77 research outputs found

    Strategies to fine-map genetic associations with lipid levels by combining epigenomic annotations and liver-specific transcription profiles

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    Characterization of the epigenome promises to yield the functional elements buried in the human genome sequence, thus helping to annotate non-coding DNA polymorphisms with regulatory functions. Here, we develop two novel strategies to combine epigenomic data with transcriptomic profiles in humans or mice to prioritize potential candidate SNPs associated with lipid levels by genome-wide association study (GWAS). First, after confirming that lipid-associated loci that are also expression quantitative trait loci (eQTL) in human livers are enriched for ENCODE regulatory marks in the human hepatocellular HepG2 cell line, we prioritize candidate SNPs based on the number of these marks that overlap the variant position. This method recognized the known SORT1 rs12740374 regulatory SNP associated with LDL-cholesterol, and highlighted candidate functional SNPs at 15 additional lipid loci. In the second strategy, we combine ENCODE chromatin immunoprecipitation followed by high-throughput DNA sequencing (ChIP-seq) data and liver expression datasets from knockout mice lacking specific transcription factors. This approach identified SNPs in specific transcription factor binding sites that are located near target genes of these transcription factors. We show that FOXA2 transcription factor binding sites are enriched at lipid-associated loci and experimentally validate that alleles of one such proxy SNP located near the FOXA2 target gene BIRC5 show allelic differences in FOXA2-DNA binding and enhancer activity. These methods can be used to generate testable hypotheses for many non-coding SNPs associated with complex diseases or traits

    Identification of a Regulatory Variant That Binds FOXA1 and FOXA2 at the CDC123/CAMK1D Type 2 Diabetes GWAS Locus

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    Many of the type 2 diabetes loci identified through genome-wide association studies localize to non-protein-coding intronic and intergenic regions and likely contain variants that regulate gene transcription. The CDC123/CAMK1D type 2 diabetes association signal on chromosome 10 spans an intergenic region between CDC123 and CAMK1D and also overlaps the CDC123 3′UTR. To gain insight into the molecular mechanisms underlying the association signal, we used open chromatin, histone modifications and transcription factor ChIP-seq data sets from type 2 diabetes-relevant cell types to identify SNPs overlapping predicted regulatory regions. Two regions containing type 2 diabetes-associated variants were tested for enhancer activity using luciferase reporter assays. One SNP, rs11257655, displayed allelic differences in transcriptional enhancer activity in 832/13 and MIN6 insulinoma cells as well as in human HepG2 hepatocellular carcinoma cells. The rs11257655 risk allele T showed greater transcriptional activity than the non-risk allele C in all cell types tested. Using electromobility shift and supershift assays we demonstrated that the rs11257655 risk allele showed allele-specific binding to FOXA1 and FOXA2. We validated FOXA1 and FOXA2 enrichment at the rs11257655 risk allele using allele-specific ChIP in human islets. These results suggest that rs11257655 affects transcriptional activity through altered binding of a protein complex that includes FOXA1 and FOXA2, providing a potential molecular mechanism at this GWAS locus

    Allelic expression imbalance at high-density lipoprotein cholesterol locus MMAB-MVK

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    Genome-wide association studies (GWAS) have identified numerous loci associated with various complex traits for which the underlying susceptibility gene(s) remain unknown. In a GWAS for high-density lipoprotein-cholesterol (HDL-C) level, one strongly associated locus contains at least two biologically compelling candidates, methylmalonic aciduria cblB type (MMAB) and mevalonate kinase (MVK). To detect evidence of cis-acting regulation at this locus, we measured relative allelic expression of transcribed SNPs in five genes using human hepatocyte samples heterozygous for the transcribed SNP. If an HDL-C-associated SNP allele differentially regulates mRNA level in cis, samples heterozygous both for a transcribed SNP and an HDL-C-associated SNP should display allelic expression imbalance (AEI) of the transcribed SNP. We designed statistical tests to detect AEI in a comprehensive set of linkage disequilibrium (LD) scenarios between the transcribed SNP and an HDL-C-associated SNP (rs7298565) in phase unknown samples. We observed significant AEI of 22% in MMAB (P = 1.4 × 10−13, transcribed SNP rs11067231), and the allele associated with lower HDL-C level was associated with greater MMAB transcript level. The same rs7298565 allele was also associated with higher MMAB mRNA level (P = 0.0081) and higher MMAB protein level (P = 0.0020). In contrast, MVK, UBE3B, KCTD10 and ACACB did not show significant AEI (P ≥ 0.05). These data suggest MMAB is the most likely gene influencing HDL-C levels at this locus and demonstrate that measuring AEI at loci containing more than one candidate gene can prioritize genes for functional studies

