008

Cited by 343 publications

(328 citation statements)

References 116 publications

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“…However, most of the associated SNPs explain a modest proportion of heritability for most common diseases, 2 and they do not provide variants directly applicable for diagnosis, prevention and treatment. 3 With the advent of whole-genome sequencing, there is now the possibility to evaluate the role of genetic variants that were too rare to be picked up by GWAS. 4 Because rare and potentially deleterious variants arose more recently than common variants, they were not yet eliminated by selection and they might provide most of the medically actionable alleles.…”

Section: Introductionmentioning

confidence: 99%

“…4 Because rare and potentially deleterious variants arose more recently than common variants, they were not yet eliminated by selection and they might provide most of the medically actionable alleles. 3,5 These alleles, because of their recent origin, tend to cluster within a lineage and therefore, many disease-related traits have been found in population isolates. 6 Likewise, non-isolated populations displaying fine-scale genetic structure, within a short geographical distance, may be appropriate for gene mapping because they likely present high frequency of rare alleles.…”

Section: Introductionmentioning

confidence: 99%

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Fine-scale human genetic structure in Western France

Karakachoff¹,

Duforet-Frebourg²,

Simonet³

et al. 2014

Eur J Hum Genet

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The difficulties arising from association analysis with rare variants underline the importance of suitable reference population cohorts, which integrate detailed spatial information. We analyzed a sample of 1684 individuals from Western France, who were genotyped at genome-wide level, from two cohorts D.E.S.I.R and CavsGen. We found that fine-scale population structure occurs at the scale of Western France, with distinct admixture proportions for individuals originating from the Brittany Region and the Vendé e Department. Genetic differentiation increases with distance at a high rate in these two parts of Northwestern France and linkage disequilibrium is higher in Brittany suggesting a lower effective population size. When looking for genomic regions informative about Breton origin, we found two prominent associated regions that include the lactase region and the HLA complex. For both the lactase and the HLA regions, there is a low differentiation between Bretons and Irish, and this is also found at the genome-wide level. At a more refined scale, and within the Pays de la Loire Region, we also found evidence of fine-scale population structure, although principal component analysis showed that individuals from different departments cannot be confidently discriminated. Because of the evidence for fine-scale genetic structure in Western France, we anticipate that rare and geographically localized variants will be identified in future full-sequence analyses.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fine-scale human genetic structure in Western France

Karakachoff¹,

Duforet-Frebourg²,

Simonet³

et al. 2014

Eur J Hum Genet

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“…Various authors have speculated that the dramatic increase in the number of new alleles caused by population expansion has altered the genetic architecture of disease and the explanation for missing heritability (42)(43)(44). Specifically, it has been suggested that expansion may have dramatically increased (i) the total frequency of genetic disease by raising mutational load; (ii) the relative importance of new alleles in disease risk; or (iii) the role of rare variants in disease risk.…”

Section: Impact Of Population Expansion On the Genetic Architecture Ofmentioning

confidence: 99%

Searching for missing heritability: Designing rare variant association studies

Zuk

Schaffner

Samocha

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

596

559

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Genetic studies have revealed thousands of loci predisposing to hundreds of human diseases and traits, revealing important biological pathways and defining novel therapeutic hypotheses. However, the genes discovered to date typically explain less than half of the apparent heritability. Because efforts have largely focused on common genetic variants, one hypothesis is that much of the missing heritability is due to rare genetic variants. Studies of common variants are typically referred to as genomewide association studies, whereas studies of rare variants are often simply called sequencing studies. Because they are actually closely related, we use the terms common variant association study (CVAS) and rare variant association study (RVAS). In this paper, we outline the similarities and differences between RVAS and CVAS and describe a conceptual framework for the design of RVAS. We apply the framework to address key questions about the sample sizes needed to detect association, the relative merits of testing disruptive alleles vs. missense alleles, frequency thresholds for filtering alleles, the value of predictors of the functional impact of missense alleles, the potential utility of isolated populations, the value of gene-set analysis, and the utility of de novo mutations. The optimal design depends critically on the selection coefficient against deleterious alleles and thus varies across genes. The analysis shows that common variant and rare variant studies require similarly large sample collections. In particular, a well-powered RVAS should involve discovery sets with at least 25,000 cases, together with a substantial replication set. mapping disease genes | power analysis | statistical genetics G enomic studies over the last half decade have shed light on the genetic basis of common polygenic human diseases and traits, identifying thousands of loci and revealing key biological pathways. Nonetheless, the genetic variants identified thus far appear to explain less than half of the estimated heritability in most diseases and traits. The sources of the so-called missing heritability remain unclear (1). This article is our second paper exploring the mystery of missing heritability.In our first paper (2), we explored a methodological issue. We showed that genetic interactions, if present, could account for substantial missing heritability. Still, this is likely to be only a partial explanation. In this paper, we turn to the search for additional genetic variants underlying common human diseases, focusing on rare genetic variants.The discovery of genes underlying common diseases depends on association studies (except in special cases where Mendelian subtypes of common diseases show clear segregation in large families). Association studies involve testing whether the frequency of a set of one or more alleles differs between cases and a control population, indicating that the set of alleles is associated with the disease. Association studies to date have largely focused on studying individual common variants, because ...

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“…It is likely that genome-wide association studies focusing on common variants and segregation of marker genotypes in populations do not apply when rare variants and de novo gene mutations contribute in a substantial way to a (disease) trait not under selection pressure? 10 The data emerging from genome-wide association studies, including array comparative genomic hybridization and exome sequencing, suggest that both rare variants and new mutations contribute significantly to medically actionable problems. These observations, embedded in the concept of "clan genomics, "…”

Section: Genetics In Medicine | Volume 15 | Number 3 | March 2013mentioning

confidence: 99%

“…10 There is a need to consider a new genetic arithmetic. Even though there is a lack of statistical significance for association (P = 0.26), Moles et al 7 have convinced us of the causality of this duplication CNV.…”

Section: Genetics In Medicine | Volume 15 | Number 3 | March 2013mentioning

confidence: 99%