Autoantibodies in COVID-19 correlate with anti-viral humoral responses and distinct immune signatures

Background: Several autoimmune features occur during coronavirus disease 2019 (COVID-19), with possible implications for disease course, immunity, and autoimmune pathology. Objective: We longitudinally screened for clinically relevant systemic autoantibodies to assess their prevalence, temporal trajectory, and association with immunity, comorbidities, and severity of COVID-19. Methods: We performed highly sensitive indirect immunofluorescence assays to detect anti-nuclear antibodies (ANA) and anti-neutrophil cytoplasmic antibodies (ANCA), along with serum proteomics and virome-wide serological profiling in a multicentric cohort of 175 COVID-19 patients followed-up to one year after infection, eleven vaccinated individuals, and 41 unexposed controls. Results: Compared to healthy controls, similar prevalence and patterns of ANA were present in patients during acute COVID-19 and recovery. However, paired analysis revealed a subgroup of patients with transient presence of certain ANA patterns during acute COVID-19. Furthermore, patients with severe COVID-19 exhibited a high prevalence of ANCA during acute disease. These autoantibodies were quantitatively associated with higher SARS-CoV-2-specific antibody titers in COVID-19 patients and in vaccinated individuals, thus linking autoantibody production to increased antigen-specific humoral responses. Notably, the qualitative breadth of antibodies cross-reactive with other coronaviruses was comparable in ANA-positive and ANA-negative individuals during acute COVID-19. In autoantibody-positive patients, multiparametric characterization demonstrated an inflammatory signature during acute COVID-19 and alterations of the B cell compartment after recovery. Conclusion: Highly sensitive indirect immunofluorescence assays revealed transient autoantibody production during acute SARS-CoV-2 infection, while the presence of autoantibodies in COVID-19 patients correlated with increased anti-viral humoral immune responses and inflammatory immune signatures.

Fox Serum Proteomics Analysis Suggests Host-Specific Responses to Angiostrongylus vasorum Infection in Canids

Dogs infected with the cardiopulmonary nematode Angiostrongylus vasorum may suffer from respiratory distress and/or bleeding disorders. Descriptions of clinical signs in foxes are rare, despite high prevalence. To evaluate the impact of infection on coagulation and immune response, serum proteins from eight experimentally infected foxes before and after inoculation (day 0, 35, 84, 154) were subjected to differential proteomic analyses based on quantitative data and compared to available data from dogs. The number of proteins with differential abundance compared to the uninfected baseline increased with chronicity of infection. Bone marrow proteoglycan, chitinase 3-like protein 1 and pulmonary surfactant-associated protein B were among the most prominently increased proteins. The abundance of several proteins involved in coagulation was decreased. Enriched pathways obtained from both increased and decreased proteins included, among others, “platelet degranulation” and “haemostasis”, and indicated both activation and suppression of coagulation. Qualitative comparison to dog data suggests some parallel serum proteomic alterations. The comparison, however, also indicates that foxes have a more adequate immunopathological response to A. vasorum infection compared to dogs, facilitating persistent infections in foxes. Our findings imply that foxes may be more tolerant to A. vasorum infection, as compared to dogs, reflecting a longer evolutionary host–parasite adaptation in foxes, which constitute a key wildlife reservoir.

Proteomic Approaches to Defining Remission and the Risk of Relapse in Rheumatoid Arthritis

ObjectivesPatients with Rheumatoid Arthritis (RA) are increasingly achieving stable disease remission, yet the mechanisms that govern ongoing clinical disease and subsequent risk of future flare are not well understood. We sought to identify serum proteomic alterations that dictate clinically important features of stable RA, and couple broad-based proteomics with machine learning to predict future flare.MethodsWe studied baseline serum samples from a cohort of stable RA patients (RETRO, n = 130) in clinical remission (DAS28<2.6) and quantified 1307 serum proteins using the SOMAscan platform. Unsupervised hierarchical clustering and supervised classification were applied to identify proteomic-driven clusters and model biomarkers that were associated with future disease flare after 12 months of follow-up and RA medication withdrawal. Network analysis was used to define pathways that were enriched in proteomic datasets.ResultsWe defined 4 proteomic clusters, with one cluster (Cluster 4) displaying a lower mean DAS28 score (p = 0.03), with DAS28 associating with humoral immune responses and complement activation. Clustering did not clearly predict future risk of flare, however an XGboost machine learning algorithm classified patients who relapsed with an AUC (area under the receiver operating characteristic curve) of 0.80 using only baseline serum proteomics.ConclusionsThe serum proteome provides a rich dataset to understand stable RA and its clinical heterogeneity. Combining proteomics and machine learning may enable prediction of future RA disease flare in patients with RA who aim to withdrawal therapy.

