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Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data.

ABSTRACT: Genome-wide association studies (GWASs) identify single nucleotide polymorphisms (SNPs) that are enriched in individuals suffering from a given disease. Most disease-associated SNPs fall into non-coding regions, so that it is not straightforward to infer phenotype or function; moreover, many SNPs are in tight genetic linkage, so that a SNP identified as associated with a particular disease may not itself be causal, but rather signify the presence of a linked SNP that is functionally relevant to disease pathogenesis. Here, we present an analysis method that takes advantage of the recent rapid accumulation of epigenomics data to address these problems for some SNPs. Using asthma as a prototypic example; we show that non-coding disease-associated SNPs are enriched in genomic regions that function as regulators of transcription, such as enhancers and promoters. Identifying enhancers based on the presence of the histone modification marks such as H3K4me1 in different cell types, we show that the location of enhancers is highly cell-type specific. We use these findings to predict which SNPs are likely to be directly contributing to disease based on their presence in regulatory regions, and in which cell types their effect is expected to be detectable. Moreover, we can also predict which cell types contribute to a disease based on overlap of the disease-associated SNPs with the locations of enhancers present in a given cell type. Finally, we suggest that it will be possible to re-analyze GWAS studies with much higher power by limiting the SNPs considered to those in coding or regulatory regions of cell types relevant to a given disease.

SUBMITTER: Gerasimova A

PROVIDER: S-EPMC3559682 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data.

Gerasimova Anna A Chavez Lukas L Li Bin B Seumois Gregory G Greenbaum Jason J Rao Anjana A Vijayanand Pandurangan P Peters Bjoern B

PloS one 20130130 1

Genome-wide association studies (GWASs) identify single nucleotide polymorphisms (SNPs) that are enriched in individuals suffering from a given disease. Most disease-associated SNPs fall into non-coding regions, so that it is not straightforward to infer phenotype or function; moreover, many SNPs are in tight genetic linkage, so that a SNP identified as associated with a particular disease may not itself be causal, but rather signify the presence of a linked SNP that is functionally relevant to ...[more]

PMID: 23382893

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Project description:Genome-wide association studies (GWAS) explore the relationship between genome variability and disease susceptibility with either population- or family-based data. Here, we have evaluated the utility of combining population- and family-based statistical association tests and have proposed a method for reducing the burden of multiple testing. Unrelated singleton and parent-offspring trio cases and controls from the Genetics of Kidneys in Diabetes (GoKinD) study were analyzed for genetic association with diabetic nephropathy (DN) in type 1 diabetics (T1D). The Cochran-Armitage test for trend and the family-based association test were employed using either unrelated cases and controls or trios, respectively. In addition to combining single nucleotide polymorphism (SNP) p-values across these tests via Fisher's method, we employed a novel screening approach to rank SNPs based on conditional power for more efficient testing. Using either the population-based or family-based subset alone predictably limited resolution to detect DN SNPs. For 384,197 SNPs passing quality control (QC), none achieved strict genome-wide significance (1.4 × 10(-7)) using 1171 singletons (577/594 cases/controls) or 1738 pooled singletons and offspring probands (841/897). Similarly, none of the 352,004 SNPs passing QC in 567 family trios (264/303 case/control proband trios) reached genome-wide significance. Testing the top 10 SNPs ranked using aggregated conditional power resulted in two SNPs reaching genome-wide significance, rs11645147 on chromosome 16 (p = 1.74 × 10(-4) < 0.05/10 = 0.005) and rs7866522 on chromosome 9 (p = 0.0033). Efficient usage of mixed designs incorporating both unrelated and family-based data may help to uncover associations otherwise difficult to detect in the presence of massive multiple testing corrections. Capitalizing on the strengths of both types while using screening approaches may be useful especially in light of large-scale, next-generation sequencing and rare variant studies.

Project description:BACKGROUND: De novo retrotransposition of Alu elements has been recognized as a major driver for insertion polymorphisms in human populations. In this study, we exploited Alu-anchored bisulfite PCR libraries to identify evolutionarily recent Alu element insertions, and to investigate their genetic and epigenetic variation. RESULTS: A total of 327 putatively recent Alu insertions were identified, altogether represented by 1,762 sequence reads. Nearly all such de novo retrotransposition events (316/327) were novel. Forty-seven out of forty-nine randomly selected events, corresponding to nineteen genomic loci, were sequence-verified. Alu element insertions remained hemizygous in one or more individuals in sixteen of the nineteen genomic loci. The Alu elements were found to be enriched for young Alu families with characteristic sequence features, such as the presence of a longer poly(A) tail. In addition, we documented the occurrence of a duplication of the AT-rich target site in their immediate flanking sequences, a hallmark of retrotransposition. Furthermore, we found the sequence motif (TT/AAAA) that is recognized by the ORF2P protein encoded by LINE-1 in their 5'-flanking regions, consistent with the fact that Alu retrotransposition is facilitated by LINE-1 elements. While most of these Alu elements were heavily methylated, we identified an Alu localized 1.5 kb downstream of TOMM5 that exhibited a completely unmethylated left arm. Interestingly, we observed differential methylation of its immediate 5' and 3' flanking CpG dinucleotides, in concordance with the unmethylated and methylated statuses of its internal 5' and 3' sequences, respectively. Importantly, TOMM5's CpG island and the 3 Alu repeats and 1 MIR element localized upstream of this newly inserted Alu were also found to be unmethylated. Methylation analyses of two additional genomic loci revealed no methylation differences in CpG dinucleotides flanking the Alu insertion sites in the two homologous chromosomes, irrespective of the presence or absence of the insertion. CONCLUSIONS: We anticipate that the combination of methodologies utilized in this study, which included repeat-anchored bisulfite PCR sequencing and the computational analysis pipeline herein reported, will prove invaluable for the generation of genetic and epigenetic variation maps.

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Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data.

Publications

Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data.

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