Monocyte subpopulation counts and TNF alpha associations with clinical outcome post ST elevation myocardial infarction

Background Monocytes are implicated in the initiation and progression of the atherosclerotic plaque contributing to its instability and rupture. Although peripheral monocytosis has been related to poor clinical outcome post ST elevation myocardial infarction (STEMI), only scarce information is available of mechanisms of this association. Tumour necrosis factor alpha (TNFα) is a key cytokine in the acute phase inflammatory response, and it is predominantly produced by inflammatory macrophages. Little is known about TNFα association with circulating monocyte subpopulations post STEMI. Method A total of 142 STEMI patients (mean age 62±13 years; 72% male) treated with percutaneous revascularization were recruited with blood samples obtained within first 24 hours from the onset and on day 10-14. Peripheral blood monocyte subpopulations were enumerated and characterized using flow cytometry after staining for CD14, CD16 and CCR2 and were defined as: CD14++CD16-CCR2+ (Mon1), CD14++CD16+CCR+ (Mon2) and CD14+CD16++CCR2- (Mon3) cells. Plasma levels of TNFα were measured by enzyme-linked immunosorbent assay (ELISA, Peprotec system, UK). Major adverse cardiac events (MACE), defined as recurrent STEMI, new diagnosis of heart failure and death were recorded at follow up, mean of 164±134 days. Results TNFα levels were significantly higher 24 hours post STEMI, compared to day 14 (paired t-test, p <0.001) with day 1 levels weakly correlated with total monocyte count as well as Mon1 (Spearman’s correlation, r=0.19, p=0.02 and r=0.22, p=0.01, respectively). There was no correlation between TNFα and Mon2 or Mon3 subpopulations. TNFα levels were significantly higher in patients with a recorded MACE (n=28, Mann-Whitney test, p<0.001) (figure 1).⇓

An investigation into the effects of metabolic disturbance on monocyte inflammatory response and regulation

The presence of chronic inflammation is associated with increased nutrient availability during obesity or type 2 diabetes which contributes to the development of complications such as atherosclerosis, stroke and myocardial infarction. The link between increased nutrient availability and inflammatory response remains poorly understood. The functioning of monocytes, the primary instigators of the inflammatory response was assessed in response to obesity and increased glucose availability. Monocyte microRNA expression was assessed in obese individuals prior to and up to one year after bariatric surgery. A number of microRNAs were identified to be dysregulated in obesity, some of which have previously been linked to the regulation of monocyte inflammatory responses including the microRNAs 146a-5p and 424-5p. Weight loss in response to bariatric surgery lead to the reversal of microRNA changes towards control values. In vitro treatments of THP-1 monocytes with high concentrations of D-glucose resulted in decreased intracellular NAD+:NADH ratio, decreased SIRT1 deacetylase activity and increased P65 acetylation. However the increased osmotic concentration inhibited LPS induced inflammatory response and TNFα mRNA expression. In vitro treatment of primary human monocytes with increased concentrations of D-glucose resulted in increased secretion of a number of inflammatory cytokines and increased expression of TNFα mRNA. Treatment also resulted in decreased intracellular NAD+:NADH ratio and increased binding of acetylated P65 to the TNFα promoter region. In vitro treatments of primary monocytes also replicated the altered expression of the microRNAs 146a-5p and miR-424-5p, as seen in obese individuals. In conclusion a number of changes in monocyte function were observed in response to obesity and treatment with high concentrations of D-glucose. These may lead to the dysregulation of inflammatory responses contributing to the development of co-morbidities.

Cocaine Enhances HIV-1 Infectivity in Monocyte Derived Dendritic Cells by Suppressing microRNA-155

Cocaine and other drugs of abuse increase HIV-induced immunopathogenesis; and neurobiological mechanisms of cocaine addiction implicate a key role for microRNAs (miRNAs), single-stranded non-coding RNAs that regulate gene expression and defend against viruses. In fact, HIV defends against miRNAs by actively suppressing the expression of polycistronic miRNA cluster miRNA-17/92, which encodes miRNAs including miR-20a. IFN-g production by natural killer cells is regulated by miR-155 and this miRNA is also critical to dendritic cell (DC) maturation. However, the impact of cocaine on miR-155 expression and subsequent HIV replication is unknown. We examined the impact of cocaine on two miRNAs, miR-20a and miR-155, which are integral to HIV replication, and immune activation. Using miRNA isolation and analysis, RNA interference, quantitative real time PCR, and reporter assays we explored the effects of cocaine on miR-155 and miR-20 in the context of HIV infection. Here we demonstrate using monocyte-derived dendritic cells (MDCCs) that cocaine significantly inhibited miR-155 and miR-20a expression in a dose dependent manner. Cocaine and HIV synergized to lower miR-155 and miR-20a in MDDCs by 90%. Cocaine treatment elevated LTR-mediated transcription and PU.1 levels in MDCCs. But in context of HIV infection, PU.1 was reduced in MDDCs regardless of cocaine presence. Cocaine increased DC-SIGN and and decreased CD83 expression in MDDC, respectively. Overall, we show that cocaine inhibited miR-155 and prevented maturation of MDDCs; potentially, resulting in increased susceptibility to HIV-1. Our findings could lead to the development of novel miRNA-based therapeutic strategies targeting HIV infected cocaine abusers.

