Characterization of myocardial injury phenotype by thermal liquid biopsy

Background and aims

With the advent and implementation of high-sensitivity cardiac troponin assays, differentiation of patients with distinct types of myocardial injuries, including acute thrombotic myocardial infarction (TMI), acute non-thrombotic myocardial injury (nTMi), and chronic coronary atherosclerotic disease (cCAD), is of pressing clinical importance. Thermal liquid biopsy (TLB) emerges as a valuable diagnostic tool, relying on identifying thermally induced conformational changes of biomolecules in blood plasma. While TLB has proven useful in detecting and monitoring several cancers and autoimmune diseases, its application in cardiovascular diseases remains unexplored. In this proof-of-concept study, we sought to determine and characterize TLB profiles in patients with TMI, nTMi, and cCAD at multiple acute-phase time points (T 0 h, T 2 h, T 4 h, T 24 h, T 48 h) as well as a follow-up time point (Tfu) when the patient was in a stable state.

Methods

TLB profiles were collected for 115 patients (60 with TMI, 35 with nTMi, and 20 with cCAD) who underwent coronary angiography at the event presentation and had subsequent follow-up. Medical history, physical, electrocardiographic, histological, biochemical, and angiographic data were gathered through medical records, standardized patient interviews, and core laboratory measurements.

Results

Distinctive signatures were noted in the median TLB profiles across the three patient types. TLB profiles for TMI and nTMi patients exhibited gradual changes from T0 to Tfu, with significant differences during the acute and quiescent phases. During the quiescent phase, all three patient types demonstrated similar TLB signatures. An unsupervised clustering analysis revealed a unique TLB signature for the patients with TMI. TLB metrics generated from specific features of TLB profiles were tested for differences between patient groups. The first moment temperature (TFM) metric distinguished all three groups at time of presentation (T0). In addition, 13 other TLB-derived metrics were shown to have distinct distributions between patients with TMI and those with cCAD.

Conclusion

Our findings demonstrated the use of TLB as a sensitive and data-rich technique to be explored in cardiovascular diseases, thus providing valuable insight into acute myocardial injury events.

Suppression of Phytophthora capsici in Chile Pepper Using Brassica juncea and Hordeum vulgare Cover Crop Residues and Trichoderma harzianum as a Biocontrol Agent

Phytophthora blight, caused by Phytophthora capsici, is a serious disease of many vegetable crops worldwide. In New Mexico, U.S.A., the disease affects chile pepper (Capsicum annuum L.), a major crop in the state. There is no single tool that effectively controls the disease. Continuous research is needed in identifying combination of tools that can reduce the impact of Phytophthora blight. We explored the potential of combining cover crops and biocontrol agents to reduce soilborne diseases. This study aimed to evaluate the effects of Indian mustard (Brassica juncea L.) cover crop on the antagonistic ability of Trichoderma harzianum against P. capsici in vitro and to quantify the impacts of combining soil amendment with residues from B. juncea and barley (Hordeum vulgare L.) cover crops and plastic covering on infection of chile pepper seedlings by P. capsici under greenhouse conditions. Volatiles from macerated tissue of B. juncea significantly reduced P. capsici and T. harzianum growth in the absence of soil by 89.0 and 79.0%, respectively. When incorporated in soils, volatiles from macerated tissue of B. juncea significantly reduced P. capsici and T. harzianum by 33.4 and 7.8%, respectively. T. harzianum was more resilient to B. juncea biofumigation than P. capsici. Significant reduction in disease incidence was observed with B. juncea-fumigated soil, while no disease suppression was observed with soil incorporation of H. vulgare residues. Covering soil with plastic was necessary for increasing the efficacy of B. juncea biofumigation.

Risk factor associations with individual myocardial infarction subtypes and acute non-ischemic myocardial injury in the Multi-Ethnic Study of Atherosclerosis (MESA): Design and rationale

BACKGROUND

Despite different prevalence, pathobiology, and prognosis between etiologically distinct myocardial infarction (MI) subtypes, prospective study of risk factor for MI in large NHLBI-sponsored cardiovascular cohorts is limited to acute MI as a singular entity. Therefore, we sought to utilize the Multi-Ethnic Study of Atherosclerosis (MESA), a large prospective primary prevention cardiovascular study, to define the incidence and risk factor profile of individual myocardial injury subtypes.

