Circulating Donor Lung-specific Exosome Profiles Enable Noninvasive Monitoring of Acute Rejection in a Rodent Orthotopic Lung Transplantation Model.

BACKGROUND: There is a critical need for development of biomarkers to noninvasively monitor for lung transplant rejection. We investigated the potential of circulating donor lung-specific exosome profiles for time-sensitive diagnosis of acute rejection in a rat orthotopic lung transplant model. METHODS: Left lungs from Wistar transgenic rats expressing human CD63-GFP, an exosome marker, were transplanted into fully MHC-mismatched Lewis recipients or syngeneic controls. Recipient blood was collected between 4 h and 10 d after transplantation, and plasma was processed for exosome isolation by size exclusion column chromatography and ultracentrifugation. Circulating donor exosomes were profiled using antihuman CD63 antibody quantum dot on the nanoparticle detector and via GFP trigger on the nanoparticle flow cytometer. RESULTS: In syngeneic controls, steady-state levels of circulating donor exosomes were detected at all posttransplant time points. Allogeneic grafts lost perfusion by day 8, consistent with acute rejection. Levels of circulating donor exosomes peaked on day 1, decreased significantly by day 2, and then reached baseline levels by day 3. Notably, decrease in peripheral donor exosome levels occurred before grafts had histological evidence of acute rejection. CONCLUSIONS: Circulating donor lung-specific exosome profiles enable an early detection of acute rejection before histologic manifestation of injury to the pulmonary allograft. As acute rejection episodes are a major risk factor for the development of chronic lung allograft dysfunction, this biomarker may provide a novel noninvasive diagnostic platform that can translate into earlier therapeutic intervention for lung transplant patients.

Tailor: Targeting heavy tails in flow cytometry data with fast, interpretable mixture modeling.

Automated clustering workflows are increasingly used for the analysis of high parameter flow cytometry data. This trend calls for algorithms which are able to quickly process tens of millions of data points, to compare results across subjects or time points, and to provide easily actionable interpretations of the results. To this end, we created Tailor, a model-based clustering algorithm specialized for flow cytometry data. Our approach leverages a phenotype-aware binning scheme to provide a coarse model of the data, which is then refined using a multivariate Gaussian mixture model. We benchmark Tailor using a simulation study and two flow cytometry data sets, and show that the results are robust to moderate departures from normality and inter-sample variation. Moreover, Tailor provides automated, non-overlapping annotations of its clusters, which facilitates interpretation of results and downstream analysis. Tailor is released as an R package, and the source code is publicly available at www.github.com/matei-ionita/Tailor.

Vascular Health Profile predicts cardiovascular outcomes in patients with diabetes.

BACKGROUND: We previously reported the development of a novel high dimensional cytomic assay, the Vascular Health Profile (VHP) based on measurements of angiogenic circulating hematopoietic stem and progenitor cells (CHSPCAng ) and extracellular vesicles (EVs), that discovered a unique signature, differentiating the vascular status of diabetics and normal healthy controls. Here, we present data from a 3-year follow-up to evaluate the power of the VHP to identify individuals at risk for cardiovascular (CV) events. METHODS: The original data were generated as previously described by measuring a broad panel of progenitor cells and EVs and profiled using cytometric fingerprinting. Subjects were classified into groups according to the occurrence of adjudicated CV events including myocardial infarction, stroke, major adverse cardiovascular events, revascularization, and irregular rhythm. Cross-validated Linear Discriminate Analysis (LDA) models were constructed and used to predict the occurrence of events, and were evaluated for predictive accuracy (AUC, area under the curve) using receiver operating characteristic (ROC) analysis. RESULTS: Over the period of this analysis, follow-up data was obtained on 87 subjects, with 32 events occurring overall, and only in the diabetic group. In all cases, the VHP added significant predictive power, in the form of ROC analysis, for all evaluated outcomes with the exception of irregular rhythm. CONCLUSIONS: The VHP, a relatively simple blood test, can provide sensitive and clinically relevant information on the vascular status of a patient that may be useful for a variety of applications including drug development, clinical risk assessment, and companion diagnostics. © 2015 International Clinical Cytometry Society.

