6 results on '"Ansari, M. Azim"'
Search Results
2. Distinct patterns of within-host virus populations between two subgroups of human respiratory syncytial virus
- Author
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Lin, Gu-Lung, Drysdale, Simon B., Snape, Matthew D., O’Connor, Daniel, Brown, Anthony, MacIntyre-Cockett, George, Mellado-Gomez, Esther, de Cesare, Mariateresa, Bonsall, David, Ansari, M. Azim, Öner, Deniz, Aerssens, Jeroen, Butler, Christopher, Bont, Louis, Openshaw, Peter, Martinón-Torres, Federico, Nair, Harish, Bowden, Rory, Golubchik, Tanya, and Pollard, Andrew J.
- Published
- 2021
- Full Text
- View/download PDF
3. T cell assays differentiate clinical and subclinical SARS-CoV-2 infections from cross-reactive antiviral responses
- Author
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Ogbe, Ane, Kronsteiner, Barbara, Skelly, Donal T, Pace, Matthew, Brown, Anthony, Adland, Emily, Adair, Kareena, Akhter, Hossain Delowar, Ali, Mohammad, Ali, Serat-E, Angyal, Adrienn, Ansari, M Azim, Arancibia-Carcamo, Carolina V, Brown, Helen, Chinnakannan, Senthil, Conlon, Christopher, de Lara, Catherine, de Silva, Thushan, Dold, Christina, Dong, Tao, Donnison, Timothy, Eyre, David, Flaxman, Amy, Fletcher, Helen, Gardner, Joshua, Grist, James T, Hackstein, Carl-Philipp, Jaruthamsophon, Kanoot, Jeffery, Katie, Lambe, Teresa, Lee, Lian, Li, Wenqin, Lim, Nicholas, Matthews, Philippa C, Mentzer, Alexander J, Moore, Shona C, Naisbitt, Dean J, Ogese, Monday, Ogg, Graham, Openshaw, Peter, Pirmohamed, Munir, Pollard, Andrew J, Ramamurthy, Narayan, Rongkard, Patpong, Rowland-Jones, Sarah, Sampson, Oliver, Screaton, Gavin, Sette, Alessandro, Stafford, Lizzie, Thompson, Craig, Thomson, Paul J, Thwaites, Ryan, Vieira, Vinicius, Weiskopf, Daniela, Zacharopoulou, Panagiota, Chalk, Jeremy, Kerr, Georgina, Phalora, Prabhjeet, Csala, Anna, Jones, Mathew, Robinson, Nicola, Brown, Rachael, Hutchings, Claire, Provine, Nicholas, Ratcliff, Jeremy, Amini, Ali, Borak, Martyna, Dimitriadis, Stavros, Fordwoh, Thomas, Horsington, Bryn, Johnson, Sile, Morrow, Jordan, Warren, Yolanda, Wells, Charlie, Turtle, Lance, Klenerman, Paul, Goulder, Philip, Frater, John, Barnes, Eleanor, Dunachie, Susanna, Immunology, Oxford, and Oxford, Protective TC
- Subjects
0301 basic medicine ,CD4-Positive T-Lymphocytes ,animal diseases ,T-Lymphocytes ,General Physics and Astronomy ,CD8-Positive T-Lymphocytes ,Immunological memory ,0302 clinical medicine ,030212 general & internal medicine ,Subclinical infection ,Immunoassay ,Multidisciplinary ,ELISPOT ,3. Good health ,Multidisciplinary Sciences ,medicine.anatomical_structure ,Science & Technology - Other Topics ,VIRUS ,Cytokines ,Science ,T cell ,Health Personnel ,Oxford Protective T Cell Immunology for COVID-19 (OPTIC) Clinical Team ,chemical and pharmacologic phenomena ,Biology ,Cross Reactions ,Antiviral Agents ,General Biochemistry, Genetics and Molecular Biology ,Article ,03 medical and health sciences ,Interferon-gamma ,Immune system ,Antigen ,Immunity ,medicine ,Humans ,Pandemics ,Cell Proliferation ,Science & Technology ,Cell growth ,SARS-CoV-2 ,Oxford Immunology Network Covid-19 Response T Cell Consortium ,COVID-19 ,General Chemistry ,biochemical phenomena, metabolism, and nutrition ,030104 developmental biology ,HEK293 Cells ,Viral infection ,Immunoglobulin G ,Immunology ,bacteria ,Peptides ,Immunologic Memory ,Ex vivo - Abstract
Identification of protective T cell responses against SARS-CoV-2 requires distinguishing people infected with SARS-CoV-2 from those with cross-reactive immunity to other coronaviruses. Here we show a range of T cell assays that differentially capture immune function to characterise SARS-CoV-2 responses. Strong ex vivo ELISpot and proliferation responses to multiple antigens (including M, NP and ORF3) are found in 168 PCR-confirmed SARS-CoV-2 infected volunteers, but are rare in 119 uninfected volunteers. Highly exposed seronegative healthcare workers with recent COVID-19-compatible illness show T cell response patterns characteristic of infection. By contrast, >90% of convalescent or unexposed people show proliferation and cellular lactate responses to spike subunits S1/S2, indicating pre-existing cross-reactive T cell populations. The detection of T cell responses to SARS-CoV-2 is therefore critically dependent on assay and antigen selection. Memory responses to specific non-spike proteins provide a method to distinguish recent infection from pre-existing immunity in exposed populations., Understanding the immune response to SARS-CoV-2 is dependent on being able to distinguish COVID-19 immune responses from cross-reactive immune responses to other coronaviruses. Here the authors show that choice of antigens and whether an ICS, ELISPOT or T cell proliferation assay is used has a major effect on this discriminatory ability.