Characterization by Quantitative Serum Proteomics of Immune-Related Prognostic Biomarkers for COVID-19 Symptomatology

The COVID-19 pandemic caused by SARS-CoV-2 challenges the understanding of factors affecting disease progression and severity. The identification of prognostic biomarkers and physiological processes associated with disease symptoms is relevant for the development of new diagnostic and therapeutic interventions to contribute to the control of this pandemic. To address this challenge, in this study, we used a quantitative proteomics together with multiple data analysis algorithms to characterize serum protein profiles in five cohorts from healthy to SARS-CoV-2-infected recovered (hospital discharge), nonsevere (hospitalized), and severe [at the intensive care unit (ICU)] cases with increasing systemic inflammation in comparison with healthy individuals sampled prior to the COVID-19 pandemic. The results showed significantly dysregulated proteins and associated biological processes and disorders associated to COVID-19. These results corroborated previous findings in COVID-19 studies and highlighted how the representation of dysregulated serum proteins and associated BPs increases with COVID-19 disease symptomatology from asymptomatic to severe cases. The analysis was then focused on novel disease processes and biomarkers that were correlated with disease symptomatology. To contribute to translational medicine, results corroborated the predictive value of selected immune-related biomarkers for disease recovery [Selenoprotein P (SELENOP) and Serum paraoxonase/arylesterase 1 (PON1)], severity [Carboxypeptidase B2 (CBP2)], and symptomatology [Pregnancy zone protein (PZP)] using protein-specific ELISA tests. Our results contributed to the characterization of SARS-CoV-2–host molecular interactions with potential contributions to the monitoring and control of this pandemic by using immune-related biomarkers associated with disease symptomatology.

Glycoprotein Pathways Altered in Frontotemporal Dementia With Autoimmune Disease

Behavioral variant frontotemporal dementia (bvFTD) is a younger onset form of neurodegeneration initiated in the frontal and/or temporal lobes with a slow clinical onset but rapid progression. bvFTD is highly complex biologically with different pathological signatures and genetic variants that can exhibit a spectrum of overlapping clinical manifestations. Although the role of innate immunity has been extensively investigated in bvFTD, the involvement of adaptive immunity in bvFTD pathogenesis is poorly understood. We analyzed blood serum proteomics to identify proteins that are associated with autoimmune disease in bvFTD. Eleven proteins (increased: ATP5B, CALML5, COLEC11, FCGBP, PLEK, PLXND1; decreased: APOB, ATP8B1, FAM20C, LOXL3, TIMD4) were significantly altered in bvFTD with autoimmune disease compared to those without autoimmune disease. The majority of these proteins were enriched for glycoprotein-associated proteins and pathways, suggesting that the glycome is targeted in bvFTD with autoimmune disease.

Quantitative Serum Proteomics Reveals The Predictive and Prognostic Potential of Clusterin and Gelsolin in Head and Neck Squamous Cell Carcinoma Treated With Radiotherapy

Background Radiotherapy (RT) with concomitant chemotherapy (CTRT) is the standard treatment for advanced head and neck squamous cell carcinoma (HNSCC). Despite advancements in treatment, a significant proportion of patients develop local recurrence and/or metastasis indicating resistance to treatment. Early identification of radio-resistant tumors using predictive and prognostic biomarkers is an important goal. We used a quantitative serum proteomics platform to evaluate the differential expression of proteins in HNSCC patients treated with CTRT. Methods Fifty patients with biopsy-proven, HPV-negative, squamous cell carcinoma of the oropharynx and larynx, undergoing curative CTRT were included in this prospective, IRB-approved study. Serum samples were collected before the start of RT (PreRT), 48 hours after RT (48hrsRT), and 1week after RT (1WeekRT). Patients were classified as “good responders” or “poor responders” based on their clinical outcome at follow-up. Relative quantitation of serum was carried out by iTRAQ to identify differentially expressed proteins. A total of 180–200 proteins were identified, of which twenty proteins showed more than 1.5 fold differential expression. PreRT protein expression levels were compared across good and poor responders to identify proteins with prognostic potential. Differential expression of proteins during RT was analyzed to identify proteins with predictive potential. Finally, twelve proteins were validated using targeted mass spectrometry in ten good and poor responders. Results A 1.5–2.5 fold pre-treatment upregulation of clusterin, gelsolin, extracellular matrix proteins, and proteins of the IGF pathway was observed in poor responders. A 2.0–5.0 fold upregulation of S100 proteins, clusterin, gelsolin, extracellular matrix proteins, IGF1, IGF2, and IGFBP3 was observed in poor responders within 48 hours to 1 week of starting RT. Conclusions The present results are the first report for a panel of twelve potential proteins that would help in early risk stratification and therapeutic prognosis of HNSCC treated with radiotherapy. The significant upregulation of clusterin and gelsolin at PreRT and within 48 hours to 1 week of starting RT, indicates their ability to act as prognostic and predictive markers, respectively. The panel of twelve proteins may facilitate the early identification of patients who are most likely to develop resistance to radiotherapy.