The Immunomodulatory Role of Alcohol on HIV-Infected Monocyte-Derived Dendritic Cells

Alcohol is known to induce inflammation in the presence of the human immunodeficiency virus (HIV). In our previous studies, we revealed that alcohol induces cannabinoid receptors which play a role in the regulation of inflammatory cytokine production in monocyte-derived dendritic cells (MDDC). However, the ability of alcohol to alter MDDC function during HIV infection has not been clearly elucidated yet. To study the potential impact of alcohol on HIV-infected MDDC (confirmed by p24 ELISA), monocytes were isolated from commercially available buffy coats and cultured for 7 days with GM-CSF and IL-4. MDDC were infected with HIV- 1Ba-L and treated with different concentrations of alcohol (0.1% band 0.2%) for 4-7 days. MDDC phenotype, endocytosis, cytokine production, and ability to transmit HIV to T cells were analyzed. Uninfected CD4+ T cells were co-cultured for 7 days with either infected/treated MDDC or the supernatants from infected/treated MDDC. Inflammatory cytokine arrays were performed using supernatants from HIV-infected MDDC treated with alcohol. Results showed that HIV positive MDDC treated with alcohol had higher levels of infection compared to untreated HIV positive controls. CD4+ T cells exposed to HIV-infected MDDC acquired 100-fold higher levels of p24 compared to CD4+ T cells exposed to only supernatants. CD4+ T cells exposed to HIV-infected and alcohol-treated MDDC had higher levels of infection compared to controls. Cytokine array data show dysregulation of cytokine production by alcohol. In addition, MDDC phenotype and endocytic capacity were altered in the alcohol treated MDDC. Our results indicate a crucial role of MDDC in HIV transmission to T cells and provide insights into the inflammatory role alcohol exerts on dendritic cell function in the context of HIV infection. Supported by the National Institute on Alcohol Abuse and Alcoholism award R00AA021264, the National Institute on Drug Abuse award R01DA034547, and the Institute on NeuroImmune Pharmacology at FIU.

Cystathionine γ-lyase regulates arteriogenesis through NO-dependent monocyte recruitment

AIMS: Hydrogen sulfide (H2S) is a vasoactive gasotransmitter that is endogenously produced in the vasculature by the enzyme cystathionine γ-lyase (CSE). However, the importance of CSE activity and local H2S generation for ischaemic vascular remodelling remains completely unknown. In this study, we examine the hypothesis that CSE critically regulates ischaemic vascular remodelling involving H2S-dependent mononuclear cell regulation of arteriogenesis. METHODS AND RESULTS: Arteriogenesis including mature vessel density, collateral formation, blood flow, and SPY angiographic blush rate were determined in wild-type (WT) and CSE knockout (KO) mice at different time points following femoral artery ligation (FAL). The role of endogenous H2S in regulation of IL-16 expression and subsequent recruitment of monocytes, and expression of VEGF and bFGF in ischaemic tissues, were determined along with endothelial progenitor cell (CD34/Flk1) formation and function. FAL of WT mice significantly increased CSE activity, expression and endogenous H2S generation in ischaemic tissues, and monocyte infiltration, which was absent in CSE-deficient mice. Treatment of CSE KO mice with the polysulfide donor diallyl trisulfide restored ischaemic vascular remodelling, monocyte infiltration, and cytokine expression. Importantly, exogenous H2S therapy restored nitric oxide (NO) bioavailability in CSE KO mice that was responsible for monocyte recruitment and arteriogenesis. CONCLUSION: Endogenous CSE/H2S regulates ischaemic vascular remodelling mediated during hind limb ischaemia through NO-dependent monocyte recruitment and cytokine induction revealing a previously unknown mechanism of arteriogenesis.