METHODS

We describe the rationale and design of re-adjudicating 4,080 events that occurred over the first 14 years of follow-up in MESA for the presence and subtype of myocardial injury as defined by the Fourth Universal Definition of MI: MI type 1 to 5, acute non-ischemic myocardial injury, and chronic myocardial injury. The project utilizes a 2-physician adjudication process via examination of medical records, abstracted data collection forms, cardiac biomarker results, and electrocardiograms of all relevant clinical events. Comparison of the magnitude and direction of associations between baseline traditional and novel cardiovascular risk factors with incident and recurrent acute MI subtypes and acute non-ischemic myocardial injury events will be made.

CONCLUSIONS

This project will result in one of the first large prospective cardiovascular cohort with modern classification of acute MI subtypes, as well as a full accounting of non-ischemic myocardial injury events, with implications for numerous ongoing and future studies in MESA. By creating precise MI phenotypes, and defining their epidemiology, this project will allow for discovery of novel pathobiology-specific risk factors, allow for development of more accurate risk prediction, and suggest more targeted preventive strategies.

Blood Levels of Angiotensinogen and Hypertension in the Multi-Ethnic Study of Atherosclerosis (MESA)

BACKGROUND

Angiotensinogen is the proximal precursor of the angiotensin peptide hormones of the renin-angiotensin-aldosterone system (RAAS). Clinical trials are ongoing targeting angiotensinogen for the treatment of hypertension and heart failure. The epidemiology of angiotensinogen is not well defined, particularly its relationship to ethnicity, sex, and blood pressure (BP)/hypertension.

OBJECTIVES

The authors sought to determine the relationship of circulating angiotensinogen levels to ethnicity, sex, BP, incident hypertension, and prevalent hypertension in a modern sex-balanced ethnically diverse cohort.

METHODS

Plasma angiotensinogen levels were measured in 5,786 participants from the MESA (Multi-Ethnic Study of Atherosclerosis). Linear, logistic, and Cox proportional hazards models were utilized to examine the associations of angiotensinogen with BP, prevalent hypertension, and incident hypertension, respectively.

RESULTS

Angiotensinogen levels were significantly higher in females than males and differed across self-reported ethnicities with the ordering (from highest to lowest): White, Black, Hispanic, and Chinese adults. Higher levels were associated with higher BP and odds of prevalent hypertension, after adjusting for other risk factors. Equivalent relative differences in angiotensinogen were associated with greater differences in BP in males vs females. In males not taking RAAS-blocking medications, a standard deviation increment in log-angiotensinogen was associated with 2.61 mm Hg higher systolic BP (95% CI: 1.49-3.80), while in females the same increment in angiotensinogen was associated with 0.97 mm Hg higher systolic BP (95% CI: 0.30-1.65).

CONCLUSIONS

Significant differences in angiotensinogen levels are present between sexes and ethnicities. A positive association is present between levels and prevalent hypertension and BP, which differs between sexes.

Atherothrombotic factors and atherosclerotic cardiovascular events: the multi-ethnic study of atherosclerosis

AIMS

Traditional atherosclerotic cardiovascular disease (ASCVD) risk factors fail to address the full spectrum of the complex interplay of atherosclerotic and atherothrombotic factors integral to ASCVD events. This study sought to examine the association between atherothrombotic biomarkers and ASCVD events.

METHODS AND RESULTS

The association between atherothrombotic biomarkers and 877 ASCVD events with and without adjustment for traditional risk factors was evaluated via Cox proportional hazards models and factor analysis in 5789 Multi-Ethnic Study of Atherosclerosis participants over a median follow-up of 14.7 years. Factor analysis accounted for multidimensional relationship and shared variance among study biomarkers, which identified two new variables: a thrombotic factor (Factor 1), principally defined by shared variance in fibrinogen, plasmin-antiplasmin complex, factor VIII, D-dimer, and lipoprotein(a), and a fibrinolytic factor (Factor 2), principally defined by shared variance of plasminogen and oxidized phospholipids on plasminogen. In a model including both factors, the thrombotic factor was associated with the higher risk of ASCVD events [hazard ratio (HR) 1.57, 95% confidence interval (CI) 1.45, 1.70], while the fibrinolytic factor was associated with the lower risk of ASCVD events (HR 0.76, 95% CI 0.70, 0.82), with estimated ASCVD free survival highest for low atherothrombotic Factor 1 and high atherothrombotic Factor 2.

