Proteomics Investigation of Diverse Serological Patterns in COVID-19.

Serum antibodies IgM and IgG are elevated during Coronavirus Disease 2019 (COVID-19) to defend against viral attacks. Atypical results such as negative and abnormally high antibody expression were frequently observed whereas the underlying molecular mechanisms are elusive. In our cohort of 144 COVID-19 patients, 3.5% were both IgM and IgG negative, whereas 29.2% remained only IgM negative. The remaining patients exhibited positive IgM and IgG expression, with 9.3% of them exhibiting over 20-fold higher titers of IgM than the others at their plateau. IgG titers in all of them were significantly boosted after vaccination in the second year. To investigate the underlying molecular mechanisms, we classed the patients into four groups with diverse serological patterns and analyzed their 2-year clinical indicators. Additionally, we collected 111 serum samples for TMTpro-based longitudinal proteomic profiling and characterized 1494 proteins in total. We found that the continuously negative IgM and IgG expression during COVID-19 were associated with mild inflammatory reactions and high T cell responses. Low levels of serum IgD, inferior complement 1 activation of complement cascades, and insufficient cellular immune responses might collectively lead to compensatory serological responses, causing overexpression of IgM. Serum CD163 was positively correlated with antibody titers during seroconversion. This study suggests that patients with negative serology still developed cellular immunity for viral defense and that high titers of IgM might not be favorable to COVID-19 recovery.

Potential Use of Serum Proteomics for Monitoring COVID-19 Progression to Complement RT-PCR Detection.

RT-PCR is the primary method to diagnose COVID-19 and is also used to monitor the disease course. This approach, however, suffers from false negatives due to RNA instability and poses a high risk to medical practitioners. Here, we investigated the potential of using serum proteomics to predict viral nucleic acid positivity during COVID-19. We analyzed the proteome of 275 inactivated serum samples from 54 out of 144 COVID-19 patients and shortlisted 42 regulated proteins in the severe group and 12 in the non-severe group. Using these regulated proteins and several key clinical indexes, including days after symptoms onset, platelet counts, and magnesium, we developed two machine learning models to predict nucleic acid positivity, with an AUC of 0.94 in severe cases and 0.89 in non-severe cases, respectively. Our data suggest the potential of using a serum protein-based machine learning model to monitor COVID-19 progression, thus complementing swab RT-PCR tests. More efforts are required to promote this approach into clinical practice since mass spectrometry-based protein measurement is not currently widely accessible in clinic.

Proteomic and metabolomic investigation of serum lactate dehydrogenase elevation in COVID-19 patients.

Serum lactate dehydrogenase (LDH) has been established as a prognostic indicator given its differential expression in COVID-19 patients. However, the molecular mechanisms underneath remain poorly understood. In this study, 144 COVID-19 patients were enrolled to monitor the clinical and laboratory parameters over 3 weeks. Serum LDH was shown elevated in the COVID-19 patients on admission and declined throughout disease course, and its ability to classify patient severity outperformed other biochemical indicators. A threshold of 247 U/L serum LDH on admission was determined for severity prognosis. Next, we classified a subset of 14 patients into high- and low-risk groups based on serum LDH expression and compared their quantitative serum proteomic and metabolomic differences. The results showed that COVID-19 patients with high serum LDH exhibited differentially expressed blood coagulation and immune responses including acute inflammatory responses, platelet degranulation, complement cascade, as well as multiple different metabolic responses including lipid metabolism, protein ubiquitination and pyruvate fermentation. Specifically, activation of hypoxia responses was highlighted in patients with high LDH expressions. Taken together, our data showed that serum LDH levels are associated with COVID-19 severity, and that elevated serum LDH might be consequences of hypoxia and tissue injuries induced by inflammation.

Multi-organ proteomic landscape of COVID-19 autopsies.

The molecular pathology of multi-organ injuries in COVID-19 patients remains unclear, preventing effective therapeutics development. Here, we report a proteomic analysis of 144 autopsy samples from seven organs in 19 COVID-19 patients. We quantified 11,394 proteins in these samples, in which 5,336 were perturbed in the COVID-19 patients compared to controls. Our data showed that cathepsin L1, rather than ACE2, was significantly upregulated in the lung from the COVID-19 patients. Systemic hyperinflammation and dysregulation of glucose and fatty acid metabolism were detected in multiple organs. We also observed dysregulation of key factors involved in hypoxia, angiogenesis, blood coagulation, and fibrosis in multiple organs from the COVID-19 patients. Evidence for testicular injuries includes reduced Leydig cells, suppressed cholesterol biosynthesis, and sperm mobility. In summary, this study depicts a multi-organ proteomic landscape of COVID-19 autopsies that furthers our understanding of the biological basis of COVID-19 pathology.