Flower lose, a cell fitness marker, predicts COVID‐19 prognosis
Abstract Risk stratification of COVID‐19 patients is essential for pandemic management. Changes in the cell fitness marker, hFwe‐Lose, can precede the host immune response to infection, potentially making such a biomarker an earlier triage tool. Here, we evaluate whether hFwe‐Lose gene expression ca...
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Wiley
2021
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oai:doaj.org-article:f8eb078fb27a469bb4350f69d131fd6a2021-11-08T09:27:45ZFlower lose, a cell fitness marker, predicts COVID‐19 prognosis1757-46841757-467610.15252/emmm.202013714https://doaj.org/article/f8eb078fb27a469bb4350f69d131fd6a2021-11-01T00:00:00Zhttps://doi.org/10.15252/emmm.202013714https://doaj.org/toc/1757-4676https://doaj.org/toc/1757-4684Abstract Risk stratification of COVID‐19 patients is essential for pandemic management. Changes in the cell fitness marker, hFwe‐Lose, can precede the host immune response to infection, potentially making such a biomarker an earlier triage tool. Here, we evaluate whether hFwe‐Lose gene expression can outperform conventional methods in predicting outcomes (e.g., death and hospitalization) in COVID‐19 patients. We performed a post‐mortem examination of infected lung tissue in deceased COVID‐19 patients to determine hFwe‐Lose’s biological role in acute lung injury. We then performed an observational study (n = 283) to evaluate whether hFwe‐Lose expression (in nasopharyngeal samples) could accurately predict hospitalization or death in COVID‐19 patients. In COVID‐19 patients with acute lung injury, hFwe‐Lose is highly expressed in the lower respiratory tract and is co‐localized to areas of cell death. In patients presenting in the early phase of COVID‐19 illness, hFwe‐Lose expression accurately predicts subsequent hospitalization or death with positive predictive values of 87.8–100% and a negative predictive value of 64.1–93.2%. hFwe‐Lose outperforms conventional inflammatory biomarkers and patient age and comorbidities, with an area under the receiver operating characteristic curve (AUROC) 0.93–0.97 in predicting hospitalization/death. Specifically, this is significantly higher than the prognostic value of combining biomarkers (serum ferritin, D‐dimer, C‐reactive protein, and neutrophil–lymphocyte ratio), patient age and comorbidities (AUROC of 0.67–0.92). The cell fitness marker, hFwe‐Lose, accurately predicts outcomes in COVID‐19 patients. This finding demonstrates how tissue fitness pathways dictate the response to infection and disease and their utility in managing the current COVID‐19 pandemic.Michail YekelchykEsha MadanJochen WilhelmKirsty R ShortAntónio M PalmaLinbu LiaoDenise CamachoEverlyne NkadoriMichael T WintersEmily S RiceInês RolimRaquel Cruz‐DuarteChristopher J PelhamMasaki NaganeKartik GuptaSahil ChaudharyThomas BraunRaghavendra PillappaMark S ParkerThomas MenterMatthias MatterJasmin Dionne HaslbauerMarkus TolnayKornelia D GaliorKristina A MatkwoskyjStephanie M McGregorLaura K MullerEmad A RakhaAntonio Lopez‐BeltranRonny DrapkinMaximilian AckermannPaul B FisherSteven R GrossmanAndrew K GodwinArutha KulasingheIvan MartinezClay B MarshBenjamin TangMax S WichaKyoung Jae WonAlexandar TzankovEduardo MorenoRajan GognaWileyarticlebiomarkercell fitnessCOVID‐19flowerprognosisMedicine (General)R5-920GeneticsQH426-470ENEMBO Molecular Medicine, Vol 13, Iss 11, Pp n/a-n/a (2021) |
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DOAJ |
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DOAJ |
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| topic |
biomarker cell fitness COVID‐19 flower prognosis Medicine (General) R5-920 Genetics QH426-470 |
| spellingShingle |
biomarker cell fitness COVID‐19 flower prognosis Medicine (General) R5-920 Genetics QH426-470 Michail Yekelchyk Esha Madan Jochen Wilhelm Kirsty R Short António M Palma Linbu Liao Denise Camacho Everlyne Nkadori Michael T Winters Emily S Rice Inês Rolim Raquel Cruz‐Duarte Christopher J Pelham Masaki Nagane Kartik Gupta Sahil Chaudhary Thomas Braun Raghavendra Pillappa Mark S Parker Thomas Menter Matthias Matter Jasmin Dionne Haslbauer Markus Tolnay Kornelia D Galior Kristina A Matkwoskyj Stephanie M McGregor Laura K Muller Emad A Rakha Antonio Lopez‐Beltran Ronny Drapkin Maximilian Ackermann Paul B Fisher Steven R Grossman Andrew K Godwin Arutha Kulasinghe Ivan Martinez Clay B Marsh Benjamin Tang Max S Wicha Kyoung Jae Won Alexandar Tzankov Eduardo Moreno Rajan Gogna Flower lose, a cell fitness marker, predicts COVID‐19 prognosis |
