A reduced proteomic signature in critically ill Covid-19 patients determined with plasma antibody micro-array and machine learning

BACKGROUND

COVID-19 is a complex, multi-system disease with varying severity and symptoms. Identifying changes in critically ill COVID-19 patients' proteomes enables a better understanding of markers associated with susceptibility, symptoms, and treatment. We performed plasma antibody microarray and machine learning analyses to identify novel proteins of COVID-19.

METHODS

A case-control study comparing the concentration of 2000 plasma proteins in age- and sex-matched COVID-19 inpatients, non-COVID-19 sepsis controls, and healthy control subjects. Machine learning was used to identify a unique proteome signature in COVID-19 patients. Protein expression was correlated with clinically relevant variables and analyzed for temporal changes over hospitalization days 1, 3, 7, and 10. Expert-curated protein expression information was analyzed with Natural language processing (NLP) to determine organ- and cell-specific expression.

RESULTS

Machine learning identified a 28-protein model that accurately differentiated COVID-19 patients from ICU non-COVID-19 patients (accuracy = 0.89, AUC = 1.00, F1 = 0.89) and healthy controls (accuracy = 0.89, AUC = 1.00, F1 = 0.88). An optimal nine-protein model (PF4V1, NUCB1, CrkL, SerpinD1, Fen1, GATA-4, ProSAAS, PARK7, and NET1) maintained high classification ability. Specific proteins correlated with hemoglobin, coagulation factors, hypertension, and high-flow nasal cannula intervention (P < 0.01). Time-course analysis of the 28 leading proteins demonstrated no significant temporal changes within the COVID-19 cohort. NLP analysis identified multi-system expression of the key proteins, with the digestive and nervous systems being the leading systems.

CONCLUSIONS

The plasma proteome of critically ill COVID-19 patients was distinguishable from that of non-COVID-19 sepsis controls and healthy control subjects. The leading 28 proteins and their subset of 9 proteins yielded accurate classification models and are expressed in multiple organ systems. The identified COVID-19 proteomic signature helps elucidate COVID-19 pathophysiology and may guide future COVID-19 treatment development.

The plasma proteome differentiates the multisystem inflammatory syndrome in children (MIS-C) from children with SARS-CoV-2 negative sepsis

BACKGROUND

The Multi-System Inflammatory Syndrome in Children (MIS-C) can develop several weeks after SARS-CoV-2 infection and requires a distinct treatment protocol. Distinguishing MIS-C from SARS-CoV-2 negative sepsis (SCNS) patients is important to quickly institute the correct therapies. We performed targeted proteomics and machine learning analysis to identify novel plasma proteins of MIS-C for early disease recognition.

METHODS

A case-control study comparing the expression of 2,870 unique blood proteins in MIS-C versus SCNS patients, measured using proximity extension assays. The 2,870 proteins were reduced in number with either feature selection alone or with a prior COMBAT-Seq batch effect adjustment. The leading proteins were correlated with demographic and clinical variables. Organ system and cell type expression patterns were analyzed with Natural Language Processing (NLP).

RESULTS

The cohorts were well-balanced for age and sex. Of the 2,870 unique blood proteins, 58 proteins were identified with feature selection (FDR-adjusted P < 0.005, P < 0.0001; accuracy = 0.96, AUC = 1.00, F1 = 0.95), and 15 proteins were identified with a COMBAT-Seq batch effect adjusted feature selection (FDR-adjusted P < 0.05, P < 0.0001; accuracy = 0.92, AUC = 1.00, F1 = 0.89). All of the latter 15 proteins were present in the former 58-protein model. Several proteins were correlated with illness severity scores, length of stay, and interventions (LTA4H, PTN, PPBP, and EGF; P < 0.001). NLP analysis highlighted the multi-system nature of MIS-C, with the 58-protein set expressed in all organ systems; the highest levels of expression were found in the digestive system. The cell types most involved included leukocytes not yet determined, lymphocytes, macrophages, and platelets.

CONCLUSIONS

The plasma proteome of MIS-C patients was distinct from that of SCNS. The key proteins demonstrated expression in all organ systems and most cell types. The unique proteomic signature identified in MIS-C patients could aid future diagnostic and therapeutic advancements, as well as predict hospital length of stays, interventions, and mortality risks.

Pediatric sepsis inflammatory blood biomarkers that correlate with clinical variables and severity of illness scores

BACKGROUND

Sepsis is a dysregulated systemic inflammatory response triggered by infection, resulting in organ dysfunction. A major challenge in clinical pediatrics is to identify sepsis early and then quickly intervene to reduce morbidity and mortality. As blood biomarkers hold promise as early sepsis diagnostic tools, we aimed to measure a large number of blood inflammatory biomarkers from pediatric sepsis patients to determine their predictive ability, as well as their correlations with clinical variables and illness severity scores.

METHODS

Pediatric patients that met sepsis criteria were enrolled, and clinical data and blood samples were collected. Fifty-eight inflammatory plasma biomarker concentrations were determined using immunoassays. The data were analyzed with both conventional statistics and machine learning.

RESULTS

Twenty sepsis patients were enrolled (median age 13 years), with infectious pathogens identified in 75%. Vasopressors were administered to 85% of patients, while 55% received invasive ventilation and 20% were ventilated non-invasively. A total of 24 inflammatory biomarkers were significantly different between sepsis patients and age/sex-matched healthy controls. Nine biomarkers (IL-6, IL-8, MCP-1, M-CSF, IL-1RA, hyaluronan, HSP70, MMP3, and MMP10) yielded AUC parameters > 0.9 (95% CIs: 0.837-1.000; p < 0.001). Boruta feature reduction yielded 6 critical biomarkers with their relative importance: IL-8 (12.2%), MCP-1 (11.6%), HSP70 (11.6%), hyaluronan (11.5%), M-CSF (11.5%), and IL-6 (11.5%); combinations of 2 biomarkers yielded AUC values of 1.00 (95% CI: 1.00-1.00; p < 0.001). Specific biomarkers strongly correlated with illness severity scoring, as well as other clinical variables. IL-3 specifically distinguished bacterial versus viral infection (p < 0.005).

CONCLUSIONS

Specific inflammatory biomarkers were identified as markers of pediatric sepsis and strongly correlated to both clinical variables and sepsis severity.

Kinome and phosphoproteome reprogramming underlies the aberrant immune responses in critically ill COVID-19 patients

SARS-CoV-2 infection triggers extensive host immune reactions, leading to severe diseases in certain individuals. However, the molecular basis underlying the excessive yet non-productive immune responses in severe COVID-19 remains incompletely understood. In this study, we conducted a comprehensive analysis of the peripheral blood mononuclear cell (PBMC) proteome and phosphoproteome in sepsis patients positive or negative for SARS-CoV-2 infection, as well as healthy subjects, using quantitative mass spectrometry. Our findings demonstrate dynamic changes in the COVID-19 PBMC proteome and phosphoproteome during disease progression, with distinctive protein or phosphoprotein signatures capable of distinguishing longitudinal disease states. Furthermore, SARS-CoV-2 infection induces a global reprogramming of the kinome and phosphoproteome, resulting in defective adaptive immune response mediated by the B and T lymphocytes, compromised innate immune responses involving the SIGLEC and SLAM family of immunoreceptors, and excessive cytokine-JAK-STAT signaling. In addition to uncovering host proteome and phosphoproteome aberrations caused by SARS-CoV-2, our work recapitulates several reported therapeutic targets for COVID-19 and identified numerous new candidates, including the kinases PKG1, CK2, ROCK1/2, GRK2, SYK, JAK2/3, TYK2, DNA-PK, PKCδ, and the cytokine IL-12.

Post-Intensive Care Sequelae in Pediatrics-Results of an Early Rehabilitation Implementation Study

OBJECTIVES

To compare post-PICU discharge functioning, health-related quality of life (HRQL), and parental stress before and after the implementation of an early rehabilitation bundle.

DESIGN AND SETTING

Prospective cohort substudy within an early rehabilitation implementation program, conducted at the PICUs at McMaster Children's Hospital and London Health Sciences, London, Ontario, Canada.

INTERVENTIONS

A bundle consisting of: 1) analgesia-first sedation; 2) delirium monitoring and prevention; and 3) early mobilization. Patients with an anticipated 48-hour PICU length of stay were approached for consent to participate.

PATIENTS

Critically ill children with an anticipated 48-hour PICU length of stay were approached for consent to participate.

MEASUREMENTS AND MAIN RESULTS

Patient-/proxy-reported outcome measures were assessed at baseline, PICU discharge, and 1 and 3 months post-PICU discharge using: 1) Pediatric Evaluation of Disability Inventory Computer Adaptive Test to assess physical, social, cognitive, and responsibility/caregiver domains of functioning; 2) KIDSCREEN to assess HRQL; and 3) the Pediatric Inventory for Parents to assess caregiver stress. A total of 117 participants were enrolled. Patient demographic characteristics were similar in the pre- and post-intervention groups. Following bundle implementation, 30 of 47 respondents (63.8%) experienced functional decline and 18 of 45 (40%) experienced low HRQL at PICU discharge. Eighteen of 36 (50%) at 1 month and 14 of 38 (36.8%) at 3 months experienced either persistent functional decline and/or low HRQL; 2.8% and 2.6% at 1- and 3-month follow-up, respectively, experienced both persistent functional decline and low HRQL. There were no significant differences in the rates of persistent functional decline, low HRQL, or caregiver stress scores post-bundle compared with pre-rehabilitation bundle implementation.

CONCLUSIONS

We were unable to adequately determine the efficacy of a rehabilitation bundle on patient-centered outcomes as this substudy was not powered for these outcomes. Our results did reveal that persistent low functioning is common in PICU survivors, more common than low HRQL, while experiencing both functional decline and low HRQL was uncommon.

Early Rehabilitation in Critically ill Children: A Two Center Implementation Study

OBJECTIVES

To implement an early rehabilitation bundle in two Canadian PICUs.

DESIGN AND SETTING

Implementation study in the PICUs at McMaster Children's Hospital (site 1) and London Health Sciences (site 2).

PATIENTS

All children under 18 years old admitted to the PICU were eligible for the intervention.

INTERVENTIONS

A bundle consisting of: 1) analgesia-first sedation; 2) delirium monitoring and prevention; and 3) early mobilization.

