Victoria J. Wright’s research while affiliated with Imperial College London and other places
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Multisystem inflammatory syndrome in children is a post-infectious presentation SARS-CoV-2 associated with expansion of the T cell receptor Vβ21.3+ T-cell subgroup. Here we apply muti-single cell omics to compare the inflammatory process in children with acute respiratory COVID-19 and those presenting with non SARS-CoV-2 infections in children. Here we show that in Multi-Inflammatory Syndrome in Children (MIS-C), the natural killer cell and monocyte population demonstrate heightened CD95 (Fas) and Interleuking 18 receptor expression. Additionally, TCR Vβ21.3+ CD4+ T-cells exhibit skewed differentiation towards T helper 1, 17 and regulatory T cells, with increased expression of the co-stimulation receptors ICOS, CD28 and interleukin 18 receptor. We observe no functional evidence for NLRP3 inflammasome pathway overactivation, though MIS-C monocytes show elevated active caspase 8. This, coupled with raised IL18 mRNA expression in CD16- NK cells on single cell RNA sequencing analysis, suggests interleukin 18 and CD95 signalling may trigger activation of TCR Vβ21.3+ T-cells in MIS-C, driven by increased IL-18 production from activated monocytes and CD16- Natural Killer cells.
Objectives
Optimization of antimicrobial stewardship (AMS) is key to tackling antimicrobial resistance (AMR), which is exacerbated by over-prescription of antibiotics in pediatric Emergency Departments (EDs). We described patterns of empiric antibiotic use in European EDs, and characterized appropriateness and consistency of prescribing.
Methods
Between August 2016 and December 2019 febrile children attending the ED in nine European countries with suspected infection were recruited into the PERFORM (Personalised Risk assessment in Febrile illness to Optimise Real-life Management) study. Empiric systemic antibiotic use was determined in view of assigned final ‘bacterial’ or ‘viral’ phenotype. Antibiotics were classified according to WHO AWaRe.
Results
Of 2130 febrile episodes (excluding children with non-bacterial/non-viral phenotypes), 1549 (72.7%) were assigned a ‘bacterial’ and 581 (27.3%) a ‘viral’ phenotype. A total of 1318/1549 (85.1%) episodes with a ‘bacterial’ and 269/581 (46.3%) with a ‘viral’ phenotype received empiric systemic antibiotics (first two days of admission). Of those, the majority (87.8% in ‘bacterial’ and 87.0% in ‘viral’ group) received parenteral antibiotics. The top three antibiotics prescribed were third-generation cephalosporins, penicillins and penicillin/beta-lactamase inhibitor combinations. Of those treated with empiric systemic antibiotics in the ‘viral’ group 216/269 (80.3%) received ≥ one Watch antibiotic.
Conclusions
Differentiating bacterial from viral etiology in febrile illness on initial ED presentation remains challenging, resulting in a substantial over-prescription of antibiotics. A significant proportion of patients with a ‘viral’ phenotype received systemic antibiotics, predominantly classified as WHO Watch. Rapid and accurate point-of-care tests in the ED differentiating between bacterial and viral etiology, could significantly improve AMS.
Gene expression has great potential to be used as a clinical diagnostic tool. However, despite the progress in identifying these gene expression signatures, clinical translation has been hampered by a lack of purpose-built, readily deployable testing platforms. We have developed Competitive Amplification Networks (CANs) to enable analysis of an entire gene expression signature in a single PCR reaction. CANs consist of natural and synthetic amplicons that compete for shared primers during amplification, forming a reaction network that leverages the molecular machinery of PCR. These reaction components are tuned such that the final fluorescent signal from the assay is exactly calibrated to the conclusion of a statistical model. In essence, the reaction acts as a biological computer, simultaneously detecting the RNA targets, interpreting their level in the context of the gene expression signature, and aggregating their contributions to the final diagnosis. We illustrate the clinical validity of this technique, demonstrating perfect diagnostic agreement with the gold-standard approach of measuring each gene independently. Crucially, CAN assays are compatible with existing qPCR instruments and workflows. CANs hold the potential to enable rapid deployment and massive scalability of gene expression analysis to clinical laboratories around the world, in highly developed and low-resource settings alike.