    A map of open chromatin in human pancreatic islets

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    Tissue-specific transcriptional regulation is central to human disease(1). To identify regulatory DNA active in human pancreatic islets, we profiled chromatin by formaldehyde-assisted isolation of regulatory elements(2-4) coupled with high-throughput sequencing (FAIRE-seq). We identified similar to 80,000 open chromatin sites. Comparison of FAIRE-seq data from islets to that from five non-islet cell lines revealed similar to 3,300 physically linked clusters of islet-selective open chromatin sites, which typically encompassed single genes that have islet-specific expression. We mapped sequence variants to open chromatin sites and found that rs7903146, a TCF7L2 intronic variant strongly associated with type 2 diabetes(5), is located in islet-selective open chromatin. We found that human islet samples heterozygous for rs7903146 showed allelic imbalance in islet FAIRE signals and that the variant alters enhancer activity, indicating that genetic variation at this locus acts in cis with local chromatin and regulatory changes. These findings illuminate the tissue-specific organization of cis-regulatory elements and show that FAIRE-seq can guide the identification of regulatory variants underlying disease susceptibility

    Population-specific coding variant underlies genome-wide association with adiponectin level

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    Adiponectin is a protein hormone that can affect major metabolic processes including glucose regulation and fat metabolism. Our previous genome-wide association (GWA) study of circulating plasma adiponectin levels in Filipino women from the Cebu Longitudinal Health and Nutrition Survey (CLHNS) detected a 100 kb two-SNP haplotype at KNG1–ADIPOQ associated with reduced adiponectin (frequency = 0.050, P = 1.8 × 10−25). Subsequent genotyping of CLHNS young adult offspring detected an uncommon variant [minor allele frequency (MAF) = 0.025] located ∼800 kb from ADIPOQ that showed strong association with lower adiponectin levels (P = 2.7 × 10−15, n = 1695) and tagged a subset of KNG1–ADIPOQ haplotype carriers with even lower adiponectin levels. Sequencing of the ADIPOQ-coding region detected variant R221S (MAF = 0.015, P = 2.9 × 10−69), which explained 17.1% of the variance in adiponectin levels and largely accounted for the initial GWA signal in Filipinos. R221S was not present in 12 514 Europeans with previously sequenced exons. To explore the mechanism of this substitution, we re-measured adiponectin level in 20 R221S offspring carriers and 20 non-carriers using two alternative antibodies and determined that the presence of R221S resulted in artificially low quantification of adiponectin level using the original immunoassay. These data provide an example of an uncommon variant responsible for a GWA signal and demonstrate that genetic associations with phenotypes measured by antibody-based quantification methods can be affected by uncommon coding SNPs residing in the antibody target region

    Multiple Hepatic Regulatory Variants at the GALNT2 GWAS Locus Associated with High-Density Lipoprotein Cholesterol

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    Genome-wide association studies (GWASs) have identified more than 150 loci associated with blood lipid and cholesterol levels; however, the functional and molecular mechanisms for many associations are unknown. We examined the functional regulatory effects of candidate variants at the GALNT2 locus associated with high-density lipoprotein cholesterol (HDL-C). Fine-mapping and conditional analyses in the METSIM study identified a single locus harboring 25 noncoding variants (r2 > 0.7 with the lead GWAS variants) strongly associated with total cholesterol in medium-sized HDL (e.g., rs17315646, p = 3.5 × 10−12). We used luciferase reporter assays in HepG2 cells to test all 25 variants for allelic differences in regulatory enhancer activity. rs2281721 showed allelic differences in transcriptional activity (75-fold [T] versus 27-fold [C] more than the empty-vector control), as did a separate 780-bp segment containing rs4846913, rs2144300, and rs6143660 (49-fold [AT– haplotype] versus 16-fold [CC+ haplotype] more). Using electrophoretic mobility shift assays, we observed differential CEBPB binding to rs4846913, and we confirmed this binding in a native chromatin context by performing chromatin-immunoprecipitation (ChIP) assays in HepG2 and Huh-7 cell lines of differing genotypes. Additionally, sequence reads in HepG2 DNase-I-hypersensitivity and CEBPB ChIP-seq signals spanning rs4846913 showed significant allelic imbalance. Allelic-expression-imbalance assays performed with RNA from primary human hepatocyte samples and expression-quantitative-trait-locus (eQTL) data in human subcutaneous adipose tissue samples confirmed that alleles associated with increased HDL-C are associated with a modest increase in GALNT2 expression. Together, these data suggest that at least rs4846913 and rs2281721 play key roles in influencing GALNT2 expression at this HDL-C locus

    Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion

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    Insulin secretion plays a critical role in glucose homeostasis, and failure to secrete sufficient insulin is a hallmark of type 2 diabetes. Genome-wide association studies (GWAS) have identified loci contributing to insulin processing and secretion1,2; however, a substantial fraction of the genetic contribution remains undefined. To examine low-frequency (minor allele frequency (MAF) 0.5% to 5%) and rare (MAF<0.5%) nonsynonymous variants, we analyzed exome array data in 8,229 non-diabetic Finnish males. We identified low-frequency coding variants associated with fasting proinsulin levels at the SGSM2 and MADD GWAS loci and three novel genes with low-frequency variants associated with fasting proinsulin or insulinogenic index: TBC1D30, KANK1, and PAM. We also demonstrate that the interpretation of single-variant and gene-based tests needs to consider the effects of noncoding SNPs nearby and megabases (Mb) away. This study demonstrates that exome array genotyping is a valuable approach to identify low-frequency variants that contribute to complex traits
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