Lethal COVID-19 Associates With RAAS-Induced Inflammation For Multiple Organ Damage Including Mediastinal Lymph Nodes

Abstract

Lethal COVID-19 outcomes are most often attributed to classic cytokine storm and attendant excessive immune signaling. We re-visit this question using RNA sequencing in nasopharyngeal and 40 autopsy samples from COVID-19-positive and negative individuals. In nasal swabs, the top 100 genes which significantly correlated with COVID-19 viral load, include many canonical innate immune genes. However, 22 much less studied "non-canonical" genes are found and despite the absence of viral transcripts, subsets of these are upregulated in heart, lung, kidney, and liver, but not mediastinal lymph nodes. An important regulatory potential emerges for the non-canonical genes for over-activating the renin-angiotensin-activation-system (RAAS) pathway, resembling this phenomenon in hereditary angioedema (HAE) and its overlapping multiple features with lethal COVID-19 infections. Specifically, RAAS overactivation links increased fibrin deposition, leaky vessels, thrombotic tendency, and initiating the PANoptosis death pathway, as suggested in heart, lung, and especially mediastinal lymph nodes, with a tightly associated mitochondrial dysfunction linked to immune responses. For mediastinal lymph nodes, immunohistochemistry studies validate the transcriptomic findings showing abnormal architecture, excess fibrin and collagen deposition, and pathogenic fibroblasts. Further, our findings overlap findings in COVID-19 infected hamsters, C57BL/6 and BALB/c mouse models, and importantly peripheral blood mononuclear cell (PBMC) and whole blood samples from COVID-19 patients infected with early variants and later SARS-CoV-2 Omicron strains. We thus present cytokine storm in lethal COVID-19 disease as an interplay between upstream immune gene signaling producing downstream RAAS overactivation with resultant severe organ damage, especially compromising mediastinal lymph node function.

Multi-System-Level Analysis Reveals Differential Expression of Stress Response-Associated Genes in Inflammatory Solar Lentigo

“…Since alterations of inflammatory-specific gene expressions were the primary interest, we focused on gene expression profile changes between the inflammatory and noninflammatory SLs from the custom-made core inflammatory gene list [22], along with the inflammatory-associated gene list from MSigDB. Several genes exhibiting heightened expression in the inflammatory SL, including IL15RA in Extracellular Immunity, might indicate impaired regulation of SL-associated skin inflammation by suppressing key inflammation-associated pathways and modulating T-cell proliferation [31].…”

“…To identify a potential gene list of SL-specific inflammatory responses, we explored specific gene expression alterations between the inflammatory and non-inflammatory SLs. In this analysis (Figure 3), we specifically referenced the custom-made core-inflammatoryresponse gene list from Guarnieri et al [22]. Several genes from the core list were upregulated in the inflammatory SL.…”

“…In other words, while the gene expression profile pat terns associated with the core inflammatory responses differed between the inflammatory and non-inflammatory SLs, the patterns associated with cellular stresses, including oxida tive stress, appeared to be similar across both patient groups. where the pathways were customized by Guarnieri et al [22]. The length of the stick is the degree of nominal enrichment score (NES).…”

“…After all the preprocessing, we proceeded with typical differential analysis and gene ontology (GO) analysis by applying R packages such as EnhancedVolcano [51] and clus-terProfiler [52] using inflammation-associated genes from the GO database. In order to selectively explore inflammatory-specific gene expression patterns, we also adopted the custom-made gene list of inflammatory responses from [22], where Wald-test statistics were applied. To estimate activity levels of modules/systems, a pathway enrichment method, a fast Gene Set Enrichment Analysis (fGSEA) [23], with its Nominal Enrichment Score (NES), was implemented.…”

“…Figure 4. Lollipop plot of pathway enrichment analysis by fast Gene Set Enrichment Analysis (fGSEA)where the pathways were customized by Guarnieri et al[22]. The length of the stick is the degree of nominal enrichment score (NES).…”