468 research outputs found

    Hemostasis and ageing

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    On March 19, 2008 a Symposium on Pathophysiology of Ageing and Age-Related Diseases was held in Palermo, Italy. The lecture of D. Mari on Hemostasis and ageing is summarized herein. Physiological ageing is associated with increased plasma levels of many proteins of blood coagulation together with fibrinolysis impairment. This may be of great concern in view of the known association between vascular and thromboembolic diseases and ageing. On the other hand, centenarians are characterized by a state of hypercoagulability and possession of several high-risk alleles and well-known atherothrombotic risk markers but this appears to be compatible with longevity and/or health. Parameters considered risk factors for atherosclerotic vascular diseases in young people may lose their biological significance in advanced age and assume a different role

    Efficacy of TachoSil® patches in controlling Dacron suture-hole bleeding after abdominal aortic aneurysm open repair

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    <p>Abstract</p> <p>Purpose</p> <p>The aim of this study is evaluate the efficacy of TachoSil<sup>® </sup>patches in controlling suture-hole bleeding after elective infrarenal abdominal aortic aneurysm (AAA) replacement with Dacron graft.</p> <p>Materials and methods</p> <p>Patients undergoing elective replacement of infrarenal AAA with Dacron grafts were prospectively randomized to TachoSil<sup>® </sup>patches (Group I) or standard compression with surgical swabs (Group II).</p> <p>We evaluated time to haemostasis, blood loss during the operation, blood loss after cross-clamp removal, duration of operation, drain volume, requirement for blood transfusion and surgeons rating of efficacy.</p> <p>Results</p> <p>Twenty patients were randomized (10 patients in each treatment Group). The mean time to haemostasis was 264 ± 127.1 s (range: 180-600 s) in Group I and 408 ± 159.5 s (range: 120-720 s) in Group II (p = 0.026); mean blood loss during the operation was 503.5 ± 20.7 cc (range: 474-545 cc) in Group I and 615.7 ± 60.3 cc (range: 530-720 cc) in Group II (p < 0.001); mean blood loss after cross-clamp removal was 26.5 ± 4 g (range: 22-34 g) in Group I and 45.4 ± 4.6 (range: 38-52 g) in Group II (p < 0.001) and mean drain volume was 116.7 ± 41.4 cc (range: 79-230 cc) in Group I and 134.5 ± 42.8 cc (range: 101-250 cc) in Group II (p = 0.034). There were no serious adverse events associated with use of TachoSil<sup>® </sup>patches.</p> <p>Conclusion</p> <p>For patients undergoing aortic reconstruction with Dacron grafts, TachoSil<sup>® </sup>patches were found to be safe and effective for the control of suture-hole bleeding.</p

    Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

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    Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P &lt; 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms

    Practical Issues in Imputation-Based Association Mapping

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    Imputation-based association methods provide a powerful framework for testing untyped variants for association with phenotypes and for combining results from multiple studies that use different genotyping platforms. Here, we consider several issues that arise when applying these methods in practice, including: (i) factors affecting imputation accuracy, including choice of reference panel; (ii) the effects of imputation accuracy on power to detect associations; (iii) the relative merits of Bayesian and frequentist approaches to testing imputed genotypes for association with phenotype; and (iv) how to quickly and accurately compute Bayes factors for testing imputed SNPs. We find that imputation-based methods can be robust to imputation accuracy and can improve power to detect associations, even when average imputation accuracy is poor. We explain how ranking SNPs for association by a standard likelihood ratio test gives the same results as a Bayesian procedure that uses an unnatural prior assumption—specifically, that difficult-to-impute SNPs tend to have larger effects—and assess the power gained from using a Bayesian approach that does not make this assumption. Within the Bayesian framework, we find that good approximations to a full analysis can be achieved by simply replacing unknown genotypes with a point estimate—their posterior mean. This approximation considerably reduces computational expense compared with published sampling-based approaches, and the methods we present are practical on a genome-wide scale with very modest computational resources (e.g., a single desktop computer). The approximation also facilitates combining information across studies, using only summary data for each SNP. Methods discussed here are implemented in the software package BIMBAM, which is available from http://stephenslab.uchicago.edu/software.html

    Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE Collaboration): a meta-analysis of genome-wide association studies

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    &lt;p&gt;Background - Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.&lt;/p&gt; &lt;p&gt;Methods - We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls.&lt;/p&gt; &lt;p&gt;Findings - We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10−16) and ZFHX3 (p=2·28×10−8), and for large-vessel stroke at a 9p21 locus (p=3·32×10−5) and HDAC9 (p=2·03×10−12). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p&#60;5×10−6. However, we were unable to replicate any of these novel associations in the replication cohort.&lt;/p&gt; &lt;p&gt;Interpretation - Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes.&lt;/p&gt

