Broadbent HM, Peden JF, Lorkowski S, Goel A, Ongen H, Green F et al.. Susceptibility to coronary artery disease and diabetes is encoded by distinct, tightly linked SNPs in the ANRIL locus on chromosome 9p. Hum Mol Genet 17: 806-814

Department of Cardiovascular Medicine, University of Oxford, UK.
Human Molecular Genetics (Impact Factor: 6.39). 04/2008; 17(6):806-14. DOI: 10.1093/hmg/ddm352
Source: PubMed


Genome-wide association studies have identified a region on chromosome 9p that is associated with coronary artery disease (CAD). The region is also associated with type 2 diabetes (T2D), a risk factor for CAD, although different SNPs were reported to be associated to each disease in separate studies. We have undertaken a case-control study in 4251 CAD cases and 4443 controls in four European populations using previously reported ('literature') and tagging SNPs. We replicated the literature SNPs (P = 8x10(-13); OR = 1.29; 95% CI: 1.20-1.38) and showed that the strong consistent association detected by these SNPs is a consequence of a 'yin-yang' haplotype pattern spanning 53 kb. There was no evidence of additional CAD susceptibility alleles over the major risk haplotype. CAD patients without myocardial infarction (MI) showed a trend towards stronger association than MI patients. The CAD susceptibility conferred by this locus did not differ by sex, age, smoking, obesity, hypertension or diabetes. A simultaneous test of CAD and diabetes susceptibility with CAD and T2D-associated SNPs indicated that these associations were independent of each other. Moreover, this region was not associated with differences in plasma levels of low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, fibrinogen, albumin, uric acid, bilirubin or homocysteine, although the CAD-high-risk allele was paradoxically associated with lower triglyceride levels. A large antisense non-coding RNA gene (ANRIL) collocates with the high-risk haplotype, is expressed in tissues and cell types that are affected by atherosclerosis and is a prime candidate gene for the chromosome 9p CAD locus.

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Available from: Udo Seedorf, Jul 25, 2014
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    • "In addition, with ChIPSeq dataset, we identified 139,576 SNPs in 304,517 transcription factor peaks of 4,813 lincRNAs. Then, we downloaded the annotation information of minor allele frequencies and others from 1000 Genomes Project (release of July 2012) datasets across 11 populations [31], and performed comprehensive annotation for these SNPs in lincRNA TFBSs. For each SNP in a lincRNA TFBS, we also extracted the flanking sequence of 30 nt up-/down-stream of the SNP position from RefSeq reference genomic sequence. "
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    ABSTRACT: Large intergenic non-coding RNAs (lincRNAs) are a new class of functional transcripts, and aberrant expression of lincRNAs was associated with several human diseases. The genetic variants in lincRNA transcription factor binding sites (TFBSs) can change lincRNA expression, thereby affecting the susceptibility to human diseases. To identify and annotate these functional candidates, we have developed a database SNP@lincTFBS, which is devoted to the exploration and annotation of single nucleotide polymorphisms (SNPs) in potential TFBSs of human lincRNAs. We identified 6,665 SNPs in 6,614 conserved TFBSs of 2,423 human lincRNAs. In addition, with ChIPSeq dataset, we identified 139,576 SNPs in 304,517 transcription factor peaks of 4,813 lincRNAs. We also performed comprehensive annotation for these SNPs using 1000 Genomes Project datasets across 11 populations. Moreover, one of the distinctive features of SNP@lincTFBS is the collection of disease-associated SNPs in the lincRNA TFBSs and SNPs in the TFBSs of disease-associated lincRNAs. The web interface enables both flexible data searches and downloads. Quick search can be query of lincRNA name, SNP identifier, or transcription factor name. SNP@lincTFBS provides significant advances in identification of disease-associated lincRNA variants and improved convenience to interpret the discrepant expression of lincRNAs. The SNP@lincTFBS database is available at
    PLoS ONE 07/2014; 9(7):e103851. DOI:10.1371/journal.pone.0103851 · 3.23 Impact Factor
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    • "Scott et al. reported that SNPs adjacent to the lncRNA ANRIL were associated with increased risks of type 2 diabetes [56]. The viewpoint was also confirmed by a separate study, which reported that distinct SNPs in the lncRNA ANRIL locus were associated with susceptibility to coronary artery disease and atherosclerosis [57]. Further characterization of the identified polymorphisms showed that SNPs can disrupt ANRIL splicing, leading to a circular transcript that is resistant to RNase digestion [35]. "
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    ABSTRACT: Genome-wide association studies have identified that genetic variants in 8q24 confer susceptibility to colorectal cancer (CRC). Recently, a novel lncRNA (PRNCR1) that located in the 8q24 was discovered. Single nucleotide polymorphisms (SNPs) in the lncRNAs may influence the process of splicing and stability of mRNA conformation, resulting in the modification of its interacting partners. We hypothesized that SNPs in the lncRNA PRNCR1 may be related to the risk of CRC. We conducted a case-control study and genotyped five tag SNPs in the lncRNA PRNCR1 in 908 subjects including 313 cases with CRC and 595 control subjects using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. In overall analyses, we found that the rs13252298 and rs1456315 were associated with significantly decreased risks of CRC. In stratification analyses, we found that CRC patients carrying the rs1456315G were likely to have a tumor size of greater than 5 cm (G vs. A: adjusted OR = 1.56, 95% CI: 1.10-2.23). Additionally, patients with the rs7007694C and rs16901946G had decreased risks to develop poorly differentiated CRC, whereas patients with the rs1456315G had an increased risk to develop poorly differentiated CRC. These findings suggest that SNPs in the lncRNA PRNCR1 may contribute to susceptibility to CRC.
    Journal of Experimental & Clinical Cancer Research 12/2013; 32(1):104. DOI:10.1186/1756-9966-32-104 · 4.43 Impact Factor
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    • "In general , common genetic variants with small effects do not significantly improve predictive algorithms for other complex disorders; however, the chromosome 9p21 locus indicates some clinical benefit (Meigs et al. 2008). Haplotype analyses have found an interesting CVD association with a group of SNPs residing in a 60 kb region that includes ANRIL (Samani et al. 2007; Broadbent et al. 2008). A decreased risk associated with the long to short variant ratio has been reported for this allele (Jarinova et al. 2009; Kathiresan et al. 2009). "
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    ABSTRACT: Diabetic vascular complications (DVC) affecting several important organ systems of human body such as the cardiovascular system constitute a major public health problem. There is evidence demonstrating that genetic factors contribute to the risk of DVC genetic variants, structural variants, and epigenetic changes play important roles in the development of DVC. Genetic linkage studies have uncovered a number of genetic loci that may shape the risk of DVC. Genetic association studies have identified many common genetic variants for susceptibility to DVC. Structural variants such as copy number variation and interactions of gene x environment have also been detected by association analysis. Apart from the nuclear genome, mitochondrial DNA plays a critical role in regulation of development of DVC. Epigenetic studies have indicated epigenetic changes in chromatin affecting gene transcription in response to environmental stimuli, which provided a large body of evidence of regulating development of diabetes mellitus. Recently, a new window has opened on identifying rare and common genetic loci through next generation sequencing technologies. This review focusses on the current knowledge of the genetic and epigenetic basis of DVC. Ultimately, identification of genes or genetic loci, structural variants and epigenetic changes contributing to risk of or protection from DVC will help uncover the complex mechanism(s) underlying DVC, with crucial implications for the development of personalized medicine for diabetes mellitus and its complications.
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