CONCLUSION

Two atherothrombotic factors, one representative of thrombotic propensity and the other representative of fibrinolytic propensity, were significantly and complementarily associated with incident ASCVD events, remained significantly associated with incident ASCVD after controlling for traditional risk factors, and have promise for identifying patients at high ASCVD event risk specifically due to their atherothrombotic profile.

Human Arylamine N-Acetyltransferase 1 (NAT1) Knockout in MDA-MB-231 Breast Cancer Cell Lines Leads to Transcription of NAT2

Many cancers, including breast cancer, have shown differential expression of human arylamine N-acetyltransferase 1 (NAT1). The exact effect this differential expression has on disease risk and progression remains unclear. While NAT1 is classically defined as a xenobiotic metabolizing enzyme, other functions and roles in endogenous metabolism have recently been described providing additional impetus for investigating the effects of varying levels of NAT1 on global gene expression. Our objective is to further evaluate the role of NAT1 in breast cancer by determining the effect of NAT1 overexpression, knockdown, and knockout on global gene expression in MDA-MB-231 cell lines. RNA-seq was utilized to interrogate differential gene expression (genes correlated with NAT1 activity) across three biological replicates of previously constructed and characterized MDA-MB-231 breast cancer cell lines expressing parental (Scrambled), increased (Up), decreased (Down, CRISPR 2–12), or knockout (CRISPR 2–19, CRISPR 5–50) levels of NAT1. 3,889 genes were significantly associated with the NAT1 N-acetylation activity of the cell lines (adjusted p ≤ 0.05); of those 3,889 genes, 1,756 were positively associated with NAT1 N-acetylation activity and 2,133 were negatively associated with NAT1 N-acetylation activity. An enrichment of genes involved in cell adhesion was observed. Additionally, human arylamine N-acetyltransferase 2 (NAT2) transcripts were observed in the complete NAT1 knockout cell lines (CRISPR 2–19 and CRISPR 5–50). This study provides further evidence that NAT1 functions as more than just a drug metabolizing enzyme given the observation that differences in NAT1 activity have significant impacts on global gene expression. Additionally, our data suggests the knockout of NAT1 results in transcription of its isozyme NAT2.

CRISPR/Cas9 knockout of human arylamine N-acetyltransferase 1 in MDA-MB-231 breast cancer cells suggests a role in cellular metabolism

Human arylamine N-acetyltransferase 1 (NAT1), present in all tissues, is classically described as a phase-II xenobiotic metabolizing enzyme but can also catalyze the hydrolysis of acetyl-Coenzyme A (acetyl-CoA) in the absence of an arylamine substrate using folate as a cofactor. NAT1 activity varies inter-individually and has been shown to be overexpressed in estrogen receptor-positive (ER+) breast cancers. NAT1 has also been implicated in breast cancer progression however the exact role of NAT1 remains unknown. The objective of this study was to evaluate the effect of varying levels of NAT1 N-acetylation activity in MDA-MB-231 breast cancer cells on global cellular metabolism and to probe for unknown endogenous NAT1 substrates. Global, untargeted metabolomics was conducted via ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) on MDA-MB-231 breast cancer cell lines constructed with siRNA and CRISPR/Cas9 technologies to vary only in NAT1 N-acetylation activity. Many metabolites were differentially abundant in NAT1-modified cell lines compared to the Scrambled parental cell line. N-acetylasparagine and N-acetylputrescine abundances were strongly positively correlated (r = 0.986 and r = 0.944, respectively) with NAT1 N-acetylation activity whereas saccharopine abundance was strongly inversely correlated (r = −0.876). Two of the most striking observations were a reduction in de novo pyrimidine biosynthesis and defective β-oxidation of fatty acids in the absence of NAT1. We have shown that NAT1 expression differentially affects cellular metabolism dependent on the level of expression. Our results support the hypothesis that NAT1 is not just a xenobiotic metabolizing enzyme and may have a role in endogenous cellular metabolism.

