384 research outputs found

    Application of statistical and functional methodologies for the investigation of genetic determinants of coronary heart disease biomarkers: lipoprotein lipase genotype and plasma triglycerides as an exemplar

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    Genome-wide association studies have proved very successful in identifying novel single-nucleotide polymorphisms (SNPs) associated with disease or traits, but the related, functional SNP is usually unknown. In this paper, we describe a methodology to locate and validate candidate functional SNPs using lipoprotein lipase (LPL), a gene previously associated with triglyceride levels, as an exemplar. Two thousand seven hundred and eighty-six healthy middle-aged men from the NPHSII UK prospective study (with up to six measures of plasma lipid levels) were genotyped for 20 LPL tagging (t)SNPs using Illumina Bead technology. Using model-selection procedures and haplotypes, we identified eight SNPs that consistently maximized the fit of the model to the phenotype. Fifteen SNPs in high linkage disequilibrium with these were identified, and functional assays were carried out on all 23 SNPs. Electrophoretic mobility shift assay (EMSA) was used to identify SNPs that had the potential to alter DNA–protein interactions, reducing the number to eight possible candidate SNPs. These were examined for ability to alter expression using a luciferase reporter assay, and two regulatory SNPs, showing genotype differences, rs327 and rs3289, were identified. Finally, multiplexed-competitor-EMSA (MC-EMSA) and supershift EMSA identified FOXA2 to rs327T, and CREB-binding protein (CBP) and CCAAT displacement protein (CDP) to rs3289C as the factors responsible for transcription binding. We have identified two novel candidate functional SNPs in LPL and presented a procedure aimed to efficiently detect SNPs potentially causal to genetic association. We believe that this methodology could be successfully applied to future re-sequencing data

    Integration of genetics into a systems model of electrocardiographic traits using humanCVD BeadChip

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    <p>Background—Electrocardiographic traits are important, substantially heritable determinants of risk of arrhythmias and sudden cardiac death.</p> <p>Methods and Results—In this study, 3 population-based cohorts (n=10 526) genotyped with the Illumina HumanCVD Beadchip and 4 quantitative electrocardiographic traits (PR interval, QRS axis, QRS duration, and QTc interval) were evaluated for single-nucleotide polymorphism associations. Six gene regions contained single nucleotide polymorphisms associated with these traits at P<10−6, including SCN5A (PR interval and QRS duration), CAV1-CAV2 locus (PR interval), CDKN1A (QRS duration), NOS1AP, KCNH2, and KCNQ1 (QTc interval). Expression quantitative trait loci analyses of top associated single-nucleotide polymorphisms were undertaken in human heart and aortic tissues. NOS1AP, SCN5A, IGFBP3, CYP2C9, and CAV1 showed evidence of differential allelic expression. We modeled the effects of ion channel activity on electrocardiographic parameters, estimating the change in gene expression that would account for our observed associations, thus relating epidemiological observations and expression quantitative trait loci data to a systems model of the ECG.</p> <p>Conclusions—These association results replicate and refine the mapping of previous genome-wide association study findings for electrocardiographic traits, while the expression analysis and modeling approaches offer supporting evidence for a functional role of some of these loci in cardiac excitation/conduction.</p&gt

    Polymorphisms in the Lipoprotein Lipase and Hepatic Lipase Genes and Plasma Lipid Values in the Czech Population

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    Summary We have determined the genotypes of two common polymorphisms in the lipoprotein lipase (S447X) and hepatic lipase (-480C/T) genes in a cohort of 285 representative selected Czech probands (131 male and 154 female), examined in 1988 and reinvestigated in 1996. The genotype distributions of both polymorphisms were in Hardy-Weinberg equilibrium and did not differ between male and female subjects. The rare allele frequency of the lipoprotein lipase polymorphism did not differ significantly from the other European populations. Compared to the German populations, the frequency of the hepatic lipase -480T allele was significantly higher in the Czech group (20% vs. 36%, p<0.0001). There were no significant associations between the lipoprotein lipase gene variants and lipid parameters measured either in 1988, or in 1996 or with changes of lipid parameters over the 8-year period. The carriers of the T-480 allele of the hepatic lipase polymorphism were found to have higher HDL cholesterol levels (p=0.02). However, this difference was confined to female subjects only. The male carriers of the -480T allele had higher concentrations of total cholesterol (p=0.03) as compared to CC-480 subjects. Both associations were observed in 1996 only. In the Slavic Czech population, a common polymorphism in the hepatic lipase gene (-480C/T), but not in the lipoprotein lipase gene (S447X), is a significant determinant of plasma HDL cholesterol in females and plasma total cholesterol in males and indicates the importance of gender-associated effects in the genetic determinations of plasma lipids

    Evaluation of the zucker diabetic fatty (ZDF) rat as a model for human disease based on urinary peptidomic profiles

