by Keyword: Severity prediction
Guercetti, J, Alorda, M, Sappia, L, Galve, R, Duran-Corbera, M, Pulido, D, Berardi, G, Royo, M, Lacoma, A, Muñoz, J, Padilla, E, Castañeda, S, Sendra, E, Horcajada, JP, Gutierrez-Galvez, A, Marco, S, Salvador, JP, Marco, MP, (2025). Immuno-μSARS2 Chip: A Peptide-Based Microarray to Assess COVID-19 Prognosis Based on Immunological Fingerprints Acs Pharmacology And Translational Science 8, 871-884 
A multiplexed microarray chip (Immuno-mu SARS2) aiming at providing information on the prognosis of the COVID-19 has been developed. The diagnostic technology records information related to the profile of the immunological response of patients infected by the SARS-CoV-2 virus. The diagnostic technology delivers information on the avidity of the sera against 28 different peptide epitopes and 7 proteins printed on a 25 mm2 area of a glass slide. The peptide epitopes (12-15 mer) derived from structural proteins (Spike and Nucleocapsid) have been rationally designed, synthesized, and used to develop Immuno-mu SARS2 as a multiplexed and high-throughput fluorescent microarray platform. The analysis of 755 human serum samples (321 from PCR+ patients; 288 from PCR- patients; 115 from prepandemic individuals and classified as hospitalized, admitted to intensive-care unit (ICU), and exitus) from three independent cohorts has shown that the chips perform with a 98% specificity and 91% sensitivity identifying RT-PCR+ patients. Computational analysis utilized to correlate the immunological signatures of the samples analyzed indicate significant prediction rates against exitus conditions with 82% accuracy, ICU admissions with 80% accuracy, and 73% accuracy over hospitalization requirement compared to asymptomatic patients' fingerprints. The miniaturized microarray chip allows simultaneous determination of 96 samples (24 samples/slide) in 90 min and requires only 10 mu L of sera. The diagnostic approach presented for the first time here could have a great value in assisting clinicians in decision-making based on the information provided by the Immuno-mu SARS2 regarding progression of the disease and could be easily implemented in diagnostics of other infectious diseases.
JTD Keywords: Antibodies, Clinical diagnostic, Diagnosis, High-throughput, Machine learning, Microarray, Multiplexation, Nucleocapsid protein, Peptide epitopes, Sars-cov-, Sars-cov-2, Serological signature, Seroprevalence, Severity prediction, Spik