Abstract Figure
Background
Emergency admissions for infection often lack initial diagnostic certainty. COVID-19 has highlighted a need for novel diagnostic approaches to indicate likelihood of viral infection in a pandemic setting. We aimed to derive and validate a blood transcriptional signature to detect viral infections, including COVID-19, among adults with suspected infection who presented to the emergency department.
Methods
Individuals (aged ≥18 years) presenting with suspected infection to an emergency department at a major teaching hospital in the UK were prospectively recruited as part of the Bioresource in Adult Infectious Diseases (BioAID) discovery cohort. Whole-blood RNA sequencing was done on samples from participants with subsequently confirmed viral, bacterial, or no infection diagnoses. Differentially expressed host genes that met additional filtering criteria were subjected to feature selection to derive the most parsimonious discriminating signature. We validated the signature via RT-qPCR in a prospective validation cohort of participants who presented to an emergency department with undifferentiated fever, and a second case-control validation cohort of emergency department participants with PCR-positive COVID-19 or bacterial infection. We assessed signature performance by calculating the area under receiver operating characteristic curves (AUROCs), sensitivities, and specificities.
Findings
A three-gene transcript signature, comprising HERC6, IGF1R, and NAGK, was derived from the discovery cohort of 56 participants with bacterial infections and 27 with viral infections. In the validation cohort of 200 participants, the signature differentiated bacterial from viral infections with an AUROC of 0·976 (95% CI 0·919−1·000), sensitivity of 97·3% (85·8−99·9), and specificity of 100% (63·1−100). The AUROC for C-reactive protein (CRP) was 0·833 (0·694−0·944) and for leukocyte count was 0·938 (0·840−0·986). The signature achieved higher net benefit in decision curve analysis than either CRP or leukocyte count for discriminating viral infections from all other infections. In the second validation analysis, which included SARS-CoV-2-positive participants, the signature discriminated 35 bacterial infections from 34 SARS-CoV-2-positive COVID-19 infections with AUROC of 0·953 (0·893−0·992), sensitivity 88·6%, and specificity of 94·1%.
Interpretation
This novel three-gene signature discriminates viral infections, including COVID-19, from other emergency infection presentations in adults, outperforming both leukocyte count and CRP, thus potentially providing substantial clinical utility in managing acute presentations with infection.
Funding
National Institute for Health Research, Medical Research Council, Wellcome Trust, and EU-FP7.
Purpose
Despite significant progress, challenges remain in the management of critically ill children, including early identification of infection and organ failure and robust early risk stratification to predict poor outcome. The Biomarkers of Acute Serious Illness in Children study aims to identify genetic and biological pathways underlying the development of critical illness in infections and organ failure and those leading to poor outcome (death or severe disability) in children requiring emergency intensive care.
Participants
We recruited a prospective cohort of critically ill children undergoing emergency transport to four paediatric intensive care units (PICUs) in Southeast England between April 2014 and December 2016.
Findings to date
During the study period, 1017 patients were recruited by the regional PICU transport team, and blood and urine samples were obtained at/around first contact with the patient by the transport team. Consent for participation in the study was deferred until after PICU admission and 674 parents/carers were consented. Further samples (blood, urine, stool and throat swabs) were collected after consent. Samples were processed and stored for genomic, transcriptomic, proteomic and metabolomic analyses. Demographic, clinical and laboratory data at first contact, during PICU stay and at discharge, were collected, as were detailed data regarding infectious or non-infectious aetiology. In addition, 115 families have completed 12-month validated follow-up questionnaires to assess quality of life and child behaviour.
The first phase of sample analyses (transcriptomic profiling) is currently in progress.
Future plans
Stored samples will be analysed using genomic, proteomic and metabolic profiling. Advanced bioinformatics techniques will be used to identify biomarkers for early diagnosis of infection, identification of organ failure and risk stratification to predict poor outcome (death/severe disability).
Trial registration number
NCT03238040 .
