Bibliographic record
Abstract
In a recent report in Science, Cervia-Hasler identified the complement system as the top dysregulated biological pathway in long coronavirus disease (COVID), thus implicating complement in the disease process and raising the prospect of blocking complement activation as a promising therapeutic intervention (1). However, this finding has not been independently validated, which emphasizes the need for data replication to draw a reliable conclusion. In this brief commentary, I seek to set this observation in context. The legacy of COVID-19 extends far beyond the acute phase with approximately 20% of cases (in the UK, approximately 1.9 million people or 2.9% of the population) experiencing symptoms >12 weeks after the acute infection, referred to as long COVID or postacute sequelae of severe acute respiratory syndrome-related coronavirus (SARS-CoV-2) infection. Typical symptoms include persistent fatigue, shortness of breath, muscle pains, and brain fog. Long COVID imposes a substantial burden on the economy, as individuals grappling with the condition are often incapacitated, unable to work, and cannot contribute fully to society. In our recent study, almost 90% of individuals with long COVID were not in employment (2). The long-term repercussions of long COVID may extend to future health complications such as diabetes, cardiovascular disease, and dementia (1, 2). Understanding mechanisms to guide therapy is thus an urgent priority. Persistent inflammation is a key feature in long COVID, perhaps a consequence of virus persistence in endothelial cells. Increased levels of inflammatory cytokines along with C-reactive protein and serum amyloid A were found in long COVID patients 6–9 months post-SARS-CoV-2 infection. In a systematic review including 22 studies, increased concentrations of plasma interleukin-6 in plasma were consistently associated with long COVID (3). Conversely, the presence of autoantibodies against inflammatory chemokines during the convalescent phase correlated with improved outcome and a reduced likelihood of developing long COVID. Activation of innate immune cells has also been identified as a contributing factor to lung fibrosis and inflammation in a humanized mouse model of long COVID [reviewed in ref. (2)]. All these reports provide evidence of immune system dysregulation with accompanying inflammation as crucial factors in long COVID, yet none pinpoint an obvious inflammatory trigger or target for therapy. Although complement, a key driver of inflammation, is strongly implicated in acute COVID-19, its contribution to long COVID is underexplored. One recent study reported that levels of the small complement component C4 (C4) fragment C4d were associated with chest computed tomography changes at 3 months in long COVID patients and that increased levels of complement activation products were present in plasma at 3 months and 1 year in long COVID individuals compared to healthy controls (4). We identified a set of complement activation markers in long COVID cases implicating the activation loop [complement small factor B (FB) fragment (Ba), complement small complement component (C3) fragment (iC3b), complement small complement C5 (C5) fragments (C5a)] and downstream terminal pathway [terminal complement complex (TCC)], providing a diagnostic tool for long COVID (2). Notably, we previously showed that the amplification loop is dysregulated in acute COVID-19 subjects with a single amplification loop-specific biomarker, Ba, being the best death predictor [reviewed in (2)]. The study by Cervia-Hasler et al. comprised a longitudinal study of 268 serum samples obtained from 39 healthy controls and 113 COVID-19 patients followed for up to 1 year after acute SARS-CoV-2 infection. They used a nontargeted approach to identify the best predictive biomarker(s) associated with long COVID by measuring >6500 proteins in these serum samples using the SomaScan proteomics platform. At the 6-month follow-up, 40 patients exhibited long COVID symptoms. Machine learning and other computational tools were applied to identify candidate biomarkers predictive of long COVID; these were then validated in wet laboratory settings (using ELISA and mass spectrometry). Best hits in this analysis included elevated levels of complement activation products (TCC, complement small C3 fragment C3d) and complement proteins [complement component C2 (C2), FB, complement component C5 (C5)]; increased complement activity was also noted. The most informative biomarkers were the complement component C7 (C7) and C7 containing complexes, both markedly reduced in long COVID, implicating the terminal complement pathway (1). Whether the observed reduction in terminal pathway markers reflected decreased synthesis or increased consumption secondary to membrane attack complex formation in tissues was not tested, although the latter might explain the observed tissue damage. The authors suggest that monitoring C7 levels in acute COVID-19 cases could provide a predictive biomarker for long COVID, supporting prediction of disease course and associated tissue damage. Regardless of the precise mechanism these analyses provide compelling evidence of ongoing complement dysregulation in long COVID, a likely driver of the observed persistent inflammation. Our study implicated complement activation products Ba, iC3b, C5a, and TCC as informative biomarkers for long COVID (2), while Cervia-Hasler et al. identified C7 and C7-containing complexes as most relevant biomarkers of long COVID. Unfortunately, these markers are not routinely measured in clinical laboratories and assays are poorly validated even in specialist laboratories, a major limitation to their use as potential disease biomarkers. If these assays are to be used in assessment of long COVID, efforts are needed to further develop and standardize them to allow their use in routine settings. Cervia-Hasler and colleagues did seek further insight into the underlying pathological mechanism. They showed correlation of complement dysregulation with markers of thromboinflammation, a