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1.
medrxiv; 2023.
Preprint en Inglés | medRxiv | ID: ppzbmed-10.1101.2023.09.03.23294989

RESUMEN

Background. The overlapping clinical presentations of patients with acute respiratory disease can complicate disease diagnosis. Whilst PCR diagnostic methods to identify SARS-CoV-2 are highly sensitive, they have their shortcomings including false-positive risk and slow turnaround times. Changes in host gene expression can be used to distinguish between disease groups of interest, providing a viable alternative to infectious disease diagnosis. Methods. We interrogated the whole blood gene expression profiles of patients with COVID-19 (n=87), bacterial infections (n=88), viral infections (n=36), and not-infected controls (n=27) to identify a sparse diagnostic signature for distinguishing COVID-19 from other clinically similar infectious and non-infectious conditions. The sparse diagnostic signature underwent validation in a new cohort using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and then underwent further external validation in an independent in silico RNA-seq cohort. Findings. We identified a 10-gene signature (OASL, UBP1, IL1RN, ZNF684, ENTPD7, NFKBIE, CDKN1C, CD44, OTOF, MSR1) that distinguished COVID-19 from other infectious and non-infectious diseases with an AUC of 87.1% (95% CI: 82.6%-91.7%) in the discovery cohort and 88.7% and 93.6% when evaluated in the RT-qPCR validation, and in silico cohorts respectively. Interpretation. Using well-phenotyped samples collected from patients admitted acutely with a spectrum of infectious and non-infectious syndromes, we provide a detailed catalogue of blood gene expression at the time of hospital admission. The findings result in the identification of a 10-gene host diagnostic signature to accurately distinguish COVID-19 from other infection syndromes presenting to hospital. This could be developed into a rapid point-of-care diagnostic test, providing a valuable syndromic diagnostic tool for future early pandemic use.


Asunto(s)
Enfermedades Transmisibles Emergentes , Infecciones , Síndrome Respiratorio Agudo Grave , Infecciones Bacterianas , Enfermedades Transmisibles , Virosis , COVID-19
2.
medrxiv; 2023.
Preprint en Inglés | medRxiv | ID: ppzbmed-10.1101.2023.03.09.23287028

RESUMEN

Background: The amount of SARS-CoV-2 detected in the upper respiratory tract (URT viral load) is a key driver of transmission of infection. Current evidence suggests that mechanisms constraining URT viral load are different from those controlling lower respiratory tract viral load and disease severity. Understanding such mechanisms may help to develop treatments and vaccine strategies to reduce transmission. Combining mathematical modelling of URT viral load dynamics with transcriptome analyses we aimed to identify mechanisms controlling URT viral load. Methods: COVID-19 patients were recruited in Spain during the first wave of the pandemic. RNA sequencing of peripheral blood and targeted NanoString nCounter transcriptome analysis of nasal epithelium were performed and gene expression analysed in relation to paired URT viral load samples collected within 15 days of symptom onset. Proportions of major immune cells in blood were estimated from transcriptional data using computational differential estimation. Weighted correlation network analysis (adjusted for cell proportions) and fixed transcriptional repertoire analysis were used to identify associations with URT viral load, quantified as standard deviations (z-scores) from an expected trajectory over time. Results: Eighty-two subjects (50% female, median age 54 years (range 3-73)) with COVID-19 were recruited. Paired URT viral load samples were available for 16 blood transcriptome samples, and 17 respiratory epithelial transcriptome samples. Natural Killer (NK) cells were the only blood cell type significantly correlated with URT viral load z-scores (r = -0.62, P = 0.010). Twenty-four blood gene expression modules were significantly correlated with URT viral load z-score, the most significant being a module of genes connected around IFNA14 (Interferon Alpha-14) expression (r = -0.60, P = 1e-10). In fixed repertoire analysis, prostanoid-related gene expression was significantly associated with higher viral load. In nasal epithelium, only GNLY (granulysin) gene expression showed significant negative correlation with viral load. Conclusions: Correlations between the transcriptional host response and inter-individual variations in SARS-CoV-2 URT viral load, revealed many molecular mechanisms plausibly favouring or constraining viral load. Existing evidence corroborates many of these mechanisms, including likely roles for NK cells, granulysin, prostanoids and interferon alpha-14. Inhibition of prostanoid production, and administration of interferon alpha-14 may be attractive transmission-blocking interventions.


