Project description:Venous thromboembolism (VTE) is a major cause of morbidity and mortality. Pulmonary embolism is a life threatening manifestation of VTE that occurs in at least half the patients on presentation. In addition, VTE recurs in up to 30% of patients after a standard course of anticoagulation, and there is not a reliable way of predicting recurrence. We investigated whether gene expression profiles of whole blood could distinguish patients with VTE from healthy controls, single VTE from those with recurrence, and DVT alone from those with PE. 70 adults with VTE on warfarin and 63 healthy controls were studied. Patients with antiphospholipid syndrome or cancer were excluded. Blood was collected in PAXgene tubes, RNA isolated, and gene expression profiles obtained using Affymetrix arrays. We developed a 50 gene model that distinguished healthy controls from subjects with VTE with excellent receiver operating characteristics (AUC 0.94; P < 0.0001). We also discovered a separate 50 gene model that distinguished subjects with a single VTE from those with recurrent VTE with good receiver operating characteristics (AUC 0.75; P=0.008). In contrast, we were unable to distinguish subjects with DVT from those with PE using gene expression profiles. Gene expression profiles of whole blood can distinguish subjects with VTE from healthy controls and subjects with a single VTE from those with recurrence. Additional studies should be performed to validate these results and develop diagnostic tests. Gene expression profiling is likely translatable to other thrombotic disorders(e.g., patients with cancer and VTE). 70 adults with one or more prior VTE on warfarin and 63 healthy controls were studied. Patients with antiphospholipid syndrome or cancer were excluded. Blood was collected in PAXgene tubes, RNA isolated, and gene expression profiles obtained using Affymetrix arrays.
Project description:Venous thromboembolism (VTE) is a major cause of morbidity and mortality. Pulmonary embolism is a life threatening manifestation of VTE that occurs in at least half the patients on presentation. In addition, VTE recurs in up to 30% of patients after a standard course of anticoagulation, and there is not a reliable way of predicting recurrence. We investigated whether gene expression profiles of whole blood could distinguish patients with VTE from healthy controls, single VTE from those with recurrence, and DVT alone from those with PE. 70 adults with VTE on warfarin and 63 healthy controls were studied. Patients with antiphospholipid syndrome or cancer were excluded. Blood was collected in PAXgene tubes, RNA isolated, and gene expression profiles obtained using Affymetrix arrays. We developed a 50 gene model that distinguished healthy controls from subjects with VTE with excellent receiver operating characteristics (AUC 0.94; P < 0.0001). We also discovered a separate 50 gene model that distinguished subjects with a single VTE from those with recurrent VTE with good receiver operating characteristics (AUC 0.75; P=0.008). In contrast, we were unable to distinguish subjects with DVT from those with PE using gene expression profiles. Gene expression profiles of whole blood can distinguish subjects with VTE from healthy controls and subjects with a single VTE from those with recurrence. Additional studies should be performed to validate these results and develop diagnostic tests. Gene expression profiling is likely translatable to other thrombotic disorders(e.g., patients with cancer and VTE).
Project description:The aim of our study was to optimize quantitative proteomic analysis of fibrin clots prepared ex vivo from citrated plasma of the peripheral blood drawn from patients with prior venous thromboembolism. We used a multiple enzyme digestion filter aided sample preparation (MED FASP) method combined with LC-MS/MS analysis performed on a Proxeon Easy-nLC System coupled to Q Exactive HF mass spectrometer. We also evaluated the impact of peptide fractionation with pipet-tip strong anion exchange (SAX) method on the obtained results. Our proteomic approach revealed >500 proteins repeatedly identified in the plasma fibrin clots from patients with venous thromboembolism. The multienzyme digestion (MED) FASP method using three different enzymes: LysC, trypsin and chymotrypsin increased the number of identified peptides and proteins and their sequence coverage as compared to a single and double step digestion. Peptide fractionation with SAX protocol slightly increased the depth of proteomic analyses, but also extended the time needed for sample analysis with LC-MS/MS.
Project description:Recurrent venous thromboembolism (VTE) occurs infrequently following a provoked event but occurs in up to 30% of individuals following an initial unprovoked event. We studied 134 patients with VTE separated into 3 groups: (1) ‘low-risk’ patients had ≥1 provoked VTE; (2) ‘moderate-risk’ patients had no more than 1 unprovoked VTE; (3) ‘high-risk’ patients had ≥2 unprovoked VTE. 44 individuals with no history of VTE were enrolled as healthy controls. Consented individuals were enrolled at 4 medical centers in the US. Total RNA from whole blood was isolated and hybridized to Illumina HT-12 V4 Beadchips to assay whole genome expression. Using class prediction analysis, we distinguished high-risk patients from healthy controls with good receiver operating curve characteristics (AUC=0.88). We also distinguished high-risk from low-risk individuals, moderate-risk individuals from healthy controls, and low-risk individuals from healthy controls with AUC’s of 0.72, 0.77 and 0.72, respectively. Using differential expression analysis, we identified genes relevant to coagulation, immune response and vascular biology, such as SELP and CD46, which were differentially expressed in at least two comparisons. Neither approach distinguished the moderate-risk patients from the high-risk or low-risk groups. Gene expression profiles may provide insights into biological mechanisms associated with patients at risk for recurrent VTE. Prospective studies are needed to validate these findings.