hallmark of long COVID; these included coagulation factor VIII, thrombospondin-1, von Willebrand factor (vWF), fibrinogen beta, factor XI, protein C, and heparin cofactor II (1). The observed link between complement dysregulation and thromboinflammation confirms the importance of cross-talk between complement and coagulation systems, a finding seen in other contexts; cross-talk is bidirectional, tightly controlled, and crucial for driving the immune response, inflammation, and hemostasis (1, 5). The authors propose that after acute COVID-19 infection, localized activation of complement and coagulation systems persists across various tissues in those who progress to long COVID. The endothelial cell damage is mediated by complement terminal pathway complexes perturbing cell membranes and leading to the release of thrombotic markers, including vWF and TSP1. These in turn induce platelet activation, facilitate thrombin generation, and promote interactions between monocytes and platelets, resulting in microclot formation, a common feature of long COVID. Accumulating vWF aggregates in turn activate the amplification loop of complement resulting in the small complement component of C3 fragment C3b deposition and sustaining local complement activation and inflammation. Currently, there are no specific therapies available for long COVID; available treatments primarily involve alleviating symptoms and rehabilitation. Some ongoing clinical trials are exploring medications for specific symptoms, such as ivabradine for cardiac damage, pirfenidone and inhaled interferon-1 for fibrotic lung injury, and leronlimab for inflammation triggered by acute SAR-CoV-2 infection. The demonstration that dysregulation of complement is a core feature of long COVID highlights the potential for use of anticomplement drugs in therapy of the condition. Therapeutic complement inhibition might break the vicious cycle of complement activation and tissue damage and restore normal homeostasis. Several complement inhibitors are already in the clinic (5), and could be repurposed for long COVID therapy (Fig. 1). Given the evidence implicating the amplification loop detailed previously, drugs targeting amplification such as iptacopan (targeting FB), danicopan [targeting complement factor D (FD)], or pegcetacoplan (targeting C3) might be most effective. However, targeting the terminal pathway, for example with the long established C5-blocking antibody eculizumab, may also be beneficial. Anticomplement drugs used in trials for acute COVID-19 showed limited success with a single drug, the anti-C5a antibody vilobelimab, gaining limited FDA approval (2, 5). Long COVID is a very different disease, manifesting with low-grade inflammation as opposed to the acute hyperinflammatory state typifying some cases of acute COVID-19. Anticomplement therapies may prove to be more effective in this scenario, particularly if used in conjunction with reliable complement biomarkers (e.g., complement activation products; Ba, iC3b, TCC) to identify patients likely to benefit from the treatment. A reliable biomarker would inform treatment response, particularly indicating a reduction in complement activation. A proof-of-concept study or clinical trial using complement inhibitors is needed to validate this hypothesis. The complement cascade and complement drugs in clinics. The complement system is activated via the classical and lectin pathways and amplified by the amplification loop of the alternative pathway. The classical pathway is initiated by C1 binding to antigen–antibody complexes. A small fragment of C1 C1s in the C1 complex cleaves C4 and C2 to form the C3 convertase C4b2a. The lectin pathway is activated by mannose binding lectin or other lectins binding surface carbohydrates; attached mannan binding lectin serine proteases (MASPs) are activated to cleave C4 and C2 to generate C4b2a. The C3 convertase cleaves C3 to C3b (a small fragment of C3) and C3a. C3b, C4b (a small fragment of C4) and their degradation products are important opsonins. C3b also binds FB enabling its cleavage by FD to form the C3bBb convertase that cleaves more C3 in a feedback cycle, the alternative pathway amplification loop. Binding of a further C3b to either C3 convertase creates a C5 convertase that cleaves C5 to initiate the terminal pathway culminating in formation of the soluble (TCC) and membrane-inserted (membrane attack complex; MAC) complexes. Complement small fragments of C3, C3a, and C5a, are anaphylatoxins that signal via their receptors to recruit immune cells. FDA-approved complement drugs in clinics are shown. Numerous other complement inhibitors are currently in development, undergoing preclinical and clinical trials, with a focus on targeting diverse pathways. Figure created with BioRender (BioRender.com). Color figure available at https://academic.oup.com/clinchem. COVID, coronavirus disease; SARS-CoV-2, severe acute respiratory syndrome-related coronavirus-2; C3, complement component 3; C5, complement component 5; C4, complement component C4; FB, complement factor B; TCC, terminal complement component; C2, complement component 2; C7, complement component 7; vWF, von Willebrand factor. The corresponding author takes full responsibility that all authors on this publication have met the following required criteria of eligibility for authorship: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; (c) final approval of the published article; and (d) agreement to be accountable for all aspects of the article thus ensuring that questions related to the accuracy or integrity of any part of the article are appropriately investigated and resolved. Nobody who qualifies for authorship has been omitted from the list. Upon manuscript submission, all authors completed the author disclosure form. W. Zelek is supported by the Race Against Dementia Alzheimer's Research Fellowship Award. None declared. I would like to thank Professor Paul Morgan for his valuable feedback during the preparation of this commentary and for his continuous support.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".