Endothelial cell-, platelet-, and monocyte/macrophage-derived microparticles are elevated in psoriasis beyond cardiometabolic risk factors.

BACKGROUND: Psoriasis, especially when severe, is a risk factor for cardiometabolic disease beyond traditional risk factors. The mechanism of atherogenesis in psoriasis remains unknown. Cell membrane vesicles (ie, microparticles), released upon cell activation or apoptosis, have recently been associated with cardiometabolic disease and may play a pathogenic role. Microparticle levels, particularly from endothelial cells and platelets, are elevated in patients with cardiovascular disorders, metabolic syndrome, other inflammatory diseases, autoimmune conditions, and have been shown to be predictive of cardiovascular outcomes. METHODS AND RESULTS: Concentrations of microparticles with positive expression for any of 7 cell surface markers (Annexin V, CD3, CD31, CD41a, CD64, CD105, and CD144) were measured in blood samples from psoriasis patients (n=53) and control subjects without psoriasis (n=41). Platelet-free plasma was separated from whole blood by one-step centrifugation for microparticle analysis. Microparticles were fluorescently labeled and characterized by flow cytometry. Higher concentrations of CD105 (5.5/µL versus 2.5/µL, P<0.001), CD31 (31/µL versus 18/µL, P=0.002), CD41a (50/µL versus 22/µL, P<0.001), and CD64 (5.0/µL versus 4.1/µL, P=0.02) singly positive microparticles corresponding to endothelial cell-, platelet-, and monocyte/macrophage-derived microparticles, respectively, were found in psoriasis patients compared with controls. These differences persisted after adjustment for traditional cardiometabolic risk factors including body mass index. CONCLUSIONS: Increased microparticle concentrations, independent of cardiometabolic risk factors, in patients with psoriasis suggest that the presence of increased endothelial cell, platelet, and monocyte/macrophage activation with cell turnover may contribute to the heightened atherogenesis associated with psoriasis.

The diagnostic performance of the Mass Restricted (MR) score in the identification of microbial invasion of the amniotic cavity or intra-amniotic inflammation is not superior to amniotic fluid interleukin-6.

OBJECTIVE: Intra-amniotic infection/inflammation are major causes of spontaneous preterm labor and delivery. However, diagnosis of intra-amniotic infection is challenging because most are subclinical and amniotic fluid (AF) cultures take several days before results are available. Several tests have been proposed for the rapid diagnosis of microbial invasion of the amniotic cavity (MIAC) or intra-amniotic inflammation. The aim of this study was to examine the diagnostic performance of the AF Mass Restricted (MR) score in comparison with interleukin-6 (IL-6) and matrix metalloproteinase-8 (MMP-8) for the identification of MIAC or inflammation. METHODS: AF samples were collected from patients with singleton gestations and symptoms of preterm labor (n = 100). Intra-amniotic inflammation was defined as >100 white blood cells/mm(3) (WBCs) in AF; MIAC was defined as a positive AF culture. AF IL-6 and MMP-8 were determined using ELISA. The MR score was obtained using the Surface-Enhanced Laser Desorption Ionization Time of Flight (SELDI-TOF) mass spectrometry. Sensitivity and specificity were calculated and logistic regression models were fit to construct receiver-operating characteristic (ROC) curves for the identification of each outcome. The McNemar's test and paired sample non-parametric statistical techniques were used to test for differences in diagnostic performance metrics. RESULTS: (1) The prevalence of MIAC and intra-amniotic inflammation was 34% (34/100) and 40% (40/100), respectively; (2) there were no significant differences in sensitivity of the three tests under study (MR score, IL-6 or MMP-8) in the identification of either MIAC or intra-amniotic inflammation (using the following cutoffs: MR score >2, IL-6 >11.4 ng/mL, and MMP-8 >23 ng/mL); (3) there was no significant difference in the sensitivity among the three tests for the same outcomes when the false positive rate was fixed at 15%; (4) the specificity for IL-6 was not significantly different from that of the MR score in identifying either MIAC or intra-amniotic inflammation when using previously reported thresholds; and (5) there were no significant differences in the area under the ROC curve when comparing the MR score, IL-6 or MMP-8 in the identification of these outcomes. CONCLUSIONS: IL-6 and the MR score have equivalent diagnostic performance in the identification of MIAC or intra-amniotic inflammation. Selection from among these three tests (MR score, IL-6 and MMP-8) for diagnostic purposes should be based on factors such as availability, reproducibility, and cost. The MR score requires a protein chip and a SELDI-TOF instrument which are not widely available or considered "state of the art". In contrast, immunoassays for IL-6 can be performed in the majority of clinical laboratories.