The WHO estimates around a million children contract tuberculosis (TB) annually with over 80 000 deaths from dissemination of infection outside of the lungs. The insidious onset and association with skin test anergy suggests failure of the immune system to both recognise and respond to infection. To understand the immune mechanisms, we studied genome-wide whole blood RNA expression in children with TB meningitis (TBM). Findings were validated in a second cohort of children with TBM and pulmonary TB (PTB), and functional T-cell responses studied in a third cohort of children with TBM, other extrapulmonary TB (EPTB) and PTB. The predominant RNA transcriptional response in children with TBM was decreased abundance of multiple genes, with 140/204 (68%) of all differentially regulated genes showing reduced abundance compared to healthy controls. Findings were validated in a second cohort with concordance of the direction of differential expression in both TBM (r² = 0.78 p = 2x10⁻¹⁶) and PTB patients (r² = 0.71 p = 2x10⁻¹⁶) when compared to a second group of healthy controls. Although the direction of expression of these significant genes was similar in the PTB patients, the magnitude of differential transcript abundance was less in PTB than in TBM. The majority of genes were involved in activation of leucocytes (p = 2.67E⁻¹¹) and T-cell receptor signalling (p = 6.56E⁻⁰⁷). Less abundant gene expression in immune cells was associated with a functional defect in T-cell proliferation that recovered after full TB treatment (p<0.0003). Multiple genes involved in T-cell activation show decreased abundance in children with acute TB, who also have impaired functional T-cell responses. Our data suggest that childhood TB is associated with an acquired immune defect, potentially resulting in failure to contain the pathogen. Elucidation of the mechanism causing the immune paresis may identify new treatment and prevention strategies.
Distinguishing children with potentially life-threatening bacterial infections from febrile children with viral infections remains a major challenge. Herberg and colleagues,¹ in a preliminary, cross-sectional study of 370 febrile children (aged <17 years) in Europe and the United States, reported that children with bacterial infection may be characterized by the difference in blood RNA expression values of 2 genes. In a recent study, Mahajan and colleagues² reported a 66-transcript blood RNA signature that distinguished bacterial from viral infection in 279 febrile infants younger than 60 days. Young infants are at high risk of bacterial infection; diagnosis is difficult and prompt treatment important. To provide further validation of the 2-gene signature and to evaluate its performance in the infant population, we applied the signature to the RNA expression data of Mahajan et al.
Motivation:
We introduce PRINCESS, a privacy-preserving international collaboration framework for analyzing rare disease genetic data that are distributed across different continents. PRINCESS leverages Software Guard Extensions (SGX) and hardware for trustworthy computation. Unlike a traditional international collaboration model, where individual-level patient DNA are physically centralized at a single site, PRINCESS performs a secure and distributed computation over encrypted data, fulfilling institutional policies and regulations for protected health information.
Results:
To demonstrate PRINCESS' performance and feasibility, we conducted a family-based allelic association study for Kawasaki Disease, with data hosted in three different continents. The experimental results show that PRINCESS provides secure and accurate analyses much faster than alternative solutions, such as homomorphic encryption and garbled circuits (over 40 000× faster).
Availability and implementation:
https://github.com/achenfengb/PRINCESS_opensource CONTACT: shw070@ucsd.eduSupplementary information: Supplementary data are available at Bioinformatics online.
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Citations (16)
... Other potential TCR binding sites were also identified, including a site with homology to known neurotoxins. Modeling and sequence analyses work reaffirmed the TCR binding hypothesis (3)(4)(5), and recent work exploring the link between MIS-C and SARS-CoV-2 infection in children theorized activation by a viral superantigen (6). Further commentary has even raised the possibility of a link between the proposed TCR interaction and severe acute hepatitis in children (7). ...
... For example, extraction of features from unstructured clinical notes through natural language processing (NLP) techniques as well as the use of photo or video data as training features (e.g. for predicting/detecting middle ear infections, diabetic foot ulcers, or surgical site infections) have started to be increasingly explored over the past few years [106][107][108][109][110][111][112][113][114][115]. In addition, automated streaming or recording of heart rate variability, respiration, and/or body motion, or also of raw biosignals have been explored as relevant features for training ML models to recognize development of sepsis in neonates [116][117][118][119][120]. Finally, a future increase in the availability of omics data from routine clinical practice holds promises to further improve the predictive accuracy of ML-based models for the early detection of bacterial infections or their imminent/rapid worsening, in turn impacting the use of antibiotics [121,122]. ...
