Probing long COVID through a proteomic lens: a comprehensive two-year longitudinal cohort study of hospitalised survivors

Abstract:

Background: As a debilitating condition that can impact a whole spectrum of people and involve multi-organ systems, long COVID has aroused the most attention than ever. However, mechanisms of long COVID are not clearly understood, and underlying biomarkers that can affect the long-term consequences of COVID-19 are paramount to be identified.

Methods: Participants for the current study were from a cohort study of COVID-19 survivors discharged from hospital between Jan 7, and May 29, 2020. We profiled the proteomic of plasma samples from hospitalised COVID-19 survivors at 6-month, 1-year, and 2-year after symptom onset and age and sex matched healthy controls. Fold-change of >2 or <0.5, and false-discovery rate adjusted P value of 0.05 were used to filter differentially expressed proteins (DEPs). In-genuity pathway analysis was performed to explore the down-stream effects in the dataset of significantly up- or down-regulated proteins. Proteins were integrated with long-term consequences of COVID-19 survivors to explore potential biomarkers of long COVID.

Findings: The proteomic of 709 plasma samples from 181 COVID-19 survivors and 181 matched healthy controls was profiled. In both COVID-19 and control group, 114 (63%) were male. The results indicated four major recovery modes of biological processes. Pathways related to cell-matrix interactions and cytoskeletal remodeling and hypertrophic cardiomyopathy and dilated cardiomyopathy pathways recovered relatively earlier which was before 1-year after infection. Majority of immune response pathways, complement and coagulation cascade, and cholesterol metabolism returned to similar status of matched healthy controls later but before 2-year after infection. Fc receptor signaling pathway still did not return to status similar to healthy controls at 2-year follow-up. Pathways related to neuron generation and differentiation showed persistent suppression across 2-year after infection. Among 98 DEPs from the above pathways, evidence was found for association of 11 proteins with lung function recovery, with the associations consistent at two consecutive or all three follow-ups. These proteins were mainly enriched in complement and coagulation (COMP, PLG, SERPINE1, SRGN, COL1A1, FLNA, and APOE) and hypertrophic/dilated cardiomyopathy (TPM2, TPM1, and AGT) pathways. Two DEPs (APOA4 and LRP1) involved in both neuron and cholesterol pathways showed associations with smell disorder.

Interpretation: The study findings provided molecular insights into potential mechanism of long COVID, and put forward biomarkers for more precise intervention to reduce burden of long COVID.

Source: Gu X, Wang S, Zhang W, Li C, Guo L, Wang Z, Li H, Zhang H, Zhou Y, Liang W, Li H, Liu Y, Wang Y, Huang L, Dong T, Zhang D, Wong CCL, Cao B. Probing long COVID through a proteomic lens: a comprehensive two-year longitudinal cohort study of hospitalised survivors. EBioMedicine. 2023 Nov 2;98:104851. doi: 10.1016/j.ebiom.2023.104851. Epub ahead of print. PMID: 37924708. https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(23)00417-6/fulltext (Full text)

Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation

Abstract:

Introduction: Persistent symptoms after COVID-19 infection (“long COVID”) negatively affects almost half of COVID-19 survivors. Despite its prevalence, its pathophysiology is poorly understood, with multiple host systems likely affected. Here, we followed patients from hospital to discharge and used a systems-biology approach to identify mechanisms of long COVID.

Methods: RNA-seq was performed on whole blood collected early in hospital and 4-12 weeks after discharge from 24 adult COVID-19 patients (10 reported post-COVID symptoms after discharge). Differential gene expression analysis, pathway enrichment, and machine learning methods were used to identify underlying mechanisms for post-COVID symptom development.

Results: Compared to patients with post-COVID symptoms, patients without post-COVID symptoms had larger temporal gene expression changes associated with downregulation of inflammatory and coagulation genes over time. Patients could also be separated into three patient endotypes with differing mechanistic trajectories, which was validated in another published patient cohort. The “Resolved” endotype (lowest rate of post-COVID symptoms) had robust inflammatory and hemostatic responses in hospital that resolved after discharge. Conversely, the inflammatory/hemostatic responses of “Suppressive” and “Unresolved” endotypes (higher rates of patients with post-COVID symptoms) were persistently dampened and activated, respectively. These endotypes were accurately defined by specific blood gene expression signatures (6-7 genes) for potential clinical stratification.

Discussion: This study allowed analysis of long COVID whole blood transcriptomics trajectories while accounting for the issue of patient heterogeneity. Two of the three identified and externally validated endotypes (“Unresolved” and “Suppressive”) were associated with higher rates of post-COVID symptoms and either persistently activated or suppressed inflammation and coagulation processes. Gene biomarkers in blood could potentially be used clinically to stratify patients into different endotypes, paving the way for personalized long COVID treatment.

Source: An AY, Baghela A, Zhang PGY, Blimkie TM, Gauthier J, Kaufmann DE, Acton E, Lee AHY, Levesque RC, Hancock REW. Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation. Front Immunol. 2023 Aug 23;14:1243689. doi: 10.3389/fimmu.2023.1243689. PMID: 37680625; PMCID: PMC10482103. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10482103/ (Full text)