Immunologic consequences of chemotherapy for ovarian cancer: impaired responses to the influenza vaccine.

OBJECTIVES: To examine the effect of chemotherapy for ovarian cancer on immunologic function and to define the effect on the serologic response to the influenza vaccine. METHODS: Under IRB approved protocols, patients with ovarian cancer were administered seasonal trivalent killed influenza vaccines. Peripheral blood was collected for immunologic assessments. Serum was analyzed for hemagglutination inhibition (HAI) antibody titers. Peripheral blood mononuclear cells were isolated to characterize T and B cell populations and function. RESULTS: Thirty-one patients were recruited: 13 in remission receiving a dendritic cell vaccine with or without a single dose of low-dose cyclophosphamide, 3 in remission not receiving treatment, and 15 undergoing standard therapy. Significant effects on T cell and B cell subset distributions were seen. Functional effects were also seen. Few patients were able to mount a 4-fold HAI antibody response. A 4-fold response was observed for H1N1 in 20%, for H3N2 in 26%, and for influenza B in 6%. Pre-existing exposure to influenza was predictive of responders. CONCLUSIONS: Despite CDC recommendations that patients undergoing chemotherapy receive influenza vaccine, there is little evidence to support its serologic effectiveness in this population. Patients with ovarian cancer are almost uniformly unable to mount a meaningful antibody response. These findings have serious implications for future resource allocation for both seasonal and novel pandemic influenza outbreak and understanding the immunologic deficits as a result of chemotherapy may improve patient care.

Endothelial microparticles: sophisticated vesicles modulating vascular function.

Endothelial microparticles (EMPs) belong to a family of extracellular vesicles that are dynamic, mobile, biological effectors capable of mediating vascular physiology and function. The release of EMPs can impart autocrine and paracrine effects on target cells through surface interaction, cellular fusion, and, possibly, the delivery of intra-vesicular cargo. A greater understanding of the formation, composition, and function of EMPs will broaden our understanding of endothelial communication and may expose new pathways amenable for therapeutic manipulation.

Personalized cytomic assessment of vascular health: Evaluation of the vascular health profile in diabetes mellitus.

BACKGROUND: An inexpensive and accurate blood test does not currently exist that can evaluate the cardiovascular health of a patient. This study evaluated a novel high dimensional flow cytometry approach in combination with cytometric fingerprinting (CF), to comprehensively enumerate differentially expressed subsets of pro-angiogenic circulating progenitor cells (CPCs), involved in the repair of vasculature, and microparticles (MPs), frequently involved in inflammation and thrombosis. CF enabled discovery of a unique pattern, involving both MPs and CPCs and generated a personalized signature of vascular health, the vascular health profile (VHP). METHODS: Levels of CPCs and MPs were measured with a broad panel of cell surface markers in a population with atherosclerosis and type 2 diabetes mellitus (DM) and age-similar Healthy controls (HC) using an unbiased computational approach, termed CF. RESULTS: Circulating hematopoietic stem and progenitor cell (CHSPCAng) levels were detected at significantly lower concentrations in DM (P < 0.001), whereas levels of seven phenotypically distinct MPs were present at significantly higher concentrations in DM patients and one MP subset was present at significantly lower concentration in DM patients. Collectively, the combination of CHSPC(Ang) and MP levels was more informative than any one measure alone. CONCLUSIONS: This work provides the basis for a personalized cytomic vascular health profile that may be useful for a variety of applications including drug development, clinical risk assessment and companion diagnostics.

Effect of darbepoetin alfa on endothelial progenitor cells and vascular reactivity in chronic kidney disease.