Flow cytometric evaluation of platelet-leukocyte conjugate stability over time: methodological implications of sample handling and processing

Platelet activation and subsequent aggregation is a vital component of atherothrombosis resulting in acute myocardial infarction. Therefore, quantifying platelet aggregation is a valuable measure for elucidating the pathogenesis of acute coronary syndromes (ACS). Circulating platelet-monocyte conjugates (PMC) as determined by flow cytometry (FCM) are an important measure of in vivo platelet aggregation. However, the influence of sample handling on FCM measurement of PMC is not well-studied. The changes in FCM measurement of PMC with variation in sample handling techniques were evaluated. The stability of PMC concentrations over time with changes in fixation and immunolabeling intervals was assessed. The effect of Time-to-Fix and Time-to-Stain on FCM PMC measurements was investigated in five healthy volunteers. Time-to-Fix (i.e., interval between phlebotomy and sample fixation) was performed at 3, 30, and 60 min. Time-to-Stain (i.e., time of fixed sample storage to staining) was performed at 1, 24, and 48 h. Increasing Time-to-Stain from 1 to 24 or 48 h resulted in lower PMC measures (p < 0.0001). A statistically significant difference in PMC measurement with increasing Time-to-Fix was not observed (p < 0.41). Postponement of sample staining has deleterious effects on the measurement of PMC via FCM. Delays in immunolabeling of fixed samples compromised measurement of PMC by 30% over the first 24 h. Staining/FCM should be completed within an hour of collection.

Knockout of human arylamine N-acetyltransferase 1 (NAT1) in MDA-MB-231 breast cancer cells leads to increased reserve capacity, maximum mitochondrial capacity, and glycolytic reserve capacity

Human arylamine N-acetyltransferase 1 (NAT1) is a phase II xenobiotic metabolizing enzyme found in almost all tissues. NAT1 can also hydrolyze acetyl-coenzyme A (acetyl-CoA) in the absence of an arylamine substrate. Expression of NAT1 varies between individuals and is elevated in several cancers including estrogen receptor positive (ER+) breast cancers. To date, however, the exact mechanism by which NAT1 expression affects mitochondrial bioenergetics in breast cancer cells has not been described. To further evaluate the role of NAT1 in energy metabolism MDA-MB-231 breast cancer cells with parental, increased, and knockout levels of NAT1 activity were compared for bioenergetics profile. Basal oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) were measured followed by programmed sequential injection of Oligomycin (ATP synthase inhibitor), FCCP (ETC uncoupler), Antimycin A (Complex III inhibitor), and Rotenone (Complex I inhibitor) to evaluate mitochondrial bioenergetics. Compared to the cell lines with parental NAT1 activity, NAT1 knockout MDA-MB-231 cell lines exhibited significant differences in bioenergetics profile, while those with increased NAT1 did not. Significant increases in reserve capacity, maximum mitochondrial capacity, and glycolytic reserve capacity were observed in NAT1 knockout MDA-MB-231 cell lines compared to those with parental and increased NAT1 activity. These data indicate that NAT1 knockout in MDA-MB-231 breast cancer cells may enhance adaptation to stress by increasing plasticity in response to energy demand.

Viral DNA integration and methylation of human papillomavirus type 16 in high-grade oral epithelial dysplasia and head and neck squamous cell carcinoma

This study evaluated the integration and methlyation of human papillomavirus type 16 (HPV16) in head and neck squamous cell carcinoma (HNSCC) and its oral precursor, high-grade oral epithelial dysplasia (hgOED). Archival samples of HPV16-positive hgOED (N = 19) and HNSCC (N = 15) were evaluated, along with three HNSCC (UMSCC-1, -47 and -104) and two cervical cancer (SiHa and CaSki) cell lines. HgOED cases were stratified into three groups with increasing degrees of cytologic changes (mitosis, karyorrhexis and apoptosis). The viral load was higher and the E2/E6 ratio lower (indicating a greater tendency toward viral integration) in group 3 than in groups 1 or 2 (p = 0.002, 0.03). Methylation was not observed in hgOED cases and occurred variably in only three HNSCC cases (26.67%, 60.0% and 93.3%). In HNSCC cell lines, lower E7 expression correlated with higher levels of methylation. HgOED with increased cytologic change, now termed HPV-associated oral epithelial dysplasia (HPV-OED), exhibited an increased viral load and a tendency toward DNA integration, suggesting a potentially increased risk for malignant transformation. More detailed characterization and clinical follow-up of HPV-OED patients is needed to determine whether HPV-OED is a true precursor to HPV-associated HNSCC and to clarify the involvement of HPV in HNSCC carcinogenesis.

Wisdom of artificial crowds feature selection in untargeted metabolomics: An application to the development of a blood-based diagnostic test for thrombotic myocardial infarction

INTRODUCTION

Heart disease remains a leading cause of global mortality. While acute myocardial infarction (colloquially: heart attack), has multiple proximate causes, proximate etiology cannot be determined by a blood-based diagnostic test. We enrolled a suitable patient cohort and conducted a non-targeted quantification of plasma metabolites by mass spectrometry for developing a test that can differentiate between thrombotic MI, non-thrombotic MI, and stable disease. A significant challenge in developing such a diagnostic test is solving the NP-hard problem of feature selection for constructing an optimal statistical classifier.

