Abstract Interferon (IFN)-specific autoantibodies have been implicated in severe COVID-19 and have been proposed as a potential driver of the persistent symptoms characterizing Long COVID, a type of post-acute sequelae of SARS-CoV-2 infection (PASC). We report than only two of 215 SARS-CoV-2 convalescent participants tested over 394 timepoints, including 121 people experiencing Long COVID symptoms, had detectable IFN-α2 antibodies. Both had been hospitalized during the acute phase of the infection. These data suggest that persistent anti-IFN antibodies, although a potential driver of severe COVID-19, are unlikely to contribute to Long COVID symptoms in the post-acute phase of the infection.

Background: Latent class analyses in patients with acute respiratory distress syndrome (ARDS) have identified “hyper-inflammatory” and “hypo-inflammatory” phenotypes with divergent clinical outcomes and treatment responses. ARDS phenotypes are defined using plasma biomarkers and clinical variables. It is currently unknown if these phenotypes have distinct pulmonary biology and if pre-clinical models of disease replicate the biology of either phenotype. Methods: 45 subjects with ARDS (Berlin Definition) and 5 mechanically ventilated controls were selected from cohorts of mechanically ventilated patients at UCSF and ZSFG. Patients with COVID-19 were excluded from this analysis. A 3-variable classifier model (plasma IL-8, protein C, and bicarbonate;Sinha 2020) was used to assign ARDS phenotypes. Tracheal aspirate (TA) RNA was analyzed using established bulk and single-cell sequencing pipelines (Langelier 2018, Sarma 2021). Differentially expressed (DE) genes were analyzed using Ingenuity Pathway Analysis (IPA). Microbial community composition was analyzed with vegan. Fgsea was used to test for enrichment of gene sets from experimental ARDS models in genes that were differentially expressed between each phenotype and mechanically ventilated controls. Results: Bulk RNA sequencing (RNAseq) was available from 29 subjects with hypoinflammatory ARDS and 10 subjects with hyperinflammatory ARDS. 2,777 genes were differentially expressed between ARDS phenotypes. IPA identified several candidate upstream regulators of gene expression in hyperinflammatory ARDS including IL6, TNF, IL17C, and interferons (Figure 1A). 2,953 genes were differentially expressed between hyperinflammatory ARDS and 5 ventilated controls;in contrast, only 243 genes were differentially expressed between hypoinflammatory ARDS and controls, suggesting gene expression in the hypoinflammatory phenotype was more heterogeneous. Gene sets from experimental models of acute lung injury were enriched in hyperinflammatory ARDS but not in hypoinflammatory ARDS (Figure 1B). Single cell RNA sequencing (scRNAseq) was available from 6 additional subjects with ARDS, of whom 3 had hyperinflammatory ARDS. 14,843 cells passed quality control filters. Hyperinflammatory ARDS subjects had a markedly higher burden of neutrophils (Figure 1C), including a cluster of stressed neutrophils expressing heat shock protein RNA that was not present in hypoinflammatory ARDS. Expression of a Th1 signature was higher in T cells from hyperinflammatory ARDS. Differential expression analysis in macrophages identified increased expression of genes associated with mortality in a previous study of ARDS patients (Morell 2019). Conclusions: The respiratory tract biology of ARDS phenotypes is distinct. Hyperinflammatory ARDS is characterized by neutrophilic inflammation with distinct immune cell polarization. Transcriptomic profiling identifies candidate preclinical disease models that replicate gene expression observed in hyperinflammatory ARDS.

Background: The coronavirus disease 2019 (COVID-19) pandemic has led to a rapid increase in the incidence of acute respiratory distress syndrome (ARDS). The distinct features of pulmonary biology in COVID-19 ARDS compared to other causes of ARDS, including other lower respiratory tract infections (LRTIs), are not well understood. Methods: Tracheal aspirates (TA) and plasma were collected within five days of intubation from mechanically ventilated adults admitted to one of two academic medical centers. ARDS and LRTI diagnoses and were verified by study physicians. Subjects were excluded if they received immunosuppression. TA from subjects with COVID-ARDS was compared to gene expression in TA from subjects with other causes of ARDS (OtherARDS) or mechanically ventilated control subjects without evidence of pulmonary pathology (NoARDS). Plasma concentrations of IL-6, IL-8, and protein C also were compared between these groups. Upstream regulator and pathway analysis was performed on significantly differentially expressed genes with Ingenuity Pathway Analysis (IPA). Subgroup analyses were performed to compare gene expression in COVID to ARDS associated with other viral LRTIs and bacterial LRTIs. The association of interferon-stimulated gene expression with SARS-CoV2 viral load was compared to the same association in nasopharyngeal swabs in a cohort of subjects with mild SARS-CoV2. Results: TA sequencing was available from 15 subjects with COVID, 32 subjects with other causes of ARDS (OtherARDS), and 5 mechanically ventilated subjects without evidence of pulmonary pathology (NoARDS). 696 genes were differentially expressed between COVID and OtherARDS (Figure 1A). IL-6, IL-8, B-cell receptor, and hypoxia inducible factor-1a signaling were attenuated in COVID compared to OtherARDS. Peroxisome proliferator-activated receptor (PPAR) and PTEN signaling were higher in COVID compared to OtherARDS (Figure 1B). Plasma levels of IL-6, IL-8, and protein C were not significantly different between COVID and OtherARDS. In subgroup analyses, IL-8 signaling was higher in COVID compared to viral LRTI, but lower than bacterial LRTI. Type I/III interferon was higher in COVID compared to bacterial ARDS, but lower compared to viral ARDS (Figure 1C). Compared to nasopharyngeal swabs from subjects with mild COVID-19, expression of several interferon stimulated genes was less strongly correlated with SARS-CoV2 viral load in TA (Figure 1D). IPA identified several candidate medications to treat COVID-19, including dexamethasone, G-CSF, and etanercept. Conclusions: TA sequencing identifies unique features of the host response in COVID-19. These differentially expressed pathways may represent potential therapeutic targets. An impaired interferon response in the lung may increase susceptibility to severe SARS-COV2.