Project description:Objective: Pathogenesis of antiphospholipid syndrome (APS) isn't fully elucidated. We aimed to identify gene signatures characterizing thrombotic primary APS (thrPAPS) and subgroups at high risk for worse outcomes. Methods: We performed whole blood next-generation RNA-sequencing in 62 patients with thrPAPS and 29 age-/sex-matched healthy controls (HCs), followed by differential gene expression analysis (DGEA) and enrichment analysis. We trained models on transcriptomics data using machine learning. Results: DGEA of 12.306 genes revealed 34 deregulated genes in thrPAPS versus HCs; 33 were upregulated by at least 2-fold, and 14/33 were type I and II interferon-regulated genes (IRGs) as determined by interferome database. Machine learning applied to deregulated genes returned 79% accuracy to discriminate thrPAPS from HCs, which increased to 82% when only the most informative IRGs were analyzed. Comparison of thrPAPS subgroups versus HCs showed an increased presence of IRGs among upregulated genes in venous thrombosis (21/23, 91%), triple-antiphospholipid antibody (aPL) positive (30/50, 60%), and recurrent thrombosis (19/42, 45%) subgroups. Enrichment analysis of upregulated genes in triple-aPL positive patients revealed terms related to 'type I interferon signaling pathway' and 'innate immune response'. DGEA among thrPAPS subgroups revealed upregulated genes, including IRGs, in patients with venous versus arterial thrombosis (n = 11, 9 IRGs), triple-aPL versus non-triple aPL (n = 10, 9 IRGs), and recurrent versus non-recurrent thrombosis (n = 10, 3 IRGs). Conclusion: Upregulated IRGs may better discriminate thrPAPS from HCs than all deregulated genes in peripheral blood. Taken together with DGEA data, IRGs are highly expressed in thrPAPS and high-risk subgroups of triple-aPL and recurrent thrombosis, with potential treatment implications.
Project description:Recurrent venous thromboembolism (VTE) occurs infrequently following a provoked event but occurs in up to 30% of individuals following an initial unprovoked event. We studied 134 patients with VTE separated into 3 groups: (1) âlow-riskâ patients had â¥1 provoked VTE; (2) âmoderate-riskâ patients had no more than 1 unprovoked VTE; (3) âhigh-riskâ patients had â¥2 unprovoked VTE. 44 individuals with no history of VTE were enrolled as healthy controls. Consented individuals were enrolled at 4 medical centers in the US. Total RNA from whole blood was isolated and hybridized to Illumina HT-12 V4 Beadchips to assay whole genome expression. Using class prediction analysis, we distinguished high-risk patients from healthy controls with good receiver operating curve characteristics (AUC=0.88). We also distinguished high-risk from low-risk individuals, moderate-risk individuals from healthy controls, and low-risk individuals from healthy controls with AUCâs of 0.72, 0.77 and 0.72, respectively. Using differential expression analysis, we identified genes relevant to coagulation, immune response and vascular biology, such as SELP and CD46, which were differentially expressed in at least two comparisons. Neither approach distinguished the moderate-risk patients from the high-risk or low-risk groups. Gene expression profiles may provide insights into biological mechanisms associated with patients at risk for recurrent VTE. Prospective studies are needed to validate these findings. This study includes a total of 218 samples/individuals (in 5 groups; APS, high-risk VTE, moderate-risk VTE, low-risk VTE and healthy-controls). Samples in which the percent of probes present was 15% or less (n=51) were excluded leaving 167 samples. The data for these 167 samples were normalized together. However, this record represents the 132 individual samples in the following groups; high-risk (n=40); moderate-risk (n=33); low-risk (n=34); and healthy controls (n=25). The 35 samples in APS group are represented in GSE48001.
Project description:Background: Patients with high-grade gliomas are at high risk of venous thromboembolism (VTE). MicroRNAs (miRNAs) are small non-coding RNAs with multiple roles in tumor biology, hemostasis and platelet function. We aimed to explore the association between plasma miRNAs and risk of VTE in high-grade glioma. Results: We conducted a nested-case control study within 152 patients with WHO grade IV glioma that had been included in the Vienna Cancer and Thrombosis Study (CATS), a prospective cohort study focused on risk factors for VTE in newly diagnosed or recurrent cancer. At study inclusion a single blood draw was taken, and patients were thereafter followed for a maximum of two years. During that time, 24 patients (16%) developed VTE. Of the other 128 patients, we randomly selected 24 age- and sex-matched controls. After sample quality control, the final group size was 21 VTE-patients and 23 without VTE. Small RNA next-generation sequencing of plasma was performed. We observed that hsa-miR-451a was globally the most abundant miRNA. Notably, 51% of all miRNAs showed a correlation with platelet count. The analysis of miRNAs differentially regulated in VTE patients – with and without platelet adjustment – identified potential VTE biomarker candidates such as has-miR- 221-3p. Conclusion: We here provide one of the largest and deepest peripheral blood miRNA datasets of high-grade glioma patients so far. Further, we confirm previous observations of a considerable impact of platelet count on the blood miRNome. And, finally, we present first VTE biomarker candidates that can serve as the starting point for future confirmatory research.
Project description:Systems biology is an approach to comprehensively study complex interactions within a biological system. Most published systems vaccinology studies have utilized whole blood or peripheral blood mononuclear cells (PBMC) to monitor the immune response after vaccination. Because human blood is comprised of multiple hematopoietic cell types, the potential for masking responses of under-represented cell populations is increased when analyzing whole blood or PBMC. To investigate the contribution of individual cell types to the immune response after vaccination, we established a rapid and efficient method to purify human T and B cells, natural killer (NK) cells, myeloid dendritic cells (mDC), monocytes, and neutrophils from fresh venous blood. Purified cells were fractionated and processed in a single day. RNA-Seq and quantitative shotgun proteomics were performed to determine expression profiles for each cell type prior to and after inactivated seasonal influenza vaccination. Our results show that transcriptomic and proteomic profiles generated from purified immune cells differ significantly from PBMC. Differential expression analysis for each immune cell type also shows unique transcriptomic and proteomic expression profiles as well as changing biological networks at early time points after vaccination. This cell type-specific information provides a more comprehensive approach to monitor vaccine responses.