OBJECTIVE

We employed a Wisdom of Artificial Crowds (WoAC) strategy for solving the feature selection problem and evaluated the accuracy and parsimony of downstream classifiers in comparison with traditional feature selection techniques including the Lasso and selection using Random Forest variable importance criteria.

MATERIALS AND METHODS

Artificial Crowd Wisdom was generated via aggregation of the best solutions from independent and diverse genetic algorithm populations that were initialized with bootstrapping and a random subspaces constraint.

RESULTS/CONCLUSIONS

Strong evidence was observed that a statistical classifier utilizing WoAC feature selection can discriminate between human subjects presenting with thrombotic MI, non-thrombotic MI, and stable Coronary Artery Disease given abundances of selected plasma metabolites. Utilizing the abundances of twenty selected metabolites, a leave-one-out cross-validation estimated misclassification rate of 2.6% was observed. However, the WoAC feature selection strategy did not perform better than the Lasso over the current study.

Circulating Prolidase Activity in Patients with Myocardial Infarction

Background

Collagen is a major determinant of atherosclerotic plaque stability. Thus, identification of differences in enzymes that regulate collagen integrity could be useful for predicting susceptibility to atherothrombosis or for diagnosing plaque rupture. In this study, we sought to determine whether prolidase, the rate-limiting enzyme of collagen turnover, differs in human subjects with acute myocardial infarction (MI) versus those with stable coronary artery disease (CAD).

Methods

We measured serum prolidase activity in 15 patients with stable CAD and 49 patients with acute MI, of which a subset had clearly defined thrombotic MI (n = 22) or non-thrombotic MI (n = 12). Prolidase activity was compared across study time points (at cardiac catheterization, T0; 6 h after presentation, T6; and at a quiescent follow-up, Tf/u) in acute MI and stable CAD subjects. We performed subgroup analyses to evaluate prolidase activity in subjects presenting with acute thrombotic versus non-thrombotic MI.

Results

Although prolidase activity was lower at T0 and T6 versus the quiescent phase in acute MI and stable CAD subjects (p < 0.0001), it was not significantly different between acute MI and stable CAD subjects at any time point (T0, T6, and Tf/u) or between thrombotic and non-thrombotic MI groups. Preliminary data from stratified analyses of a small number of diabetic subjects (n = 8) suggested lower prolidase activity in diabetic acute MI subjects compared with non-diabetic acute MI subjects (p = 0.02).

Conclusion

Circulating prolidase is not significantly different between patients with acute MI and stable CAD or between patients with thrombotic and non-thrombotic MI. Further studies are required to determine if diabetes significantly affects prolidase activity and how this might relate to the risk of MI.

Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics

Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k-Nearest Neighbors (k-NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction, classifier performance (least to greatest error) was ranked as follows: SVM, Random Forest, Naïve Bayes, sPLS-DA, Neural Networks, PLS-DA and k-NN classifiers. When non-normal error distributions were introduced, the performance of PLS-DA and k-NN classifiers deteriorated further relative to the remaining techniques. Over the real datasets, a trend of better performance of SVM and Random Forest classifier performance was observed.

Abstract 344: Comparative Metabolomic Profiling of Thrombotic Myocardial Infarction Reveals a Metabolic Signature Distinct From Non-Thrombotic Myocardial Infarction and Stable Coronary Artery Disease in Human Participants

Background: Current non-invasive diagnostics for acute myocardial infarction (MI) identify myocardial necrosis rather than the primary cause and therapeutic target—plaque disruption and resultant thrombosis.

Aim: The aim of this study is to identify change specific to plaque disruption and pathological thrombosis.

Methods: We quantified 1,032 plasma metabolites by mass spectrometry in 11 thrombotic MI, 12 non-thrombotic MI and 15 stable CAD subjects at two acute phase [time of catheterization (T0), six hours (T6)] and one quiescent (>3 months follow-up) time points. A statistical classifier was constructed utilizing (T0) abundances of a parsimonious set of metabolites that demonstrated a significant change between quiescent phase and the acute phase that was distinct from any change seen in non-thrombotic MI or stable CAD subjects. Classifier performance as estimated by 10-fold cross-validation was suggestive of high sensitivity and specificity for differentiating thrombotic from non-thrombotic MI and stable CAD subjects.

