Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19.

The biological determinants underlying the range of coronavirus 2019 (COVID-19) clinical manifestations are not fully understood. Here, over 1,400 plasma proteins and 2,600 single-cell immune features comprising cell phenotype, endogenous signaling activity, and signaling responses to inflammatory ligands are cross-sectionally assessed in peripheral blood from 97 patients with mild, moderate, and severe COVID-19 and 40 uninfected patients. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identify and independently validate a multi-variate model classifying COVID-19 severity (multi-class area under the curve [AUC]training = 0.799, p = 4.2e-6; multi-class AUCvalidation = 0.773, p = 7.7e-6). Examination of informative model features reveals biological signatures of COVID-19 severity, including the dysregulation of JAK/STAT, MAPK/mTOR, and nuclear factor κB (NF-κB) immune signaling networks in addition to recapitulating known hallmarks of COVID-19. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for prevention and/or treatment of COVID-19 progression.

Perinatal infection, inflammation, preterm birth, and brain injury: A review with proposals for future investigations.

Preterm newborns are exposed to several risk factors for developing brain injury. Clinical studies have suggested that the presence of intrauterine infection is a consistent risk factor for preterm birth and white matter injury. Animal models have confirmed these associations by identifying inflammatory cascades originating at the maternofetal interface that penetrate the fetal blood-brain barrier and result in brain injury. Acquired diseases of prematurity further potentiate the risk for cerebral injury. Systems biology approaches incorporating ante- and post-natal risk factors and analyzing omic and multiomic data using machine learning are promising methodologies for further elucidating biologic mechanisms of fetal and neonatal brain injury.

Single-Cell Analysis of the Neonatal Immune System Across the Gestational Age Continuum.

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.

A Peripheral Immune Signature of Labor Induction.

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.

Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset.

Estimating the time of delivery is of high clinical importance because pre- and postterm deviations are associated with complications for the mother and her offspring. However, current estimations are inaccurate. As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is key to understanding these physiological transitions and identifying predictive biomarkers of delivery. Here, a longitudinal study was conducted in 63 women who went into labor spontaneously. More than 7000 plasma analytes and peripheral immune cell responses were analyzed using untargeted mass spectrometry, aptamer-based proteomic technology, and single-cell mass cytometry in serial blood samples collected during the last 100 days of pregnancy. The high-dimensional dataset was integrated into a multiomic model that predicted the time to spontaneous labor [R = 0.85, 95% confidence interval (CI) [0.79 to 0.89], P = 1.2 × 10-40, N = 53, training set; R = 0.81, 95% CI [0.61 to 0.91], P = 3.9 × 10-7, N = 10, independent test set]. Coordinated alterations in maternal metabolome, proteome, and immunome marked a molecular shift from pregnancy maintenance to prelabor biology 2 to 4 weeks before delivery. A surge in steroid hormone metabolites and interleukin-1 receptor type 4 that preceded labor coincided with a switch from immune activation to regulation of inflammatory responses. Our study lays the groundwork for developing blood-based methods for predicting the day of labor, anchored in mechanisms shared in preterm and term pregnancies.

Understanding how biologic and social determinants affect disparities in preterm birth and outcomes of preterm infants in the NICU.

To understand the disparities in spontaneous preterm birth (sPTB) and/or its outcomes, biologic and social determinants as well as healthcare practice (such as those in neonatal intensive care units) should be considered. Disparities in sPTB have been largely intractable and remain obscure in most cases, despite a myriad of identified risk factors for and causes of sPTB. We still do not know how they lead to the different outcomes at different gestational ages and if they are independent of NICU practices. Here we describe an integrated approach to study the interplay between the genome and exposome, which may drive biochemistry and physiology and lead to health disparities.

Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19.

The biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in peripheral blood from patients with mild, moderate, and severe COVID-19, at the time of diagnosis. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identified and independently validated a multivariate model classifying COVID-19 severity (multi-class AUCtraining = 0.799, p-value = 4.2e-6; multi-class AUCvalidation = 0.773, p-value = 7.7e-6). Features of this high-dimensional model recapitulated recent COVID-19 related observations of immune perturbations, and revealed novel biological signatures of severity, including the mobilization of elements of the renin-angiotensin system and primary hemostasis, as well as dysregulation of JAK/STAT, MAPK/mTOR, and NF-κB immune signaling networks. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for the prevention of COVID-19 progression.

Multiomic immune clockworks of pregnancy.

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.

Outcomes and Resource Use Among Overweight and Obese Children With Sepsis in the Pediatric Intensive Care Unit.

OBJECTIVE: To evaluate the effect of overweight and obesity on outcomes and resource use among patients with sepsis in the pediatric intensive care unit (PICU). DESIGN: Retrospective analysis of clinical characteristics, resource use, and mortality among children 0 to 20 years of age admitted to the C.S. MottChildren's Hospital PICU (University of Michigan) between January 2009 and December 2015, with a diagnostic code for sepsis at admission (based on International Classification of Diseases, Ninth Revision-Clinical Modification codes) and with weight and height measurements at PICU admission. MEASUREMENTS AND MAIN RESULTS: A total of 454 participants met the inclusion criteria. Seventy-six were categorized as underweight (body mass index [BMI] percentile <5th) and were excluded, which left a final sample size of 378 participants. Children with a BMI >5th and <85th percentiles for age were categorized as normal weight and those with a BMI >85th percentile as overweight/obese. After descriptive and bivariate analyses, multivariate regression methods were used to assess the independent effect of obesity status on mortality and the use of PICU technology after adjustment for patient age and illness severity at admission. Of the 378 patients studied, 41.3% were overweight/obese. There was no difference in microbiologic etiology of sepsis (P = .36), median PICU length of stay in days (5.4 vs 5.6; P = .61), or PICU mortality (6.4% vs 7.2%; P = .76) by weight status. The use of specialized PICU technology including extracorporeal membrane oxygenation (odds ratio [OR]: 2.77, 95% confidence interval [CI]:1.13-6.79) and continuous renal replacement therapy (OR: 4.58, 95% CI: 1.16-18.0) was higher among overweight/obese patients, compared with normal weight patients. CONCLUSIONS: Although PICU mortality and length of stay were similar for obese-overweight patients and normal weight critically ill children with sepsis, there was significantly higher use of specialized organ-supportive technology among obese patients, likely indicating higher occurrence of multiple organ dysfunction.

Differential Dynamics of the Maternal Immune System in Healthy Pregnancy and Preeclampsia.

Preeclampsia is one of the most severe pregnancy complications and a leading cause of maternal death. However, early diagnosis of preeclampsia remains a clinical challenge. Alterations in the normal immune adaptations necessary for the maintenance of a healthy pregnancy are central features of preeclampsia. However, prior analyses primarily focused on the static assessment of select immune cell subsets have provided limited information for the prediction of preeclampsia. Here, we used a high-dimensional mass cytometry immunoassay to characterize the dynamic changes of over 370 immune cell features (including cell distribution and functional responses) in maternal blood during healthy and preeclamptic pregnancies. We found a set of eight cell-specific immune features that accurately identified patients well before the clinical diagnosis of preeclampsia (median area under the curve (AUC) 0.91, interquartile range [0.82-0.92]). Several features recapitulated previously known immune dysfunctions in preeclampsia, such as elevated pro-inflammatory innate immune responses early in pregnancy and impaired regulatory T (Treg) cell signaling. The analysis revealed additional novel immune responses that were strongly associated with, and preceded the onset of preeclampsia, notably abnormal STAT5ab signaling dynamics in CD4+T cell subsets (AUC 0.92, p = 8.0E-5). These results provide a global readout of the dynamics of the maternal immune system early in pregnancy and lay the groundwork for identifying clinically-relevant immune dysfunctions for the prediction and prevention of preeclampsia.

