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Your search keyword '"Buang, Norzawani B"' showing total 7 results
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7 results on '"Buang, Norzawani B"'

1. Multi-omics identify falling LRRC15 as a COVID-19 severity marker and persistent pro-thrombotic signals in convalescence

Author

Gisby, Jack S., Buang, Norzawani B., Papadaki, Artemis, Clarke, Candice L., Malik, Talat H., Medjeral-Thomas, Nicholas, Pinheiro, Damiola, Mortimer, Paige M., Lewis, Shanice, Sandhu, Eleanor, McAdoo, Stephen P., Prendecki, Maria F., Willicombe, Michelle, Pickering, Matthew C., Botto, Marina, Thomas, David C., and Peters, James E.

Published
2022
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2. Multi-omics identify LRRC15 as a COVID-19 severity predictor and persistent pro-thrombotic signals in convalescence

Author

Gisby, Jack S., primary, Buang, Norzawani B., additional, Papadaki, Artemis, additional, Clarke, Candice L., additional, Malik, Talat H., additional, Medjeral-Thomas, Nicholas, additional, Pinheiro, Damiola, additional, Mortimer, Paige M., additional, Lewis, Shanice, additional, Sandhu, Eleanor, additional, McAdoo, Stephen P., additional, Prendecki, Maria F., additional, Willicombe, Michelle, additional, Pickering, Matthew C., additional, Botto, Marina, additional, Thomas, David C., additional, and Peters, James E., additional

Published
2022
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3. Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death

Author

Gisby, Jack, primary, Clarke, Candice L, additional, Medjeral-Thomas, Nicholas, additional, Malik, Talat H, additional, Papadaki, Artemis, additional, Mortimer, Paige M, additional, Buang, Norzawani B, additional, Lewis, Shanice, additional, Pereira, Marie, additional, Toulza, Frederic, additional, Fagnano, Ester, additional, Mawhin, Marie-Anne, additional, Dutton, Emma E, additional, Tapeng, Lunnathaya, additional, Richard, Arianne C, additional, Kirk, Paul DW, additional, Behmoaras, Jacques, additional, Sandhu, Eleanor, additional, McAdoo, Stephen P, additional, Prendecki, Maria F, additional, Pickering, Matthew C, additional, Botto, Marina, additional, Willicombe, Michelle, additional, Thomas, David C, additional, and Peters, James E, additional

Published
2021
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4. Author response: Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death

Author

Gisby, Jack, primary, Clarke, Candice L, additional, Medjeral-Thomas, Nicholas, additional, Malik, Talat H, additional, Papadaki, Artemis, additional, Mortimer, Paige M, additional, Buang, Norzawani B, additional, Lewis, Shanice, additional, Pereira, Marie, additional, Toulza, Frederic, additional, Fagnano, Ester, additional, Mawhin, Marie-Anne, additional, Dutton, Emma E, additional, Tapeng, Lunnathaya, additional, Richard, Arianne C, additional, Kirk, Paul DW, additional, Behmoaras, Jacques, additional, Sandhu, Eleanor, additional, McAdoo, Stephen P, additional, Prendecki, Maria F, additional, Pickering, Matthew C, additional, Botto, Marina, additional, Willicombe, Michelle, additional, Thomas, David C, additional, and Peters, James E, additional

Published
2021
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5. Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death

Author

Gisby, Jack, primary, Clarke, Candice L., additional, Medjeral-Thomas, Nicholas, additional, Malik, Talat H., additional, Papadaki, Artemis, additional, Mortimer, Paige M., additional, Buang, Norzawani B., additional, Lewis, Shanice, additional, Pereira, Marie, additional, Toulza, Frederic, additional, Fagnano, Ester, additional, Mawhin, Marie-Anne, additional, Dutton, Emma E., additional, Tapeng, Lunnathaya, additional, Richard, Arianne C., additional, Kirk, Paul D. W., additional, Behmoaras, Jacques, additional, Sandhu, Eleanor, additional, McAdoo, Stephen P., additional, Prendecki, Maria F., additional, Pickering, Matthew C., additional, Botto, Marina, additional, Willicombe, Michelle, additional, Thomas, David C., additional, and Peters, James E., additional

