bioRxiv Science⌕ Search

bioRxiv · 10.1101/2023.06.22.546100

Classification of patients with COVID-19 by blood RNA endotype: A prospective cohort study

Abstract

BackgroundAlthough the development of vaccines has considerably reduced the severity of COVID-19, its incidence is still high. Hence, a targeted approach based on RNA endotypes of a population should be developed to help design biomarker-based therapies for COVID-19. ObjectivesWe evaluated the major RNAs transcribed in blood cells during COVID-19 using PCR to further elucidate its pathogenesis and determine predictive phenotypes in COVID-19 patients. Study designIn a discovery cohort of 40 patients with COVID-19, 26,354 RNAs were measured on day 1 and day 7. Five RNAs associated with disease severity and prognosis were derived. In a validation cohort of 153 patients with COVID-19 treated in the intensive care unit, we focused on prolactin (PRL), and toll-like receptor 3 (TLR3) among RNAs, which have a strong association with prognosis, and evaluated the accuracy for predicting survival of PRL-to-TL3 ratios (PRL/TLR3) with the areas under the ROC curves (AUC). The validation cohort was divided into two groups based on the cut-off value in the ROC curve with the maximum AUC. The two groups were defined by high PRL/TLR3 (n=47) and low PRL/TLR3 groups (n=106) and the clinical outcomes were compared. ResultsIn the validation cohort, the AUC for PRL/TLR3 was 0.79, showing superior prognostic ability compared to severity scores such as APACHE II and SOFA. The high PRL/TLR3 group had a significantly higher 28-day mortality than the low PRL/TLR3 group (17.0% vs 0.9%, P<0.01). ConclusionsA new RNA endotype classified using high PRL/TLR3 was associated with mortality in COVID-19 patients.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Yoshimura, J., Togami, Y., Ebihara, T., Matsumoto, H., Mitsuyama, Y., Sugihara, F., Hirata, H., Okuzaki, D., Ogura, H.. 2023-06-26. Classification of patients with COVID-19 by blood RNA endotype: A prospective cohort study. https://doi.org/10.1101/2023.06.22.546100

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Pangenome Discoveries from Clinical Long-Read Genomes in Underrepresented Populations with Neurodevelopmental Disorders

Genetic diagnoses remain elusive for many individuals with neurodevelopmental disorders (NDDs), and the gap is wider in populations poorly represented in genomic reference resources. To demonstrate the equitable advantage of long-read whole genome sequencing (LR-WGS) and pangenomes in terms of clinical utility, we analyzed 211 NDD cases and 107 unaffected relatives from 24 populations, integrating their assemblies, resulting in a total of 1204 haplotypes with the Human Pangenome Reference Consortium Release 2 (HPRC_r2) and the Arab Pangenome Reference (APR) datasets. Clinical interpretation of small variants and structural variants (SVs) revealed pathogenic or likely pathogenic findings in 38.9% of the cases (82/211), and our workflow further detected pathogenic repeat expansions in 3.8% of the cases and runs of homozygosity (ROHs) exceeding 300 Mb in 4.7% of the cases, revealing substantial autozygosity suggestive of strong inbreeding. Beyond these clinical assessments, pangenome analysis revealed 3.9 million population-level novel small variants, 39,782 SVs and an average of 2.17 Mb of novel sequence per individual absent from linear references and global pangenomes. We identified 85.9 kb of case-unique nonreference sequences in exonic segments overlapping with curated NDD gene sets. Graph-based tertiary analysis further identified rare exonic complex homozygous rearrangements in the NDD associated genes for 2.4% of the cases. Together, these findings emphasize how diverse genome assemblies extend variant discovery beyond established linear reference-based clinical interpretation.

genetics↗

Integrated exome-transcriptome analysis of a schizophrenia case with an exceptionally low polygenic risk score

Schizophrenia liability reflects both common polygenic variation and rarer variants of larger effect. We investigated a post-mortem schizophrenia case (SZ07) with a schizophrenia polygenic risk score below the first percentile among ancestry-matched cases, asking whether individual-level genomic and transcriptomic analyses could help identify potentially novel schizophrenia-relevant variants. We used exome analysis with multiple variant-prediction tools to generate a panel of variants and corresponding candidate genes potentially implicated in the pathological process in SZ07. The prioritised variants were then assessed using RNA sequencing of three cortical regions. Of these, only an IZUMO4 splice-acceptor variant showed direct RNA-level support. Beyond variant-specific analyses, we characterised broader transcriptomic abnormalities in the SZ07 brain. Pathway analysis of gene-level expression deviations implicated innate immune processes, calcium signalling, synaptic biology, and axon remodelling. Notably, compared with conventional single-sample biological pathway analysis, the analysis we used showed only a weak association with neuronal specificity, suggesting their reduced sensitivity to the main axis of variation related to cellular composition in bulk brain tissue gene expression data. Although the candidate genes showed no significant pathway-level convergence, the broader transcriptomic profile revealed coherent biological alterations largely compatible with the documented history of cerebrovascular disease in SZ07. These results demonstrate how the integration of exome and transcriptome data at the individual level enables the formulation and constraint of hypotheses regarding patient-specific genetic features and their molecular consequences, while highlighting important limitations related to tissue composition, comorbidity, and the choice of reference cohort.

genetics↗

A genetic screen to identify host factors required for commensal bacterial adherence to the gut epithelia

Bacterial adherence to gut epithelial cells likely involves host genetic components. We isolated a gut commensal bacterium, Lelliottia jeotgali, that can robustly colonize C. elegans through attachment to intestinal epithelial cells. Here, we developed a novel screen in C. elegans to identify host genes required for microbiome bacterial colonization. Using transgenic L. jeotgali strain expressing tdTomato, we conducted forward genetic screens in C. elegans to select for mutants that completely lost colonization. We identified multiple allelic mutations in five different C. elegans genes, termed knockout of Lelliottia adherence (kola) mutants, with a near complete loss of adherence. Each of kola-1-5 is uncharacterized and predicted to encode for a secreted or membrane-bound protein. We also identified gly-5, a GalNAc transferase that initiates O-linked glycosylation. Overall, we describe the first C. elegans screen to identify host factors that control microbiome bacterial colonization in the gut.

genetics↗