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Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease.

ABSTRACT: One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood¹. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain-gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials.

SUBMITTER: Liew F

PROVIDER: S-EPMC11003868 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

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Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease.

Liew Felicity F Efstathiou Claudia C Fontanella Sara S Richardson Matthew M Saunders Ruth R Swieboda Dawid D Sidhu Jasmin K JK Ascough Stephanie S Moore Shona C SC Mohamed Noura N Nunag Jose J King Clara C Leavy Olivia C OC Elneima Omer O McAuley Hamish J C HJC Shikotra Aarti A Singapuri Amisha A Sereno Marco M Harris Victoria C VC Houchen-Wolloff Linzy L Greening Neil J NJ Lone Nazir I NI Thorpe Matthew M Thompson A A Roger AAR Rowland-Jones Sarah L SL Docherty Annemarie B AB Chalmers James D JD Ho Ling-Pei LP Horsley Alexander A Raman Betty B Poinasamy Krisnah K Marks Michael M Kon Onn Min OM Howard Luke S LS Wootton Daniel G DG Quint Jennifer K JK de Silva Thushan I TI Ho Antonia A Chiu Christopher C Harrison Ewen M EM Greenhalf William W Baillie J Kenneth JK Semple Malcolm G MG Turtle Lance L Evans Rachael A RA Wain Louise V LV Brightling Christopher C Thwaites Ryan S RS Openshaw Peter J M PJM

Nature immunology 20240408 4

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood<sup>1</sup>. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 ...[more]

PMID: 38589621

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Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.

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Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease.

Publications

Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease.

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