MEASUREMENTS AND MAIN RESULTS

Primary outcomes were the duration of implementation, bundle compliance, process of care, safety, and the factors influencing implementation. Secondary endpoints were the impact of the bundle on clinical outcomes such as pain, delirium, iatrogenic withdrawal, ventilator-free days, length of stay, and mortality. Implementation occurred over 26 months (August 2018 to October 2020). Data were collected on 1,036 patients representing 4,065 patient days. Bundle compliance was optimized within 6 months of roll-out. Goal setting for mobilization and level of arousal improved significantly (p < 0.01). Benzodiazepine, opioid, and dexmedetomidine use decreased in site 1 by 23.2% (95% CI, 30.8-15.5%), 26.1% (95% CI, 34.8-17.4%), and 9.2% (95% CI, 18.2-0.2%) patient exposure days, respectively, while at site 2, only dexmedetomidine exposure decreased significantly by 10.5% patient days (95% CI, 19.8-1.1%). Patient comfort, safety, and nursing workload were not adversely affected. There was no significant impact of the bundle on the rate of delirium, ventilator-free days, length of PICU stay, or mortality. Key facilitators to implementation included institutional support, unit-wide practice guidelines, dedicated PICU educators, easily accessible resources, and family engagement.

CONCLUSIONS

A rehabilitation bundle can improve processes of care and reduce patient sedative exposure without increasing patient discomfort, nursing workload, or harm. We did not observe an impact on short-term clinical outcomes. The efficacy of a PICU-rehabilitation bundle requires ongoing study. Lessons learned in this study provide evidence to inform rehabilitation implementation in the PICU setting.

Pharmacokinetics of recombinant human annexin A5 (SY-005) in patients with severe COVID-19

Objective: Annexin A5 is a phosphatidylserine binding protein with anti-inflammatory, anticoagulant and anti-apoptotic properties. Preclinical studies have shown that annexin A5 inhibits pro-inflammatory responses and improves organ function and survival in rodent models of sepsis. This clinical trial aimed to evaluate the pharmacokinetic (PK) properties of the recombinant human annexin A5 (SY-005) in severe COVID-19. Methods: This was a pilot randomized, double-blind, placebo-controlled trial. Severe COVID-19 patients were randomly assigned to receive intravenous 50 μg/kg (low dose, n = 3), 100 μg/kg (high dose, n = 5) of SY-005 or placebo (n = 5) every 12 h for 7 days. Plasma SY-005 levels were assessed using enzyme-linked immunosorbent assay (ELISA) and the PK parameters were determined using non-compartmental analysis. Results: All patients treated with SY-005 had a normal baseline estimated glomerular filtration rate (eGFR, 104-125 mL/min/1.73 m2). Both low and high doses of SY-005 were cleared within 6 h after intravenous administration. Plasma maximum concentrations (Cmax), half-life, clearance and volume distribution of low and high doses of SY-005 were 402.4 and 848.9 ng/mL, 0.92 and 0.96 h, 7.52 and 15.19 L/h, and 9.98 and 20.79 L, respectively. Daily pre-dose circulating annexin A5 levels were not significantly different when SY-005 was administered at the low or the high dose 12-h intervals. There was no significant effect on activated partial thromboplastin time (aPTT) or INR (international normalized ratio of prothrombin time) during 7 days of SY-005 treatment. Conclusion: SY-005 doses of 50 and 100 μg/kg were detectable and subsequently cleared from the plasma in severe COVID-19 patients with normal baseline renal function. There was no significant plasma SY-005 accumulation 6 h after drug administration and coagulation was not altered during 7 days of treatment. Clinical trials Registration: This study was registered with ClinicalTrials.gov (NCT04748757, first posted on 10 February 2021).

A novel multiplex biomarker panel for profiling human acute and chronic kidney disease

Acute and chronic kidney disease continues to confer significant morbidity and mortality in the clinical setting. Despite high prevalence of these conditions, few validated biomarkers exist to predict kidney dysfunction. In this study, we utilized a novel kidney multiplex panel to measure 21 proteins in plasma and urine to characterize the spectrum of biomarker profiles in kidney disease. Blood and urine samples were obtained from age-/sex-matched healthy control subjects (HC), critically-ill COVID-19 patients with acute kidney injury (AKI), and patients with chronic or end-stage kidney disease (CKD/ESKD). Biomarkers were measured with a kidney multiplex panel, and results analyzed with conventional statistics and machine learning. Correlations were examined between biomarkers and patient clinical and laboratory variables. Median AKI subject age was 65.5 (IQR 58.5-73.0) and median CKD/ESKD age was 65.0 (IQR 50.0-71.5). Of the CKD/ESKD patients, 76.1% were on hemodialysis, 14.3% of patients had kidney transplant, and 9.5% had CKD without kidney replacement therapy. In plasma, 19 proteins were significantly different in titer between the HC versus AKI versus CKD/ESKD groups, while NAG and RBP4 were unchanged. TIMP-1 (PPV 1.0, NPV 1.0), best distinguished AKI from HC, and TFF3 (PPV 0.99, NPV 0.89) best distinguished CKD/ESKD from HC. In urine, 18 proteins were significantly different between groups except Calbindin, Osteopontin and TIMP-1. Osteoactivin (PPV 0.95, NPV 0.95) best distinguished AKI from HC, and β2-microglobulin (PPV 0.96, NPV 0.78) best distinguished CKD/ESKD from HC. A variety of correlations were noted between patient variables and either plasma or urine biomarkers. Using a novel kidney multiplex biomarker panel, together with conventional statistics and machine learning, we identified unique biomarker profiles in the plasma and urine of patients with AKI and CKD/ESKD. We demonstrated correlations between biomarker profiles and patient clinical variables. Our exploratory study provides biomarker data for future hypothesis driven research on kidney disease.

Pivoting injury prevention efforts during a pandemic: results of an international survey

BACKGROUND

The COVID-19 a pandemic changed the world. Public health directives to socially distance with stay-at-home orders altered injury risk factor exposure, resulting injury patterns and conducting injury prevention (IP). The objective of this study was to determine the impact the COVID-19 pandemic on injury and IP at North American trauma centers (TC).

RESULTS

Sixty-two responses were received from pediatric (44%), adult (11%), and combined (31%) TC, from 22 American states, 5 Canadian provinces and Australia. The majority (91%) of programs targeted age groups from birth to 15 years old. Nearly one-third reported IP to be less of an institutional priority with funding redistributed in 15% of centers [median (IQR) - 25% (- 43, 1)], and resultant staffing changes at 38% of centers. A decrease in IP efforts was reported at 64% of TC. Overall, the majority of respondents reviewed injury data, with the top reported increased mechanisms mainly intentional: Firearm-related (75%), assaults (72%), and abuse (71%). Leading increased unintentional injuries were injuries occurring in the home such as falls (70%), followed by ATV (62%), and cycling (57%). Sites pivoted by presenting (74%) or participating (73%) in IP education virtually, social media posts (61%) and the addition of technology (29%). Top barriers were redeployment of partners (45%) and staff (31%), as well as lack of technology (40%) in the target population. Facilitators were technology at TC (74%), support of trauma program (63%), and having IP funding maintained (55%).

CONCLUSIONS

Nearly two-thirds of TC decreased IP efforts during the pandemic due to staffing and funding reductions. The leading reported increased injuries were intentional, indicating that violence prevention is needed, along with support for mental health. While TC successfully pivoted by using technology, access issues in the target population was a barrier resulting in health inequities.

Use of Biostatistical Models to Manage Replicate Error in Concussion Biomarker Research

Importance

Advancing research on fluid biomarkers associated with sport-related concussion (SRC) highlights the importance of detecting low concentrations using ultrasensitive platforms. However, common statistical practices may overlook replicate errors and specimen exclusion, emphasizing the need to explore robust modeling approaches that consider all available replicate data for comprehensive understanding of sample variation and statistical inferences.

Objective

To evaluate the impact of replicate error and different biostatistical modeling approaches on SRC biomarker interpretation.

Design, Setting, and Participants

This cross-sectional study within the Surveillance in High Schools to Reduce the Risk of Concussions and Their Consequences study used data from healthy youth athletes (ages 11-18 years) collected from 3 sites across Canada between September 2019 and November 2021. Data were analyzed from November 2022 to February 2023.

Exposures

Demographic variables included age, sex, and self-reported history of previous concussion.

Main Outcomes and Measures

Outcomes of interest were preinjury plasma glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), neurofilament-light (NFL), total tau (t-tau) and phosphorylated-tau-181 (p-tau-181) assayed in duplicate. Bland-Altman analysis determined the 95% limits of agreement (LOAs) for each biomarker. The impact of replicate error was explored using 3 biostatistical modeling approaches assessing the associations of age, sex, and previous concussion on biomarker concentrations: multilevel regression using all available replicate data, single-level regression using the means of replicate data, and single-level regression with replicate means, excluding specimens demonstrating more than 20% coefficient variation (CV).

Results

The sample included 149 healthy youth athletes (78 [52%] male; mean [SD] age, 15.74 [1.41] years; 51 participants [34%] reporting ≥1 previous concussions). Wide 95% LOAs were observed for GFAP (-17.74 to 18.20 pg/mL), UCH-L1 (-13.80 to 14.77 pg/mL), and t-tau (65.27% to 150.03%). GFAP and UCH-L1 were significantly associated with sex in multilevel regression (GFAP: effect size, 15.65%; β = -0.17; 95% CI, -0.30 to -0.04]; P = .02; UCH-L1: effect size, 17.24%; β = -0.19; 95% CI, -0.36 to -0.02]; P = .03) and single-level regression using the means of replicate data (GFAP: effect size, 15.56%; β = -0.17; 95% CI, -0.30 to -0.03]; P = .02; UCH-L1: effect size, 18.02%; β = -0.20; 95% CI, -0.37 to -0.03]; P = .02); however, there was no association for UCH-L1 after excluding specimens demonstrating more than 20% CV. Excluding specimens demonstrating more than 20% CV resulted in decreased differences associated with sex in GFAP (effect size, 12.29%; β = -0.14; 95% CI, -0.273 to -0.004]; P = .04) and increased sex differences in UCH-L1 (effect size, 23.59%; β = -0.27; 95% CI, -0.55 to 0.01]; P = .06), with the widest 95% CIs (ie, least precision) found in UCH-L1.

Conclusions and Relevance

In this cross-sectional study of healthy youth athletes, varying levels of agreement between SRC biomarker technical replicates suggested that means of measurements may not optimize precision for population values. Multilevel regression modeling demonstrated how incorporating all available biomarker data could capture replicate variation, avoiding challenges associated with means and percentage of CV exclusion thresholds to produce more representative estimates of association.