Influence of chylomicron remnants on human monocyte activation in vitro

Background and aims Atherosclerosis is known to be an inflammatory disease and there is increasing evidence that chylomicron remnants (CMR), the lipoproteins which carry dietary fats in the blood, cause macrophage foam cell formation and inflammation. In early atherosclerosis the frequency of activated monocytes in the peripheral circulation is increased, and clearance of CMR from blood may be delayed, however, whether CMR contribute directly to monocyte activation and subsequent egress into the arterial wall has not been established. Here, the contribution of CMR to activation of monocyte pro-inflammatory pathways was assessed using an in vitro model. Methods and results Primary human monocytes and CMR-like particles (CRLP) were used to measure several endpoints of monocyte activation. Treatment with CRLP caused rapid and prolonged generation of reactive oxygen species by monocytes. The pro-inflammatory chemokines MCP-1 and IL-8 were secreted in nanogram quantities by the cells in the absence of CRLP. IL-8 secretion was transiently increased after CRLP treatment, and CRLP maintained secretion in the presence of pharmacological inhibitors of IL-8 production. In contrast, exposure to CRLP significantly reduced MCP-1 secretion. Chemotaxis towards MCP-1 was increased in monocytes pre-exposed to CRLP and was reversed by addition of exogenous MCP-1. Conclusion Our findings indicate that CRLP activate human monocytes and augment their migration in vitro by reducing cellular MCP-1 expression. Our data support the current hypothesis that CMR contribute to the inflammatory milieu of the arterial wall in early atherosclerosis, and suggest that this may reflect direct interaction with circulating blood monocytes.

Dietary fats induce human monocyte activation in vitro

In early atherosclerosis the frequency of activated monocytes in the peripheral circulation is amplified, and migration of monocytes into the walls of the aorta and large arteries is increased, due partly to de novo expression or activation of monocyte adhesion molecules. Although there is increasing evidence that CMRs (chylomicron remnants) are strongly atherogenic, the outcomes of interactions between blood monocytes and circulating CMRs are not known. Here, we have studied the effects of CRLPs (CMR-like particles) on THP-1 human monocyte oxidative burst. The particles induced a significant increase in reactive oxygen species within 1 h, which persisted for 24 h. We suggest that monocyte–CMR interactions may be important in early atherosclerosis when many activated monocytes are found in susceptible areas of the artery wall.

A Central Role for Monocyte-Platelet Interactions in Heart Failure

Heart failure (HF) is an increasingly prevalent and costly multifactorial syndrome with high morbidity and mortality rates. The exact pathophysiological mechanisms leading to the development of HF are not completely understood. Several emerging paradigms implicate cardiometabolic risk factors, inflammation, endothelial dysfunction, myocardial fibrosis, and myocyte dysfunction as key factors in the gradual progression from a healthy state to HF. Inflammation is now a recognized factor in disease progression in HF and a therapeutic target. Furthermore, the monocyte-platelet interaction has been highlighted as an important pathophysiological link between inflammation, thrombosis, endothelial activation, and myocardial malfunction. The contribution of monocytes and platelets to acute cardiovascular injury and acute HF is well established. However, their role and interaction in the pathogenesis of chronic HF are not well understood. In particular, the cross talk between monocytes and platelets in the peripheral circulation and in the vicinity of the vascular wall in the form of monocyte-platelet complexes (MPCs) may be a crucial element, which influences the pathophysiology and progression of chronic heart disease and HF. In this review, we discuss the role of monocytes and platelets as key mediators of cardiovascular inflammation in HF, the mechanisms of cell activation, and the importance of monocyte-platelet interaction and complexes in HF pathogenesis. Finally, we summarize recent information on pharmacological inhibition of inflammation and studies of antithrombotic strategies in the setting of HF that can inform opportunities for future work. We discuss recent data on monocyte-platelet interactions and the potential benefits of therapy directed at MPCs, particularly in the setting of HF with preserved ejection fraction.

Exaggerated inflammation and monocytosis associate with diastolic dysfunction in heart failure with preserved ejection fraction: evidence of M2 macrophage activation in disease pathogenesis

BACKGROUND: Heart failure with preserved ejection fraction (HFPEF) is a major health problem associated with myocardial leukocyte infiltration, inflammation, and fibrosis. Monocyte and macrophage subsets play a role in HFPEF but have not been studied. We analyzed peripheral blood monocyte phenotype and plasma markers of monocyte activation in patients with HFPEF, asymptomatic LV diastolic dysfunction (aLVDD), and asymptomatic hypertension (aHTN).

