Sera proteomic features of active and recovered COVID-19 patients: potential diagnostic and prognostic biomarkers.
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ABSTRACT:
SUBMITTER: Leng L
PROVIDER: S-EPMC8173321 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The early diagnosis and prognosis of COVID-19, the disease caused by SARS-CoV-2 infection remain major challenges. Clinical information assessment combined with biomarkers based on molecular changes is of great value in the diagnosis and prognosis of COVID-19. However, the biomarkers for COVID-19 have not been identified. Here, we described the sera proteomic features that could distinguish patients with COVID-19 from healthy patients. In addition, we characterized the serum proteomes of paired samples obtained from 15 patients with COVID-19 during hospitalization and after recovery, as well as samples from the healthy patients, and found several prognostic biomarkers by comparing with published studies, among which 10 were verified by parallel reaction monitoring. Further, we found that the protein changes in sera of COVID-19 patients can reflect in its organ-enriched expression. These findings provide diagnostic biomarkers for COVID-19 and prognostic biomarkers to comprehensively evaluate COVID-19 patient recovery status. Furthermore, our results provide new insights into the pathological changes monitoring by serum changes in COVID-19 patients.
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Project description:Although numerous biomarkers or biomarker candidates have been discovered to detect levels of drinking and intervals of time after last drinking episode, only a few biomarkers have been applied to monitor abstinence in a longer interval (?6 wks) from alcohol abuse. Considering sample sources, sensitivity, and specificity, new biomarkers from blood with better accuracy are needed. To address this, serum proteomic profiles were compared between pre- and post- treatment samples from subjects seeking treatment for alcohol abuse and dependence in an intensive 6 wk daily outpatient program using high-abundance plasma protein immunodepletion and LC-MS/MS techniques. Protein identification, quantification, candidate biomarker selection, and prioritization analyses were carried out. Among the 246 quantified serum proteins, abundance of 13 and 45 proteins in female and male subjects were significantly changed (p ? 0.05), respectively. Of these biomarker candidate proteins, 2 (female) and 8 (male) proteins were listed in category 1, with high area under the receiver operating characteristic curve, sensitivity, specificity, and fold change. In summary, several new biomarker candidates have been identified to monitor abstinence from alcohol abuse.
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Project description:BACKGROUND:New, more sensitive and specific biomarkers are needed to support other means of clinical diagnosis of neurodegenerative disorders. Proteomics technology is widely used in discovering new biomarkers. There are several difficulties with in-depth analysis of human plasma/serum, including that there is no one proteomic platform that can offer complete identification of differences in proteomic profiles. Another set of problems is associated with heterogeneity of human samples in addition intrinsic variability associated with every step of proteomic investigation. Validation is the very last step of proteomic investigation and it is very often difficult to validate potential biomarker with desired sensitivity and specificity. Even though it may be possible to validate a differentially expressed protein, it may not necessarily prove to be a valid diagnostic biomarker. RESULTS:In the current study we report results of proteomic analysis of sera from HIV-infected individuals with or without cognitive impairment. Application of SELDI-TOF analysis followed by weak cation exchange chromatography and 1-dimensional electrophoresis led to discovery of gelsolin and prealbumin as differentially expressed proteins which were not detected in this cohort of samples when previously investigated by 2-dimensional electrophoresis with Difference Gel Electrophoresis technology. CONCLUSION:Validation using western-blot analysis led us to conclude that relative change of the levels of these proteins in one patient during a timeframe might be more informative, sensitive and specific than application of average level estimated based on an even larger cohort of patients.
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Project description:Early detection and effective treatment of severe COVID-19 patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model was validated using 10 independent patients, 7 of which were correctly classified. Targeted proteomics and metabolomics assays were employed to further validate this molecular classifier in a second test cohort of 19 COVID-19 patients, leading to 16 correct assignments. We identified molecular changes in the sera of COVID-19 patients compared to other groups implicating dysregulation of macrophage, platelet degranulation, complement system pathways, and massive metabolic suppression. This study revealed characteristic protein and metabolite changes in the sera of severe COVID-19 patients, which might be used in selection of potential blood biomarkers for severity evaluation.
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