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Background: Aldehyde dehydrogenase 2 (ALDH2) is critical for alcohol metabolism by converting acetaldehyde to acetic acid. In East Asian descendants, an inactive genetic variant in ALDH2, rs671, triggers an alcohol flushing response due to acetaldehyde accumulation. As alcohol flushing is not exclusive to those of East Asian descent, we questioned whether additional ALDH2 genetic variants can drive facial flushing and inefficient acetaldehyde metabolism using human testing and biochemical assays. Methods: After IRB approval, human subjects were given an alcohol challenge (0.25 g/kg) while quantifying acetaldehyde levels and the physiological response (heart rate and skin temperature) to alcohol. Further, by employing biochemical techniques including human purified ALDH2 proteins and transiently transfected NIH 3T3 cells, we characterized two newly identified ALDH2 variants for ALDH2 enzymatic activity, ALDH2 dimer/tetramer formation, and reactive oxygen species production after alcohol treatment. Results: Humans heterozygous for rs747096195 (R101G) or rs190764869 (R114W) had facial flushing and a 2-fold increase in acetaldehyde levels, while rs671 (E504K) had facial flushing and a 6-fold increase in acetaldehyde levels relative to wild type ALDH2 carriers. In vitro studies with recombinant R101G and R114W ALDH2 enzyme showed a reduced efficiency in acetaldehyde metabolism that is unique when compared to E504K or wild-type ALDH2. The effect is caused by a lack of functional dimer/tetramer formation for R101G and decreased Vmax for both R101G and R114W. Transiently transfected NIH-3T3 cells with R101G and R114W also had a reduced enzymatic activity by ~ 50% relative to transfected wild-type ALDH2 and when subjected to alcohol, the R101G and R114W variants had a 2-3-fold increase in reactive oxygen species formation with respect to wild type ALDH2. Conclusions: We identified two additional ALDH2 variants in humans causing facial flushing and acetaldehyde accumulation after alcohol consumption. As alcohol use is associated with a several-fold higher risk for esophageal cancer for the E504K variant, the methodology developed here to characterize ALDH2 genetic variant response to alcohol can lead the way precision medicine strategies to further understand the interplay of alcohol consumption, ALDH2 genetics, and cancer. [ABSTRACT FROM AUTHOR]

Understanding the role of stress in pregnancy and its consequences is important, particularly given documented associations between maternal stress and preterm birth and other pathological outcomes. Physical and psychological stressors can elicit the same biological responses, known as biological strain. Chronic stressors, like poverty and racism (race-based discriminatory treatment), may create a legacy or trajectory of biological strain that no amount of coping can relieve in the absence of larger-scale socio-behavioral or societal changes. An integrative approach that takes into consideration simultaneously social and biological determinants of stress may provide the best insights into the risk of preterm birth. The most successful computational approaches and the most predictive machine-learning models are likely to be those that combine information about the stressors and the biological strain (for example, as measured by different omics) experienced during pregnancy. [ABSTRACT FROM AUTHOR]

Preterm birth (PTB) is the leading cause of infant mortality globally. Research has focused on developing predictive models for PTB without prioritizing cost-effective interventions. Physical activity and sleep present unique opportunities for interventions in low- and middle-income populations (LMICs). However, objective measurement of physical activity and sleep remains challenging and self-reported metrics suffer from low-resolution and accuracy. In this study, we use physical activity data collected using a wearable device comprising over 181,944 h of data across N = 1083 patients. Using a new state-of-the art deep learning time-series classification architecture, we develop a 'clock' of healthy dynamics during pregnancy by using gestational age (GA) as a surrogate for progression of pregnancy. We also develop novel interpretability algorithms that integrate unsupervised clustering, model error analysis, feature attribution, and automated actigraphy analysis, allowing for model interpretation with respect to sleep, activity, and clinical variables. Our model performs significantly better than 7 other machine learning and AI methods for modeling the progression of pregnancy. We found that deviations from a normal 'clock' of physical activity and sleep changes during pregnancy are strongly associated with pregnancy outcomes. When our model underestimates GA, there are 0.52 fewer preterm births than expected (P = 1.01e − 67, permutation test) and when our model overestimates GA, there are 1.44 times (P = 2.82e − 39, permutation test) more preterm births than expected. Model error is negatively correlated with interdaily stability (P = 0.043, Spearman's), indicating that our model assigns a more advanced GA when an individual's daily rhythms are less precise. Supporting this, our model attributes higher importance to sleep periods in predicting higher-than-actual GA, relative to lower-than-actual GA (P = 1.01e − 21, Mann-Whitney U). Combining prediction and interpretability allows us to signal when activity behaviors alter the likelihood of preterm birth and advocates for the development of clinical decision support through passive monitoring and exercise habit and sleep recommendations, which can be easily implemented in LMICs. [ABSTRACT FROM AUTHOR]