METHODS AND RESULTS: Peripheral blood was collected from 23 aHTN, 30 aLVDD, and 30 HFPEF patients. Peripheral cytokines of classic/pro-inflammatory (tumor necrosis factor alpha, interleukin (IL) 12, IL-6, monocyte chemoattractant protein 1, C-X-C motif chemokine 10) and alternative/anti-inflammatory monocytes (chemokine-C-C motif ligand (CCL) 17, CCL-18, soluble CD163) were increased in aLVDD and HFPEF. Peripheral blood mononuclear cells and monocytes were purified and surface-stained for CD14, CD16, CD163, and CD206. Peripheral monocyte percentage was increased in aLVDD and HFPEF and correlated with echocardiographic LVDD indices. Classic/pro-inflammatory monocyte numbers were increased in aLVDD and HFPEF, and alternative/anti-inflammatory monocyte numbers were increased in HFPEF. CD163 M2-macrophage receptor was reduced in HFPEF. Culture of healthy donor monocytes (n = 3) with HFPEF patient-derived sera (n = 6) promoted M2 macrophage features as evidenced by altered morphology and genes (CD206, IL-10).

CONCLUSIONS: Increased peripheral inflammation, monocytosis, and monocyte differentiation to anti-inflammatory/profibrotic M2 macrophages likely associate with HFPEF and its precedent asymptomatic LVDD phase.

Attenuation of monocyte chemotaxis--a novel anti-inflammatory mechanism of action for the cardio-protective hormone B-type natriuretic peptide

B-type natriuretic peptide (BNP) is a prognostic and diagnostic marker for heart failure (HF). An anti-inflammatory, cardio-protective role for BNP was proposed. In cardiovascular diseases including pressure overload-induced HF, perivascular inflammation and cardiac fibrosis are, in part, mediated by monocyte chemoattractant protein (MCP)1-driven monocyte migration. We aimed to determine the role of BNP in monocyte motility to MCP1. A functional BNP receptor, natriuretic peptide receptor-A (NPRA) was identified in human monocytes. BNP treatment inhibited MCP1-induced THP1 (monocytic leukemia cells) and primary monocyte chemotaxis (70 and 50 %, respectively). BNP did not interfere with MCP1 receptor expression or with calcium. BNP inhibited activation of the cytoskeletal protein RhoA in MCP1-stimulated THP1 (70 %). Finally, BNP failed to inhibit MCP1-directed motility of monocytes from patients with hypertension (n = 10) and HF (n = 6) suggesting attenuation of this anti-inflammatory mechanism in chronic heart disease. We provide novel evidence for a direct role of BNP/NPRA in opposing human monocyte migration and support a role for BNP as a cardio-protective hormone up-regulated as part of an adaptive compensatory response to combat excess inflammation.

Demonstration of changes in plasma cell subsets in multiple myeloma.

Increases in free light chain (FLC) production are associated with disease progression in multiple myeloma (MM). Using a double immunofluorescence staining method to produce a differential count of plasma cells in bone marrow, single populations were demonstrated, containing intact monoclonal immunoglobulins (M-Igs) in 74% and FLCs only in 8% of cases. However, 18% contained a mixture of both cell populations. Progression from cells making intact M-Ig to cells restricted to FLC only production occurred in individual cases during the course of their disease. The presence of FLC only cells was associated with shortened survival.

Cell surface Glut1 levels distinguish human CD4 and CD8 T lymphocyte subsets with distinct effector functions

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Development of a particle number and particle mass vehicle emissions inventory for an urban fleet

Motor vehicles are major emitters of gaseous and particulate pollution in urban areas, and exposure to particulate pollution can have serious health effects, ranging from respiratory and cardiovascular disease to mortality. Motor vehicle tailpipe particle emissions span a broad size range from 0.003-10µm, and are measured as different subsets of particle mass concentrations or particle number count. However, no comprehensive inventories currently exist in the international published literature covering this wide size range. This paper presents the first published comprehensive inventory of motor vehicle tailpipe particle emissions covering the full size range of particles emitted. The inventory was developed for urban South-East Queensland by combining two techniques from distinctly different disciplines, from aerosol science and transport modelling. A comprehensive set of particle emission factors were combined with traffic modelling, and tailpipe particle emissions were quantified for particle number (ultrafine particles), PM1, PM2.5 and PM10 for light and heavy duty vehicles and buses. A second aim of the paper involved using the data derived in this inventory for scenario analyses, to model the particle emission implications of different proportions of passengers travelling in light duty vehicles and buses in the study region, and to derive an estimate of fleet particle emissions in 2026. It was found that heavy duty vehicles (HDVs) in the study region were major emitters of particulate matter pollution, and although they contributed only around 6% of total regional vehicle kilometres travelled, they contributed more than 50% of the region’s particle number (ultrafine particles) and PM1 emissions. With the freight task in the region predicted to double over the next 20 years, this suggests that HDVs need to be a major focus of mitigation efforts. HDVs dominated particle number (ultrafine particles) and PM1 emissions; and LDV PM2.5 and PM10 emissions. Buses contributed approximately 1-2% of regional particle emissions.