ABSTRACTBackgroundAcquired lipodystrophy is often characterized as an idiopathic subtype of lipodystrophy. Despite suspicion of an immune-mediated pathology, biomarkers such as autoantibodies are generally lacking.MethodsHere, we used an unbiased proteome-wide screening approach to identify autoantibodies to the adipocyte specific lipid droplet protein Perilipin-1 in a murine model of Autoimmune Polyendocrine Syndrome 1 (APS1). We then tested for PLIN1 autoantibodies in human subjects with lipodystrophy with two independent severe breaks in immune tolerance (including APS1) along with controls using a specific Radioligand Binding Assay and indirect immunofluorescence on fat tissue.ResultsWe identified autoantibodies to the lipid-droplet protein Perilipin-1 (PLIN1) in two human case reports including the first reported case of human APS1 with acquired lipodystrophy. Further, we extend PLIN1 autoantibodies to a second non-APS1 patient who acquired lipodystrophy as an immune-related adverse event following cancer immunotherapy.ConclusionThese data suggest that PLIN1 autoantibodies may represent a unifying marker of autoimmune lipodystrophy.

Mutation, recombination, and reassortment generate virus particles with variable genotypes, some of which may be better adapted to infect a new host, resist drug treatment, or escape immune pressure. The arenaviruses are a family of viruses that package a large (L) and small (S) genome segment. Arenaviruses infect mammals and snakes and are associated with fatal disease in both groups of animals. Although recombination and reassortment are well documented in some virus families, neither process has been observed in natural arenavirus infections. In this study, we documented a surprising degree of genetic diversity in arenavirus-infected snakes. Instead of one or two viral species or quasispecies, individual animals harbored complex populations of viral genotypes composed of up to 5 S and 11 L genotypes, which replicated as stable ensembles in culture. S and L segment genotype accumulation was not balanced and a particular S segment genotype dominated, both in individual animals and at a population level. Numerous instances of recombination and reassortment were detected. Some recombinant segments had unusual organizations with 2 intergenic regions. This genetic fluidity is closer to that observed in influenza viruses than to the relatively placid genetics of mammalian arenavirus. However, the observed imbalance between the S and L segments and the intrahost accumulation and persistence of multiple genotypes is previously undocumented. Overall, this provides an opportunity to study basic mechanisms of viral adaptation and stretches the idea of what it means to be infected by “a virus”.

This report describes three possibly related incidences of encephalitis, two of them lethal, in captive polar bears (Ursus maritimus). Standard diagnostic methods failed to identify pathogens in any of these cases. A comprehensive, three-stage diagnostic 'pipeline' employing both standard serological methods and new DNA microarray and next generation sequencing-based diagnostics was developed, in part as a consequence of this initial failure. This pipeline approach illustrates the strengths, weaknesses and limitations of these tools in determining pathogen caused deaths in non-model organisms such as wildlife species and why the use of a limited number of diagnostic tools may fail to uncover important wildlife pathogens.

Current techniques for viral detection and discovery, which include culture and serological methods as well as polymer chain reaction (PCR)-based protocols, possess a variety of inherent limitations. In an effort to augment the capabilities of existing diagnostic methodologies, the use of virus-specific DNA microarray technology has been recently applied in both research and clinical settings with favorable results. The primary advantage of this approach is that DNA microarrays containing literally thousands of virus-specific sequences allow simultaneous testing for essentially all known viral species. While previous methods have been limited to testing for a single pathogen, or small numbers of specific pathogens, a panviral assay is less biased and can be designed to detect variant or even novel members of existing viral families. The use of DNA microarrays in both research and clinical settings has the potential to substantially increase the number of instances in which a virus may be identified in biological samples. With the proper bioinformatics methodologies, this technology will also maximize the probability that previously uncharacterized pathogens are detected potentially leading to an improved understanding of the etiology for many chronic human diseases. This article focuses on all aspects of virus-specific DNA microarray implementation, from array design to sample processing, amplification, and data analysis.