Technologies for single‐cell profiling of the immune system have enabled researchers to extract rich interconnected networks of cellular abundance, phenotypical and functional cellular parameters. These studies can power machine learning approaches to understand the role of the immune system in various diseases. However, the performance of these approaches and the generalizability of the findings have been hindered by limited cohort sizes in translational studies, partially due to logistical demands and costs associated with longitudinal data collection in sufficiently large patient cohorts. An evolving challenge is the requirement for ever‐increasing cohort sizes as the dimensionality of datasets grows. We propose a deep learning model derived from a novel pipeline of optimal temporal cell matching and overcomplete autoencoders that uses data from a small subset of patients to learn to forecast an entire patient's immune response in a high dimensional space from one timepoint to another. In our analysis of 1.08 million cells from patients pre‐ and post‐surgical intervention, we demonstrate that the generated patient‐specific data are qualitatively and quantitatively similar to real patient data by demonstrating fidelity, diversity, and usefulness. [ABSTRACT FROM AUTHOR]

Objectives The aim of the study was to: (1) Identify (early in pregnancy) psychosocial and stress-related factors that predict risk of spontaneous preterm birth (PTB, gestational age <37 weeks); (2) Investigate whether "protective" factors (e.g., happiness/social support) decrease risk; (3) Use the Dhabhar Quick-Assessment Questionnaire for Stress and Psychosocial Factors (DQAQ-SPF) to rapidly quantify harmful or protective factors that predict increased or decreased risk respectively, of PTB. Study Design This is a prospective cohort study. Relative risk (RR) analyses investigated association between individual factors and PTB. Machine learning-based interdependency analysis (IDPA) identified factor clusters, strength, and direction of association with PTB. A nonlinear model based on support vector machines was built for predicting PTB and identifying factors that most strongly predicted PTB. Results Higher levels of deleterious factors were associated with increased RR for PTB: General anxiety (RR = 8.9; 95% confidence interval [CI] = 2.0,39.6), pain (RR = 5.7; CI = 1.7,17.0); tiredness/fatigue (RR = 3.7; CI = 1.09,13.5); perceived risk of birth complications (RR = 4; CI = 1.6,10.01); self-rated health current (RR = 2.6; CI = 1.0,6.7) and previous 3 years (RR = 2.9; CI = 1.1,7.7); and divorce (RR = 2.9; CI = 1.1,7.8). Lower levels of protective factors were also associated with increased RR for PTB: low happiness (RR = 9.1; CI = 1.25,71.5); low support from parents/siblings (RR = 3.5; CI = 0.9,12.9), and father-of-baby (RR = 3; CI = 1.1,9.9). These factors were also components of the clusters identified by the IDPA: perceived risk of birth complications (p < 0.05 after FDR correction), and general anxiety, happiness, tiredness/fatigue, self-rated health, social support, pain, and sleep (p < 0.05 without FDR correction). Supervised analysis of all factors, subject to cross-validation, produced a model highly predictive of PTB (AUROC or area under the receiver operating characteristic = 0.73). Model reduction through forward selection revealed that even a small set of factors (including those identified by RR and IDPA) predicted PTB. Conclusion These findings represent an important step toward identifying key factors, which can be assessed rapidly before/after conception, to predict risk of PTB, and perhaps other adverse pregnancy outcomes. Quantifying these factors, before, or early in pregnancy, could identify women at risk of delivering preterm, pinpoint mechanisms/targets for intervention, and facilitate the development of interventions to prevent PTB. Key Points Newly designed questionnaire used for rapid quantification of stress and psychosocial factors early during pregnancy. Deleterious factors predict increased preterm birth (PTB) risk. Protective factors predict decreased PTB risk. [ABSTRACT FROM AUTHOR]

Approximately 1 in 4 pregnant women in the United States undergo labor induction. The onset and establishment of labor, particularly induced labor, is a complex and dynamic process influenced by multiple endocrine, inflammatory, and mechanical factors as well as obstetric and pharmacological interventions. The duration from labor induction to the onset of active labor remains unpredictable. Moreover, prolonged labor is associated with severe complications for the mother and her offspring, most importantly chorioamnionitis, uterine atony, and postpartum hemorrhage. While maternal immune system adaptations that are critical for the maintenance of a healthy pregnancy have been previously characterized, the role of the immune system during the establishment of labor is poorly understood. Understanding maternal immune adaptations during labor initiation can have important ramifications for predicting successful labor induction and labor complications in both induced and spontaneous types of labor. The aim of this study was to characterize labor-associated maternal immune system dynamics from labor induction to the start of active labor. Serial blood samples from fifteen participants were collected immediately prior to labor induction (baseline) and during the latent phase until the start of active labor. Using high-dimensional mass cytometry, a total of 1,059 single-cell immune features were extracted from each sample. A multivariate machine-learning method was employed to characterize the dynamic changes of the maternal immune system after labor induction until the establishment of active labor. A cross-validated linear sparse regression model (least absolute shrinkage and selection operator, LASSO) predicted the minutes since induction of labor with high accuracy (R = 0.86, p = 6.7e-15, RMSE = 277 min). Immune features most informative for the model included STAT5 signaling in central memory CD8+ T cells and pro-inflammatory STAT3 signaling responses across multiple adaptive and innate immune cell subsets. Our study reports a peripheral immune signature of labor induction, and provides important insights into biological mechanisms that may ultimately predict labor induction success as well as complications, thereby facilitating clinical decision-making to improve maternal and fetal well-being. [ABSTRACT FROM AUTHOR]