Endothelial progenitor cells (EPCs) are thought to be important for maintaining normal vascular function. We conducted a prospective study evaluating the effect of the erythropoiesis-stimulating agent darbepoetin alfa on EPCs and vascular function in patients with chronic kidney disease (CKD), with or without diabetes. Thirty subjects with CKD (20 subjects with type II diabetes mellitus and 10 without diabetes mellitus) received weekly subcutaneous administration of darbepoetin alfa for 4 weeks. EPCs were measured at baseline and 2 and 4 weeks after drug administration. Vascular function was measured with brachial ultrasound and cell activity was measured with a cell proliferation assay. Cells expressing CD133, CD34, CD146 and CD146/31 were significantly elevated (all p < 0.05), flow-mediated vasodilatation increased 2.1%, 95% CI: (0.4%, 3.8%) and colony-forming units increased twofold, 95% CI: (1.7, 2.3) after 4 weeks of treatment with darbepoetin alfa. Subjects with diabetes exhibited an increase in a subset of EPCs (CD133( +) and 34(+), p < 0.01 and p = 0.06, respectively), vasodilatation and proliferation. In conclusion, the administration of darbepoetin alfa for 4 weeks increased a subset of EPCs, improved endothelial function and increased cell proliferation, including those with diabetes, which is consistent with a favorable improvement in vascular health.

Circulating lymphocyte subsets in normal adults are variable and can be clustered into subgroups.

BACKGROUND: Flow cytometry is used to monitor lymphocyte subsets in both the clinical and research settings. An understanding of the degree of inter- and intrasubject variability of these populations is critical for data interpretation. METHODS: Peripheral blood lymphocytes of 18 healthy adults were analyzed on two separate occasions using a multicolor flow cytometric panel with B, T, and NK cell markers. Variability was calculated using the coefficient of variation and compared between and within individuals using agglomerative clustering. RESULTS: Each subject appears to have B and T cell subset profiles that are stable over the two time points, but differ from the profiles of other subjects. Thus, the range of measurements for a particular B or T cell subset is larger between subjects and narrower for an individual. In addition, the level of variability correlates inversely with the size of the lymphocyte subset. When lymphocyte profiles are analyzed by agglomerative clustering, replicate samples from the same individual tend to cluster. When single samples from different individuals are analyzed, individuals appear to cluster into different subgroups. CONCLUSIONS: Variability of lymphocyte subsets is usually greater between individuals than within a single individual and each person appears to have a characteristic profile of lymphocyte subsets. These results underscore the importance of obtaining a baseline value for each subject when investigating the impact of a treatment on lymphocyte subsets over time. These results also highlight the potential utility of cluster analysis as a tool for immune subset profiling and biomarker discovery. © 2011 International Clinical Cytometry Society.

Analysis of B cell subsets following pancreatic islet cell transplantation in a patient with type 1 diabetes by cytometric fingerprinting.

Manual gating of bivariate plots remains the most frequently used data analysis method in flow cytometry. However, gating is operator-dependent and cumbersome, particularly with the increasing complexity of modern multicolor immunophenotyping data. A method that can remove operator bias, enable systematic and thorough analysis of complex high-dimensional data, correlate temporal changes in different subsets and lead to biomarker discovery is needed. Here we apply such a method, called cytometric fingerprinting (CF), to data obtained on peripheral blood B cells from an adult patient with type-1 diabetes who underwent pancreatic islet transplantation. We establish that CF can be used to analyze longitudinal trends in immunophenotypic data, and show that results from CF are comparable to those obtained with traditional gating methods. Both methods reveal the appearance of transitional B cells and subsequent accumulation of more mature B cells following immunosuppression and transplantation. This pattern is consistent with a temporally ordered process of B cell auto-reconstitution. We also show the comparative efficiency of fingerprinting in recognizing relative changes in B cell subsets with respect to time, its ability to couple the data with statistical methods (agglomerative clustering) and its potential to define novel subsets.

Isobaric labeling and tandem mass spectrometry: a novel approach for profiling and quantifying proteins differentially expressed in amniotic fluid in preterm labor with and without intra-amniotic infection/inflammation.