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    Representative animal models for diabetes-associated vascular complications are extremely relevant in assessing potential therapeutic drugs. While several rodent models for type 2 diabetes (T2D) are available, their relevance in recapitulating renal and cardiovascular features of diabetes in man is not entirely clear. Here we evaluate at the molecular level the similarity between Zucker diabetic fatty (ZDF) rats, as a model of T2D-associated vascular complications, and human disease by urinary proteome analysis. Urine analysis of ZDF rats at early and late stages of disease compared to age- matched LEAN rats identified 180 peptides as potentially associated with diabetes complications. Overlaps with human chronic kidney disease (CKD) and cardiovascular disease (CVD) biomarkers were observed, corresponding to proteins marking kidney damage (eg albumin, alpha-1 antitrypsin) or related to disease development (collagen). Concordance in regulation of these peptides in rats versus humans was more pronounced in the CVD compared to the CKD panels. In addition, disease-associated predicted protease activities in ZDF rats showed higher similarities to the predicted activities in human CVD. Based on urinary peptidomic analysis, the ZDF rat model displays similarity to human CVD but might not be the most appropriate model to display human CKD on a molecular level

    Variants of ADRA2A are associated with fasting glucose, blood pressure, body mass index and type 2 diabetes risk: meta-analysis of four prospective studies

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    AIMS/HYPOTHESIS: We quantified the effect of ADRA2A (encoding α-2 adrenergic receptor) variants on metabolic traits and type 2 diabetes risk, as reported in four studies. METHODS: Genotype data for ADRA2A single nucleotide polymorphisms (SNPs) rs553668 and rs10885122 were analysed in >17,000 individuals (1,307 type 2 diabetes cases) with regard to metabolic traits and type 2 diabetes risk. Two studies (n = 9,437), genotyped using the Human Cardiovascular Disease BeadChip, provided 12 additional ADRA2A SNPs. RESULTS: Rs553668 was associated with per allele effects on fasting glucose (0.03 mmol/l, p = 0.016) and type 2 diabetes risk (OR 1.17, 95% CI 1.04-1.31; p = 0.01). No significant association was observed with rs10885122. Of the 12 SNPs, several showed associations with metabolic traits. Overall, after variable selection, rs553668 was associated with type 2 diabetes risk (OR 1.38, 95% CI 1.09-1.73; p = 0.007). rs553668 (per allele difference 0.036 mmol/l, 95% CI 0.008-0.065) and rs17186196 (per allele difference 0.066 mmol/l, 95% CI 0.017-0.115) were independently associated with fasting glucose, and rs17186196 with fasting insulin and HOMA of insulin resistance (4.3%, 95% CI 0.6-8.1 and 4.9%, 95% CI 1.0-9.0, respectively, per allele). Per-allele effects of rs491589 on systolic and diastolic blood pressure were 1.19 mmHg (95% CI 0.43-1.95) and 0.61 mmHg (95% CI 0.11-1.10), respectively, and those of rs36022820 on BMI 0.58 kg/m(2) (95% CI 0.15-1.02). CONCLUSIONS/INTERPRETATION: Multiple ADRA2A SNPs are associated with metabolic traits, blood pressure and type 2 diabetes risk. The α-2 adrenergic receptor should be revisited as a therapeutic target for reduction of the adverse consequences of metabolic trait disorders and type 2 diabetes

    Post-GWAS methodologies for localisation of functional non-coding variants: ANGPTL3

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    © 2015 The Authors. Genome-wide association studies have confirmed the involvement of non-coding angiopoietin-like 3 (ANGPTL3) gene variants with coronary artery disease, levels of low-density lipoprotein cholesterol (LDL-C), triglycerides and ANGPTL3 mRNA transcript. Extensive linkage disequilibrium at the locus, however, has hindered efforts to identify the potential functional variants. Using regulatory annotations from ENCODE, combined with functional in vivo assays such as allele-specific formaldehyde-assisted isolation of regulatory elements, statistical approaches including eQTL/lipid colocalisation, and traditional in vitro methodologies including electrophoretic mobility shift assay and luciferase reporter assays, variants affecting the ANGPTL3 regulome were examined. From 253 variants associated with ANGPTL3 mRNA expression, and/or lipid traits, 46 were located within liver regulatory elements and potentially functional. One variant, rs10889352, demonstrated allele-specific effects on DNA-protein interactions, reporter gene expression and chromatin accessibility, in line with effects on LDL-C levels and expression of ANGPTL3 mRNA. The ANGPTL3 gene lies within DOCK7, although the variant is within non-coding regions outside of ANGPTL3, within DOCK7, suggesting complex long-range regulatory effects on gene expression. This study illustrates the power of combining multiple genome-wide datasets with laboratory data to localise functional non-coding variation and provides a model for analysis of regulatory variants from GWAS.British Heart Foundation [ PG2008/008 to JP and FD, FS/13/6/29977 to AS; European Commission [GA No 278397 to PH

    Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology

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    This work was funded through grants from the British Heart Foundation (BHF, SP/07/007/23671, RG/13/5/30112) and the National Institute for Health Research University College London Hospitals Biomedical Research Centre; The Zebrafish Model Organism Database: National Human Genome Research Institute (NHGRI, HG002659, HG004838, HG004834); The Rat Genome Database: National Heart, Lung, and Blood Institute on behalf of the NIH (HL64541); The Mouse Genome Database: NGHRI (HG003300); FlyBase: UK Medical Research Council (G1000968); and Gene Ontology Consortium: NIH NHGRI (U41 HG002273) to Drs Blake, Cherry, Lewis, Sternberg, and Thomas. Professor Riley received BHF personal chair award (CH/11/1/28798). Professors Lambiase and Tinker received support from BHF and UK Medical Research Council. Professor Tinker received National Institute for Health Research Biomedical Research Centre at Barts and BHF grant (RG/15/15/31742). Dr Roncaglia received EMBL-EBI Core funds
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