Lung Spatial Profiling Reveals a T Cell Signature in COPD Patients with Fatal SARS-CoV-2 Infection
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Abstract
People with pre-existing lung diseases such as chronic obstructive pulmonary disease (COPD) are more likely to get very sick from SARS-CoV-2 disease 2019 (COVID-19). Still, an interrogation of the immune response to COVID-19 infection, spatially throughout the lung structure, is lacking in patients with COPD. For this study, we characterized the immune microenvironment of the lung parenchyma, airways, and vessels of never- and ever-smokers with or without COPD, all of whom died of COVID-19, using spatial transcriptomic and proteomic profiling. The parenchyma, airways, and vessels of COPD patients, compared to control lungs had (1) significant enrichment for lung-resident CD45RO+ memory CD4+ T cells; (2) downregulation of genes associated with T cell antigen priming and memory T cell differentiation; and (3) higher expression of proteins associated with SARS-CoV-2 entry and primary receptor ubiquitously across the ROIs and in particular the lung parenchyma, despite similar SARS-CoV-2 structural gene expression levels. In conclusion, the lung parenchyma, airways, and vessels of COPD patients have increased T-lymphocytes with a blunted memory CD4 T cell response and a more invasive SARS-CoV-2 infection pattern and may underlie the higher death toll observed with COVID-19.
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SciScore for 10.1101/2022.04.20.488968: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: The study conformed to the Declaration of Helsinki and was approved by the University of Arizona ethics committee (IRB #1811124026). Sex as a biological variable not detected. Randomization For each lung section, we randomly selected 16 total regions of interest (ROI) from the parenchyma, airways and vessels, uniformly spread throughout the section to ensure sample randomization (Figure 2A). Blinding The number of positive cells were counted by two blinded observers and normalized using Metamorph software. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Computed tomography (CT) scans were analyzed for tissue volume and emphysema (% lower attenuation areas … SciScore for 10.1101/2022.04.20.488968: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: The study conformed to the Declaration of Helsinki and was approved by the University of Arizona ethics committee (IRB #1811124026). Sex as a biological variable not detected. Randomization For each lung section, we randomly selected 16 total regions of interest (ROI) from the parenchyma, airways and vessels, uniformly spread throughout the section to ensure sample randomization (Figure 2A). Blinding The number of positive cells were counted by two blinded observers and normalized using Metamorph software. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Computed tomography (CT) scans were analyzed for tissue volume and emphysema (% lower attenuation areas [LAA] <-950 Hounsfield units [HU]), using Vida Vision software (Version 2.20, Iowa, USA). Vidasuggested: NoneThe number of positive cells were counted by two blinded observers and normalized using Metamorph software. Metamorphsuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study has limitations to note: first, the sample size of the COVID-19 patients is small, due to ongoing challenges that limit the access to tissue from these patients. However, spatial profiling generates a high amount of multiplexed information on different regions of interest within the lung structure. Second, recent spirometry data are lacking for 15 out of 18 subjects as most of the COVID-19 patients were admitted in critical condition. However, the patients had a prior clinical diagnosis of COPD, and emphysema was confirmed on the CT scans of the COPD patients. Third, previous cigarette smoke exposure can affect the gene expression profile within the lung31. However, all our study subjects ceased smoking at least one year prior to the study, and there was no difference in pack/years between COPD and ever-smoker controls, which minimizes the effect of cigarette smoke on the transcriptomic data. Fourth, it is difficult to distinguish how much of the immune profile found in COPD patients versus controls is driven by the presence of COPD, and how much it is driven by the presence of SARS-CoV2 infection. To address this, we profiled CD45RO expression in a non-infected cohort of never- and ever-smokers with and without COPD, these data confirmed that the upregulation of CD45RO expressing memory T lymphocytes in COPD patients who died of COVID-19, is likely driven by SARS-CoV-2 infection. Last, our main study cohort is skewed towards the most severe cases of SARS-CoV-2 inf...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- No funding statement was detected.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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