39 research outputs found

    Growth differentiation factor 15 and cardiovascular risk: individual patient meta-analysis

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    AIMS: Levels of growth differentiation factor 15 (GDF-15), a cytokine secreted in response to cellular stress and inflammation, have been associated with multiple types of cardiovascular (CV) events. However, its comparative prognostic performance across different presentations of atherosclerotic cardiovascular disease (ASCVD) remains unknown. METHODS AND RESULTS: An individual patient meta-analysis was performed using data pooled from eight trials including 53 486 patients. Baseline GDF-15 concentration was analyzed as a continuous variable and using established cutpoints ( 1800 ng/L) to evaluate its prognostic performance for CV death/hospitalization for heart failure (HHF), major adverse cardiovascular events (MACE), and their components using Cox models adjusted for clinical variables and established CV biomarkers. Analyses were further stratified on ASCVD status: acute coronary syndrome (ACS), stabilized after recent ACS, and stable ASCVD. Overall, higher GDF-15 concentration was significantly and independently associated with an increased rate of CV death/HHF and MACE (P < 0.001 for each). However, while GDF-15 showed a robust and consistent independent association with CV death and HHF across all presentations of ASCVD, its prognostic association with future myocardial infarction (MI) and stroke only remained significant in patients stabilized after recent ACS or with stable ASCVD [hazard ratio (HR): 1.24, 95% confidence interval (CI): 1.17-1.31 and HR: 1.16, 95% CI: 1.05-1.28 for MI and stroke, respectively] and not in ACS (HR: 0.98, 95% CI: 0.90-1.06 and HR: 0.87, 95% CI: 0.39-1.92, respectively). CONCLUSION: Growth differentiation factor 15 consistently adds prognostic information for CV death and HHF across the spectrum of ASCVD. GDF-15 also adds prognostic information for MI and stroke beyond clinical risk factors and cardiac biomarkers but not in the setting of ACS

    Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals

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    Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors

    Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

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    Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies

    Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

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    Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies

    Large-scale exome-wide association analysis identifies loci for White Blood Cell Traits and Pleiotropy with Immune-Mediated Diseases

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    White blood cells play diverse roles in innate and adaptive immunity. Genetic association analyses of phenotypic variation in circulating white blood cell (WBC) counts from large samples of otherwise healthy individuals can provide insights into genes and biologic pathways involved in production, differentiation, or clearance of particular WBC lineages (myeloid, lymphoid) and also potentially inform the genetic basis of autoimmune, allergic, and blood diseases. We performed an exome array-based meta-analysis of total WBC and subtype counts (neutrophils, monocytes, lymphocytes, basophils, and eosinophils) in a multi-ancestry discovery and replication sample of ∼157,622 individuals from 25 studies. We identified 16 common variants (8 of which were coding variants) associated with one or more WBC traits, the majority of which are pleiotropically associated with autoimmune diseases. Based on functional annotation, these loci included genes encoding surface markers of myeloid, lymphoid, or hematopoietic stem cell differentiation (CD69, CD33, CD87), transcription factors regulating lineage specification during hematopoiesis (ASXL1, IRF8, IKZF1, JMJD1C, ETS2-PSMG1), and molecules involved in neutrophil clearance/apoptosis (C10orf54, LTA), adhesion (TNXB), or centrosome and microtubule structure/function (KIF9, TUBD1). Together with recent reports of somatic ASXL1 mutations among individuals with idiopathic cytopenias or clonal hematopoiesis of undetermined significance, the identification of a common regulatory 3 UTR variant of ASXL1 suggests that both germline and somatic ASXL1 mutations contribute to lower blood counts in otherwise asymptomatic individuals. These association results shed light on genetic mechanisms that regulate circulating WBC counts and suggest a prominent shared genetic architecture with inflammatory and autoimmune diseases

    Women and Heart Attacks

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    Plasma ceramide and phospholipid-based risk score and the risk of cardiovascular death in patients after acute coronary syndrome

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    Aims Ceramide (Cer) and phosphatidylcholine (PC) lipids are associated with pathophysiological processes in cardiovascular (CV) diseases. A previously derived and validated plasma Cer-PC risk score (CERT2) was associated with CV death risk in patients with stable disease, but its prognostic value has not been evaluated in patients early post-acute coronary syndrome (ACS). Methods and results Prespecified plasma Cer and PC species in the CERT2 risk score were measured in 4871 subjects from SOLID-TIMI 52, which enrolled patients ≤30 days after ACS (median follow-up 2.5 years). The CERT2 score (scale 0–12 points) was calculated as previously defined. The primary outcome was CV death; Coronary heart disease death, all-cause death, hospitalization for heart failure (HF), myocardial infarction (MI) and stroke were also analyzed. Poisson models included baseline characteristics and established biomarkers. Patients with higher CERT2 risk scores were more likely to be older, female, current smokers, presenting with STEMI, and to have impaired renal function and higher LDL-C. After multivariable adjustment, patients in the highest risk score category remained at a nearly two-fold higher risk of CV death (adj relative risk [RR] 1.92, 95% CI 1.01–3.66, P = 0.047). Patients in the highest risk score category were also at higher risk of all-cause death (adj RR 2.01, 95% CI 1.21–3.35, P = 0.007), whereas the relationships with HF, MI, and stroke were attenuated with multivariable adjustment. Conclusions A plasma ceramide and phospholipid-based risk score is associated with the risk of CV death independent of established clinical risk factors and biomarkers in patients after ACS.</p
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