OBJECTIVE: Examination of the amniotic fluid (AF) proteome has been previously attempted to identify useful biomarkers in predicting the outcome of preterm labor (PTL). Isobaric Tag for Relative and Absolute Quantitation (iTRAQ) labeling allows direct ratiometric comparison of relative abundance of identified protein species among multiplexed samples. The purpose of this study was to apply, for the first time, the combination of iTRAQ and tandem mass spectrometry to identify proteins differentially regulated in AF samples of women with spontaneous PTL and intact membranes with and without intra-amniotic infection/inflammation (IAI). METHODS: A cross-sectional study was designed and included AF samples from patients with spontaneous PTL and intact membranes in the following groups: (1) patients without IAI who delivered at term (n = 26); (2) patients who delivered preterm without IAI (n = 25); and (3) patients with IAI (n = 24). Proteomic profiling of AF samples was performed using a workflow involving tryptic digestion, iTRAQ labeling and multiplexing, strong cation exchange fractionation, and liquid chromatography tandem mass spectrometry. Twenty-five separate 4-plex samples were prepared and analyzed. RESULTS: Collectively, 123,011 MS(2) spectra were analyzed, and over 25,000 peptides were analyzed by database search (X!Tandem and Mascot), resulting in the identification of 309 unique high-confidence proteins. Analysis of differentially present iTRAQ reporter peaks revealed many proteins that have been previously reported to be associated with preterm delivery with IAI. Importantly, many novel proteins were found to be up-regulated in the AF of patients with PTL and IAI including leukocyte elastase precursor, Thymosin-like 3, and 14-3-3 protein isoforms. Moreover, we observed differential expression of proteins in AF of patients who delivered preterm in the absence of IAI in comparison with those with PTL who delivered at term including Mimecan precursor, latent-transforming growth factor beta-binding protein isoform 1L precursor, and Resistin. These findings have been confirmed for Resistin in an independent cohort of samples using ELISA. Gene ontology enrichment analysis was employed to reveal families of proteins participating in distinct biological processes. We identified enrichment for host defense, anti-apoptosis, metabolism/catabolism and cell and protein mobility, localization and targeting. CONCLUSIONS: (1) Proteomics with iTRAQ labeling is a profiling tool capable of revealing differential expression of proteins in AF; (2) We discovered 82 proteins differentially expressed in three clinical subgroups of premature labor, 67 which were heretofore unknown. Of particular importance is the identification of proteins differentially expressed in AF from women who delivered preterm in the absence of IAI. This is the first report of the positive identification of biomarkers in this subgroup of patients.

FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data.

A new software package called flowFP for the analysis of flow cytometry data is introduced. The package, which is tightly integrated with other Bioconductor software for analysis of flow cytometry, provides tools to transform raw flow cytometry data into a form suitable for direct input into conventional statistical analysis and empirical modeling software tools. The approach of flowFP is to generate a description of the multivariate probability distribution function of flow cytometry data in the form of a "fingerprint." As such, it is independent of a presumptive functional form for the distribution, in contrast with model-based methods such as Gaussian Mixture Modeling. FlowFP is computationally efficient and able to handle extremely large flow cytometry data sets of arbitrary dimensionality. Algorithms and software implementation of the package are described. Use of the software is exemplified with applications to data quality control and to the automated classification of Acute Myeloid Leukemia.

Resistin in amniotic fluid and its association with intra-amniotic infection and inflammation.