Annexin A5 in Patients With Severe COVID-19 Disease: A Single-Center, Randomized, Double-Blind, Placebo-Controlled Feasibility Trial

OBJECTIVES

To evaluate the study design and feasibility of drug administration and safety in a randomized clinical trial of recombinant human annexin A5 (SY-005), a constitutively expressed protein with anti-inflammatory, antiapoptotic, and anticoagulant properties, in patients with severe coronavirus disease 2019 (COVID-19).

DESIGN

Double-blind, randomized clinical trial.

SETTING

Two ICUs at an academic medical center.

PATIENTS/SUBJECTS

Adults admitted to the ICU with a confirmed diagnosis of COVID-19 and requiring ventilatory or vasopressor support.

INTERVENTIONS

SY-005, a recombinant human annexin A5, at 50 or 100 µg/kg IV every 12 hours for 7 days.

MEASUREMENTS AND MAIN RESULTS

We enrolled 18 of the 55 eligible patients (33%) between April 21, 2021, and February 3, 2022. We administered 82% (196/238) of the anticipated doses of study medication and 86% (169/196) were given within 1 hour of the scheduled time. There were no drug-related serious adverse events. We captured 100% of the data that would be required for measuring clinical outcomes in a phase 2 or 3 trial.

LIMITATIONS

The small sample size was a result of decreasing admissions of patients with COVID-19, which triggered a stopping rule for the trial.

CONCLUSIONS

Although enrollment was low, administration of SY-005 to critically ill patients with COVID-19 every 12 hours for up to 7 days was feasible and safe. Further clinical trials of annexin A5 for the treatment of COVID-19 are warranted. Given reduction of severe COVID-19 disease, future studies should explore the safety and effectiveness of SY-005 use in non-COVID-related sepsis.

The utility of syndecan-1 circulating levels as a biomarker in patients with previous or active COVID-19: a systematic review and meta-analysis

BACKGROUND

With the emergence of coronavirus disease of 2019 (COVID-19), several blood biomarkers have been identified, including the endothelial biomarker syndecan-1, a surface proteoglycan. In the current systematic review and meta-analysis, we aimed to assess the diagnostic and prognostic role of syndecan-1 in COVID-19.

METHODS

PubMed, Embase, Scopus, and Web of Science, as international databases, were searched for relevant studies measuring blood syndecan-1 levels in COVID-19 patients, COVID-19 convalescents, and healthy control subjects, in patients with different COVID-19 severities and/or in COVID-19 patients with poor outcomes. Random-effect meta-analysis was performed using STATA to calculate the standardized mean difference (SMD) and 95% confidence interval (CI) for the comparison between COVID-19 patients and healthy control subjects or COVID-19 convalescents and controls.

RESULTS

After screening by title/abstract and full text, 17 studies were included in the final review. Meta-analysis of syndecan-1 levels in COVID-19 compared with healthy control subjects revealed that patients with COVID-19 had significantly higher syndecan-1 levels (SMD 1.53, 95% CI 0.66 to 2.41, P < 0.01). In contrast, COVID-19 convalescent patients did not show significant difference with non-convalescents (SMD 0.08, 95% CI -0.63 to 0.78, P = 0.83). Regarding disease severity, two studies reported that more severe forms of the disease were associated with increased syndecan-1 levels. Moreover, patients who died from COVID-19 had higher syndecan-1 levels compared with survivors (SMD 1.22, 95% CI 0.10 to 2.33, P = 0.03).

CONCLUSION

Circulating syndecan-1 level can be used as a biomarker of endothelial dysfunction in COVID-19, as it was increased in COVID-19 patients and was higher in more severe instances of the disease. Further larger studies are needed to confirm these findings and further enlighten the role of syndecan-1 in clinical settings.

Tachykinins and the potential causal factors for post-COVID-19 condition

The most prevalent symptoms of post-COVID-19 condition are pulmonary dysfunction, fatigue and muscle weakness, anxiety, anosmia, dysgeusia, headaches, difficulty in concentrating, sexual dysfunction, and digestive disturbances. Hence, neurological dysfunction and autonomic impairments predominate in post-COVID-19 condition. Tachykinins including the most studied substance P are neuropeptides expressed throughout the nervous and immune systems, and contribute to many physiopathological processes in the nervous, immune, gastrointestinal, respiratory, urogenital, and dermal systems and participate in inflammation, nociception, and cell proliferation. Substance P is a key molecule in neuroimmune crosstalk; immune cells near the peripheral nerve endings can send signals to the brain with cytokines, which highlights the important role of tachykinins in neuroimmune communication. We reviewed the evidence that relates the symptoms of post-COVID-19 condition to the functions of tachykinins and propose a putative pathogenic mechanism. The antagonism of tachykinins receptors can be a potential treatment target.

Plasma proteome of Long-COVID patients indicates HIF-mediated vasculo-proliferative disease with impact on brain and heart function

AIMS

Long-COVID occurs after SARS-CoV-2 infection and results in diverse, prolonged symptoms. The present study aimed to unveil potential mechanisms, and to inform prognosis and treatment.

METHODS

Plasma proteome from Long-COVID outpatients was analyzed in comparison to matched acutely ill COVID-19 (mild and severe) inpatients and healthy control subjects. The expression of 3072 protein biomarkers was determined with proximity extension assays and then deconvoluted with multiple bioinformatics tools into both cell types and signaling mechanisms, as well as organ specificity.

RESULTS

Compared to age- and sex-matched acutely ill COVID-19 inpatients and healthy control subjects, Long-COVID outpatients showed natural killer cell redistribution with a dominant resting phenotype, as opposed to active, and neutrophils that formed extracellular traps. This potential resetting of cell phenotypes was reflected in prospective vascular events mediated by both angiopoietin-1 (ANGPT1) and vascular-endothelial growth factor-A (VEGFA). Several markers (ANGPT1, VEGFA, CCR7, CD56, citrullinated histone 3, elastase) were validated by serological methods in additional patient cohorts. Signaling of transforming growth factor-β1 with probable connections to elevated EP/p300 suggested vascular inflammation and tumor necrosis factor-α driven pathways. In addition, a vascular proliferative state associated with hypoxia inducible factor 1 pathway suggested progression from acute COVID-19 to Long-COVID. The vasculo-proliferative process predicted in Long-COVID might contribute to changes in the organ-specific proteome reflective of neurologic and cardiometabolic dysfunction.

CONCLUSIONS

Taken together, our findings point to a vasculo-proliferative process in Long-COVID that is likely initiated either prior hypoxia (localized or systemic) and/or stimulatory factors (i.e., cytokines, chemokines, growth factors, angiotensin, etc). Analyses of the plasma proteome, used as a surrogate for cellular signaling, unveiled potential organ-specific prognostic biomarkers and therapeutic targets.

Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning

BACKGROUND

Survivors of acute COVID-19 often suffer prolonged, diffuse symptoms post-infection, referred to as "Long-COVID". A lack of Long-COVID biomarkers and pathophysiological mechanisms limits effective diagnosis, treatment and disease surveillance. We performed targeted proteomics and machine learning analyses to identify novel blood biomarkers of Long-COVID.

METHODS

A case-control study comparing the expression of 2925 unique blood proteins in Long-COVID outpatients versus COVID-19 inpatients and healthy control subjects. Targeted proteomics was accomplished with proximity extension assays, and machine learning was used to identify the most important proteins for identifying Long-COVID patients. Organ system and cell type expression patterns were identified with Natural Language Processing (NLP) of the UniProt Knowledgebase.

RESULTS

Machine learning analysis identified 119 relevant proteins for differentiating Long-COVID outpatients (Bonferonni corrected P < 0.01). Protein combinations were narrowed down to two optimal models, with nine and five proteins each, and with both having excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, F1 = 1.00). NLP expression analysis highlighted the diffuse organ system involvement in Long-COVID, as well as the involved cell types, including leukocytes and platelets, as key components associated with Long-COVID.

CONCLUSIONS

Proteomic analysis of plasma from Long-COVID patients identified 119 highly relevant proteins and two optimal models with nine and five proteins, respectively. The identified proteins reflected widespread organ and cell type expression. Optimal protein models, as well as individual proteins, hold the potential for accurate diagnosis of Long-COVID and targeted therapeutics.

Cross-immunity against SARS-COV-2 variants of concern in naturally infected critically ill COVID-19 patients

Critically ill patients infected with SARS-CoV-2 display adaptive immunity, but it is unknown if they develop cross-reactivity to variants of concern (VOCs). We profiled cross-immunity against SARS-CoV-2 VOCs in naturally infected, non-vaccinated, critically ill COVID-19 patients. Wave-1 patients (wild-type infection) were similar in demographics to Wave-3 patients (wild-type/alpha infection), but Wave-3 patients had higher illness severity. Wave-1 patients developed increasing neutralizing antibodies to all variants, as did patients during Wave-3. Wave-3 patients, when compared to Wave-1, developed more robust antibody responses, particularly for wild-type, alpha, beta and delta variants. Within Wave-3, neutralizing antibodies were significantly less to beta and gamma VOCs, as compared to wild-type, alpha and delta. Patients previously diagnosed with cancer or chronic obstructive pulmonary disease had significantly fewer neutralizing antibodies. Naturally infected ICU patients developed adaptive responses to all VOCs, with greater responses in those patients more likely to be infected with the alpha variant, versus wild-type.

Novel plasma protein biomarkers from critically ill sepsis patients

BACKGROUND

Despite the high morbidity and mortality associated with sepsis, the relationship between the plasma proteome and clinical outcome is poorly understood. In this study, we used targeted plasma proteomics to identify novel biomarkers of sepsis in critically ill patients.

METHODS

Blood was obtained from 15 critically ill patients with suspected/confirmed sepsis (Sepsis-3.0 criteria) on intensive care unit (ICU) Day-1 and Day-3, as well as age- and sex-matched 15 healthy control subjects. A total of 1161 plasma proteins were measured with proximal extension assays. Promising sepsis biomarkers were narrowed with machine learning and then correlated with relevant clinical and laboratory variables.

