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High-resolution serum proteome trajectories in COVID-19 reveal patient-specific seroconversion.

ABSTRACT: A deeper understanding of COVID-19 on human molecular pathophysiology is urgently needed as a foundation for the discovery of new biomarkers and therapeutic targets. Here we applied mass spectrometry (MS)-based proteomics to measure serum proteomes of COVID-19 patients and symptomatic, but PCR-negative controls, in a time-resolved manner. In 262 controls and 458 longitudinal samples of 31 patients, hospitalized for COVID-19, a remarkable 26% of proteins changed significantly. Bioinformatics analyses revealed co-regulated groups and shared biological functions. Proteins of the innate immune system such as CRP, SAA1, CD14, LBP, and LGALS3BP decreased early in the time course. Regulators of coagulation (APOH, FN1, HRG, KNG1, PLG) and lipid homeostasis (APOA1, APOC1, APOC2, APOC3, PON1) increased over the course of the disease. A global correlation map provides a system-wide functional association between proteins, biological processes, and clinical chemistry parameters. Importantly, five SARS-CoV-2 immunoassays against antibodies revealed excellent correlations with an extensive range of immunoglobulin regions, which were quantified by MS-based proteomics. The high-resolution profile of all immunoglobulin regions showed individual-specific differences and commonalities of potential pathophysiological relevance.

SUBMITTER: Geyer PE

PROVIDER: S-EPMC8687121 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundRisk factors for progression of coronavirus disease 2019 (COVID-19) to severe disease or death are underexplored in U.S. cohorts.ObjectiveTo determine the factors on hospital admission that are predictive of severe disease or death from COVID-19.DesignRetrospective cohort analysis.SettingFive hospitals in the Maryland and Washington, DC, area.Patients832 consecutive COVID-19 admissions from 4 March to 24 April 2020, with follow-up through 27 June 2020.MeasurementsPatient trajectories and outcomes, categorized by using the World Health Organization COVID-19 disease severity scale. Primary outcomes were death and a composite of severe disease or death.ResultsMedian patient age was 64 years (range, 1 to 108 years); 47% were women, 40% were Black, 16% were Latinx, and 21% were nursing home residents. Among all patients, 131 (16%) died and 694 (83%) were discharged (523 [63%] had mild to moderate disease and 171 [20%] had severe disease). Of deaths, 66 (50%) were nursing home residents. Of 787 patients admitted with mild to moderate disease, 302 (38%) progressed to severe disease or death: 181 (60%) by day 2 and 238 (79%) by day 4. Patients had markedly different probabilities of disease progression on the basis of age, nursing home residence, comorbid conditions, obesity, respiratory symptoms, respiratory rate, fever, absolute lymphocyte count, hypoalbuminemia, troponin level, and C-reactive protein level and the interactions among these factors. Using only factors present on admission, a model to predict in-hospital disease progression had an area under the curve of 0.85, 0.79, and 0.79 at days 2, 4, and 7, respectively.LimitationThe study was done in a single health care system.ConclusionA combination of demographic and clinical variables is strongly associated with severe COVID-19 disease or death and their early onset. The COVID-19 Inpatient Risk Calculator (CIRC), using factors present on admission, can inform clinical and resource allocation decisions.Primary funding sourceHopkins inHealth and COVID-19 Administrative Supplement for the HHS Region 3 Treatment Center from the Office of the Assistant Secretary for Preparedness and Response.

Project description:In the last two years, the coronavirus disease 19 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a scientific and social challenge worldwide. Vaccines have been the most effective intervention for reducing virus transmission and disease severity. However, virus genetic variants are still circulating among vaccinated individuals with different symptomatology disease cases. Understanding the protective or disease associated mechanisms in vaccinated individuals is relevant to advance in vaccine development and implementation. To address this objective, serum protein profiles were characterized by quantitative proteomics and data analysis algorithms in four cohorts of vaccinated individuals uninfected and SARS-CoV-2 infected with asymptomatic, nonsevere and severe disease symptomatology. The results showed that immunoglobulins were the most overrepresented proteins in infected cohorts when compared to PCR-negative individuals. The immunoglobulin profile varied between different infected cohorts and correlated with protective or disease associated capacity. Overrepresented immunoglobulins in PCR-positive individuals correlated with protective response against SARS-CoV-2, other viruses, and thrombosis in asymptomatic cases. In nonsevere cases, correlates of protection against SARS-CoV-2 and HBV together with risk of myasthenia gravis and allergy and autoantibodies were observed. Patients with severe symptoms presented risk for allergy, chronic idiopathic thrombocytopenic purpura, and autoantibodies. The analysis of underrepresented immunoglobulins in PCR-positive compared to PCR-negative individuals identified vaccine-induced protective epitopes in various coronavirus proteins including the Spike receptor-binding domain RBD. Non-immunoglobulin proteins were associated with COVID-19 symptoms and biological processes. These results evidence host-associated differences in response to vaccination and the possibility of improving vaccine efficacy against SARS-CoV-2.

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High-resolution serum proteome trajectories in COVID-19 reveal patient-specific seroconversion.

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