Results: Nineteen metabolites (Table 1) with an intra-subject fold change from time of acute thrombotic MI presentation to the quiescent state were distinct from any change measured in both the non-thrombotic MI and stable CAD subjects undergoing cardiac catheterization over the same time course (false discovery rate <5%).

Conclusions: We have identified a candidate metabolic signature that differentiates acute thrombotic MI from quiescent state and from acute non-thrombotic MI and stable CAD. Further validation of these metabolites is warranted given their potential as diagnostic biomarkers and novel therapeutic targets for the prevention or treatment of acute MI.

Abstract 151: Parsimonious Model for the Detection of Acute Coronary Thrombus

Background: There is limited data to determine accuracy and precision of detecting acute coronary thrombus via angiography.

Objective: To build a parsimonious model for the prediction of acute coronary thrombus from four commonly used angiographic characteristics (spherical, ovoid, or irregular filling defect; abrupt vessel cutoff with persistence of contrast; intraluminal staining; any coronary filling defect).

Methods: Angiographic Core Laboratory (Baltimore, Maryland) evaluated angiograms of 80 acute MI / stable CAD subjects in blinded fashion. Outcome was defined as presence of thrombus by histological examination. Multivariable generalized linear modeling was conducted to determine best combinations of characteristics for discriminating between lesions with a histologically confirmed thrombus versus lesions without a histologically confirmed thrombus.

Results: A best-fit parsimonious model revealed that individual presence of abrupt vessel cutoff with persistence of contrast (O.R=16, P<0.0001) or any coronary filling defect (O.R=84, P<0.0001), or both in concurrence (O.R=105, P<0.0001) (Figure 1 and Table 1), was most significantly associated with the presence of coronary thrombus.

Conclusions: Modeling suggests that the presence of abrupt vessel cutoff with persistence of contrast or any filling defect, individually or in concurrence, is significantly associated with acute coronary thrombus, and therefore warrants validation in an independent cohort.

Identification of a plasma metabolomic signature of thrombotic myocardial infarction that is distinct from non-thrombotic myocardial infarction and stable coronary artery disease

Aims

Current non-invasive diagnostics for acute myocardial infarction (MI) identify myocardial necrosis rather than the primary cause and therapeutic target—plaque disruption and resultant thrombosis. The aim of this study was to identify changes specific to plaque disruption and pathological thrombosis that are distinct from acute myocardial necrosis.

Methods and results

We quantified 1,032 plasma metabolites by mass spectrometry in 11 thrombotic MI, 12 non-thrombotic MI, and 15 stable coronary artery disease (CAD) subjects at two acute phase (time of catheterization [T0], six hours [T6]) and one quiescent (>3 months follow-up) time points. A statistical classifier was constructed utilizing baseline (T0) abundances of a parsimonious set of 17 qualifying metabolites. Qualifying metabolites were those that demonstrated a significant change between the quiescent phase and the acute phase and that were distinct from any change seen in non-thrombotic MI or stable CAD subjects. Classifier performance as estimated by 10-fold cross-validation was suggestive of high sensitivity and specificity for differentiating thrombotic from non-thrombotic MI and stable CAD subjects at presentation.

Nineteen metabolites demonstrated an intra-subject change from time of acute thrombotic MI presentation to the quiescent state that was distinct from any change measured in both the non-thrombotic MI and stable CAD subjects undergoing cardiac catheterization over the same time course (false discovery rate <5%).

Conclusions

We have identified a candidate metabolic signature that differentiates acute thrombotic MI from quiescent state after MI, from acute non-thrombotic MI, and from stable CAD. Further validation of these metabolites is warranted given their potential as diagnostic biomarkers and novel therapeutic targets for the prevention or treatment of acute MI.

Systems characterization of differential plasma metabolome perturbations following thrombotic and non-thrombotic myocardial infarction

Myocardial infarction (MI) is an acute event characterized by myocardial necrosis. Thrombotic MI is caused by spontaneous atherosclerotic plaque disruption that results in a coronary thrombus; non-thrombotic MI occurs secondary to oxygen supply-demand mismatch. We sought to characterize the differential metabolic perturbations associated with these subtypes utilizing a systems approach. Subjects presenting with thrombotic MI, non-thrombotic MI and stable coronary artery disease (CAD) were included. Whole blood was collected at two acute time-points and at a time-point representing the quiescent stable disease state. Plasma metabolites were analyzed by untargeted UPLC-MS/MS and GC-MS. A weighted network was constructed, and modules were determined from the resulting topology. To determine perturbed modules, an enrichment analysis for metabolites that demonstrated between-group differences in temporal change across the disease state transition was then conducted.

