Systematic evaluation of transcriptomic disease risk and diagnostic biomarker overlap between COVID-19 and tuberculosis : a patient-level meta-analysis
BACKGROUND: The novel coronavirus, SARS-CoV-2, has increased the burden on healthcare systems already strained by a high incidence of tuberculosis (TB) as co-infection and dual presentation are occurring in syndemic settings. We aimed to understand the interaction between these diseases by profiling COVID-19 gene expression signatures on RNA-sequencing data from TB-infected individuals.
METHODS: We performed a systematic review and patient-level meta-analysis by querying PubMed and pre-print servers to derive eligible COVID-19 gene expression signatures from human whole blood (WB), PBMCs or BALF studies. A WB influenza dataset served as a control respiratory disease signature. Three large TB RNA-seq datasets, comprising multiple cohorts from the UK and Africa and consisting of TB patients across the disease spectrum, were chosen to profile these signatures. Putative "COVID-19 risk scores" were generated for each sample in the TB datasets using the TBSignatureProfiler package. Risk was stratified by time to TB diagnosis in progressors and contacts of pulmonary and extra-pulmonary TB. An integrative analysis between TB and COVID-19 single-cell RNA-seq data was performed and a population-level meta-analysis was conducted to identify shared gene ontologies between the diseases and their relative enrichment in COVID-19 disease severity states.
RESULTS: 35 COVID-19 gene signatures from nine eligible studies comprising 98 samples were profiled on TB RNA-seq data from 1181 samples from 853 individuals. 25 signatures had significantly higher COVID-19 risk in active TB (ATB) compared with latent TB infection (p <0·005), 13 of which were validated in two independent datasets. FCN1 - and SPP1 -expressing macrophages enriched in BALF during severe COVID-19 were identified in circulation during ATB. Shared perturbed ontologies included antigen presentation, epigenetic regulation, platelet activation, and ROS/RNS production were enriched with increasing COVID-19 severity. Finally, we demonstrate that the overlapping transcriptional responses may complicate development of blood-based diagnostic signatures of co-infection.
INTERPRETATION: Our results identify shared dysregulation of immune responses in COVID-19 and TB as a dual risk posed by co-infection to COVID-19 severity and TB disease progression. These individuals should be followed up for TB in the months subsequent to SARS-CoV-2 diagnosis.
| Errataetall: |
UpdateIn: iScience. 2022 May 25;25(6):104464. - PMID 35634577 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2020 |
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| Enthalten in: |
medRxiv : the preprint server for health sciences - (2020) vom: 26. Nov. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Sheerin, Dylan [VerfasserIn] |
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Date Revised 03.04.2024 published: Electronic UpdateIn: iScience. 2022 May 25;25(6):104464. - PMID 35634577 Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1101/2020.11.25.20236646 |
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| PPN (Katalog-ID): |
NLM318355353 |
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| 500 | |a UpdateIn: iScience. 2022 May 25;25(6):104464. - PMID 35634577 | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a BACKGROUND: The novel coronavirus, SARS-CoV-2, has increased the burden on healthcare systems already strained by a high incidence of tuberculosis (TB) as co-infection and dual presentation are occurring in syndemic settings. We aimed to understand the interaction between these diseases by profiling COVID-19 gene expression signatures on RNA-sequencing data from TB-infected individuals | ||
| 520 | |a METHODS: We performed a systematic review and patient-level meta-analysis by querying PubMed and pre-print servers to derive eligible COVID-19 gene expression signatures from human whole blood (WB), PBMCs or BALF studies. A WB influenza dataset served as a control respiratory disease signature. Three large TB RNA-seq datasets, comprising multiple cohorts from the UK and Africa and consisting of TB patients across the disease spectrum, were chosen to profile these signatures. Putative "COVID-19 risk scores" were generated for each sample in the TB datasets using the TBSignatureProfiler package. Risk was stratified by time to TB diagnosis in progressors and contacts of pulmonary and extra-pulmonary TB. An integrative analysis between TB and COVID-19 single-cell RNA-seq data was performed and a population-level meta-analysis was conducted to identify shared gene ontologies between the diseases and their relative enrichment in COVID-19 disease severity states | ||
| 520 | |a RESULTS: 35 COVID-19 gene signatures from nine eligible studies comprising 98 samples were profiled on TB RNA-seq data from 1181 samples from 853 individuals. 25 signatures had significantly higher COVID-19 risk in active TB (ATB) compared with latent TB infection (p <0·005), 13 of which were validated in two independent datasets. FCN1 - and SPP1 -expressing macrophages enriched in BALF during severe COVID-19 were identified in circulation during ATB. Shared perturbed ontologies included antigen presentation, epigenetic regulation, platelet activation, and ROS/RNS production were enriched with increasing COVID-19 severity. Finally, we demonstrate that the overlapping transcriptional responses may complicate development of blood-based diagnostic signatures of co-infection | ||
| 520 | |a INTERPRETATION: Our results identify shared dysregulation of immune responses in COVID-19 and TB as a dual risk posed by co-infection to COVID-19 severity and TB disease progression. These individuals should be followed up for TB in the months subsequent to SARS-CoV-2 diagnosis | ||
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| 700 | 1 | |a Wang, Xutao |e verfasserin |4 aut | |
| 700 | 1 | |a Johnson, W Evan |e verfasserin |4 aut | |
| 700 | 1 | |a Coussens, Anna |e verfasserin |4 aut | |
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