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Genotype-specific recurrence risks as indicators of the genetic architecture of complex diseases.

ABSTRACT: A statistic is introduced that relates discoveries made in genome-wide association (GWA) studies to patterns of disease risks among relatives. The genotype-specific recurrence risk (GSR) is the genotype-specific risk to relatives of known relationship to affected probands. The GSRs can be used for three purposes. (1) They can provide an independent test of whether an allele identified in a GWA study is associated with the disease. (2) They can provide a test of whether interactions among loci affecting the disease are multiplicative. (3) They can be used by genetic counselors to incorporate information from GWA studies for predicting the risk to relatives of known genotype. Under a multiplicative model of disease causation, the GSRs for a locus are the genotypic risks in probands for that locus multiplied by lambda(R)/lambda(jR), where lambda(R) is Risch's recurrence risk ratio and lambda(jR) is the contribution to lambda(R) from the locus of interest. If there is saturation of risk with increasing numbers of causative alleles, then observed GSRs for individuals with high-risk genotypes will be lower than predicted by the multiplicative model.

SUBMITTER: Slatkin M

PROVIDER: S-EPMC2443843 | biostudies-literature | 2008 Jul

REPOSITORIES: biostudies-literature

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Genotype-specific recurrence risks as indicators of the genetic architecture of complex diseases.

Slatkin Montgomery M

American journal of human genetics 20080701 1

A statistic is introduced that relates discoveries made in genome-wide association (GWA) studies to patterns of disease risks among relatives. The genotype-specific recurrence risk (GSR) is the genotype-specific risk to relatives of known relationship to affected probands. The GSRs can be used for three purposes. (1) They can provide an independent test of whether an allele identified in a GWA study is associated with the disease. (2) They can provide a test of whether interactions among loci af ...[more]

PMID: 18597734

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Project description:BackgroundLack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle.ResultsWe cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance, PIK3CG, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle. ICAM, a T cell-specific gene, was significantly associated with both allergic diseases in human and metritis in cattle.ConclusionCollectively, our results highlighted that comparative epigenomics in conjunction with GWAS and selection signature analyses could provide biological insights into the phenotypic variation and adaptive evolution. Cattle may serve as a model for human complex traits, by providing additional information beyond laboratory model organisms, particularly when more novel phenotypes become available in the near future.

Project description:Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype-metabolite associations distributed non-randomly within the genome. These clusters of genotype-metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype-metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable.

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Genotype-specific recurrence risks as indicators of the genetic architecture of complex diseases.

Publications

Genotype-specific recurrence risks as indicators of the genetic architecture of complex diseases.

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