Identification of potential biomarkers to predict organ morbidity in COVID-19: A repository based proteomics perspective

被引:3
|
作者
Bandyopadhyay, Sabyasachi [1 ]
Rajan, Madhan Vishal [2 ]
Kaur, Punit [2 ]
Hariprasad, Gururao [2 ]
机构
[1] All India Inst Med Sci, Prote Subfacil, Centralized Core Res Facil, New Delhi 110029, India
[2] All India Inst Med Sci, Dept Biophys, New Delhi 110029, India
关键词
COVID-19; sequela; Organ diseases; Proteomics; Repository data; Protein biomarker; STATES;
D O I
10.1016/j.bbrep.2023.101493
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
SARS-CoV-2 causes substantial extrapulmonary manifestations in addition to pulmonary disease. Some of the major organs affected are cardiovascular, hematological and thrombotic, renal, neurological, and digestive systems. These types of muti-organ dysfunctions make it difficult and challenging for clinicians to manage and treat COVID-19 patients. The article focuses to identify potential protein biomarkers that can flag various organ systems affected in COVID-19. Publicly reposited high throughput proteomic data from human serum (HS), HEK293T/17 (HEK) and Vero E6 (VE) kidney cell culture were downloaded from ProteomeXchange consortium. The raw data was analyzed in Proteome Discoverer 2.4 to delineate the complete list of proteins in the three studies. These proteins were analyzed in Ingenuity Pathway Analysis (IPA) to associate them to various organ diseases. The shortlisted proteins were analyzed in MetaboAnalyst 5.0 to shortlist potential biomarker proteins. These were then assessed for disease-gene association in DisGeNET and validated by Protein-protein interactome (PPI) and functional enrichment studies (GO_BP, KEGG and Reactome pathways) in STRING. Protein profiling resulted in shortlisting 20 proteins in 7 organ systems. Of these 15 proteins showed at least 1.25-fold changes with a sensitivity and specificity of 70%. Association analysis further shortlisted 10 proteins with a potential association with 4 organ diseases. Validation studies established possible interacting networks and pathways affected, confirmingh the ability of 6 of these proteins to flag 4 different organ systems affected in COVID-19 disease. This study helps to establish a platform to seek protein signatures in different clinical phenotypes of COVID-19. The potential biomarker candidates that can flag organ systems involved are: (a) Vitamin K -depen-dent protein S and Antithrombin-III for hematological disorders; (b) Voltage-dependent anion-selective channel protein 1 for neurological disorders; (c) Filamin-A for cardiovascular disorder and, (d) Peptidyl-prolyl cis-trans isomerase A and Peptidyl-prolyl cis-trans isomerase FKBP1A for digestive disorders.
引用
收藏
页数:8
相关论文
共 50 条
  • [41] Plasma proteomics-based biomarkers for predicting response to mesenchymal stem cell therapy in severe COVID-19
    Li, Tian-Tian
    Yao, Wei-Qi
    Dong, Hai-Bo
    Wang, Ze-Rui
    Zhang, Zi-Ying
    Yuan, Meng-Qi
    Shi, Lei
    Wang, Fu-Sheng
    STEM CELL RESEARCH & THERAPY, 2023, 14 (01)
  • [42] Heritability of Protein and Metabolite Biomarkers Associated with COVID-19 Severity: A Metabolomics and Proteomics Analysis
    Haj, Amelia K.
    Hasan, Haytham
    Raife, Thomas J.
    BIOMOLECULES, 2023, 13 (01)
  • [43] Longitudinal Plasma Proteomics Analysis Reveals Novel Candidate Biomarkers in Acute COVID-19
    Mohammed, Yassene
    Goodlett, David R.
    Cheng, Matthew P.
    Vinh, Donald C.
    Lee, Todd C.
    Mcgeer, Allison
    Sweet, David
    Tran, Karen
    Lee, Terry
    Murthy, Srinivas
    Boyd, John H.
    Singer, Joel
    Walley, Keith R.
    Patrick, David M.
    Quan, Curtis
    Ismail, Sara
    Amar, Laetitia
    Pal, Aditya
    Bassawon, Rayhaan
    Fesdekjian, Lara
    Gou, Karine
    Lamontagne, Francois
    Marshall, John
    Haljan, Greg
    Fowler, Robert
    Winston, Brent W.
    Russell, James A.
    JOURNAL OF PROTEOME RESEARCH, 2022, 21 (04) : 975 - 992
  • [44] Shallow Net for COVID-19 Classification based on Biomarkers
    Rokaya, Mahmoud B.
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2022, 13 (06) : 97 - 103
  • [45] Identification and validation of predictive factors for progression to severe COVID-19 pneumonia by proteomics
    Di, Biao
    Jia, Hongling
    Luo, Oscar Junhong
    Lin, Fangqin
    Li, Kuibiao
    Zhang, Yuanliang
    Wang, Huadong
    Liang, Huiying
    Fan, Jun
    Yang, Zhicong
    SIGNAL TRANSDUCTION AND TARGETED THERAPY, 2020, 5 (01)
  • [46] Identification and validation of predictive factors for progression to severe COVID-19 pneumonia by proteomics
    Biao Di
    Hongling Jia
    Oscar Junhong Luo
    Fangqin Lin
    Kuibiao Li
    Yuanliang Zhang
    Huadong Wang
    Huiying Liang
    Jun Fan
    Zhicong Yang
    Signal Transduction and Targeted Therapy, 5
  • [47] Blood biomarkers predict clinical outcomes in patients with severe COVID-19 pneumonia
    Yoon, Hee-Young
    Chae, Ganghee
    Kim, Junghyun
    Joh, Joon-Sung
    Kim, Won-Young
    Chung, Chi Ryang
    Cho, Young-Jae
    Lee, Jinwoo
    Jegal, Yang Jin
    Park, Tae Yun
    Lee, Sang Eun
    Moon, Su-jin
    Song, Jin Woo
    RESPIROLOGY, 2023, 28 : 213 - 213
  • [48] IDENTIFICATION OF COVID-19 SEVERITY AND ASSOCIATED GENETIC BIOMARKERS BASED ON SCRNA-SEQ DATA
    Goel, Aekansh
    Mudge, Zachary
    Bi, Sarah
    Brenner, Charles
    Huffman, Nicholas
    Giuste, Felipe
    Marteau, Benoit
    Shi, Wenqi
    Wang, May D.
    13TH ACM INTERNATIONAL CONFERENCE ON BIOINFORMATICS, COMPUTATIONAL BIOLOGY AND HEALTH INFORMATICS, BCB 2022, 2022,
  • [49] Identification of Transcriptome Biomarkers for Severe COVID-19 with Machine Learning Methods
    Li, Xiaohong
    Zhou, Xianchao
    Ding, Shijian
    Chen, Lei
    Feng, Kaiyan
    Li, Hao
    Huang, Tao
    Cai, Yu-Dong
    BIOMOLECULES, 2022, 12 (12)
  • [50] Identification and Analysis of Biomarkers Associated with Lipophagy and Therapeutic Agents for COVID-19
    Wu, Yujia
    Wu, Zhenlin
    Jin, Qiying
    Liu, Jinyuan
    Xu, Peiping
    VIRUSES-BASEL, 2024, 16 (06):