BIOLOGICAL SIGNIFICANCE

We report evidence of metabolic perturbations of acute MI and determine perturbations specific to thrombotic MI. Specifically, a module characterized by elevated glucocorticoid steroid metabolites following acute MI showed greatest perturbation following thrombotic MI. Modules characterized by elevated pregnenolone metabolites, monoacylglycerols, and acylcarnitines were perturbed following acute MI. A module characterized by a decrease in plasma amino acids following thrombotic MI was differentially perturbed between MI subtypes.

Presence of multiple coronary angiographic characteristics for the diagnosis of acute coronary thrombus

BACKGROUND

Coronary angiography is frequently employed to aid in the diagnosis of acute coronary thrombosis, but there is limited data to support its efficacy. The aim of the study was to evaluate sensitivity and specificity of five commonly used angiographic characteristics for diagnosis of acute coronary thrombosis: Ambrose complex lesion morphology; spherical, ovoid, or irregular filling defect; abrupt vessel cutoff; intraluminal staining; and any coronary filling defect.

METHODS

Coronary angiography of 80 acute myocardial infarction or stable coronary artery disease subjects were assessed in blinded fashion, for the presence or absence of five angiographic characteristics. Only lesions of ≥ 10% stenosis were included in the analysis. Presence or absence of each angiographic characteristic was compared between lesions with or without the following study defined outcomes: 1) histologically confirmed thrombus, 2) highly probable thrombus, and 3) highly unlikely thrombus.

RESULTS

A total of 323 lesions were evaluated. All studied angiographic characteristics were associated with histologically confirmed and highly probable thrombotic lesions vs. lesions not meeting criteria for these outcomes (p < 0.03), except for complex Ambrose morphology which was not associated with any of the study outcomes (p > 0.05). Specificity for identifying histologically confirmed or highly probable thrombotic lesion was high (92-100%), especially for spherical, ovoid, or irregular filling defect (99-100%) and intraluminal staining (99%). Sensitivity for identification of histologically confirmed or highly probable thrombotic lesions was low for all tested angiographic characteristics (17-60%).

CONCLUSIONS

The presence of spherical, ovoid, or irregular filling defect or intraluminal staining was highly suggestive of coronary thrombus. However, none of the evaluated angiographic characteristics were useful for ruling out the presence of coronary thrombus. If confirmed in an independent cohort, these angiographic characteristic will be of significant value in confirming the diagnosis of acute coronary thrombosis.

Histologic variation in high grade oral epithelial dysplasia when associated with high-risk human papillomavirus

OBJECTIVES

Reported cytologic alterations associated with high-risk human papillomavirus (HR-HPV) in oral epithelial dysplasia (HPV-OED) need further characterization.

STUDY DESIGN

Archival cases of high-grade oral epithelial dysplasia (hgOED) (N = 38) were assigned a cytologic score (CS) based on the average number of mitotic, karyorrhectic, and apoptotic cells per high-power field. Three groups were then generated on the basis of increasing CS: Focal (group 1, N = 14), Intermediate (group 2, N = 12), and Diffuse (group 3, N = 12). Polymerase chain reaction-based HPV genotyping and p16 immunohistochemistry were performed.

RESULTS

HR-HPV was found significantly more in group 3 (83.3%) compared with groups 1 and 2 (group 1&2; 42.9% and 41.7%, respectively; P = .047). HPV16 predominated in HR-HPV-positive cases (90.5%). By location, the tongue or the floor of mouth was associated with all groups (P = .04). Increasing CS was associated with a slightly younger age (P = .04) and increased expression of p16 (P = .005). CS and p16 expression were not sensitive but were highly specific predictors for HR-HPV presence. Based on limited follow-up information, HPV-OED does not differ in clinical aggressiveness compared with conventional OED.

CONCLUSIONS

Increased CS in hgOED is strongly associated with HR-HPV (mostly HPV16) and p16 expression. CS and p16 expression are specific predictors of HR-HPV presence. Further molecular study and long-term follow-up of HPV-OED are needed.

