Serum proteomics for the identification of biomarkers to flag predilection of COVID19 patients to various organ morbidities

被引:1
|
作者
Rajan, Madhan Vishal [1 ]
Sharma, Vipra [1 ]
Upadhyay, Neelam [1 ]
Murali, Ananya [2 ]
Bandyopadhyay, Sabyasachi [3 ]
Hariprasad, Gururao [1 ]
机构
[1] All India Inst Med Sci, Dept Biophys, New Delhi, India
[2] Subbaiah Inst Med Sci, New Delhi, Karnataka, India
[3] All India Inst Med Sci, Prote Subfacil, Centralized Core Res Facil, New Delhi 110029, India
关键词
COVID19; Organ morbidity; Clinical proteomics; Differential protein expression; Biomarkers; Complement factors; Coagulation factors; ACUTE RESPIRATORY SYNDROME; POTENTIAL BIOMARKER; CYSTATIN-C; INFECTION; DEFENSINS;
D O I
10.1186/s12014-024-09512-6
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
BackgroundCOVID19 is a pandemic that has affected millions around the world since March 2020. While many patients recovered completely with mild illness, many patients succumbed to various organ morbidities. This heterogeneity in the clinical presentation of COVID19 infection has posed a challenge to clinicians around the world. It is therefore crucial to identify specific organ-related morbidity for effective treatment and better patient outcomes. We have carried out serum-based proteomic experiments to identify protein biomarkers that can flag organ dysfunctions in COVID19 patients.MethodsCOVID19 patients were screened and tested at various hospitals across New Delhi, India. 114 serum samples from these patients, with and without organ morbidities were collected and annotated based on clinical presentation and treatment history. Of these, 29 samples comprising of heart, lung, kidney, gastrointestinal, liver, and neurological morbidities were considered for the discovery phase of the experiment. Proteins were isolated, quantified, trypsin digested, and the peptides were subjected to liquid chromatography assisted tandem mass spectrometry analysis. Data analysis was carried out using Proteome Discoverer software. Fold change analysis was carried out on MetaboAnalyst. KEGG, Reactome, and Wiki Pathway analysis of differentially expressed proteins were carried out using the STRING database. Potential biomarker candidates for various organ morbidities were validated using ELISA.Results254 unique proteins were identified from all the samples with a subset of 12-31 differentially expressed proteins in each of the clinical phenotypes. These proteins establish complement and coagulation cascade pathways in the pathogenesis of the organ morbidities. Validation experiments along with their diagnostic parameters confirm Secreted Protein Acidic and Rich in Cysteine, Cystatin C, and Catalase as potential biomarker candidates that can flag cardiovascular disease, renal disease, and respiratory disease, respectively.ConclusionsLabel free serum proteomics shows differential protein expression in COVID19 patients with morbidity as compared to those without morbidity. Identified biomarker candidates hold promise to flag organ morbidities in COVID19 for efficient patient care.
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页数:11
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