RESULTS

The median age for critically ill sepsis patients was 56 (IQR 51-61) years. The median MODS and SOFA values were 7 (IQR 5.0-8.0) and 7 (IQR 5.0-9.0) on ICU Day-1, and 4 (IQR 3.5-7.0) and 6 (IQR 3.5-7.0) on ICU Day-3, respectively. Targeted proteomics, together with feature selection, identified the leading proteins that distinguished sepsis patients from healthy control subjects with ≥ 90% classification accuracy; 25 proteins on ICU Day-1 and 26 proteins on ICU Day-3 (6 proteins overlapped both ICU days; PRTN3, UPAR, GDF8, NTRK3, WFDC2 and CXCL13). Only 7 of the leading proteins changed significantly between ICU Day-1 and Day-3 (IL10, CCL23, TGFα1, ST2, VSIG4, CNTN5, and ITGAV; P < 0.01). Significant correlations were observed between a variety of patient clinical/laboratory variables and the expression of 15 proteins on ICU Day-1 and 14 proteins on ICU Day-3 (P < 0.05).

CONCLUSIONS

Targeted proteomics with feature selection identified proteins altered in critically ill sepsis patients relative to healthy control subjects. Correlations between protein expression and clinical/laboratory variables were identified, each providing pathophysiological insight. Our exploratory data provide a rationale for further hypothesis-driven sepsis research.

COVID-19 plasma proteome reveals novel temporal and cell-specific signatures for disease severity and high-precision disease management

Coronavirus disease 2019 (COVID-19) is a systemic inflammatory condition with high mortality that may benefit from personalized medicine and high-precision approaches. COVID-19 patient plasma was analysed with targeted proteomics of 1161 proteins. Patients were monitored from Days 1 to 10 of their intensive care unit (ICU) stay. Age- and gender-matched COVID-19-negative sepsis ICU patients and healthy subjects were examined as controls. Proteomic data were resolved using both cell-specific annotation and deep-analysis for functional enrichment. COVID-19 caused extensive remodelling of the plasma microenvironment associated with a relative immunosuppressive milieu between ICU Days 3-7, and characterized by extensive organ damage. COVID-19 resulted in (1) reduced antigen presentation and B/T-cell function, (2) increased repurposed neutrophils and M1-type macrophages, (3) relatively immature or disrupted endothelia and fibroblasts with a defined secretome, and (4) reactive myeloid lines. Extracellular matrix changes identified in COVID-19 plasma could represent impaired immune cell homing and programmed cell death. The major functional modules disrupted in COVID-19 were exaggerated in patients with fatal outcome. Taken together, these findings provide systems-level insight into the mechanisms of COVID-19 inflammation and identify potential prognostic biomarkers. Therapeutic strategies could be tailored to the immune response of severely ill patients.

Initial evaluation of extracorporeal immunomodulatory therapy for the treatment of critically ill COVID-19 infected patients

Severe COVID-19 infection results in significant immune dysregulation resulting from excessive recruitment and activation of neutrophils. The aim of this study was to confirm feasibility, initial safety and detect signal of efficacy of a non-propriety device delivered using an intermittent extra-corporeal system (LMOD) allowing leucocytes modulation in the setting of Severe COVID-19 infection. Twelve patients were recruited. Inclusion criteria were > 18 years age, confirmed COVID-19, acute respiratory distress syndrome requiring mechanical support and hypotension requiring vasopressor support. Primary end point was vasopressor requirements (expressed as epinephrine dose equivalents) and principle secondary endpoints related to safety, ability to deliver the therapy and markers of inflammation assessed over five days after treatment initiation. LMOD treatment appeared safe, defined by hemodynamic stability and no evidence of white cell number depletion from blood. We demonstrated a significant decrease in vasopressor doses (-37%, p = 0.02) in patients receiving LMOD therapy (despite these patients having to tolerate an additional extracorporeal intermittent therapy). Vasopressor requirements unchanged/increasing in control group (+ 10%, p = 0.48). Although much about the use of this therapy in the setting of severe COVID-19 infection remains to be defined (e.g. optimal dose and duration), this preliminary study supports the further evaluation of this novel extracorporeal approach.

Elevated vascular transformation blood biomarkers in Long-COVID indicate angiogenesis as a key pathophysiological mechanism

BACKGROUND

Long-COVID is characterized by prolonged, diffuse symptoms months after acute COVID-19. Accurate diagnosis and targeted therapies for Long-COVID are lacking. We investigated vascular transformation biomarkers in Long-COVID patients.

METHODS

A case-control study utilizing Long-COVID patients, one to six months (median 98.5 days) post-infection, with multiplex immunoassay measurement of sixteen blood biomarkers of vascular transformation, including ANG-1, P-SEL, MMP-1, VE-Cad, Syn-1, Endoglin, PECAM-1, VEGF-A, ICAM-1, VLA-4, E-SEL, thrombomodulin, VEGF-R2, VEGF-R3, VCAM-1 and VEGF-D.

RESULTS

Fourteen vasculature transformation blood biomarkers were significantly elevated in Long-COVID outpatients, versus acutely ill COVID-19 inpatients and healthy controls subjects (P < 0.05). A unique two biomarker profile consisting of ANG-1/P-SEL was developed with machine learning, providing a classification accuracy for Long-COVID status of 96%. Individually, ANG-1 and P-SEL had excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, P < 0.0001; validated in a secondary cohort). Specific to Long-COVID, ANG-1 levels were associated with female sex and a lack of disease interventions at follow-up (P < 0.05).

CONCLUSIONS

Long-COVID patients suffer prolonged, diffuse symptoms and poorer health. Vascular transformation blood biomarkers were significantly elevated in Long-COVID, with angiogenesis markers (ANG-1/P-SEL) providing classification accuracy of 96%. Vascular transformation blood biomarkers hold potential for diagnostics, and modulators of angiogenesis may have therapeutic efficacy.

Endothelial Glycocalyx Degradation in Critical Illness and Injury

The endothelial glycocalyx is a gel-like layer on the luminal side of blood vessels that is composed of glycosaminoglycans and the proteins that tether them to the plasma membrane. Interest in its properties and function has grown, particularly in the last decade, as its importance to endothelial barrier function has come to light. Endothelial glycocalyx studies have revealed that many critical illnesses result in its degradation or removal, contributing to endothelial dysfunction and barrier break-down. Loss of the endothelial glycocalyx facilitates the direct access of immune cells and deleterious agents (e.g., proteases and reactive oxygen species) to the endothelium, that can then further endothelial cell injury and dysfunction leading to complications such as edema, and thrombosis. Here, we briefly describe the endothelial glycocalyx and the primary components thought to be directly responsible for its degradation. We review recent literature relevant to glycocalyx damage in several critical illnesses (sepsis, COVID-19, trauma and diabetes) that share inflammation as a common denominator with actions by several common agents (hyaluronidases, proteases, reactive oxygen species, etc.). Finally, we briefly cover strategies and therapies that show promise in protecting or helping to rebuild the endothelial glycocalyx such as steroids, protease inhibitors, anticoagulants and resuscitation strategies.

Cohort-Specific Serological Recognition of SARS-CoV-2 Variant RBD Antigens

OBJECTIVE

Estimating the response of different population cohorts to new SARS-CoV-2 variants is important to customize measures of control. Our goal was to evaluate how antibodies from sera of infected and vaccinated people recognize antigens expressed by different SARS-CoV-2 variants.

METHODS

We compared sera from vaccinated donors and four patient/donor cohorts: Sera from critically ill patients collected 2-7 days and more than 10 days after admission to an intensive care unit, a NIBSC/WHO reference panel of SARS-CoV-2 positive individuals, and ambulatory or hospitalized (but not critically ill) positive donors. Samples were tested with an anti-SARS-CoV-2 ELISA kit coated with SARS-CoV-2 RBD recombinant antigens including mutations present in eleven of the most widespread variants.

RESULTS

Sera from vaccinated individuals exhibited higher antibody binding (P<0.001) than sera from infected (but not critically ill) individuals when tested against the wild type (WT) and each of 11 variants' receptor binding domain (RBD). Antibodies' binding to the SARS-CoV-2 antigens of at least 6 variants, including Variants of Concern (VOCs), was reduced in comparison to the WT in vaccinated and non-critically ill convalescence individuals.

CONCLUSION

Understanding differences between population cohorts in the antibody titers against WT vs variant RBD antigens can help design variant-specific immunoassays for surveillance and evaluation of the epidemiology of new variants.

Patients with severe COVID-19 do not have elevated autoantibodies against common diagnostic autoantigens

OBJECTIVES

Infection by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative pathogen of coronavirus disease 2019 (COVID-19) presents occasionally with an aberrant autoinflammatory response, including the presence of elevated circulating autoantibodies in some individuals. Whether the development of autoantibodies against self-antigens affects COVID-19 outcomes remains unclear. To better understand the prognostic role of autoantibodies in COVID-19, we quantified autoantibodies against 23 markers that are used for diagnosis of autoimmune disease. To this end, we used serum samples from patients with severe [intensive care unit (ICU)] and moderate (ward) COVID-19, across two to six consecutive time points, and compared autoantibody levels to uninfected healthy and ICU controls.

METHODS

Acute and post-acute serum (from 1 to 26 ICU days) was collected from 18 ICU COVID-19-positive patients at three to six time points; 18 ICU COVID-19-negative patients (sampled on ICU day 1 and 3); 21 ward COVID-19-positive patients (sampled on hospital day 1 and 3); and from 59 healthy uninfected controls deriving from two cohorts. Levels of IgG autoantibodies against 23 autoantigens, commonly used for autoimmune disease diagnosis, were measured in serum samples using MSD^® U-PLEX electrochemiluminescence technology (MSD division Meso Scale Discovery^®), and results were compared between groups.

RESULTS

There were no significant elevations of autoantibodies for any of the markers tested in patients with severe COVID-19.

CONCLUSIONS

Sample collections at longer time points should be considered in future studies, for assessing the possible development of autoantibody responses following infection with SARS-CoV-2.