    Genetic analysis of haemophilia A in Bulgaria

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    BACKGROUND: Haemophilias are the most common hereditary severe disorders of blood clotting. In families afflicted with heamophilia, genetic analysis provides opportunities to prevent recurrence of the disease. This study establishes a diagnostical strategy for carriership determination and prenatal diagnostics of haemophilia A in Bulgarian haemophilic population. METHODS: A diagnostical strategy consisting of screening for most common mutations in the factor VIII gene and analysis of a panel of eight linked to the factor VIII gene locus polymorphisms was established. RESULTS: Polymorphic analysis for carrier status determination of haemophilia A was successful in 30 families out of 32 (94%). Carrier status was determined in 25 of a total of 28 women at risk (89%). Fourteen prenatal diagnoses in women at high risk of having a haemophilia A – affected child were performed, resulting in 6 healthy boys and 5 girls. CONCLUSION: The compound approach proves to be a highly informative and cost-effective strategy for prevention of recurrence of haemophilia A in Bulgaria. DNA analysis facilitates carriership determination and subsequent prenatal diagnosis in the majority of Bulgarian families affected by haemophilia A

    Common Variants in CRP and LEPR Influence High Sensitivity C-Reactive Protein Levels in North Indians

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    BACKGROUND: High sensitivity C-reactive protein (hsCRP) levels are shown to be influenced by genetic variants in Europeans; however, little is explored in Indian population. METHODS: Herein, we comprehensively evaluated association of all previously reported genetic determinants of hsCRP levels, including 18 cis (proximal to CRP gene) and 73 trans-acting (distal to CRP gene) variants in 4,200 North Indians of Indo-European ethnicity. First, we evaluated association of 91 variants from 12 candidate loci with hsCRP levels in 2,115 North Indians (1,042 non-diabetic subjects and 1,073 patients with type 2 diabetes). Then, cis and trans-acting variants contributing maximally to hsCRP level variation were further replicated in an independent 2,085 North Indians (1,047 patients with type 2 diabetes and 1,038 non-diabetic subjects). RESULTS: We found association of 12 variants from CRP, LEPR, IL1A, IL6, and IL6R with hsCRP levels in non-diabetic subjects. However, only rs3093059-CRP [β = 0.33, P = 9.6×10⁻⁵] and the haplotype harboring rs3093059 risk allele [β = 0.32 µg/mL, P = 1.4×10⁻⁴/P(perm) = 9.0×10⁻⁴] retained significance after correcting for multiple testing. The cis-acting variant rs3093059-CRP had maximum contribution to the variance in hsCRP levels (1.14%). Among, trans-acting variants, rs1892534-LEPR was observed to contribute maximally to hsCRP level variance (0.59%). Associations of rs3093059-CRP and rs1892534-LEPR were confirmed by replication and attained higher significance after meta-analysis [β(meta) = 0.26/0.22; P(meta) = 4.3×10⁻⁷/7.4×10⁻³ and β(meta) = -0.15/-0.12; P(meta) = 2.0×10⁻⁶/1.6×10⁻⁶ for rs3093059 and rs1892534, respectively in non-diabetic subjects and all subjects taken together]. CONCLUSION: In conclusion, we identified rs3093059 in CRP and rs1892534 in LEPR as major cis and trans-acting contributor respectively, to the variance in hsCRP levels in North Indian population

    Genome-Wide Association Study of Blood Pressure Traits by Hispanic/Latino Background: the Hispanic Community Health Study/Study of Latinos

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    Hypertension prevalence varies between ethnic groups, possibly due to differences in genetic, environmental, and cultural determinants. Hispanic/Latino Americans are a diverse and understudied population. We performed a genome-wide association study (GWAS) of blood pressure (BP) traits in 12,278 participants from the Hispanics Community Health Study/Study of Latinos (HCHS/SOL). In the discovery phase we identified eight previously unreported BP loci. In the replication stage, we tested these loci in the 1982 Pelotas Birth Cohort Study of admixed Southern Brazilians, the COGENT-BP study of African descent, women of European descent from the Women Health Initiative (WHI), and a sample of European descent from the UK Biobank. No loci met the Bonferroni-adjusted level of statistical significance (0.0024). Two loci had marginal evidence of replication: rs78701042 (NGF) with diastolic BP (P = 0.008 in the 1982 Pelotas Birth Cohort Study), and rs7315692 (SLC5A8) with systolic BP (P = 0.007 in European ancestry replication). We investigated whether previously reported loci associated with BP in studies of European, African, and Asian ancestry generalize to Hispanics/Latinos. Overall, 26% of the known associations in studies of individuals of European and Chinese ancestries generalized, while only a single association previously discovered in a people of African descent generalized

    Testing the role of predicted gene knockouts in human anthropometric trait variation

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    National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge
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