Rationale VEGF impacts angiogenesis, atherosclerosis and cancer. Although the heritability of circulating VEGF levels is high, little is known about its genetic underpinnings. Objective Our aim was to identify genetic variants associated with circulating VEGF levels using an unbiased genome-wide approach and explore their functional significance with gene expression and pathway analysis. Methods and results We undertook a genome-wide association study (GWAS) of serum VEGF levels in 3,527 participants of the Framingham Heart Study (FHS), with pre-planned replication in 1,727 participants from two independent samples, the STANISLAS Family Study (SFS) and the Prospective Investigation of the Vasculature in Uppsala Seniors study (PIVUS). One hundred and forty SNPs reached genome-wide significance (p<5×10−8). We found evidence of replication for the most significant associations in both replication datasets. In a conditional GWAS 4 SNPs mapping to 3 chromosomal regions were independently associated with circulating VEGF levels: rs6921438 and rs4416670 (6p21.1, p=6.11×10−506 and p=1.47×10−12), rs6993770 (8q23.1, p=2.50×10−16) and rs10738760 (9p24.2, p=1.96×10−34). A genetic score including these four SNPs explained 48% of the heritability of serum VEGF levels. Six of the SNPs that reached genome-wide significance in the GWAS were significantly associated with VEGF mRNA levels in PBMCs. Ingenuity pathway analyses showed found plausible biological links between VEGF and 2 novel genes in these loci (ZFPM2 and VLDLR). Conclusions Genetic variants explaining up to half the heritability of serum VEGF levels were identified. These new insights provide important clues to the pathways regulating circulating VEGF levels.
Vascular endothelial growth factor (VEGF) is an angiogenic and neurotrophic factor, secreted by endothelial cells, known to impact various physiological and disease processes from cancer to cardiovascular disease and to be pharmacologically modifiable. We sought to identify novel loci associated with circulating VEGF levels through a genome-wide association meta-analysis combining data from European-ancestry individuals and using a dense variant map from 1000 genomes imputation panel. Six discovery cohorts including 13,312 samples were analyzed, followed by in-silico and de-novo replication studies including an additional 2,800 individuals. A total of 10 genome-wide significant variants were identified at 7 loci. Four were novel loci (5q14.3, 10q21.3, 16q24.2 and 18q22.3) and the leading variants at these loci were rs114694170 (MEF2C, P = 6.79x10-13), rs74506613 (JMJD1C, P = 1.17x10-19), rs4782371 (ZFPM1, P = 1.59x10-9) and rs2639990 (ZADH2, P = 1.72x10-8), respectively. We also identified two new independent variants (rs34528081, VEGFA, P = 1.52x10-18; rs7043199, VLDLR-AS1, P = 5.12x10-14) at the 3 previously identified loci and strengthened the evidence for the four previously identified SNPs (rs6921438, LOC100132354, P = 7.39x10-1467; rs1740073, C6orf223, P = 2.34x10-17; rs6993770, ZFPM2, P = 2.44x10-60; rs2375981, KCNV2, P = 1.48x10-100). These variants collectively explained up to 52% of the VEGF phenotypic variance. We explored biological links between genes in the associated loci using Ingenuity Pathway Analysis that emphasized their roles in embryonic development and function. Gene set enrichment analysis identified the ERK5 pathway as enriched in genes containing VEGF associated variants. eQTL analysis showed, in three of the identified regions, variants acting as both cis and trans eQTLs for multiple genes. Most of these genes, as well as some of those in the associated loci, were involved in platelet biogenesis and functionality, suggesting the importance of this process in regulation of VEGF levels. This work also provided new insights into the involvement of genes implicated in various angiogenesis related pathologies in determining circulating VEGF levels. The understanding of the molecular mechanisms by which the identified genes affect circulating VEGF levels could be important in the development of novel VEGF-related therapies for such diseases.
Acute kidney injury (AKI) following cardiac surgery significantly increases morbidity and mortality risks. Improving existing clinical methods of identifying patients at risk of perioperative AKI may advance management and treatment options. This study investigated whether a combination of biomarkers and clinical factors pre and post cardiac surgery could stratify patients at risk of developing AKI. Patients (n = 401) consecutively scheduled for elective cardiac surgery were prospectively studied. Clinical data was recorded and blood samples were tested for 31 biomarkers. Areas under receiver operating characteristic (AUROCs) were generated for biomarkers pre and postoperatively to stratify patients at risk of AKI. Preoperatively sTNFR1 had the highest predictive ability to identify risk of developing AKI postoperatively (AUROC 0.748). Postoperatively a combination of H-FABP, midkine and sTNFR2 had the highest predictive ability to identify AKI risk (AUROC 0.836). Preoperative clinical risk factors included patient age, body mass index and diabetes. Perioperative factors included cardio pulmonary bypass, cross-clamp and operation times, intra-aortic balloon pump, blood products and resternotomy. Combining biomarker risk score (BRS) with clinical risk score (CRS) enabled pre and postoperative assignment of patients to AKI risk categories. Combining BRS with CRS will allow better management of cardiac patients at risk of developing AKI.
Background: Interleukin-8 (IL-8), monocyte chemoattractant protein-1 (MCP-1), epidermal growth factor (EGF), and vascular endothelial growth factor (VEGF) are known to be involved in various diseases related to inflammation, vascular remodeling, or growth deregulation. In addition, increases in plasma concentrations of these cytokines appear to provide useful diagnostic and prognostic information. We therefore investigated which factors most strongly influence the biological variations of plasma IL-8, MCP-1, EGF, and VEGF concentrations. Methods: We used the Evidence ® biochip array analyzer to quantify plasma IL-8, MCP-1, EGF, and VEGF concentrations in a subsample of 304 children (age range, 4 -17 years) and 540 adults (age range, 18 -55 years) from the STANISLAS family study. We also calculated reference intervals for the 4 cytokines. Results: We found the following associations with plasma marker concentrations: Age, neutrophil count, and glucose concentration were positively associated with IL-8 concentrations in children and adults, as were smoking and platelet count in adults. MCP-1 concentrations were associated with age and smoking in both children and adults, monocyte count in children, and sex and hematocrit in adults. EGF concentrations were
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