Published
2020
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6. Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death

Author

Gisby, Jack, Clarke, Candice L, Medjeral-Thomas, Nicholas, Malik, Talat H, Papadaki, Artemis, Mortimer, Paige M, Buang, Norzawani B, Lewis, Shanice, Pereira, Marie, Toulza, Frederic, Fagnano, Ester, Mawhin, Marie-Anne, Dutton, Emma E, Tapeng, Lunnathaya, Richard, Arianne C, Kirk, Paul Dw, Behmoaras, Jacques, Sandhu, Eleanor, McAdoo, Stephen P, Prendecki, Maria F, Pickering, Matthew C, Botto, Marina, Willicombe, Michelle, Thomas, David C, and Peters, James E

Subjects
Male, Proteomics, medicine, longitudinal, SARS-CoV-2, COVID-19, biomarkers, Middle Aged, Prognosis, Severity of Illness Index, cytokines, 3. Good health, immunology, Hospitalization, inflammation, Renal Dialysis, end-stage kidney disease, Humans, Kidney Failure, Chronic, Female, human, Longitudinal Studies, Aged, Forecasting
Abstract

End-stage kidney disease (ESKD) patients are at high risk of severe COVID-19. We measured 436 circulating proteins in serial blood samples from hospitalised and non-hospitalised ESKD patients with COVID-19 (n = 256 samples from 55 patients). Comparison to 51 non-infected patients revealed 221 differentially expressed proteins, with consistent results in a separate subcohort of 46 COVID-19 patients. Two hundred and three proteins were associated with clinical severity, including IL6, markers of monocyte recruitment (e.g. CCL2, CCL7), neutrophil activation (e.g. proteinase-3), and epithelial injury (e.g. KRT19). Machine-learning identified predictors of severity including IL18BP, CTSD, GDF15, and KRT19. Survival analysis with joint models revealed 69 predictors of death. Longitudinal modelling with linear mixed models uncovered 32 proteins displaying different temporal profiles in severe versus non-severe disease, including integrins and adhesion molecules. These data implicate epithelial damage, innate immune activation, and leucocyte-endothelial interactions in the pathology of severe COVID-19 and provide a resource for identifying drug targets.

7. Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death

Author

Gisby, Jack, Clarke, Candice L, Medjeral-Thomas, Nicholas, Malik, Talat H, Papadaki, Artemis, Mortimer, Paige M, Buang, Norzawani B, Lewis, Shanice, Pereira, Marie, Toulza, Frederic, Fagnano, Ester, Mawhin, Marie-Anne, Dutton, Emma E, Tapeng, Lunnathaya, Richard, Arianne C, Kirk, Paul DW, Behmoaras, Jacques, Sandhu, Eleanor, McAdoo, Stephen P, Prendecki, Maria F, Pickering, Matthew C, Botto, Marina, Willicombe, Michelle, Thomas, David C, and Peters, James E

Subjects
Immunology and Inflammation, proteomics, longitudinal, end-stage kidney disease, Medicine, COVID-19, biomarkers, cytokines, 3. Good health, Research Article, Human
Abstract

Funder: The Sidharth Burman endowment, End-stage kidney disease (ESKD) patients are at high risk of severe COVID-19. We measured 436 circulating proteins in serial blood samples from hospitalised and non-hospitalised ESKD patients with COVID-19 (n = 256 samples from 55 patients). Comparison to 51 non-infected patients revealed 221 differentially expressed proteins, with consistent results in a separate subcohort of 46 COVID-19 patients. Two hundred and three proteins were associated with clinical severity, including IL6, markers of monocyte recruitment (e.g. CCL2, CCL7), neutrophil activation (e.g. proteinase-3), and epithelial injury (e.g. KRT19). Machine-learning identified predictors of severity including IL18BP, CTSD, GDF15, and KRT19. Survival analysis with joint models revealed 69 predictors of death. Longitudinal modelling with linear mixed models uncovered 32 proteins displaying different temporal profiles in severe versus non-severe disease, including integrins and adhesion molecules. These data implicate epithelial damage, innate immune activation, and leucocyte–endothelial interactions in the pathology of severe COVID-19 and provide a resource for identifying drug targets.

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