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

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

Targeted genetic testing for familial hypercholesterolaemia using next generation sequencing:a population-based study

Background<p></p> Familial hypercholesterolaemia (FH) is a common Mendelian condition which, untreated, results in premature coronary heart disease. An estimated 88% of FH cases are undiagnosed in the UK. We previously validated a method for FH mutation detection in a lipid clinic population using next generation sequencing (NGS), but this did not address the challenge of identifying index cases in primary care where most undiagnosed patients receive healthcare. Here, we evaluate the targeted use of NGS as a potential route to diagnosis of FH in a primary care population subset selected for hypercholesterolaemia.<p></p> Methods<p></p> We used microfluidics-based PCR amplification coupled with NGS and multiplex ligation-dependent probe amplification (MLPA) to detect mutations in LDLR, APOB and PCSK9 in three phenotypic groups within the Generation Scotland: Scottish Family Health Study including 193 individuals with high total cholesterol, 232 with moderately high total cholesterol despite cholesterol-lowering therapy, and 192 normocholesterolaemic controls.<p></p> Results<p></p> Pathogenic mutations were found in 2.1% of hypercholesterolaemic individuals, in 2.2% of subjects on cholesterol-lowering therapy and in 42% of their available first-degree relatives. In addition, variants of uncertain clinical significance (VUCS) were detected in 1.4% of the hypercholesterolaemic and cholesterol-lowering therapy groups. No pathogenic variants or VUCS were detected in controls.<p></p> Conclusions<p></p> We demonstrated that population-based genetic testing using these protocols is able to deliver definitive molecular diagnoses of FH in individuals with high cholesterol or on cholesterol-lowering therapy. The lower cost and labour associated with NGS-based testing may increase the attractiveness of a population-based approach to FH detection compared to genetic testing with conventional sequencing. This could provide one route to increasing the present low percentage of FH cases with a genetic diagnosis

A follow-up study for left ventricular mass on chromosome 12p11 identifies potential candidate genes

<p>Abstract</p> <p>Background</p> <p>Left ventricular mass (LVM) is an important risk factor for cardiovascular disease. Previously we found evidence for linkage to chromosome 12p11 in Dominican families, with a significant increase in a subset of families with high average waist circumference (WC). In the present study, we use association analysis to further study the genetic effect on LVM.</p> <p>Methods</p> <p>Association analysis with LVM was done in the one LOD critical region of the linkage peak in an independent sample of 897 Caribbean Hispanics. Genotype data were available on 7085 SNPs from 23 to 53 MB on chromosome 12p11. Adjustment was made for vascular risk factors and population substructure using an additive genetic model. Subset analysis by WC was performed to test for a difference in genetic effects between the high and low WC subsets.</p> <p>Results</p> <p>In the overall analysis, the most significant association was found to rs10743465, downstream of the <it>SOX5 </it>gene (p = 1.27E-05). Also, 19 additional SNPs had nominal p < 0.001. In the subset analysis, the most significant difference in genetic effect between those with high and low WC occurred with rs1157480 (p = 1.37E-04 for the difference in β coefficients), located upstream of <it>TMTC1</it>. Twelve additional SNPs in or near 6 genes had p < 0.001.</p> <p>Conclusions</p> <p>The current study supports previously identified evidence by linkage for a genetic effect on LVM on chromosome 12p11 using association analysis in population-based Caribbean Hispanic cohort. <it>SOX5 </it>may play an important role in the regulation of LVM. An interaction of <it>TMTC1 </it>with abdominal obesity may contribute to phenotypic variation of LVM.</p

Interactions of the Apolipoprotein A5 Gene Polymorphisms and Alcohol Consumption on Serum Lipid Levels