... We also compared the host transcriptional profile of patients with LRTI caused by SARS-CoV-2, other viral etiologies, and bacterial etiology, in order to identify differentially expressed genes including those involved in the activation of host immune pathways. Finally, we evaluated promising published gene signatures (29)(30)(31)(32) that effectively discriminate between bacterial and viral etiology in our transcriptional data set. ...
... A growing body of research suggests that individual infectious and inflammatory diseases are characterised by unique patterns of host RNA abundance in whole blood. Sparse gene signatures, based on small numbers of transcripts have been reported for several diseases including tuberculosis disease [16][17][18] , malaria [19], bacterial and viral infections [20,21], and KD [22]. MIS-C has already been shown to elicit specific changes in gene expression compared to healthy controls and paediatric COVID-19 using targeted and untargeted transcriptomic approaches, respectively [23,24]. ...
... Blood samples from the multicentre Biomarkers of Acute Serious Illness in Children (BASIC) biobank were used to measure NFL. The methods and cohort profiles of children enrolled in BASIC have been previously described [21]. Briefly, children 0-16 years of age (excluding those < 36 weeks of gestation) were enrolled into BASIC if they (i) were being transported to one of three participating PICUs by the regional intensive care transport service as an emergency admission and (ii) had an indwelling arterial or venous catheter for sampling. ...
... Previous studies have shown lower numbers of T cells, reduced ability to respond to Mycobacterium tuberculosis antigens or reduced expression of activation markers and cytokine production in TBM compared to PTB and healthy individuals (van Laarhoven et al., 2019;Davoudi et al., 2008;Shridhar et al., 2022. This impaired T cell function has correlated with disease severity and poor clinical outcomes in participants with PTB and TBM van Laarhoven et al., 2019;An et al., 2022;Hemingway et al., 2017). ...
... This recruits FH to the bacterial cell surface, whose normal function is to protect surfaces from AP-driven complement attack, which negates APdriven complement activation and cell killing. In support of the importance of this role of N. meningitidis immune evasion through binding FH is the genome-wide association study linking CFH variants with meningococcal disease susceptibility (Davila et al., 2010;Martinon-Torres et al., 2016). Additionally, FHR-3 also binds FHbp (Fig. 2) and competitively inhibits FHbp binding to FH (Caesar et al., 2014;Schneider et al., 2009). ...
... Among these, transcriptomics presents itself as a particularly promising approach. Host RNA expression signatures have been proven capable of discriminating bacterial infections from viral infections in young infants with high sensitivity and specificity [9][10][11]. Furthermore, clinical implementation of a bedside two-gene signature is showing promising results [12]. ...
... As such a common use case of SGX is for secure outsourced computation, in which a user with limited computational capabilities sends private data to a remote SGX enclave, controlled by an untrusted party, for secure data processing. This enticing possibility has been gathering increasing attention in the bioinformatics community in recent years [22,23,24,25,26,27,16,28,29,30] due to its potential to accelerate scientific discoveries by facilitating the sharing of sensitive biomedical data. For security in the outsourcing scenario, SGX usually employs a cryptographic protocol called remote attestation to provide proof to a remote user that both the enclave environment and the application running inside the enclave would not be tampered with; and that the communication channel for the transfer of sensitive data is secure. ...
... Furthermore, mutation of the miR-223-3p binding sites within the Slc8a1 3'-UTR abolished this effect, substantiating the specificity of this interaction (Fig. 2H). Previous reports that Slc8a1 and its encoded protein NCX1 are highly associated with arrhythmias in humans and cardiovascular inflammation in infants [23,24], we believe that the enrichment of the miRNAs and their downstream target genes in the heart rate pathway, as analyzed here, substantiates their potential binding functionality. Table 2 listed the top DEmiRNAs and their various targets. ...