Development of a particle number and particle mass emissions inventory for an urban fleet : a study in South-East Queensland

Motor vehicles are a major source of gaseous and particulate matter pollution in urban areas, particularly of ultrafine sized particles (diameters < 0.1 µm). Exposure to particulate matter has been found to be associated with serious health effects, including respiratory and cardiovascular disease, and mortality. Particle emissions generated by motor vehicles span a very broad size range (from around 0.003-10 µm) and are measured as different subsets of particle mass concentrations or particle number count. However, there exist scientific challenges in analysing and interpreting the large data sets on motor vehicle emission factors, and no understanding is available of the application of different particle metrics as a basis for air quality regulation. To date a comprehensive inventory covering the broad size range of particles emitted by motor vehicles, and which includes particle number, does not exist anywhere in the world. This thesis covers research related to four important and interrelated aspects pertaining to particulate matter generated by motor vehicle fleets. These include the derivation of suitable particle emission factors for use in transport modelling and health impact assessments; quantification of motor vehicle particle emission inventories; investigation of the particle characteristic modality within particle size distributions as a potential for developing air quality regulation; and review and synthesis of current knowledge on ultrafine particles as it relates to motor vehicles; and the application of these aspects to the quantification, control and management of motor vehicle particle emissions. In order to quantify emissions in terms of a comprehensive inventory, which covers the full size range of particles emitted by motor vehicle fleets, it was necessary to derive a suitable set of particle emission factors for different vehicle and road type combinations for particle number, particle volume, PM1, PM2.5 and PM1 (mass concentration of particles with aerodynamic diameters < 1 µm, < 2.5 µm and < 10 µm respectively). The very large data set of emission factors analysed in this study were sourced from measurement studies conducted in developed countries, and hence the derived set of emission factors are suitable for preparing inventories in other urban regions of the developed world. These emission factors are particularly useful for regions with a lack of measurement data to derive emission factors, or where experimental data are available but are of insufficient scope. The comprehensive particle emissions inventory presented in this thesis is the first published inventory of tailpipe particle emissions prepared for a motor vehicle fleet, and included the quantification of particle emissions covering the full size range of particles emitted by vehicles, based on measurement data. The inventory quantified particle emissions measured in terms of particle number and different particle mass size fractions. It was developed for the urban South-East Queensland fleet in Australia, and included testing the particle emission implications of future scenarios for different passenger and freight travel demand. The thesis also presents evidence of the usefulness of examining modality within particle size distributions as a basis for developing air quality regulations; and finds evidence to support the relevance of introducing a new PM1 mass ambient air quality standard for the majority of environments worldwide. The study found that a combination of PM1 and PM10 standards are likely to be a more discerning and suitable set of ambient air quality standards for controlling particles emitted from combustion and mechanically-generated sources, such as motor vehicles, than the current mass standards of PM2.5 and PM10. The study also reviewed and synthesized existing knowledge on ultrafine particles, with a specific focus on those originating from motor vehicles. It found that motor vehicles are significant contributors to both air pollution and ultrafine particles in urban areas, and that a standardized measurement procedure is not currently available for ultrafine particles. The review found discrepancies exist between outcomes of instrumentation used to measure ultrafine particles; that few data is available on ultrafine particle chemistry and composition, long term monitoring; characterization of their spatial and temporal distribution in urban areas; and that no inventories for particle number are available for motor vehicle fleets. This knowledge is critical for epidemiological studies and exposure-response assessment. Conclusions from this review included the recommendation that ultrafine particles in populated urban areas be considered a likely target for future air quality regulation based on particle number, due to their potential impacts on the environment. The research in this PhD thesis successfully integrated the elements needed to quantify and manage motor vehicle fleet emissions, and its novelty relates to the combining of expertise from two distinctly separate disciplines - from aerosol science and transport modelling. The new knowledge and concepts developed in this PhD research provide never before available data and methods which can be used to develop comprehensive, size-resolved inventories of motor vehicle particle emissions, and air quality regulations to control particle emissions to protect the health and well-being of current and future generations.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.