A Distinct Metabolite Signature in Military Personnel Exposed to Repetitive Low-Level Blasts

Military Breachers and Range Staff (MBRS) are subjected to repeated sub-concussive blasts, and they often report symptoms that are consistent with a mild traumatic brain injury (mTBI). Biomarkers of blast injury would potentially aid blast injury diagnosis, surveillance and avoidance. Our objective was to identify plasma metabolite biomarkers in military personnel that were exposed to repeated low-level or sub-concussive blast overpressure. A total of 37 military members were enrolled (18 MBRS and 19 controls), with MBRS having participated in 8–20 breaching courses per year, with a maximum exposure of 6 blasts per day. The two cohorts were similar except that the number of blast exposures were significantly higher in the MBRS, and the MBRS cohort suffered significantly more post-concussive symptoms and poorer health on assessment. Metabolomics profiling demonstrated significant differences between groups with 74% MBRS classification accuracy (CA). Feature reduction identified 6 metabolites that resulted in a MBRS CA of 98%, and included acetic acid (23.7%), formate (22.6%), creatine (14.8%), acetone (14.2%), methanol (12,7%), and glutamic acid (12.0%). All 6 metabolites were examined with individual receiver operating characteristic (ROC) curve analyses and demonstrated areas-under-the-curve (AUCs) of 0.82–0.91 (P ≤ 0.001) for MBRS status. Several parsimonious combinations of three metabolites increased accuracy of ROC curve analyses to AUCs of 1.00 (P < 0.001), while a combination of volatile organic compounds (VOCs; acetic acid, acetone and methanol) yielded an AUC of 0.98 (P < 0.001). Candidate biomarkers for chronic blast exposure were identified, and if validated in a larger cohort, may aid surveillance and care of military personnel. Future point-of-care screening could be developed that measures VOCs from breath, with definitive diagnoses confirmed with plasma metabolomics profiling.

Pediatric severe traumatic brain injury mortality prediction determined with machine learning-based modeling

INTRODUCTION

Severe traumatic brain injury (sTBI) is a leading cause of mortality in children. As clinical prognostication is important in guiding optimal care and decision making, our goal was to create a highly discriminative sTBI outcome prediction model for mortality.

METHODS

Machine learning and advanced analytics were applied to the patient admission variables obtained from a comprehensive pediatric sTBI database. Demographic and clinical data, head CT imaging abnormalities and blood biochemical data from 196 children and adolescents admitted to a tertiary pediatric intensive care unit (PICU) with sTBI were integrated using feature ranking by way of a forest of randomized decision trees, and a model was generated from a reduced number of admission variables with maximal ability to discriminate outcome.

RESULTS

In total, 36 admission variables were analyzed using feature ranking with variable weighting to determine their predictive importance for mortality following sTBI. Reduction analysis utilizing Borata feature selection resulted in a parsimonious six-variable model with a mortality classification accuracy of 82%. The final admission variables that predicted mortality were: partial thromboplastin time (22%); motor Glasgow Coma Scale (21%); serum glucose (16%); fixed pupil(s) (16%); platelet count (13%) and creatinine (12%). Using only these six admission variables, a t-distributed stochastic nearest neighbor embedding algorithm plot demonstrated visual separation of sTBI patients that lived or died, with high mortality predictive ability of this model on the validation dataset (AUC = 0.90) which was confirmed with a conventional area-under-the-curve statistical approach on the total dataset (AUC = 0.91; P < 0.001).

CONCLUSIONS

Machine learning-based modeling identified the most clinically important prognostic factors resulting in a pragmatic, high performing prognostic tool for pediatric sTBI with excellent discriminative ability to predict mortality risk with 82% classification accuracy (AUC = 0.90). After external multicenter validation, our prognostic model might help to guide treatment decisions, aggressiveness of therapy and prepare family members and caregivers for timely end-of-life discussions and decision making.

LEVEL OF EVIDENCE

III; Prognostic.

Putative Concussion Biomarkers Identified in Adolescent Male Athletes Using Targeted Plasma Proteomics

Sport concussions can be difficult to diagnose and if missed, they can expose athletes to greater injury risk and long-lasting neurological disabilities. Discovery of objective biomarkers to aid concussion diagnosis is critical to protecting athlete brain health. To this end, we performed targeted proteomics on plasma obtained from adolescent athletes suffering a sports concussion. A total of 11 concussed male athletes were enrolled at our academic Sport Medicine Concussion Clinic, as well as 24 sex-, age- and activity-matched healthy control subjects. Clinical evaluation was performed and blood was drawn within 72 h of injury. Proximity extension assays were performed for 1,472 plasma proteins; a total of six proteins were considered significantly different between cohorts (P < 0.01; five proteins decreased and one protein increased). Receiver operating characteristic curves on the six individual protein biomarkers identified had areas-under-the-curves (AUCs) for concussion diagnosis ≥0.78; antioxidant 1 copper chaperone (ATOX1; AUC 0.81, P = 0.003), secreted protein acidic and rich in cysteine (SPARC; AUC 0.81, P = 0.004), cluster of differentiation 34 (CD34; AUC 0.79, P = 0.006), polyglutamine binding protein 1 (PQBP1; AUC 0.78, P = 0.008), insulin-like growth factor-binding protein-like 1 (IGFBPL1; AUC 0.78, P = 0.008) and cytosolic 5'-nucleotidase 3A (NT5C3A; AUC 0.78, P = 0.009). Combining three of the protein biomarkers (ATOX1, SPARC and NT5C3A), produced an AUC of 0.98 for concussion diagnoses (P < 0.001; 95% CI: 0.95, 1.00). Despite a paucity of studies on these three identified proteins, the available evidence points to their roles in modulating tissue inflammation and regulating integrity of the cerebral microvasculature. Taken together, our exploratory data suggest that three or less novel proteins, which are amenable to a point-of-care immunoassay, may be future candidate biomarkers for screening adolescent sport concussion. Validation with protein assays is required in larger cohorts.

Magnetic Resonance Imaging Findings Are Associated with Long-Term Global Neurological Function or Death after Traumatic Brain Injury in Critically Ill Children

The identification of children with traumatic brain injury (TBI) who are at risk of death or poor global neurological functional outcome remains a challenge. Magnetic resonance imaging (MRI) can detect several brain pathologies that are a result of TBI; however, the types and locations of pathology that are the most predictive remain to be determined. Forty-two critically ill children with TBI were recruited prospectively from pediatric intensive care units at five Canadian children's hospitals. Pathologies detected on subacute phase MRIs included cerebral hematoma, herniation, cerebral laceration, cerebral edema, midline shift, and the presence and location of cerebral contusion or diffuse axonal injury (DAI) in 28 regions of interest were assessed. Global functional outcome or death more than 12 months post-injury was assessed using the Pediatric Cerebral Performance Category score. Linear modeling was employed to evaluate the utility of an MRI composite score for predicting long-term global neurological function or death after injury, and nonlinear Random Forest modeling was used to identify which MRI features have the most predictive utility. A linear predictive model of favorable versus unfavorable long-term outcomes was significantly improved when an MRI composite score was added to clinical variables. Nonlinear Random Forest modeling identified five MRI variables as stable predictors of poor outcomes: presence of herniation, DAI in the parietal lobe, DAI in the subcortical white matter, DAI in the posterior corpus callosum, and cerebral contusion in the anterior temporal lobe. Clinical MRI has prognostic value to identify children with TBI at risk of long-term unfavorable outcomes.

Proteinase 3 contributes to endothelial dysfunction in an experimental model of sepsis

In sepsis-induced inflammation, polymorphonuclear neutrophils (PMNs) contribute to vascular dysfunction. The serine proteases proteinase 3 (PR3) and human leukocyte elastase (HLE) are abundant in PMNs and are released upon degranulation. While HLE's role in inflammation-induced endothelial dysfunction is well studied, PR3's role is largely uninvestigated. We hypothesized that PR3, similarly to HLE, contributes to vascular barrier dysfunction in sepsis. Plasma PR3 and HLE concentrations and their leukocyte mRNA levels were measured by ELISA and qPCR, respectively, in sepsis patients and controls. Exogenous PR3 or HLE was applied to human umbilical vein endothelial cells (HUVECs) and HUVEC dysfunction was assessed by FITC-dextran permeability and electrical resistance. Both PR3 and HLE protein and mRNA levels were significantly increased in sepsis patients (P < 0.0001 and P < 0.05, respectively). Additionally, each enzyme independently increased HUVEC monolayer FITC-dextran permeability (P < 0.01), and decreased electrical resistance in a time- and dose-dependent manner (P < 0.001), an effect that could be ameliorated by novel treatment with carbon monoxide-releasing molecule 3 (CORM-3). The serine protease PR3, in addition to HLE, lead to vascular dysfunction and increased endothelial permeability, a hallmark pathological consequence of sepsis-induced inflammation. CORMs may offer a new strategy to reduce serine protease-induced vascular dysfunction.

Epitope-specific antibody responses differentiate COVID-19 outcomes and variants of concern

BACKGROUNDThe role of humoral immunity in COVID-19 is not fully understood, owing, in large part, to the complexity of antibodies produced in response to the SARS-CoV-2 infection. There is a pressing need for serology tests to assess patient-specific antibody response and predict clinical outcome.METHODSUsing SARS-CoV-2 proteome and peptide microarrays, we screened 146 COVID-19 patients' plasma samples to identify antigens and epitopes. This enabled us to develop a master epitope array and an epitope-specific agglutination assay to gauge antibody responses systematically and with high resolution.RESULTSWe identified linear epitopes from the spike (S) and nucleocapsid (N) proteins and showed that the epitopes enabled higher resolution antibody profiling than the S or N protein antigen. Specifically, we found that antibody responses to the S-811-825, S-881-895, and N-156-170 epitopes negatively or positively correlated with clinical severity or patient survival. Moreover, we found that the P681H and S235F mutations associated with the coronavirus variant of concern B.1.1.7 altered the specificity of the corresponding epitopes.CONCLUSIONEpitope-resolved antibody testing not only affords a high-resolution alternative to conventional immunoassays to delineate the complex humoral immunity to SARS-CoV-2 and differentiate between neutralizing and non-neutralizing antibodies, but it also may potentially be used to predict clinical outcome. The epitope peptides can be readily modified to detect antibodies against variants of concern in both the peptide array and latex agglutination formats.FUNDINGOntario Research Fund (ORF) COVID-19 Rapid Research Fund, Toronto COVID-19 Action Fund, Western University, Lawson Health Research Institute, London Health Sciences Foundation, and Academic Medical Organization of Southwestern Ontario (AMOSO) Innovation Fund.