Although most causes of death and morbidity in premature infants are related to immune maladaptation, the premature immune system remains poorly understood. We provide a comprehensive single-cell depiction of the neonatal immune system at birth across the spectrum of viable gestational age (GA), ranging from 25 weeks to term. A mass cytometry immunoassay interrogated all major immune cell subsets, including signaling activity and responsiveness to stimulation. An elastic net model described the relationship between GA and immunome (R=0.85, p=8.75e-14), and unsupervised clustering highlighted previously unrecognized GA-dependent immune dynamics, including decreasing basal MAP-kinase/NFκB signaling in antigen presenting cells; increasing responsiveness of cytotoxic lymphocytes to interferon-α; and decreasing frequency of regulatory and invariant T cells, including NKT-like cells and CD8+CD161+ T cells. Knowledge gained from the analysis of the neonatal immune landscape across GA provides a mechanistic framework to understand the unique susceptibility of preterm infants to both hyper-inflammatory diseases and infections. [ABSTRACT FROM AUTHOR]

Preterm birth is the leading cause of mortality in children under the age of five worldwide. Despite major efforts, we still lack the ability to accurately predict and effectively prevent preterm birth. While multiple factors contribute to preterm labor, dysregulations of immunological adaptations required for the maintenance of a healthy pregnancy is at its pathophysiological core. Consequently, a precise understanding of these chronologically paced immune adaptations and of the biological pacemakers that synchronize the pregnancy "immune clock" is a critical first step towards identifying deviations that are hallmarks of peterm birth. Here, we will review key elements of the fetal, placental, and maternal pacemakers that program the immune clock of pregnancy. We will then emphasize multiomic studies that enable a more integrated view of pregnancy-related immune adaptations. Such multiomic assessments can strengthen the biological plausibility of immunological findings and increase the power of biological signatures predictive of preterm birth [ABSTRACT FROM AUTHOR]

Many diseases display unequal prevalence between sexes. The sex-specific immune response to both injury and persistent pain remains underexplored and would inform treatment paradigms. We utilized high-dimensional mass cytometry to perform a comprehensive analysis of phenotypic and functional immune system differences between male and female mice after orthopedic injury. Multivariate modeling of innate and adaptive immune cell responses after injury using an elastic net algorithm, a regularized regression method, revealed sex-specific divergence at 12 h and 7 days after injury with a stronger immune response to injury in females. At 12 h, females upregulated STAT3 signaling in neutrophils but downregulated STAT1 and STAT6 signals in T regulatory cells, suggesting a lack of engagement of immune suppression pathways by females. Furthermore, at 7 days females upregulated MAPK pathways (p38, ERK, NFkB) in CD4T memory cells, setting up a possible heightened immune memory of painful injury. Taken together, our findings provide the first comprehensive and functional analysis of sex-differences in the immune response to painful injury. [ABSTRACT FROM AUTHOR]

Glucocorticoids (GC) are a controversial yet commonly used intervention in the clinical management of acute inflammatory conditions, including sepsis or traumatic injury. In the context of major trauma such as surgery, concerns have been raised regarding adverse effects from GC, thereby necessitating a better understanding of how GCs modulate the immune response. Here we report the results of a randomized controlled trial (NCT02542592) in which we employ a high-dimensional mass cytometry approach to characterize innate and adaptive cell signaling dynamics after a major surgery (primary outcome) in patients treated with placebo or methylprednisolone (MP). A robust, unsupervised bootstrap clustering of immune cell subsets coupled with random forest analysis shows profound (AUC = 0.92, p-value = 3.16E-8) MP-induced alterations of immune cell signaling trajectories, particularly in the adaptive compartments. By contrast, key innate signaling responses previously associated with pain and functional recovery after surgery, including STAT3 and CREB phosphorylation, are not affected by MP. These results imply cell-specific and pathway-specific effects of GCs, and also prompt future studies to examine GCs' effects on clinical outcomes likely dependent on functional adaptive immune responses. Glucocorticoids (GC) are commonly used to suppress undesirable inflammatory responses. Here the authors show, using hi-dimensional flow cytometry data, that GC treatment following major surgeries alters adaptive immunity without significant modulation of innate immune responses or pain/functional impairment. [ABSTRACT FROM AUTHOR]