- Published
- 2020
4. T cell assays differentiate clinical and subclinical SARS-CoV-2 infections from cross-reactive antiviral responses.
- Author
-
Ogbe, Ane, Kronsteiner, Barbara, Skelly, Donal T., Pace, Matthew, Brown, Anthony, Adland, Emily, Adair, Kareena, Akhter, Hossain Delowar, Ali, Mohammad, Ali, Serat-E, Angyal, Adrienn, Ansari, M. Azim, Arancibia-Cárcamo, Carolina V., Brown, Helen, Chinnakannan, Senthil, Conlon, Christopher, de Lara, Catherine, de Silva, Thushan, Dold, Christina, and Dong, Tao
- Subjects
SARS-CoV-2 ,MEDICAL personnel ,COVID-19 ,CELL populations ,CELL proliferation - Abstract
Identification of protective T cell responses against SARS-CoV-2 requires distinguishing people infected with SARS-CoV-2 from those with cross-reactive immunity to other coronaviruses. Here we show a range of T cell assays that differentially capture immune function to characterise SARS-CoV-2 responses. Strong ex vivo ELISpot and proliferation responses to multiple antigens (including M, NP and ORF3) are found in 168 PCR-confirmed SARS-CoV-2 infected volunteers, but are rare in 119 uninfected volunteers. Highly exposed seronegative healthcare workers with recent COVID-19-compatible illness show T cell response patterns characteristic of infection. By contrast, >90% of convalescent or unexposed people show proliferation and cellular lactate responses to spike subunits S1/S2, indicating pre-existing cross-reactive T cell populations. The detection of T cell responses to SARS-CoV-2 is therefore critically dependent on assay and antigen selection. Memory responses to specific non-spike proteins provide a method to distinguish recent infection from pre-existing immunity in exposed populations. Understanding the immune response to SARS-CoV-2 is dependent on being able to distinguish COVID-19 immune responses from cross-reactive immune responses to other coronaviruses. Here the authors show that choice of antigens and whether an ICS, ELISPOT or T cell proliferation assay is used has a major effect on this discriminatory ability. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
5. Publisher Correction: Distinct patterns of within-host virus populations between two subgroups of human respiratory syncytial virus.
- Author
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Lin, Gu-Lung, Drysdale, Simon B., Snape, Matthew D., O'Connor, Daniel, Brown, Anthony, MacIntyre-Cockett, George, Mellado-Gomez, Esther, de Cesare, Mariateresa, Bonsall, David, Ansari, M. Azim, Öner, Deniz, Aerssens, Jeroen, Butler, Christopher, Bont, Louis, Openshaw, Peter, Martinón-Torres, Federico, Nair, Harish, Bowden, Rory, RESCEU Investigators, and Campbell, Harry
- Subjects
PUBLISHING ,RESPIRATORY syncytial virus ,VIRUSES - Abstract
This has been updated so that all affiliations are accurate in the HTML version of the Article. The original HTML version of this Article contained errors in the author affiliations, which were correct in the PDF version. These authors jointly supervised this work: Tanya Golubchik, Andrew J. Pollard. [Extracted from the article]
- Published
- 2021
- Full Text
- View/download PDF
6. Viral genome wide association study identifies novel hepatitis C virus polymorphisms associated with sofosbuvir treatment failure.
- Author
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Smith DA, Fernandez-Antunez C, Magri A, Bowden R, Chaturvedi N, Fellay J, McLauchlan J, Foster GR, Irving WL, Simmonds P, Pedergnana V, Ramirez S, Bukh J, Barnes E, and Ansari MA
- Subjects
- Genotype, Hepacivirus drug effects, Hepacivirus isolation & purification, Humans, Polymorphism, Genetic, Treatment Failure, Viral Load drug effects, Viral Load genetics, Viral Nonstructural Proteins genetics, Antiviral Agents therapeutic use, Genome, Viral genetics, Hepacivirus genetics, Hepatitis C, Chronic drug therapy, Hepatitis C, Chronic virology, Sofosbuvir therapeutic use
- Abstract
Persistent hepatitis C virus (HCV) infection is a major cause of chronic liver disease, worldwide. With the development of direct-acting antivirals, treatment of chronically infected patients has become highly effective, although a subset of patients responds less well to therapy. Sofosbuvir is a common component of current de novo or salvage combination therapies, that targets the HCV NS5B polymerase. We use pre-treatment whole-genome sequences of HCV from 507 patients infected with HCV subtype 3a and treated with sofosbuvir containing regimens to detect viral polymorphisms associated with response to treatment. We find three common polymorphisms in non-targeted HCV NS2 and NS3 proteins are associated with reduced treatment response. These polymorphisms are enriched in post-treatment HCV sequences of patients unresponsive to treatment. They are also associated with lower reductions in viral load in the first week of therapy. Using in vitro short-term dose-response assays, these polymorphisms do not cause any reduction in sofosbuvir potency, suggesting an indirect mechanism of action in decreasing sofosbuvir efficacy. The identification of polymorphisms in NS2 and NS3 proteins associated with poor treatment outcomes emphasises the value of systematic genome-wide analyses of viruses in uncovering clinically relevant polymorphisms that impact treatment., (© 2021. The Author(s).)
- Published
- 2021
- Full Text
- View/download PDF
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