Static micro-array isolation, dynamic time series classification, capture and enumeration of spiked breast cancer cells in blood: the nanotube-CTC chip

We demonstrate the rapid and label-free capture of breast cancer cells spiked in blood using nanotube-antibody micro-arrays. 76-element single wall carbon nanotube arrays were manufactured using photo-lithography, metal deposition, and etching techniques. Anti-epithelial cell adhesion molecule (anti-EpCAM), Anti-human epithelial growth factor receptor 2 (anti-Her2) and non-specific IgG antibodies were functionalized to the surface of the nanotube devices using 1-pyrene-butanoic acid succinimidyl ester. Following device functionalization, blood spiked with SKBR3, MCF7 and MCF10A cells (100/1000 cells per 5 μl per device, 170 elements totaling 0.85 ml of whole blood) were adsorbed on to the nanotube device arrays. Electrical signatures were recorded from each device to screen the samples for differences in interaction (specific or non-specific) between samples and devices. A zone classification scheme enabled the classification of all 170 elements in a single map. A kernel-based statistical classifier for the 'liquid biopsy' was developed to create a predictive model based on dynamic time warping series to classify device electrical signals that corresponded to plain blood (control) or SKBR3 spiked blood (case) on anti-Her2 functionalized devices with ∼90% sensitivity, and 90% specificity in capture of 1000 SKBR3 breast cancer cells in blood using anti-Her2 functionalized devices. Screened devices that gave positive electrical signatures were confirmed using optical/confocal microscopy to hold spiked cancer cells. Confocal microscopic analysis of devices that were classified to hold spiked blood based on their electrical signatures confirmed the presence of cancer cells through staining for DAPI (nuclei), cytokeratin (cancer cells) and CD45 (hematologic cells) with single cell sensitivity. We report 55%-100% cancer cell capture yield depending on the active device area for blood adsorption with mean of 62% (∼12 500 captured off 20 000 spiked cells in 0.1 ml blood) in this first nanotube-CTC chip study.

Untargeted polar metabolomics of transformed MDA-MB-231 breast cancer cells expressing varying levels of human arylamine N-acetyltransferase 1

INTRODUCTION

Human arylamine N-acetyltransferase 1 (NAT1) is a phase II xenobiotic metabolizing enzyme found in almost all tissues. Expression of NAT1 is elevated in several cancers including breast cancer. However, the exact mechanism by which NAT1 expression affects cancer risk and progression remains unclear.

OBJECTIVE

This study explored polar metabolome differences between MDA-MB-231 breast cancer cells expressing varying levels of NAT1 activity using an untargeted approach.

METHODS

Three MDA-MB-231 breast adenocarcinoma cell lines that stably express wild-type, increased, and decreased levels of human NAT1 were investigated for differences in polar metabolic profile using a comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) system.

RESULTS

Increased levels of human NAT1 in the transformed cell lines resulted in a statistically significant decreased abundance of the metabolite palmitoleic acid (q = 0.0006), when compared to normal and decreased levels of human NAT1. The fatty acid synthesis pathway utilizes acetyl coenzyme A (acetyl-CoA) in the first two reactions of the pathway and eventually leads to the synthesis of palmitoleic acid.

CONCLUSION

These data suggest a link between increased levels of NAT1 activity and decreased flux of acetyl-CoA through this portion of the fatty acid synthesis pathway.

Classification of biosensor time series using dynamic time warping: applications in screening cancer cells with characteristic biomarkers

The development of biosensors that produce time series data will facilitate improvements in biomedical diagnostics and in personalized medicine. The time series produced by these devices often contains characteristic features arising from biochemical interactions between the sample and the sensor. To use such characteristic features for determining sample class, similarity-based classifiers can be utilized. However, the construction of such classifiers is complicated by the variability in the time domains of such series that renders the traditional distance metrics such as Euclidean distance ineffective in distinguishing between biological variance and time domain variance. The dynamic time warping (DTW) algorithm is a sequence alignment algorithm that can be used to align two or more series to facilitate quantifying similarity. In this article, we evaluated the performance of DTW distance-based similarity classifiers for classifying time series that mimics electrical signals produced by nanotube biosensors. Simulation studies demonstrated the positive performance of such classifiers in discriminating between time series containing characteristic features that are obscured by noise in the intensity and time domains. We then applied a DTW distance-based k-nearest neighbors classifier to distinguish the presence/absence of mesenchymal biomarker in cancer cells in buffy coats in a blinded test. Using a train–test approach, we find that the classifier had high sensitivity (90.9%) and specificity (81.8%) in differentiating between EpCAM-positive MCF7 cells spiked in buffy coats and those in plain buffy coats.