High‐dimensional flow cytometry has matured to a level that enables deep phenotyping of cellular systems at a clinical scale. The resulting high‐content data sets allow characterizing the human immune system at unprecedented single cell resolution. However, the results are highly dependent on sample preparation and measurements might drift over time. While various controls exist for assessment and improvement of data quality in a single sample, the challenges of cross‐sample normalization attempts have been limited to aligning marker distributions across subjects. These approaches, inspired by bulk genomics and proteomics assays, ignore the single‐cell nature of the data and risk the removal of biologically relevant signals. This work proposes CytoNorm, a normalization algorithm to ensure internal consistency between clinical samples based on shared controls across various study batches. Data from the shared controls is used to learn the appropriate transformations for each batch (e.g., each analysis day). Importantly, some sources of technical variation are strongly influenced by the amount of protein expressed on specific cell types, requiring several population‐specific transformations to normalize cells from a heterogeneous sample. To address this, our approach first identifies the overall cellular distribution using a clustering step, and calculates subset‐specific transformations on the control samples by computing their quantile distributions and aligning them with splines. These transformations are then applied to all other clinical samples in the batch to remove the batch‐specific variations. We evaluated the algorithm on a customized data set with two shared controls across batches. One control sample was used for calculation of the normalization transformations and the second control was used as a blinded test set and evaluated with Earth Mover's distance. Additional results are provided using two real‐world clinical data sets. Overall, our method compared favorably to standard normalization procedures. The algorithm is implemented in the R package "CytoNorm" and available via the following link: www.github.com/saeyslab/CytoNorm © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry. [ABSTRACT FROM AUTHOR]

Background: Placental protein expression plays a crucial role during pregnancy. We hypothesized that: (1) circulating levels of pregnancy-associated, placenta-related proteins throughout gestation reflect the temporal progression of the uncomplicated, full-term pregnancy, and can effectively estimate gestational ages (GAs); and (2) preeclampsia (PE) is associated with disruptions in these protein levels early in gestation; and can identify impending PE. We also compared gestational profiles of proteins in the human and mouse, using pregnant heme oxygenase-1 (HO-1) heterozygote (Het) mice, a mouse model reflecting PE-like symptoms. Methods: Serum levels of placenta-related proteins–leptin (LEP), chorionic somatomammotropin hormone like 1 (CSHL1), elabela (ELA), activin A, soluble fms-like tyrosine kinase 1 (sFlt-1), and placental growth factor (PlGF)–were quantified by ELISA in blood serially collected throughout human pregnancies (20 normal subjects with 66 samples, and 20 subjects who developed PE with 61 samples). Multivariate analysis was performed to estimate the GA in normal pregnancy. Mean-squared errors of GA estimations were used to identify impending PE. The human protein profiles were then compared with those in the pregnant HO-1 Het mice. Results: An elastic net-based gestational dating model was developed (R2 = 0.76) and validated (R2 = 0.61) using serum levels of the 6 proteins measured at various GAs from women with normal uncomplicated pregnancies. In women who developed PE, the model was not (R2 = -0.17) associated with GA. Deviations from the model estimations were observed in women who developed PE (P = 0.01). The model developed with 5 proteins (ELA excluded) performed similarly from sera from normal human (R2 = 0.68) and WT mouse (R2 = 0.85) pregnancies. Disruptions of this model were observed in both human PE-associated (R2 = 0.27) and mouse HO-1 Het (R2 = 0.30) pregnancies. LEP outperformed sFlt-1 and PlGF in differentiating impending PE at early human and late mouse GAs. Conclusions: Serum placenta-related protein profiles are temporally regulated throughout normal pregnancies and significantly disrupted in women who develop PE. LEP changes earlier than the well-established biomarkers (sFlt-1 and PlGF). There may be evidence of a causative action of HO-1 deficiency in LEP upregulation in a PE-like murine model. [ABSTRACT FROM AUTHOR]