OBJECTIVE: Intra-amniotic infection/inflammation (IAI) is one of the most important mechanisms of disease in preterm birth. Resistin is an adipocytokine that has been linked to insulin resistance, diabetes, obesity and inflammation. The objective of this study was to determine if resistin is present in amniotic fluid (AF) and if its concentration changes with gestational age, in the presence of labour, and in IAI in patients with spontaneous preterm labour (PTL) and intact membranes, preterm prelabour rupture of membranes (PPROM) and clinical chorioamnionitis. STUDY DESIGN: This cross-sectional study included 648 patients in the following groups: (1) women in the mid-trimester of pregnancy (14-18 weeks) who underwent amniocentesis for genetic indications and delivered a normal neonate at term (n = 61); (2) normal pregnant women at term with (n = 49) and without (n = 50) spontaneous labour; (3) patients with an episode of PTL and intact membranes who were classified into: (a) PTL who delivered at term (n = 153); (b) PTL who delivered preterm (<37 weeks gestation) without IAI (n = 108); and (c) PTL with IAI (n = 84); (4) women with PPROM with (n = 47) and without (n = 44) IAI; and (5) patients with clinical chorioamnionitis at term with (n = 22) and without (n = 30) microbial invasion of the amniotic cavity. Resistin concentration in AF was determined by enzyme-linked immunoassay. Non-parametric statistics were used for analyses. RESULTS: (1) Resistin was detected in all AF samples; (2) the median AF resistin concentration at term was significantly higher than in the mid-trimester (23.6 ng/mL vs. 10 ng/mL; p < 0.001); (3) among patients with PTL, the median AF resistin concentration was significantly higher in patients with IAI than in those without IAI (144.9 ng/mL vs. 18.7 ng/mL; p < 0.001) and those with PTL and intact membranes who delivered at term (144.9 ng/mL vs. 16.3 ng/mL; p < 0.001); (4) patients with PPROM with IAI had a significantly higher median AF resistin concentration than those without IAI (132.6 ng/mL vs. 13 ng/mL; p < 0.001); (5) no significant differences were observed in the median AF resistin concentration between patients with spontaneous labour at term and those at term not in labour (28.7 ng/mL vs. 23.6 ng/mL; p = 0.07); and (6) AF resistin concentration > or =37 ng/mL (derived from a receiver-operating characteristic curve) had a sensitivity of 85.4% and a specificity of 94.3% for the diagnosis of intra-amniotic inflammation. CONCLUSIONS: Resistin is a physiologic constituent of the AF, and its concentrations in AF: (1) are significantly elevated in the presence of IAI; (2) increase with advancing gestation; and (3) do not change in the presence of spontaneous labour at term. We propose that resistin may play a role in the innate immune response against intra-amniotic infection.

Proteomic profiling of amniotic fluid in preterm labor using two-dimensional liquid separation and mass spectrometry.

OBJECTIVE: Simultaneous analysis of the protein composition of biological fluids is now possible. Such an approach can be used to identify biological markers of disease and to understand the pathophysiology of disorders that have eluded classification, diagnosis, and treatment. The purpose of this study was to analyze the differences in protein composition of the amniotic fluid of patients in preterm labor. STUDY DESIGN: Amniotic fluid was obtained by amniocentesis from three groups of women with preterm labor and intact membranes: (1) women without intra-amniotic infection/inflammation (IAI) who delivered at term, (2) women without IAI who delivered a preterm neonate, and (3) women with IAI. Intra-amniotic infection was defined as a positive amniotic fluid culture for microorganisms. Intra-amniotic inflammation was defined as an elevated amniotic fluid interleukin (IL)-6 (> or =2.3 ng/mL). Two-dimensional (2D) chromatography was used for analysis. The first dimension separated proteins by isoelectric point, while the second, by the degree of hydrophobicity. 2D protein maps were generated using different experimental conditions (reducing agents as well as protein concentration). The maps were used to discern subsets of isoelectric point/hydrophobicity containing differentially expressed proteins. Protein identification of differentially expressed fractions was conducted with mass spectrometry. Enzyme-linked immunosorbent assays (ELISA) as well as surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS)-based on-chip antibody capture immunoassays were also used for confirmation of a specific protein that was differentially expressed. RESULTS: (1) Amniotic fluid protein composition can be analyzed using a combination of 2D liquid chromatography and mass spectrometry for the identification of proteins differentially expressed in patients in preterm labor. (2) While total insulin-like growth factor-binding protein-1 (IGFBP-1) concentration did not change, IGFBP-1 fragments at about 13.5 kDa were present in patients with IAI. (3) Proteins that were over-expressed in group 1 included von Ebner gland protein precursor, IL-7 precursor, apolipoprotein A1, tropomyosin sk1 (TPMsk1) fragment, ribosomal protein S6 kinase alpha-3, and alpha-1-microglobulin/bikunin precursor (AMBP). (4) Proteins that were over-expressed in group 3 included fibrinopeptide B, transferrin, major histocompatibility complex (MHC) class 1 chain-related A antigen fragment, transcription elongation factor A, sex-determining region Y (SRY) box 5 protein, Down syndrome critical region 2 protein (DSCR2), and human peptide 8 (HP8). (5) One protein, retinol-binding protein, was over-expressed in women who delivered preterm, regardless of the presence of IAI. CONCLUSIONS: A combination of techniques involving 2D chromatography, mass spectrometry, and immunoassays allows identification of proteins that are differentially regulated in the amniotic fluid of patients with preterm labor. Specifically, the amount of the IGFBP-1 fragments at approximately 13.5 kDa was found to be increased in patients with IAI, while the amount of the intact form of IGFBP-1 was decreased.