Fibroblast-specific plasminogen activator inhibitor-1 depletion ameliorates renal interstitial fibrosis after unilateral ureteral obstruction.

BACKGROUND: Plasminogen activator inhibitor-1 (PAI-1) expression increases extracellular matrix deposition and contributes to interstitial fibrosis in the kidney after injury. While PAI-1 is ubiquitously expressed in the kidney, we hypothesized that interstitial fibrosis is strongly dependent on fibroblast-specific PAI-1 (fbPAI-1). METHODS: Tenascin C Cre (TNC Cre) and fbPAI-1 knockdown (KD) mice with green fluorescent protein (GFP) expressed within the TNC construct underwent unilateral ureteral obstruction and were sacrificed 10 days later. RESULTS: GFP+ cells in fbPAI-1 KD mice showed significantly reduced PAI-1 expression. Interstitial fibrosis, measured by Sirius red staining and collagen I western blot, was significantly decreased in fbPAI-1 KD compared with TNC Cre mice. There was no significant difference in transforming growth factor ß (TGF-ß) expression or its activation between the two groups. However, GFP+ cells from fbPAI-1 KD mice had lower TGF ß and connective tissue growth factor (CTGF) expression. The number of fibroblasts was decreased in fbPAI-1 KD compared with TNC Cre mice, correlating with decreased alpha smooth muscle actin (α-SMA) expression and less fibroblast cell proliferation. TNC Cre mice had decreased E-cadherin, a marker of differentiated tubular epithelium, in contrast to preserved expression in fbPAI-1 KD. F4/80-expressing cells, mostly CD11c+/F4/80+ cells, were increased while M1 macrophage markers were decreased in fbPAI-1 KD compared with TNC Cre mice. CONCLUSION: These findings indicate that fbPAI-1 depletion ameliorates interstitial fibrosis by decreasing fibroblast proliferation in the renal interstitium, with resulting decreased collagen I. This is linked to decreased M1 macrophages and preserved tubular epithelium.

Human metapneumovirus small hydrophobic (SH) protein downregulates type I IFN pathway signaling by affecting STAT1 expression and phosphorylation.

Type I interferon (IFN) is a key mediator of antiviral immunity. Human metapneumovirus (HMPV) inhibits IFN signaling, but does not encode homologues of known IFN antagonists. We tested the hypothesis that a specific viral protein prevents type I IFN signaling by targeting signal transducer and activator of transcription-1 (STAT1). We found that human airway epithelial cells (capable of expressing IFNs) became impaired for STAT1 phosphorylation even without direct infection due to intrinsic negative feedback. HMPV-infected Vero cells (incapable of expressing IFN) displayed lower STAT1 expression and impaired STAT1 phosphorylation in response to type I IFN treatment compared to mock-infected cells. Transient overexpression of HMPV small hydrophobic (SH) protein significantly inhibited STAT1 phosphorylation and signaling, and recombinant virus lacking SH protein was unable to inhibit STAT1 phosphorylation. Our results indicate a role for the SH protein of HMPV in the downregulation of type I IFN signaling through the targeting of STAT1.

Effectiveness of a school-based deworming campaign in rural Kenya.

In 2007, the rate of intestinal helminth infection in primary school-aged children in a rural village in Southwestern Kenya was estimated to be at least 68%, based on direct stool smear. Since the 2007 survey, these same school children have been treated with 400-mg albendazole every 3 months. We repeated a cross-sectional stool survey in the same area in 2010 (i.e. 3 years later) to estimate the current parasite prevalence. While only 44.5% of children were infected in 2010, the decline was not as marked as one might expect from a well-managed quarterly deworming campaign. Due to the relative insensitivity of the technique utilized here-the direct smear examination of a single stool sample-we were only able to identify heavy infections, and the true rate of parasitism is likely much higher, suggesting heavy environmental contamination and rapid re-infection rates. Community education and sanitation improvements are needed for more definitive impact.