A Proteinase 3 Contribution to Juvenile Idiopathic Arthritis-Associated Cartilage Damage

A full understanding of the molecular mechanisms implicated in the etiopathogenesis of juvenile idiopathic arthritis (JIA) is lacking. A critical role for leukocyte proteolytic activity (e.g., elastase and cathepsin G) has been proposed. While leukocyte elastase’s (HLE) role has been documented, the potential contribution of proteinase 3 (PR3), a serine protease present in abundance in neutrophils, has not been evaluated. In this study we investigated: (1) PR3 concentrations in the synovial fluid of JIA patients using ELISA and (2) the cartilage degradation potential of PR3 by measuring the hydrolysis of fluorescently labeled collagen II in vitro. In parallel, concentrations and collagen II hydrolysis by HLE were assessed. Additionally, the levels of the co-secreted primary granule protein myeloperoxidase (MPO) were assessed in synovial fluid of patients diagnosed with JIA. We report the following levels of analytes in JIA synovial fluid: PR3—114 ± 100 ng/mL (mean ± SD), HLE—1272 ± 1219 ng/mL, and MPO—1129 ± 1659 ng/mL, with a very strong correlation between the PR3 and HLE concentrations (r_s = 0.898, p < 1 × 10^–6). Importantly, PR3 hydrolyzed fluorescently labeled collagen II as efficiently as HLE. Taken together, these novel findings suggest that PR3 (in addition to HLE) contributes to JIA-associated joint damage.

Novel severe traumatic brain injury blood outcome biomarkers identified with proximity extension assay

OBJECTIVES

Severe traumatic brain injury (sTBI) patients suffer high mortality. Accurate prognostic biomarkers have not been identified. In this exploratory study, we performed targeted proteomics on plasma obtained from sTBI patients to identify potential outcome biomarkers.

METHODS

Blood sample was collected from patients admitted to the ICU suffering a sTBI, using standardized clinical and computerized tomography (CT) imaging criteria. Age- and sex-matched healthy control subjects and sTBI patients were enrolled. Targeted proteomics was performed on plasma with proximity extension assays (1,161 proteins).

RESULTS

Cohorts were well-balanced for age and sex. The majority of sTBI patients were injured in motor vehicle collisions and the most frequent head CT finding was subarachnoid hemorrhage. Mortality rate for sTBI patients was 40%. Feature selection identified the top performing 15 proteins for identifying sTBI patients from healthy control subjects with a classification accuracy of 100%. The sTBI proteome was dominated by markers of vascular pathology, immunity/inflammation, cell survival and macrophage/microglia activation. Receiver operating characteristic (ROC) curve analyses demonstrated areas-under-the-curves (AUC) for identifying sTBI that ranged from 0.870-1.000 (p≤0.005). When mortality was used as outcome, ROC curve analyses identified the top 3 proteins as Willebrand factor (vWF), Wnt inhibitory factor-1 (WIF-1), and colony stimulating factor-1 (CSF-1). Combining vWF with either WIF-1 or CSF-1 resulted in excellent mortality prediction with AUC of 1.000 for both combinations (p=0.011).

CONCLUSIONS

Targeted proteomics with feature classification and selection distinguished sTBI patients from matched healthy control subjects. Two protein combinations were identified that accurately predicted sTBI patient mortality. Our exploratory findings require confirmation in larger sTBI patient populations.

Biomarkers of coagulation, endothelial function, and fibrinolysis in critically ill patients with COVID-19: A single-center prospective longitudinal study

BACKGROUND

Immunothrombosis and coagulopathy in the lung microvasculature may lead to lung injury and disease progression in coronavirus disease 2019 (COVID-19). We aim to identify biomarkers of coagulation, endothelial function, and fibrinolysis that are associated with disease severity and may have prognostic potential.

METHODS

We performed a single-center prospective study of 14 adult COVID-19(+) intensive care unit patients who were age- and sex-matched to 14 COVID-19(-) intensive care unit patients, and healthy controls. Daily blood draws, clinical data, and patient characteristics were collected. Baseline values for 10 biomarkers of interest were compared between the three groups, and visualized using Fisher's linear discriminant function. Linear repeated-measures mixed models were used to screen biomarkers for associations with mortality. Selected biomarkers were further explored and entered into an unsupervised longitudinal clustering machine learning algorithm to identify trends and targets that may be used for future predictive modelling efforts.

RESULTS

Elevated D-dimer was the strongest contributor in distinguishing COVID-19 status; however, D-dimer was not associated with survival. Variable selection identified clot lysis time, and antigen levels of soluble thrombomodulin (sTM), plasminogen activator inhibitor-1 (PAI-1), and plasminogen as biomarkers associated with death. Longitudinal multivariate k-means clustering on these biomarkers alone identified two clusters of COVID-19(+) patients: low (30%) and high (100%) mortality groups. Biomarker trajectories that characterized the high mortality cluster were higher clot lysis times (inhibited fibrinolysis), higher sTM and PAI-1 levels, and lower plasminogen levels.

CONCLUSIONS

Longitudinal trajectories of clot lysis time, sTM, PAI-1, and plasminogen may have predictive ability for mortality in COVID-19.

Proceedings From the Ice Hockey Summit III: Action on Concussion

OBJECTIVES

The Ice Hockey Summit III provided updated scientific evidence on concussions in hockey to inform these 5 objectives: (1) describe sport related concussion (SRC) epidemiology; (2) classify prevention strategies; (3) define objective, diagnostic tests; (4) identify treatment; and (5) integrate science and clinical care into prioritized action plans and policy.

METHODS

Our action plan evolved from 40 scientific presentations. The 155 attendees (physicians, athletic trainers, physical therapists, nurses, neuropsychologists, scientists, engineers, coaches, and officials) voted to prioritize these action items in the final Summit session.

RESULTS

To (1) establish a national and international hockey database for SRCs at all levels; (2) eliminate body checking in Bantam youth hockey games; (3) expand a behavior modification program (Fair Play) to all youth hockey levels; (4) enforce game ejection penalties for fighting in Junior A and professional hockey leagues; (5) establish objective tests to diagnose concussion at point of care; and (6) mandate baseline testing to improve concussion diagnosis for all age groups.

CONCLUSIONS

Expedient implementation of the Summit III prioritized action items is necessary to reduce the risk, severity, and consequences of concussion in the sport of ice hockey.

Autonomic Dysregulation in Adolescent Concussion Is Sex- and Posture-Dependent

OBJECTIVE

To study autonomic responses to postural changes in concussed adolescents. The influence of sex was also studied.

DESIGN

Longitudinal cohort observational study.

PARTICIPANTS

Concussed adolescents (CONC; n = 65; 26 male adolescents; age 15 ± 1 years, range = 12-18 years) and a control (CTRL) group of nonconcussed adolescents of similar age and sport (CTRL; n = 54; 29 male adolescents; age 14 ± 1 years, range = 12-18 years).

INTERVENTIONS

Concussed participants were monitored through 6 weekly visits throughout usual physician care. Control participants underwent 2 visits separated by at least 1 week to account for intrapersonal variation in testing measures.

MAIN OUTCOME MEASURES

Heart rate variability as the root mean square of successive differences in R-R intervals (RMSSD), heart rate (HR), and blood pressure [mean arterial pressure (MAP) and diastolic blood pressure (DBP)] were measured in supine, sitting, and standing postures.

RESULTS

A mixed analysis of variance revealed a group × sex × posture interaction (P = 0.04) where seated values of RMSSD were less in concussed female participants versus control female participants (42 ± 4 vs 61 ± 7 ms; P = 0.01; Mann-Whitney rank test). Compared with CTRL, CONC exhibited increased pretesting seated DBP (69 ± 1 vs 74 ± 1 mm Hg; P < 0.01), MAP (83 ± 1 vs 86 ± 1 mm Hg; P = 0.02), and baseline seated HR (72 ± 1 vs 77 ± 2 bpm; P = 0.03). Values of DBP (P = 0.03) and MAP (P < 0.01) improved at clinical discharge, whereas the RMSSD in female participants did not (P > 0.5). Data are mean ± SEM.

CONCLUSIONS

A modest reduction in female cardiac autonomic regulation was observed during seated postures. Alterations in seated concussed DBP and MAP, but not RMSSD, resolved at clinical discharge (median = 37 days). The results indicate that, in adolescents, concussion may impair cardiovagal function in a sex- and posture-dependent manner. The findings also suggest that BP metrics, but not RMSSD, are associated with clinical concussion recovery.

Plasma Protein Profiling by Proximity Extension Assay Technology Reveals Novel Biomarkers of Traumatic Brain Injury-A Pilot Study

BACKGROUND

Traumatic brain injury (TBI) is a significant public health issue affecting nearly 69 million patients worldwide per year. Reliable diagnostic biomarkers are urgently needed to aid in disease diagnosis and prognosis and to guide patient aftercare. Blood biomarkers represent an attractive modality to quickly, cheaply, and objectively evaluate clinical status. We hypothesize that deep and quantitative plasma proteomic profiling with a novel technology, proximity extension assay, may lead to the discovery of diagnostic and/or prognostic biomarkers of TBI.

METHODS

We used high-throughput proximity extension assays (PEA) to quantify the relative abundance of over 1000 unique proteins in plasma. PEA is a highly sensitive multiplex immunoassay capable of detecting very low-abundance proteins (down to fg/mL) in complex biological matrices. Our patient cohort consisted of severe TBI (sTBI) patients, matched healthy controls, and another non-TBI group that was included in the analysis to validate the specificity of the candidates during the selection process. The obtained protein quantification data was then filtered to identify candidate biomarkers through statistical analysis, literature searches, and comparison to our reference control groups.

RESULTS

Overall, we identified 6 novel candidate TBI biomarkers. Candidates exhibit a significant increase in plasma protein abundance in sTBI when comparing between healthy controls and sTBI patients. Candidates generally had low expression in our reference groups compared with the sTBI group.

CONCLUSIONS

Our preliminary findings represent a starting point for future validation. These biomarkers, either alone or in combination, may have significant clinical utility in aiding in TBI diagnosis, prognosis, and/or management.

Detection and Profiling of Human Coronavirus Immunoglobulins in Critically Ill Coronavirus Disease 2019 Patients

OBJECTIVES

Coronavirus disease 2019 continues to spread worldwide with high levels of morbidity and mortality. We performed anticoronavirus immunoglobulin G profiling of critically ill coronavirus disease 2019 patients to better define their underlying humoral response.

DESIGN

Blood was collected at predetermined ICU days to measure immunoglobulin G with a research multiplex assay against four severe acute respiratory syndrome coronavirus 2 proteins/subunits and against all six additionally known human coronaviruses.

SETTING

Tertiary care ICU and academic laboratory.