Proteomic analysis of amniotic fluid to identify women with preterm labor and intra-amniotic inflammation/infection: the use of a novel computational method to analyze mass spectrometric profiling.

OBJECTIVE: Examination of the amniotic fluid proteome has been used to identify biomarkers for intra-amniotic inflammation as well as those that may be useful in predicting the outcome of preterm labor. The purpose of this study was to combine a novel computational method of pattern discovery with mass spectrometric proteomic profiling of amniotic fluid to discover biomarkers of intra-amniotic infection/inflammation (IAI). METHODS: This cross-sectional study included patients with spontaneous preterm labor and intact membranes who delivered at term (n = 59) and those who delivered preterm with IAI (n = 60). Proteomic profiling was performed using surface-enhanced laser desorption/ionization (SELDI) mass spectrometry. A proteomic profile was acquired through multiple simultaneous SELDI conditions, which were combined in a single proteomic 'fingerprint' using a novel computational approach. Classification of patients based on their associated surface-enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectra as belonging to either the class of individuals with preterm delivery with IAI or term delivery was accomplished by constructing an empirical model. The first phase in the construction of this empirical model involved the selection of adjustable parameters utilizing a training/testing subset of data. The second phase tested the generalization of the model by utilizing a blinded validation set of patients who were not employed in parameter selection. RESULTS: Gestational age at amniocentesis was not significantly different between the groups. Thirty-nine unique mass spectrometric peaks discriminated patients with preterm labor/delivery with IAI from those with preterm labor and term delivery. In the testing/training dataset, the classification accuracies (averaged over 100 random draws) were: 91.4% (40.2/44) for patients with preterm delivery with IAI, and 91.2% (40.1/44) for term delivery. The overall accuracy of the classification of patients in the validation dataset was 90.3% (28/31). CONCLUSIONS: Proteomic analysis of amniotic fluid allowed the identification of mass spectrometry features, which can distinguish patients with preterm labor with IAI from those with preterm labor without inflammation or infection who subsequently delivered at term.

Cytometric fingerprinting: quantitative characterization of multivariate distributions.

Recent technological advances in flow cytometry instrumentation provide the basis for high-dimensionality and high-throughput biological experimentation in a heterogeneous cellular context. Concomitant advances in scalable computational algorithms are necessary to better utilize the information that is contained in these high-complexity experiments. The development of such tools has the potential to expand the utility of flow cytometric analysis from a predominantly hypothesis-driven mode to one of discovery, or hypothesis-generating research. A new method of analysis of flow cytometric data called Cytometric Fingerprinting (CF) has been developed. CF captures the set of multivariate probability distribution functions corresponding to list-mode data and then "flattens" them into a computationally efficient fingerprint representation that facilitates quantitative comparisons of samples. An experimental and synthetic data were generated to act as reference sets for evaluating CF. Without the introduction of prior knowledge, CF was able to "discover" the location and concentration of spiked cells in ungated analyses over a concentration range covering four orders of magnitude, to a lower limit on the order of 10 spiked events in a background of 100,000 events. We describe a new method for quantitative analysis of list-mode cytometric data. CF includes a novel algorithm for space subdivision that improves estimation of the probability density function by dividing space into nonrectangular polytopes. Additionally it renders a multidimensional distribution in the form of a one-dimensional multiresolution hierarchical fingerprint that creates a computationally efficient representation of high dimensionality distribution functions. CF supports both the generation and testing of hypotheses, eliminates sources of operator bias, and provides an increased level of automation of data analysis.