In a recent study published within the journal eBioMedicine, researchers used proteomics to research differentially expressed proteins (DEPs) related to long-COVID. Identified up- or down-regulated proteins were characterised via ingenuity pathway analyses to elucidate their downstream pathological and physiological effects. This 2-year-long longitudinal study was thereby in a position to reveal protein biomarkers useful in long-COVID diagnosis and a few potential mechanisms by which the condition debilitates survivors.

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

Long COVID and the challenges related to its treatment

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused coronavirus disease 2019 (COVID-19) has hitherto infected greater than 771 million people, leaving almost 7 million dead worldwide. Its impacts extend beyond its lethality, with a growing variety of survivors reporting symptoms that persist or, in some cases, develop long after primary disease termination. This colloquially termed ‘long-COVID’ has been confirmed to afflict 65 million people, with research estimating that between 14-55% of all COVID-19 survivors suffer from the condition.

Long-COVID has had severe and widespread impacts on COVID-19 survivors’ quality of life. The condition has further resulted in national-scale economic loss, as seen in the UK (UK) and Europe, wherein its prevalence has been directly liable for early retirement and shortages within the employment market. This is especially resulting from the physical and neurological debilitation caused by long-COVID, which can persist for 2 years or more.

Unfortunately, given the novelty of the disease, it stays poorly understood, with a clinically defined definition of long-COVID hitherto lacking. The currently accepted working definition for long COVID is that of the World Health Organization (WHO), which establishes the affliction because the persistence or development of COVID-19-like symptoms two months following hospital discharge. Given the vagueness surrounding long-COVID, research into its mechanisms and prevalence, though growing by the day, stays insufficient.

Recent research has identified race, sex, age, and severity of COVID-19 infections as possible risk aspects related to long-COVID development, with hypotheses suggesting the cross-reactivity of SARS-CoV-2 antibodies and host immune proteins because the mechanistic underpinning for the antagonistic effects of the condition. Nevertheless, targeted extensive cohort studies are required to check and confirm these hypotheses, failing which management and clinical interventions to counter long-COVID can’t be implemented. Alarmingly, clinicians still shouldn’t have any diagnostic test for the condition, with the present diagnosis being based on patient-reported symptoms.

In regards to the study

In the current study, researchers investigated the proteomic landscape surrounding long-COVID to discover protein biomarkers which will function future diagnostic determinants of the condition and supply insights into the pathophysiological impacts of severe SARS-CoV-2 infections on survivors. They conducted a 2-year-long profiling of survivor plasma samples to discover significantly up- or down-regulated proteins in long-COVID patients versus COVID-19 survivors who didn’t suffer from the condition. Identified proteins were then integrated with existing proteomic knowledge databases to elucidate the results of their altered concentrations on host physiology.

Participants were recruited from hospitals between 7 January and 29 May 2020. For inclusion within the study, participants needed to have had clinically confirmed COVID-19-associated hospital admissions. Patients who died within the six months following hospital discharge had dementia or other severe neurophysiological disorders or who were immobile were excluded from the study.

Following the screening of inclusion and exclusion criteria, 516 patients were enlisted into the study, of which 181 provided data across each years of the study. They were thus included in the information analyses. Follow-up data collection was conducted at six months, one yr, and two years following hospital discharge and comprised functional tests of the pulmonary system, kidneys, and lungs. Plasma samples were collected alongside the functional tests and used for proteomic investigations.

To elucidate the pathophysiological changes in COVID-19 survivors, 181 age- and sex-matched health controls were recruited from Wuhan, China, and underwent the identical battery of tests because the case-cohort (survivors). Moreover, demographic, clinical, disease severity (for cases), and medical intervention data was collected from hospital records (for cases) or self-reported for controls.

Plasma tests for differentially expressed proteins (DEPs) identification and quantification comprised of liquid chromatography-mass spectrometry (LC/MS) together with data-independent acquisition (DIA) tandem mass spectrometry for the generation of a spectral library. The information was enriched using differential enrichment evaluation of proteomics data (DEP) evaluation. Finally, resultant data was compared against the UniProt database for human proteins, and principal component evaluation (PCA) was used to discover proteins that significantly up-or down-regulated in cases.

A random forest (RF) machine learning (ML) model was used to check identified proteins in cases versus controls.

Study findings

Demographic and clinical data revealed significant long-term symptoms in COVID-19 cases, including physical (reduced exercise capability, mobility, and quality of life) and clinical (increased healthcare usage following hospital discharge, reduced immune response, and reduced lung function). Proteomics evaluation together with PCAs revealed distinct stratification of COVID-19 survivors into three cohorts, corroborated between all three follow-up visits.

Proteomics and DIA analyses identified 1.370 proteins, of which DEP analyses revealed 249 proteins that were significantly different between cases and controls. Numbers of DEP proteins varied between follow-up studies, with some returning to baseline (control) values while others remained distinct.

“Our data showed majority of DEPs enriched in immune response pathways were immunoglobulins. These immunoglobulins were involved in several pathways including regulation of B cell and lymphocyte activation, Fc receptor signaling pathway, and immunoglobulin mediated immune response.”

Comparisons with the UniProt database revealed 4 major recovery modes of biological processes comprising focal adhesion, regulation of motion cytoskeleton (cellular biology associated), ECM-receptor interactions, and hyper- and dilated-cardiomyopathy pathways (cardiovascular system associated). Immune response, complement cascade, and coagulation cascade pathways returned to baseline two years following discharge, however the Fc receptor signaling pathway weren’t observed to get better even on the two-year follow-up.

Conclusions

The current study identified 4 different biological processes detrimentally impacted by SARS-CoV-2 infection, thereby providing molecular insights into the mechanistic processes involved within the long-COVID condition. Multiple potential protein biomarkers of long-COVID were identified, which may lead to the longer term development of diagnostic tests for long-COVID identification.