Sudarson Sundarrajan, K N Sridhar, Manju Moorthy, Gopalakrishna Ramaswamy
{"title":"利用纳米串技术研究印度新冠肺炎患者的免疫和炎症基因反应。","authors":"Sudarson Sundarrajan, K N Sridhar, Manju Moorthy, Gopalakrishna Ramaswamy","doi":"10.1007/s12026-025-09626-5","DOIUrl":null,"url":null,"abstract":"<p><p>COVID- 19, which has affected millions of people across the globe as a pandemic, is caused by the SARS-Cov- 2 virus which has a case fatality rate of 2.3%. The clinical outcome of those who had mild and severe infection exhibited different responses for the treatment due to differences in the host immune system. Predicting immune response with reliable biomarkers to monitor the severity and also identifying potential biomarkers that could help the clinician in decision-making would be important and also beneficial for the management of COVID- 19 in the hospital setup. In our study, we have used the NanoString nCounter gene expression assay to investigate the molecular signalling of host to COVID- 19 infection. The nCounter gene expression assay identified 29 genes that were differentially regulated and specific to COVID- 19 infection; out of which, 9 genes (ICAM3, PTAFR, CEACAM6, GBP1, C7, STAT1, CEACAM8, IL16, HLA-DPB1) exhibited strong predictive performance to differentiate COVID- 19 infection from healthy controls (AUC ≥ 0.9). We also observed that three genes (MAP4 K1, CTLA4, and HLA-DQB1) were able to differentiate COVID- 19 from patients with flu-like symptoms. A group of 11 genes (C2, CD14, CDKN1 A, CMKLR1, CYBB, HLA-A, IFNA2, LAG3, MARCO, TLR7, and IL15) showed a dysregulation trend with onset of COVID- 19 infection and settled to normal levels by day 14 as patient recovered. The outcome of our study may help in understanding the host immune response towards COVID- 19 infection.</p>","PeriodicalId":13389,"journal":{"name":"Immunologic Research","volume":"73 1","pages":"77"},"PeriodicalIF":3.3000,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study of immunological and inflammatory gene response in Indian cohort of COVID- 19 patients by NanoString technology.\",\"authors\":\"Sudarson Sundarrajan, K N Sridhar, Manju Moorthy, Gopalakrishna Ramaswamy\",\"doi\":\"10.1007/s12026-025-09626-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>COVID- 19, which has affected millions of people across the globe as a pandemic, is caused by the SARS-Cov- 2 virus which has a case fatality rate of 2.3%. The clinical outcome of those who had mild and severe infection exhibited different responses for the treatment due to differences in the host immune system. Predicting immune response with reliable biomarkers to monitor the severity and also identifying potential biomarkers that could help the clinician in decision-making would be important and also beneficial for the management of COVID- 19 in the hospital setup. In our study, we have used the NanoString nCounter gene expression assay to investigate the molecular signalling of host to COVID- 19 infection. The nCounter gene expression assay identified 29 genes that were differentially regulated and specific to COVID- 19 infection; out of which, 9 genes (ICAM3, PTAFR, CEACAM6, GBP1, C7, STAT1, CEACAM8, IL16, HLA-DPB1) exhibited strong predictive performance to differentiate COVID- 19 infection from healthy controls (AUC ≥ 0.9). We also observed that three genes (MAP4 K1, CTLA4, and HLA-DQB1) were able to differentiate COVID- 19 from patients with flu-like symptoms. A group of 11 genes (C2, CD14, CDKN1 A, CMKLR1, CYBB, HLA-A, IFNA2, LAG3, MARCO, TLR7, and IL15) showed a dysregulation trend with onset of COVID- 19 infection and settled to normal levels by day 14 as patient recovered. The outcome of our study may help in understanding the host immune response towards COVID- 19 infection.</p>\",\"PeriodicalId\":13389,\"journal\":{\"name\":\"Immunologic Research\",\"volume\":\"73 1\",\"pages\":\"77\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Immunologic Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s12026-025-09626-5\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Immunologic Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12026-025-09626-5","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
Study of immunological and inflammatory gene response in Indian cohort of COVID- 19 patients by NanoString technology.
COVID- 19, which has affected millions of people across the globe as a pandemic, is caused by the SARS-Cov- 2 virus which has a case fatality rate of 2.3%. The clinical outcome of those who had mild and severe infection exhibited different responses for the treatment due to differences in the host immune system. Predicting immune response with reliable biomarkers to monitor the severity and also identifying potential biomarkers that could help the clinician in decision-making would be important and also beneficial for the management of COVID- 19 in the hospital setup. In our study, we have used the NanoString nCounter gene expression assay to investigate the molecular signalling of host to COVID- 19 infection. The nCounter gene expression assay identified 29 genes that were differentially regulated and specific to COVID- 19 infection; out of which, 9 genes (ICAM3, PTAFR, CEACAM6, GBP1, C7, STAT1, CEACAM8, IL16, HLA-DPB1) exhibited strong predictive performance to differentiate COVID- 19 infection from healthy controls (AUC ≥ 0.9). We also observed that three genes (MAP4 K1, CTLA4, and HLA-DQB1) were able to differentiate COVID- 19 from patients with flu-like symptoms. A group of 11 genes (C2, CD14, CDKN1 A, CMKLR1, CYBB, HLA-A, IFNA2, LAG3, MARCO, TLR7, and IL15) showed a dysregulation trend with onset of COVID- 19 infection and settled to normal levels by day 14 as patient recovered. The outcome of our study may help in understanding the host immune response towards COVID- 19 infection.
期刊介绍:
IMMUNOLOGIC RESEARCH represents a unique medium for the presentation, interpretation, and clarification of complex scientific data. Information is presented in the form of interpretive synthesis reviews, original research articles, symposia, editorials, and theoretical essays. The scope of coverage extends to cellular immunology, immunogenetics, molecular and structural immunology, immunoregulation and autoimmunity, immunopathology, tumor immunology, host defense and microbial immunity, including viral immunology, immunohematology, mucosal immunity, complement, transplantation immunology, clinical immunology, neuroimmunology, immunoendocrinology, immunotoxicology, translational immunology, and history of immunology.