Little is known about the interactions of apolipoprotein (Apo) A5 gene polymorphisms and alcohol consumption on serum lipid profiles. The present study was undertaken to detect the interactions of ApoA5-1131T>C, c.553G>T and c.457G>A polymorphisms and alcohol consumption on serum lipid levels.A total of 516 nondrinkers and 514 drinkers were randomly selected from our previous stratified randomized cluster samples. Genotyping was performed by polymerase chain reaction and restriction fragment length polymorphism. The levels of serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), ApoA1 and ApoB were higher in drinkers than in nondrinkers (P<0.05-0.001). The genotypic and allelic frequencies of three loci were not different between the two groups. The interactions between -1131T>C genotypes and alcohol consumption on ApoB levels (P<0.05) and the ApoA1/ApoB ratio (P<0.01), between c.553G>T genotypes and alcohol consumption on low-density lipoprotein cholesterol (LDL-C) levels (P<0.05) and the ApoA1/ApoB ratio (P<0.05), and between c.457G>A genotypes and alcohol consumption on TG levels (P<0.001) were detected by factorial regression analysis after controlling for potential confounders. Four haplotypes (T-G-G, C-G-G, T-A-G and C-G-T) had frequencies ranging from 0.06 to 0.87. Three haplotypes (C-G-G, T-A-G, and C-G-T) were significantly associated with serum lipid parameters. The -1131T>C genotypes were correlated with TG, and c.553G>T and c.457G>A genotypes were associated with HDL-C levels in nondrinkers (P<0.05 for all). For drinkers, the -1131T>C genotypes were correlated with TC, TG, LDL-C, ApoB levels and the ApoA1/ApoB ratio (P<0.01 for all); c.553G>T genotypes were correlated with TC, TG, HDL-C and LDL-C levels (P<0.05-0.01); and c.457G>A genotypes were associated with TG, LDL-C, ApoA1 and ApoB levels (P<0.05-0.01).The differences in some serum lipid parameters between the drinkers and nondrinkers might partly result from different interactions of the ApoA5 gene polymorphisms and alcohol consumption

Genome Wide Association Study to predict severe asthma exacerbations in children using random forests classifiers

<p>Abstract</p> <p>Background</p> <p>Personalized health-care promises tailored health-care solutions to individual patients based on their genetic background and/or environmental exposure history. To date, disease prediction has been based on a few environmental factors and/or single nucleotide polymorphisms (SNPs), while complex diseases are usually affected by many genetic and environmental factors with each factor contributing a small portion to the outcome. We hypothesized that the use of random forests classifiers to select SNPs would result in an improved predictive model of asthma exacerbations. We tested this hypothesis in a population of childhood asthmatics.</p> <p>Methods</p> <p>In this study, using emergency room visits or hospitalizations as the definition of a severe asthma exacerbation, we first identified a list of top Genome Wide Association Study (GWAS) SNPs ranked by Random Forests (RF) importance score for the CAMP (Childhood Asthma Management Program) population of 127 exacerbation cases and 290 non-exacerbation controls. We predict severe asthma exacerbations using the top 10 to 320 SNPs together with age, sex, pre-bronchodilator FEV1 percentage predicted, and treatment group.</p> <p>Results</p> <p>Testing in an independent set of the CAMP population shows that severe asthma exacerbations can be predicted with an Area Under the Curve (AUC) = 0.66 with 160-320 SNPs in comparison to an AUC score of 0.57 with 10 SNPs. Using the clinical traits alone yielded AUC score of 0.54, suggesting the phenotype is affected by genetic as well as environmental factors.</p> <p>Conclusions</p> <p>Our study shows that a random forests algorithm can effectively extract and use the information contained in a small number of samples. Random forests, and other machine learning tools, can be used with GWAS studies to integrate large numbers of predictors simultaneously.</p

Population genomics of cardiometabolic traits: design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium.