Stroke is a leading cause of cognitive impairment and dementia, but the mechanisms that underlie post-stroke cognitive decline are not well understood. Stroke produces profound local and systemic immune responses that engage all major innate and adaptive immune compartments. However, whether the systemic immune response to stroke contributes to long-term disability remains ill-defined. We used a single-cell mass cytometry approach to comprehensively and functionally characterize the systemic immune response to stroke in longitudinal blood samples from 24 patients over the course of 1 year and correlated the immune response with changes in cognitive functioning between 90 and 365 days post-stroke. Using elastic net regularized regression modelling, we identified key elements of a robust and prolonged systemic immune response to ischaemic stroke that occurs in three phases: an acute phase (Day 2) characterized by increased signal transducer and activator of transcription 3 (STAT3) signalling responses in innate immune cell types, an intermediate phase (Day 5) characterized by increased cAMP response element-binding protein (CREB) signalling responses in adaptive immune cell types, and a late phase (Day 90) by persistent elevation of neutrophils, and immunoglobulin M+ (IgM+) B cells. By Day 365 there was no detectable difference between these samples and those from an age- and gender-matched patient cohort without stroke. When regressed against the change in the Montreal Cognitive Assessment scores between Days 90 and 365 after stroke, the acute inflammatory phase Elastic Net model correlated with post-stroke cognitive trajectories (r = -0.692, Bonferroni-corrected P = 0.039). The results demonstrate the utility of a deep immune profiling approach with mass cytometry for the identification of clinically relevant immune correlates of long-term cognitive trajectories. [ABSTRACT FROM AUTHOR]

Motivation Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia. Results We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified. Availability and implementation Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Ageing drives changes in neuronal and cognitive function, the decline of which is a major feature of many neurological disorders. The hippocampus, a brain region subserving roles of spatial and episodic memory and learning, is sensitive to the detrimental effects of ageing at morphological and molecular levels. With advancing age, synapses in various hippocampal subfields exhibit impaired long-term potentiation, an electrophysiological correlate of learning and memory. At the molecular level, immediate early genes are among the synaptic plasticity genes that are both induced by long-term potentiation and downregulated in the aged brain. In addition to revitalizing other aged tissues, exposure to factors in young blood counteracts age-related changes in these central nervous system parameters, although the identities of specific cognition-promoting factors or whether such activity exists in human plasma remains unknown. We hypothesized that plasma of an early developmental stage, namely umbilical cord plasma, provides a reservoir of such plasticity-promoting proteins. Here we show that human cord plasma treatment revitalizes the hippocampus and improves cognitive function in aged mice. Tissue inhibitor of metalloproteinases 2 (TIMP2), a blood-borne factor enriched in human cord plasma, young mouse plasma, and young mouse hippocampi, appears in the brain after systemic administration and increases synaptic plasticity and hippocampal-dependent cognition in aged mice. Depletion experiments in aged mice revealed TIMP2 to be necessary for the cognitive benefits conferred by cord plasma. We find that systemic pools of TIMP2 are necessary for spatial memory in young mice, while treatment of brain slices with TIMP2 antibody prevents long-term potentiation, arguing for previously unknown roles for TIMP2 in normal hippocampal function. Our findings reveal that human cord plasma contains plasticity-enhancing proteins of high translational value for targeting ageing- or disease-associated hippocampal dysfunction. [ABSTRACT FROM AUTHOR]

Single-cell technologies have immense potential to shed light on molecular and biological processes that drive human diseases. Mass cytometry (or Cytometry by Time Of Flight mass spectrometry, CyTOF) has already been employed in clinical studies to comprehensively survey patients' circulating immune system. As interest in the 'bedside' application of mass cytometry is growing, the delineation of relevant methodological issues is called for. This report uses a newly generated dataset to discuss important methodological considerations when mass cytometry is implemented in a clinical study. Specifically, the use of whole blood samples versus peripheral blood mononuclear cells (PBMCs), design of mass-tagged antibody panels, technical and analytical implications of sample barcoding, and application of traditional and unsupervised approaches to analyze high-dimensional mass cytometry datasets are discussed. A mass cytometry assay was implemented in a cross-sectional study of 19 women with a history of term or preterm birth to determine whether immune traits in peripheral blood differentiate the two groups in the absence of pregnancy. Twenty-seven phenotypic and 11 intracellular markers were simultaneously analyzed in whole blood samples stimulated with lipopolysaccharide (LPS at 0, 0.1, 1, 10, and 100 ng mL−1) to examine dose-dependent signaling responses within the toll-like receptor 4 (TLR4) pathway. Complementary analyses, grounded in traditional or unsupervised gating strategies of immune cell subsets, indicated that the prpS6 and pMAPKAPK2 responses in classical monocytes are accentuated in women with a history of preterm birth (FDR<1%). The results suggest that women predisposed to preterm birth may be prone to mount an exacerbated TLR4 response during the course of pregnancy. This important hypothesis-generating finding points to the power of single-cell mass cytometry to detect biologically important differences in a relatively small patient cohort. © 2015 International Society for Advancement of Cytometry [ABSTRACT FROM AUTHOR]