SUBJECTS

ICU patients suspected of being infected with severe acute respiratory syndrome coronavirus 2 had blood collected until either polymerase chain reaction testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until death or discharge if the patient tested polymerase chain reaction positive (coronavirus disease 2019 positive).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Age- and sex-matched healthy controls and ICU patients who were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients had greater body mass indexes, presented with bilateral pneumonias more frequently, and suffered lower Pao2:Fio2 ratios, when compared with coronavirus disease 2019 negative patients (p < 0.05). Mortality rate for coronavirus disease 2019 positive patients was 50%. On ICU days 1-3, anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G was significantly elevated in coronavirus disease 2019 positive patients, as compared to both healthy control subjects and coronavirus disease 2019 negative patients (p < 0.001). Weak severe acute respiratory syndrome coronavirus immunoglobulin G serologic responses were also detected, but not other coronavirus subtypes. The four anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G were maximal by ICU day 3, with all four anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G providing excellent diagnostic potential (severe acute respiratory syndrome coronavirus 2 Spike 1 protein immunoglobulin G, area under the curve 1.0, p < 0.0005; severe acute respiratory syndrome coronavirus receptor binding domain immunoglobulin G, area under the curve, 0.93-1.0; p ≤ 0.0001; severe acute respiratory syndrome coronavirus 2 Spike proteins immunoglobulin G, area under the curve, 1.0; p < 0.0001; severe acute respiratory syndrome coronavirus 2 Nucleocapsid protein immunoglobulin G area under the curve, 0.90-0.95; p ≤ 0.0003). Anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G increased and/or plateaued over 10 ICU days.

CONCLUSIONS

Critically ill coronavirus disease 2019 patients exhibited anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G, whereas serologic responses to non-severe acute respiratory syndrome coronavirus 2 antigens were weak or absent. Detection of human coronavirus immunoglobulin G against the different immunogenic structural proteins/subunits with multiplex assays may be useful for pathogen identification, patient cohorting, and guiding convalescent plasma therapy.

Evaluation of a population health strategy to reduce distracted driving: Examining all "Es" of injury prevention

BACKGROUND

Cell phone use while driving (CPWD) increases the risk of crashing and is a major contributor to injuries and deaths. The objective of this study was to describe the evaluation of a multifaceted, evidence-based population health strategy for the reduction of distracted driving.

METHODS

A multipronged campaign was undertaken from 2014 to 2016 for 16- to 44-year-olds, based on epidemiology, focused on personal stories and consequences, using the "Es" of injury prevention (epidemiology, education, environment, enforcement, and evaluation). Education consisted of distracted driving videos, informational cards, a social media AdTube campaign, and a movie theater trailer, which were evaluated with a questionnaire regarding CPWD attitudes, opinions, and behaviors. Spatial analysis of data within a geographic information system was used to target advertisements. A random sample telephone survey evaluated public awareness of the campaign. Increased CPWD enforcement was undertaken by police services and evaluated by ARIMA time series modeling.

RESULTS

The AdTube campaign had a view rate of >10% (41,101 views), slightly higher for females. The top performing age group was 18- to 24-year-olds (49%). Our survey found 61% of respondents used handheld CPWD (14% all of the time) with 80% reporting our movie trailer made them think twice about future CPWD. A stakeholder survey and spatial analysis targeted our advertisements in areas of close proximity to high schools, universities, near intersections with previous motor vehicle collisions, high traffic volumes, and population density. A telephone survey revealed that 41% of the respondents were aware of our campaign, 17% from our print and movie theater ads and 3% from social media. Police enforcement campaign blitzes resulted in 160 tickets for CPWD. Following campaign implementation, there was a statistically significant mean decrease of 462 distracted driving citations annually (p = 0.001).

CONCLUSION

A multifaceted, evidence-based population health strategy using the Es of injury prevention with interdisciplinary collaboration is a comprehensive method to be used for the reduction of distracted driving.

LEVEL OF EVIDENCE

Therapeutic, level IV.

Development of a Mortality Prediction Tool in Pediatric Severe Traumatic Brain Injury

Severe traumatic brain injury (sTBI) is a leading cause of pediatric death, yet outcomes remain difficult to predict. The goal of this study was to develop a predictive mortality tool in pediatric sTBI. We retrospectively analyzed 196 patients with sTBI (pre-sedation Glasgow Coma Scale [GCS] score <8 and head Maximum Abbreviated Injury Scale (MAIS) score >4) admitted to a pediatric intensive care unit (PICU). Overall, 56 patients with sTBI (29%) died during PICU stay. Of the survivors, 88 (63%) were discharged home, and 52 (37%) went to an acute care or rehabilitation facility. Receiver operating characteristic (ROC) curve analyses of admission variables showed that pre-sedation GCS score, Rotterdam computed tomography (CT) score, and partial thromboplastin time (PTT) were fair predictors of PICU mortality (area under the curve [AUC] = 0.79, 0.76, and 0.75, respectively; p < 0.001). Cutoff values best associated with PICU mortality were pre-sedation GCS score <5 (sensitivity = 0.91, specificity = 0.54), Rotterdam CT score >3 (sensitivity = 0.84, specificity = 0.53), and PTT >34.5 sec (sensitivity = 0.69 specificity = 0.67). Combining pre-sedation GCS score, Rotterdam CT score, and PTT in ROC curve analysis yielded an excellent predictor of PICU mortality (AUC = 0.91). In summary, pre-sedation GCS score (<5), Rotterdam CT score (>3), and PTT (>34.5 sec) obtained on hospital admission were fair predictors of PICU mortality, ranked highest to lowest. Combining these three admission variables resulted in an excellent pediatric sTBI mortality prediction tool for further prospective validation.

Concussion Acutely Decreases Plasma Glycerophospholipids in Adolescent Male Athletes

Concussions are frequent in sports and can contribute to significant and long-lasting neurological disability. Adolescents are particularly susceptible to concussions, with accurate determination of the injury challenging. Our previous study demonstrated that concussion diagnoses could be aided by metabolomics profiling and machine learning, with particular weighting on changes in plasma glycerophospholipids (PCs). Here, our aim was to report directional change of PCs after concussion and develop a diagnostic concussion panel utilizing a minimum number of plasma PCs. To this end, we enrolled 12 concussed male athletes at our academic Sport Medicine Concussion Clinic, as well as 17 sex-, age-, and activity-matched healthy controls. Blood was drawn and 71 plasma PCs were measured for statistically significant changes within 72 h of injury, and individual PCs were further analyzed with receiver operating characteristic (ROC) curves. Our data demonstrated that 26 of 71 PCs measured were significantly decreased after sports-related concussion (p < 0.01). None of the PCs increased in plasma after concussion. ROC curve analyses identified the top four PCs with areas under the curve (AUCs) ≥0.86 for concussion diagnosis: PCaeC36:0 (0.92; p < 0.001); PCaaC42:6 (0.90; p < 0.001); PCaeC36:2 (0.86; p = 0.001), and PCaaC32:0 (0.86; p = 0.001). Cut-off values in μM were ≤0.31, 0.22, 5.07, and 4.63, respectively. Importantly, combining these four PCs produced an AUC of 0.96 for concussion diagnoses (p < 0.001; 95% confidence interval, 0.89, 1.00). Our data suggest that as few as four circulating PCs may provide excellent diagnostic potential for adolescent concussion. External validation is required in larger cohorts.

Case Report: Inflammation and Endothelial Injury Profiling of COVID-19 Pediatric Multisystem Inflammatory Syndrome (MIS-C)

Introduction: COVID-19 is associated with a novel multi-system inflammatory syndrome that shares some characteristics with Kawasaki's Disease. The syndrome manifestation is delayed relative to COVID-19 onset, with a spectrum of clinical severity. Clinical signs may include persistent fever, gastrointestinal symptoms, cardiac inflammation and/or shock. Case Presentation: We measured 59 inflammatory and endothelial injury plasma analytes in an adolescent girl that presented with malaise, fever, cough, strawberry tongue and jaundice. Her COVID-19 status was positive with detection of 2 SARS-CoV-2 viral genes using polymerase chain reaction. She was treated with intravenous immunoglobulin prior to blood draw, but our plasma measurements suggested a unique analyte expression pattern associated with inflammation, endothelial injury and microvascular glycocalyx degradation. Conclusions: COVID-19 is associated with a multi-system inflammatory syndrome and a unique inflammatory and endothelial injury signature. Summary: Analyte markers of inflammation and endothelial cell injury might serve as putative biomarkers and/or be investigated further as potential therapeutic targets.

Clinical and Physiologic Factors Associated With Mode of Death in Pediatric Severe TBI

Aims and Objectives: Severe traumatic brain injury (sTBI) is the leading cause of death in children. Our aim was to determine the mode of death for children who died with sTBI in a Pediatric Critical Care Unit (PCCU) and evaluate factors associated with mortality. Methods: We performed a retrospective cohort study of all severely injured trauma patients (Injury Severity Score ≥ 12) with sTBI (Glasgow Coma Scale [GCS] ≤ 8 and Maximum Abbreviated Injury Scale ≥ 4) admitted to a Canadian PCCU (2000-2016). We analyzed mode of death, clinical factors, interventions, lab values within 24 h of admission (early) and pre-death (48 h prior to death), and reviewed meeting notes in patients who died in the PCCU. Results: Of 195 included patients with sTBI, 55 (28%) died in the PCCU. Of these, 31 (56%) had a physiologic death (neurologic determination of death or cardiac arrest), while 24 (44%) had withdrawal of life-sustaining therapies (WLST). Median (IQR) times to death were 35.2 (11.8, 86.4) hours in the physiologic group and 79.5 (17.6, 231.3) hours in the WLST group (p = 0.08). The physiologic group had higher partial thromboplastin time (PTT) within 24 h of admission (p = 0.04) and lower albumin prior to death (p = 0.04). Conclusions: Almost half of sTBI deaths in the PCCU were by WLST. There was a trend toward a longer time to death in these patients. We found few early and late (pre-death) factors associated with mode of death, namely higher PTT and lower albumin.