Substantial advances have been made in identifying common genetic variants influencing cardiometabolic traits and disease outcomes through genome wide association studies. Nevertheless, gaps in knowledge remain and new questions have arisen regarding the population relevance, mechanisms, and applications for healthcare. Using a new high-resolution custom single nucleotide polymorphism (SNP) array (Metabochip) incorporating dense coverage of genomic regions linked to cardiometabolic disease, the University College-London School-Edinburgh-Bristol (UCLEB) consortium of highly-phenotyped population-based prospective studies, aims to: (1) fine map functionally relevant SNPs; (2) precisely estimate individual absolute and population attributable risks based on individual SNPs and their combination; (3) investigate mechanisms leading to altered risk factor profiles and CVD events; and (4) use Mendelian randomisation to undertake studies of the causal role in CVD of a range of cardiovascular biomarkers to inform public health policy and help develop new preventative therapies

Genome-Wide Association Analysis of Soluble ICAM-1 Concentration Reveals Novel Associations at the NFKBIK, PNPLA3, RELA, and SH2B3 Loci

Soluble ICAM-1 (sICAM-1) is an endothelium-derived inflammatory marker that has been associated with diverse conditions such as myocardial infarction, diabetes, stroke, and malaria. Despite evidence for a heritable component to sICAM-1 levels, few genetic loci have been identified so far. To comprehensively address this issue, we performed a genome-wide association analysis of sICAM-1 concentration in 22,435 apparently healthy women from the Women's Genome Health Study. While our results confirm the previously reported associations at the ABO and ICAM1 loci, four novel associations were identified in the vicinity of NFKBIK (rs3136642, P = 5.4×10−9), PNPLA3 (rs738409, P = 5.8×10−9), RELA (rs1049728, P = 2.7×10−16), and SH2B3 (rs3184504, P = 2.9×10−17). Two loci, NFKBIB and RELA, are involved in NFKB signaling pathway; PNPLA3 is known for its association with fatty liver disease; and SH3B2 has been associated with a multitude of traits and disease including myocardial infarction. These associations provide insights into the genetic regulation of sICAM-1 levels and implicate these loci in the regulation of endothelial function

Association of rs780094 in GCKR with Metabolic Traits and Incident Diabetes and Cardiovascular Disease: The ARIC Study

The minor T-allele of rs780094 in the glucokinase regulator gene (GCKR) associates with a number of metabolic traits including higher triglyceride levels and improved glycemic regulation in study populations of mostly European ancestry. Using data from the Atherosclerosis Risk in Communities (ARIC) Study, we sought to replicate these findings, examine them in a large population-based sample of African American study participants, and to investigate independent associations with other metabolic traits in order to determine if variation in GKCR contributes to their observed clustering. In addition, we examined the association of rs780094 with incident diabetes, coronary heart disease (CHD), and stroke over up mean follow-up times of 8, 15, and 15 years, respectively.Race-stratified analyses were conducted among 10,929 white and 3,960 black participants aged 45-64 at baseline assuming an additive genetic model and using linear and logistic regression and Cox proportional hazards models.Previous findings replicated among white participants in multivariable adjusted models: the T-allele of rs780094 was associated with lower fasting glucose (p = 10(-7)) and insulin levels (p = 10(-6)), lower insulin resistance (HOMA-IR, p = 10(-9)), less prevalent diabetes (p = 10(-6)), and higher CRP (p = 10(-8)), 2-h postprandial glucose (OGTT, p = 10(-6)), and triglyceride levels (p = 10(-31)). Moreover, the T-allele was independently associated with higher HDL cholesterol levels (p = 0.022), metabolic syndrome prevalence (p = 0.043), and lower beta-cell function measured as HOMA-B (p = 0.011). Among black participants, the T-allele was associated only with higher triglyceride levels (p = 0.004) and lower insulin levels (p = 0.002) and HOMA-IR (p = 0.013). Prospectively, the T-allele was associated with reduced incidence of diabetes (p = 10(-4)) among white participants, but not with incidence of CHD or stroke.Our findings indicate rs780094 has independent associations with multiple metabolic traits as well as incident diabetes, but not incident CHD or stroke. The magnitude of association between the SNP and most traits was of lower magnitude among African American compared to white participants