Arterial blood sampling is necessary when drugs such as the fast-acting opioid analgesic remifentanil exhibit relevant differences between arterial and venous blood concentrations. Arterial cannulation is generally considered to be clinically safe and has thus become a standard procedure in pharmacokinetic-pharmacodynamic assessments. However, rare cases of arterial occlusions have to be considered in risk-benefit assessments of arterial sampling in pharmacokinetic studies, especially when including healthy volunteers. In an actual case, arterial occlusion requiring surgical repair was caused by a factor V Leiden thrombophilia associated genetic variant F5 1691G>A (rs6025) and aggravated by a hypoplastic radial artery. Neither risk factor had been identified prior to enrolment by routine laboratory tests such as the prothrombin time (international normalized ratio), partial thromboplastin time and the clinical Allen's test of arterial function. Re-assessment of the necessity of arterial sampling showed that none of the potential alternatives, target concentrations of computerized infusions or venous concentrations during non-steady-state and steady-state conditions could provide the arterial concentrations. Relying on venous concentrations may result in erroneous pharmacodynamic parameters. Accurate pharmacokinetic-pharmacodynamic studies relying on precisely measured blood concentrations require serial sampling techniques during both steady-state and non-steady-state conditions. However, as illustrated by the presented case, incidents involving the generally safe procedure of arterial sampling are possible, although rare. To further minimize the risks, screening of subjects for prothrombotic risks and careful assessment of the suitability of the artery should be considered in pharmacokinetic studies requiring arterial cannulation. [ABSTRACT FROM AUTHOR]

The study aim was to address the need for objective markers of pain-modifying interventions by testing the hypothesis that selective gait measures of knee joint loading can distinguish differences between non-steroidal anti-inflammatory (NSAID), analgesic treatment (opioid-receptor agonist), and placebo in patients medial knee osteoarthritis (OA). A randomized, single-blind washout, double-blind treatment, double-dummy cross-over trial using three treatment arms placebo, opioid (Oxycodone), and NSAID (Celecoxib) in medial compartment knee OA patients. Six patients with Kellgren-Lawrence radiographic severity grades of 2 or 3 completed six testing sessions (gait and pain assessment) at 2-week intervals. A significant increase was found in the knee total reaction moment and vertical ground reaction force (GRF) for Celecoxib compared to placebo ( p = 0.005, p = 0.003), but not for Oxycodone compared to placebo ( p = 0.20, p = 0.27) treatments. Walking speed was significantly higher for the Celecoxib and Oxycodone compared to placebo treatment ( p = 0.041 and p = 0.031, respectively). Self-reported function (WOMAC scores) was not different among treatments ( p > 0.05). The changes in total reaction moments and GRFs for only the NSAID suggest that greater increases in joint loading occurs when joint inflammation is treated in addition to pain. The total knee reaction moment, representing the magnitude of the extrinsic moment, appears to be a sensitive marker, more so than self-reported metrics, for evaluating knee OA treatment effects. © 2011 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 30:1118-1124, 2012 [ABSTRACT FROM AUTHOR]

Identifying human genes relevant for the processing of pain requires difficult-to-conduct and expensive large-scale clinical trials. Here, we examine a novel integrative paradigm for data-driven discovery of pain gene candidates, taking advantage of the vast amount of existing disease-related clinical literature and gene expression microarray data stored in large international repositories. First, thousands of diseases were ranked according to a disease-specific pain index (DSPI), derived from Medical Subject Heading (MESH) annotations in MEDLINE. Second, gene expression profiles of 121 of these human diseases were obtained from public sources. Third, genes with expression variation significantly correlated with DSPI across diseases were selected as candidate pain genes. Finally, selected candidate pain genes were genotyped in an independent human cohort and prospectively evaluated for significant association between variants and measures of pain sensitivity. The strongest signal was with rs4512126 (5q32, ABLIM3, P = 1.3×10-10) for the sensitivity to cold pressor pain in males, but not in females. Significant associations were also observed with rs12548828, rs7826700 and rs1075791 on 8q22.2 within NCALD (P = 1.7×10-4, 1.8×10-4, and 2.2×10-4 respectively). Our results demonstrate the utility of a novel paradigm that integrates publicly available disease-specific gene expression data with clinical data curated from MEDLINE to facilitate the discovery of pain-relevant genes. This data-derived list of pain gene candidates enables additional focused and efficient biological studies validating additional candidates. [ABSTRACT FROM AUTHOR]