Asunto(s)
COVID-19
3.
medrxiv; 2022.
Preprint en Inglés | medRxiv | ID: ppzbmed-10.1101.2022.03.31.22273171

RESUMEN

ABSTRACT Tuberculosis (TB) disease causes up to 1.5 million deaths every year and represents an important problem of public health at worldwide level. Here, we quantified the gene expression signatures of granuloma biopsies across human TB pulmonary lesions, and validated the best gene candidates using NanoString technology, profiling 157 samples from 40 TB patients who underwent surgery. We characterised the transcriptional profile of the TB granuloma in comparison to healthy tissue, described an 11-gene signature and measured 7 proteins in plasma associated with it. We demonstrated a gradient of immune-related transcript abundance across the granuloma substructure and evidenced metabolically-active Mycobacterium tuberculosis in the lesions. Patients who converted to sputum negative after two months of starting treatment, showed enriched inflammatory pathways in the lesion several months after, supporting use of sputum culture conversion (SCC) as a prognostic biomarker during clinical management and as a factor to prioritise patients when considering lung surgery.


Asunto(s)
Granuloma , Tuberculosis
4.
medrxiv; 2021.
Preprint en Inglés | medRxiv | ID: ppzbmed-10.1101.2021.09.16.21263170

RESUMEN

Infection with SARS-CoV-2 has highly variable clinical manifestations, ranging from asymptomatic infection through to life-threatening disease. Host whole blood transcriptomics can offer unique insights into the biological processes underpinning infection and disease, as well as severity. We performed whole blood RNA Sequencing of individuals with varying degrees of COVID-19 severity. We used differential expression analysis and pathway enrichment analysis to explore how the blood transcriptome differs between individuals with mild, moderate, and severe COVID-19, performing pairwise comparisons between groups. Increasing COVID-19 severity was characterised by an abundance of inflammatory immune response genes and pathways, including many related to neutrophils and macrophages, in addition to an upregulation of immunoglobulin genes. Our insights into COVID-19 severity reveal the role of immune dysregulation in the progression to severe disease and highlight the need for further research exploring the interplay between SARS-CoV-2 and the inflammatory immune response.


Asunto(s)
COVID-19
5.
ssrn; 2021.
Preprint en Inglés | PREPRINT-SSRN | ID: ppzbmed-10.2139.ssrn.3766286

RESUMEN

Background: Emergency hospital admissions for infection often lack microbiological diagnostic certainty. Novel approaches to discriminate likelihood of bacterial and viral infections are required to support antimicrobial prescribing decisions and infection control practice. We sought to derive and validate a blood transcriptional signature to differentiate bacterial infections from viral infections including COVID-19.Methods: Blood RNA sequencing was performed on a discovery cohort of adults attending the Emergency Department with confirmed bacteraemia or viral infection. Differentially expressed host genes were subjected to feature selection to derive the most parsimonious discriminating signature. RT-qPCR validation of the signature was then performed in a prospective cohort of patients presenting with undifferentiated fever and a second case-control cohort of patients with bacteraemia or COVID-19.Findings: A 3-gene transcript signature was derived from the discovery cohort of 56 definite bacterial and 27 viral infection cases. In the validation cohort, the signature differentiated bacterial and viral infections with an area under receiver operating characteristic curve (AUC) of 0.976 (95% CI: 0.919-1.000), sensitivity 97.3% and specificity of 100%. The AUC for C-reactive protein and leucocyte count was 0.833 (95% CI: 0.694-0.944) and 0.938 (95% CI: 0.840-0.986) respectively. In the second validation analysis the signature discriminated 34 SARS-CoV-2 positive COVID-19 from 35 bacterial infections with AUC of 0.953 (95% CI: 0.893-0.992), sensitivity 88.6% and specificity of 94.1%.Interpretation: This novel 3-gene signature discriminates viral infections including COVID-19 from bacterial sepsis in adults, outperforming both leucocyte count and CRP, thus potentially providing significant clinical utility in managing acute presentations with infection.Funding Statement: Work in this study was funded by the NIHR Imperial Biomedical Research Centre, the Medical Research Council, the Wellcome Trust and the European Union FP7 (EC-GA 279185) (EUCLIDS).Declaration of Interests: None of the authors have any relevant interest to declare. Ethics Approval Statement: Ethical approval was obtained to take deferred consent from patients from whom an RNA specimen had been collected (or from next of kin or nominated consultee) (REC references 14/SC/0008 and 19/SC/0116).


Asunto(s)
Manifestaciones Neurológicas , Fiebre , Sepsis , Infecciones Bacterianas , Urgencias Médicas , Infecciones Virales del Ojo , COVID-19 , Enfermedad de la Hemoglobina SC
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