Blast in Context: The Neuropsychological and Neurocognitive Effects of Long-Term Occupational Exposure to Repeated Low-Level Explosives on Canadian Armed Forces' Breaching Instructors and Range Staff

Currently, there is strong interest within the military to better understand the effects of long-term occupational exposure to repeated low-level blast on health and performance. To gain traction on the chronic sequelae of blast, we focused on breaching—a tactical technique for gaining entry into closed/blocked spaces by placing explosives and maintaining a calculated safe distance from the detonation. Using a cross-sectional design, we compared the neuropsychological and neurocognitive profiles of breaching instructors and range staff to sex- and age-matched Canadian Armed Forces (CAF) controls. Univariate tests demonstrated that breaching was associated with greater post-concussive symptoms (Rivermead Post Concussion Symptoms Questionnaire) and lower levels of energy (RAND SF-36). In addition, breaching instructors and range staff were slower on a test that requires moving and thinking simultaneously (i.e., cognitive-motor integration). Next, using a multivariate approach, we explored the impact of other possible sources of injury, including concussion and prior war-zone deployment on the same outcomes. Concussion history was associated with higher post-concussive scores and musculoskeletal problems, whereas deployment was associated with higher post-concussive scores, but lower energy and greater PTSD symptomatology (using PCL-5). Our results indicate that although breaching, concussion, and deployment were similarly correlated with greater post-concussive symptoms, concussion history appears to be uniquely associated with altered musculoskeletal function, whereas deployment history appears to be uniquely associated with lower energy and risk of PTSD. We argue that the broader injury context must, therefore, be considered when studying the impact of repetitive low-level explosives on health and performance in military members.

Transcriptional profiling of leukocytes in critically ill COVID19 patients: implications for interferon response and coagulation

BACKGROUND

COVID19 is caused by the SARS-CoV-2 virus and has been associated with severe inflammation leading to organ dysfunction and mortality. Our aim was to profile the transcriptome in leukocytes from critically ill patients positive for COVID19 compared to those negative for COVID19 to better understand the COVID19-associated host response. For these studies, all patients admitted to our tertiary care intensive care unit (ICU) suspected of being infected with SARS-CoV-2, using standardized hospital screening methodologies, had blood samples collected at the time of admission to the ICU. Transcriptome profiling of leukocytes via ribonucleic acid sequencing (RNAseq) was then performed and differentially expressed genes as well as significantly enriched gene sets were identified.

RESULTS

We enrolled seven COVID19 + (PCR positive, 2 SARS-CoV-2 genes) and seven age- and sex-matched COVID19- (PCR negative) control ICU patients. Cohorts were well-balanced with the exception that COVID19- patients had significantly higher total white blood cell counts and circulating neutrophils and COVID19 + patients were more likely to suffer bilateral pneumonia. The mortality rate for this cohort of COVID19 + ICU patients was 29%. As indicated by both single-gene based and gene set (GSEA) approaches, the major disease-specific transcriptional responses of leukocytes in critically ill COVID19 + ICU patients were: (i) a robust overrepresentation of interferon-related gene expression; (ii) a marked decrease in the transcriptional level of genes contributing to general protein synthesis and bioenergy metabolism; and (iii) the dysregulated expression of genes associated with coagulation, platelet function, complement activation, and tumour necrosis factor/interleukin 6 signalling.

CONCLUSIONS

Our findings demonstrate that critically ill COVID19 + patients on day 1 of admission to the ICU display a unique leukocyte transcriptional profile that distinguishes them from COVID19- patients, providing guidance for future targeted studies exploring novel prognostic and therapeutic aspects of COVID19.

Brain Metabolite Levels in Sedentary Women and Non-contact Athletes Differ From Contact Athletes

White matter tracts are known to be susceptible to injury following concussion. The objective of this study was to determine whether contact play in sport could alter white matter metabolite levels in female varsity athletes independent of changes induced by long-term exercise. Metabolite levels were measured by single voxel proton magnetic resonance spectroscopy (MRS) in the prefrontal white matter at the beginning (In-Season) and end (Off-Season) of season in contact (N = 54, rugby players) and non-contact (N = 23, swimmers and rowers) varsity athletes. Sedentary women (N = 23) were scanned once, at a time equivalent to the Off-Season time point. Metabolite levels in non-contact athletes did not change over a season of play, or differ from age matched sedentary women except that non-contact athletes had a slightly lower myo-inositol level. The contact athletes had lower levels of myo-inositol and glutamate, and higher levels of glutamine compared to both sedentary women and non-contact athletes. Lower levels of myo-inositol in non-contact athletes compared to sedentary women indicates long-term exercise may alter glial cell profiles in these athletes. The metabolite differences observed between contact and non-contact athletes suggest that non-contact athletes should not be used as controls in studies of concussion in high-impact sports because repetitive impacts from physical contact can alter white matter metabolite level profiles. It is imperative to use athletes engaged in the same contact sport as controls to ensure a matched metabolite profile at baseline.

Metabolomics Profiling of Critically Ill Coronavirus Disease 2019 Patients: Identification of Diagnostic and Prognostic Biomarkers

OBJECTIVES

Coronavirus disease 2019 continues to spread rapidly with high mortality. We performed metabolomics profiling of critically ill coronavirus disease 2019 patients to understand better the underlying pathologic processes and pathways, and to identify potential diagnostic/prognostic biomarkers.

DESIGN

Blood was collected at predetermined ICU days to measure the plasma concentrations of 162 metabolites using both direct injection-liquid chromatography-tandem mass spectrometry and proton nuclear magnetic resonance.

SETTING

Tertiary-care ICU and academic laboratory.

SUBJECTS

Patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome coronavirus 2, using standardized hospital screening methodologies, had blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until ICU day 10 if the patient tested positive (coronavirus disease 2019 positive).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Age- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well balanced with the exception that coronavirus disease 2019 positive patients suffered bilateral pneumonia more frequently than coronavirus disease 2019 negative patients. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. Feature selection identified the top-performing metabolites for identifying coronavirus disease 2019 positive patients from healthy control subjects and was dominated by increased kynurenine and decreased arginine, sarcosine, and lysophosphatidylcholines. Arginine/kynurenine ratio alone provided 100% classification accuracy between coronavirus disease 2019 positive patients and healthy control subjects (p = 0.0002). When comparing the metabolomes between coronavirus disease 2019 positive and coronavirus disease 2019 negative patients, kynurenine was the dominant metabolite and the arginine/kynurenine ratio provided 98% classification accuracy (p = 0.005). Feature selection identified creatinine as the top metabolite for predicting coronavirus disease 2019-associated mortality on both ICU days 1 and 3, and both creatinine and creatinine/arginine ratio accurately predicted coronavirus disease 2019-associated death with 100% accuracy (p = 0.01).

CONCLUSIONS

Metabolomics profiling with feature classification easily distinguished both healthy control subjects and coronavirus disease 2019 negative patients from coronavirus disease 2019 positive patients. Arginine/kynurenine ratio accurately identified coronavirus disease 2019 status, whereas creatinine/arginine ratio accurately predicted coronavirus disease 2019-associated death. Administration of tryptophan (kynurenine precursor), arginine, sarcosine, and/or lysophosphatidylcholines may be considered as potential adjunctive therapies.

Identification of adverse events in pediatric severe traumatic brain injury patients to target evidence-based prevention for increased performance improvement and patient safety

INTRODUCTION

Trauma centres are required to continuously measure, evaluate and improve care. Severe traumatic brain injury (sTBI) patients are highly susceptible to adverse events (AE; unintended, potentially harmful events resulting from health care) due to their unstable condition requiring high risk interventions, multiple medications and invasive monitoring. Objectives were to describe: (1) a process for identifying AE in pediatric sTBI patients to identify safety risks, target and implement evidence-based prevention strategies; and (2) a tertiary care PICU's sTBI AE experience.

METHODS

Merging databases, Trauma Registry with Adverse Events Management System, identified AE in patients. Details on the event location, type and severity of harm were combined with patient demographics, injury data, costs and outcomes in a cohort of 193 PICU sTBI patients (2000-15). Descriptive statistics and multivariate logistic regression were undertaken to describe AE, and their association with risk factors and outcomes.

RESULTS

103/193 sTBI patients (53%) suffered at least one AE. 238 AE occurred (1.23 AE/patient), with 30% of patients having 2+ AE. Most resulted in no harm (54%) with decubitus ulcers (15%) the most common AE. AE patients were more likely to be monitored for elevated ICP (p<0.001), with fewer ventilator-free days (p=0.015), longer LOS for PICU (11 vs. 3.5 days; p<0.001) and in-hospital (31 vs. 11 days; p<0.001) with higher median costs ($121,234 vs. $53,341; p=0.031). AE patients required a higher level of care on discharge (p=0.035).

CONCLUSIONS

Merging databases is an effective practice to identify AE and safety risks in trauma populations. Utilizing this method, a PICU AE rate of 1.23 events per patient was found with TBI severity the most important factor to increase the odds of AE. AE represent performance improvement events, opportunities to optimize care, decrease costs, as well as improve outcomes, to ultimately improve patient safety in this vulnerable population.

Inflammation Profiling of Critically Ill Coronavirus Disease 2019 Patients

OBJECTIVES

Coronavirus disease 2019 is caused by severe acute respiratory syndrome-coronavirus-2 infection to which there is no community immunity. Patients admitted to ICUs have high mortality, with only supportive therapies available. Our aim was to profile plasma inflammatory analytes to help understand the host response to coronavirus disease 2019.

DESIGN

Daily blood inflammation profiling with immunoassays.

SETTING

Tertiary care ICU and academic laboratory.

SUBJECTS

All patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome-coronavirus-2, using standardized hospital screening methodologies, had daily blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative), or until ICU day 7 if the patient was positive (coronavirus disease 2019 positive).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Age- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients were more likely than coronavirus disease 2019 negative patients to suffer bilateral pneumonia. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. We measured 57 inflammatory analytes and then analyzed with both conventional statistics and machine learning. Twenty inflammatory analytes were different between coronavirus disease 2019 positive patients and healthy controls (p < 0.01). Compared with coronavirus disease 2019 negative patients, coronavirus disease 2019 positive patients had 17 elevated inflammatory analytes on one or more of their ICU days 1-3 (p < 0.01), with feature classification identifying the top six analytes between cohorts as tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2. While tumor necrosis factor, granzyme B, heat shock protein 70, and interleukin-18 were elevated for all seven ICU days, interferon-gamma-inducible protein 10 transiently elevated on ICU days 2 and 3 and elastase 2 increased over ICU days 2-7. Inflammation profiling predicted coronavirus disease 2019 status with 98% accuracy, whereas elevated heat shock protein 70 was strongly associated with mortality.

CONCLUSIONS

While many inflammatory analytes were elevated in coronavirus disease 2019 positive ICU patients, relative to healthy controls, the top six analytes distinguishing coronavirus disease 2019 positive ICU patients from coronavirus disease 2019 negative ICU patients were tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2.