Background: Two main classes of peripheral sensory neurons contribute to thermal pain sensitivity: the unmyelinated C fibers and thinly myelinated Aδ fibers. These two fiber types may differentially underlie different clinical pain states and distinctions in the efficacy of analgesic treatments. Methods of differentially testing C and Aδ thermal pain are widely used in animal experimentation, but these methods are not optimal for human volunteer and patient use. Thus, this project aimed to provide psychophysical and electrophysiological evidence that whether different protocols of infrared diode laser stimulation, which allows for direct activation of nociceptive terminals deep in the skin, could differentially activate Aδ or C fiber thermonociceptors in volunteers. Results: Short (60 ms), high intensity laser pulses (SP) evoked monomodal "pricking" pain which was not enhanced by topical capsaicin, whereas longer, lower power pulses (LP) evoked monomodal "burning" pain which was enhanced by topical capsaicin. SP also produced cortical evoked EEG potentials consistent with Aδ mediation, the amplitude of which was directly correlated with pain intensity but was not affected by topical capsaicin. LP also produced a distinct evoked potential pattern the amplitude of which was also correlated with pain intensity, which was enhanced by topical capsaicin, and the latency of which could be used to estimate the conduction velocity of the mediating nociceptive fibers. Conclusions: Psychophysical and electrophysiological data were consistent with the ability of short high intensity infrared laser pulses to selectively produce Aδ mediated pain and of longer pulses to selectively produce C fiber mediated thermal pain. Thus, the use of these or similar protocols may be useful in developing and testing novel therapeutics based on the differential molecular mechanisms underlying activation of the two fiber types (e.g., TRPV1, TRPV2, etc). In addition, these protocol may be useful in determining the fiber mediation of different clinical pain types which may, in turn be useful in treatment choice. [ABSTRACT FROM AUTHOR]

Opioids are the cornerstone medication for the treatment of moderate to severe pain. However, analgesic opioid requirements and the propensity to suffer from aversive opioid effects, including fatal respiratory depression and addiction, vary widely among patients. The factors underlying the substantial response variance remain largely unknown and need clarification for using opioids more effectively in appropriately selected patients. This ongoing study takes advantage of the twin paradigm to estimate the genetic and environmental contributions to inter-individual differences in opioid responses. Evidence of significant heritability will justify more detailed and extensive genomic studies. The enrollment target is 80 monozygotic and 45 dizygotic twin pairs who undergo a target-controlled infusion of the opioid alfentanil and saline placebo in sequential but randomized order. In a laboratory-type setting, well-defined pharmacodynamic endpoints are measured to quantify pain sensitivity, analgesic opioid effects, and aversive opioid effects including respiratory depression, sedation and reinforcing affective responses. First results obtained in 159 participants provide evidence for the feasibility and utility of this interventional study paradigm to estimate familial aggregation and heritability components of relevant drug effects. Areas highlighted in this report include recruitment strategies, required infrastructure and personnel, selection of relevant outcome measures, drug infusion algorithm minimizing pharmacokinetic variability, and considerations for optimizing data quality and quantity without hampering feasibility. Applying the twin paradigm to complex and potentially harmful studies comprehensively characterizing pharmacological response profiles is without much precedent. Methods and first results including heritability estimates for heat and cold pain sensitivity should be of interest to investigators considering similar studies. [ABSTRACT FROM AUTHOR]

Background -: The chronic use of opioids prior to surgery leads to lowered pain thresholds and exaggerated pain levels after these procedures. Several mechanisms have been proposed to explain this heightened sensitivity commonly termed opioid-induced hyperalgesia (OIH). Most of these proposed mechanisms involve plastic events in the central or peripheral nervous systems. Alterations in the abundance of peripheral mediators of nociception have not previously been explored. Results -: In these experiments mice were treated with saline (control) or ascending daily doses of morphine to generate a state of OIH followed by hind paw incision. In other experiments morphine treatment was initiated at the time of incision. Both mechanical allodynia and peri-incisional skin cytokine levels were measured. Myeloperoxidase (MPO) assays were used to determine neutrophil activity near the wounds. The cytokine production inhibitor pentoxifylline was used to determine the functional significance of the excess cytokines in previously morphine treated animals. Mice treated chronically treated with morphine prior to incision were found to have enhanced skin levels of IL-1β, IL-6, G-CSF, KC and TNFα after incision at one or more time points compared to saline pretreated controls. The time courses of individual cytokines followed different patterns. There was no discernable effect of chronic morphine treatment on wound area neutrophil infiltration. Pentoxifylline reduced cytokine levels and reversed the excess mechanical sensitization caused by chronic morphine administration prior to incision. Morphine treatment initiated at the time of incision did not lead to a generalized enhancement of cytokine production or nociceptive sensitization in excess of the levels observed after incision alone. Conclusion -: The enhanced level of nociceptive sensitization seen after incision in animals chronically exposed to morphine is associated with elevated levels of several cytokines previously reported to be relevant to this incisional pain model. The cytokines may be functional in supporting nociceptive sensitization because pentoxifylline reverses both peri-incisional skin cytokine levels and OIH. Opioid administration beginning at the time of incision does not seem to have the same cytokine enhancing effect. Approaches to postoperative pain control involving a reduction of cytokines may be an effective way to control excessive pain in patients chronically using opioids prior to surgical procedures. [ABSTRACT FROM AUTHOR]

Background: Inflammation and nociceptive sensitization are hallmarks of tissue surrounding surgical incisions. Recent studies demonstrate that several cytokines may participate in the enhancement of nociception near these wounds. Since opioids like morphine interact with neutrophils and other immunocytes, it is possible that morphine exerts some of its antinociceptive action after surgical incision by altering the vigor of the inflammatory response. On the other hand, keratinocytes also express opioid receptors and have the capacity to produce cytokines after injury. Our studies were directed towards determining if opioids alter cytokine production near incisions and to identify cell populations responsible for producing these cytokines. Results: A murine incisional model was used to measure the effects of acute morphine administration (0.1-10 mg/kg) on nociceptive thresholds, neutrophil infiltration and cytokine production in hind paw skin 30 minutes and 2 hours after incision. Incised hind paws displayed profound allodynia which was reduced by morphine (0.1-10 mg/kg) in the 2 hours following incision. Skin samples harvested from these mice showed enhanced levels of 5 cytokines: IL-1β, IL-6, tumor necrosis factor alpha (TNFα), granulocyte colony stimulating factor (G-CSF) and keratinocyte-derived cytokine (KC). Morphine reduced these incision-stimulated levels. Separate analyses measuring myeloperoxidase (MPO) and using immunohistochemistry demonstrated that morphine dose-dependently reduced the infiltration of neutrophils into the peri-incisional tissue. The dose of morphine required for reduction of cytokine accumulation, however, was below that required for inhibition of peri-incisional neutrophil infiltration. Additional immunohistochemical studies revealed wound edge keratinocytes as being an important source of cytokines in the acute phase after incision. Conclusion: Acute morphine administration of doses as low as 0.1 mg/kg reduces peri-incisional cytokine expression. A reduction in neutrophil infiltration does not provide a complete explanation for this effect, and keratinocytes may be responsible for some incision area cytokine production. These studies suggest that morphine may alter the inflammatory milieu of incisional wounds, but these alterations do not likely contribute significantly to analgesia in the acute setting. [ABSTRACT FROM AUTHOR]

Lamellar liposome technology has been used for several decades to produce sustained-release drug formulations for parenteral administration. Multivesicular liposomes are structurally distinct from lamellar liposomes and consist of an aggregation of hundreds of water-filled polyhedral compartments separated by bi-layered lipid septa. The unique architecture of multivesicular liposomes allows encapsulating drug with greater efficiency, provides robust structural stability and ensures reliable, steady and prolonged drug release.The favourable characteristics of multivesicular liposomes have resulted in many drug formulations exploiting this technology, which is proprietary and referred to as DepoFoam™. Currently, two formulations using multivesicular liposome technology are approved by the US FDA for clinical use, and many more formulations are at an experimental developmental stage. The first clinically available formulation contains the antineoplastic agent cytarabine (DepoCyt™) for its intrathecal injection in the treatment of malignant lymphomatous meningitis. Intrathecal injection of DepoCyt™ reliably results in the sustained release of cytarabine and produces cytotoxic concentrations in cerebrospinal fluid (CSF) that are maintained for at least 2 weeks. Early efficacy data suggest that DepoCyt™ is fairly well tolerated, and its use allows reduced dosing frequency from twice a week to once every other week and may improve the outcome compared with frequent intrathecal injections of unencapsulated cytarabine. The second available formulation contains morphine (DepoDur™) for its single epidural injection in the treatment of postoperative pain. While animal studies confirm that epidural injection of DepoDur™ results in the sustained release of morphine into CSF, the CSF pharmacokinetics have not been determined in humans. Clinical studies suggest that the use of DepoDur™ decreases the amount of systemically administered analgesics needed for adequate postoperative pain control. It may also provide superior pain control during the first 1–2 postoperative days compared with epidural administration of unencapsulated morphine or intravenous administration of an opioid. However, at this timepoint the overall clinical utility of DepoDur™ has yet to be defined and some safety concerns remain because of the unknown CSF pharmacokinetics of DepoDur™ in humans.The versatility of multivesicular liposome technology is reflected by the many agents including small inorganic and organic molecules and macromolecules including proteins that have successfully been encapsulated. Data concerning many experimental formulations containing antineoplastic, antibacterial and antiviral agents underscore the sustained, steady and reliable release of these compounds from multivesicular liposomes after injection by the intrathecal, subcutaneous, intramuscular, intraperitoneal and intraocular routes. Contingent on the specific formulation and manufacturing process, agents were released over a period of hours to weeks as reflected by a 2- to 400-fold increase in elimination half life. Published data further suggest that the encapsulation process preserves bioactivity of agents as delicate as proteins and supports the view that examined multivesicular liposomes were non-toxic at studied doses. The task ahead will be to examine whether the beneficial structural and pharmacokinetic properties of multivesicular liposome formulations will translate into improved clinical outcomes, either because of decreased drug toxicity or increased drug efficacy. [ABSTRACT FROM AUTHOR]