| description |
Abstract Risk stratification of COVID‐19 patients is essential for pandemic management. Changes in the cell fitness marker, hFwe‐Lose, can precede the host immune response to infection, potentially making such a biomarker an earlier triage tool. Here, we evaluate whether hFwe‐Lose gene expression can outperform conventional methods in predicting outcomes (e.g., death and hospitalization) in COVID‐19 patients. We performed a post‐mortem examination of infected lung tissue in deceased COVID‐19 patients to determine hFwe‐Lose’s biological role in acute lung injury. We then performed an observational study (n = 283) to evaluate whether hFwe‐Lose expression (in nasopharyngeal samples) could accurately predict hospitalization or death in COVID‐19 patients. In COVID‐19 patients with acute lung injury, hFwe‐Lose is highly expressed in the lower respiratory tract and is co‐localized to areas of cell death. In patients presenting in the early phase of COVID‐19 illness, hFwe‐Lose expression accurately predicts subsequent hospitalization or death with positive predictive values of 87.8–100% and a negative predictive value of 64.1–93.2%. hFwe‐Lose outperforms conventional inflammatory biomarkers and patient age and comorbidities, with an area under the receiver operating characteristic curve (AUROC) 0.93–0.97 in predicting hospitalization/death. Specifically, this is significantly higher than the prognostic value of combining biomarkers (serum ferritin, D‐dimer, C‐reactive protein, and neutrophil–lymphocyte ratio), patient age and comorbidities (AUROC of 0.67–0.92). The cell fitness marker, hFwe‐Lose, accurately predicts outcomes in COVID‐19 patients. This finding demonstrates how tissue fitness pathways dictate the response to infection and disease and their utility in managing the current COVID‐19 pandemic. |
| format |
article |
| author |
Michail Yekelchyk Esha Madan Jochen Wilhelm Kirsty R Short António M Palma Linbu Liao Denise Camacho Everlyne Nkadori Michael T Winters Emily S Rice Inês Rolim Raquel Cruz‐Duarte Christopher J Pelham Masaki Nagane Kartik Gupta Sahil Chaudhary Thomas Braun Raghavendra Pillappa Mark S Parker Thomas Menter Matthias Matter Jasmin Dionne Haslbauer Markus Tolnay Kornelia D Galior Kristina A Matkwoskyj Stephanie M McGregor Laura K Muller Emad A Rakha Antonio Lopez‐Beltran Ronny Drapkin Maximilian Ackermann Paul B Fisher Steven R Grossman Andrew K Godwin Arutha Kulasinghe Ivan Martinez Clay B Marsh Benjamin Tang Max S Wicha Kyoung Jae Won Alexandar Tzankov Eduardo Moreno Rajan Gogna |
| author_facet |
Michail Yekelchyk Esha Madan Jochen Wilhelm Kirsty R Short António M Palma Linbu Liao Denise Camacho Everlyne Nkadori Michael T Winters Emily S Rice Inês Rolim Raquel Cruz‐Duarte Christopher J Pelham Masaki Nagane Kartik Gupta Sahil Chaudhary Thomas Braun Raghavendra Pillappa Mark S Parker Thomas Menter Matthias Matter Jasmin Dionne Haslbauer Markus Tolnay Kornelia D Galior Kristina A Matkwoskyj Stephanie M McGregor Laura K Muller Emad A Rakha Antonio Lopez‐Beltran Ronny Drapkin Maximilian Ackermann Paul B Fisher Steven R Grossman Andrew K Godwin Arutha Kulasinghe Ivan Martinez Clay B Marsh Benjamin Tang Max S Wicha Kyoung Jae Won Alexandar Tzankov Eduardo Moreno Rajan Gogna |
| author_sort |
Michail Yekelchyk |
| title |
Flower lose, a cell fitness marker, predicts COVID‐19 prognosis |
| title_short |
Flower lose, a cell fitness marker, predicts COVID‐19 prognosis |
| title_full |
Flower lose, a cell fitness marker, predicts COVID‐19 prognosis |
| title_fullStr |
Flower lose, a cell fitness marker, predicts COVID‐19 prognosis |
| title_full_unstemmed |
Flower lose, a cell fitness marker, predicts COVID‐19 prognosis |
| title_sort |
flower lose, a cell fitness marker, predicts covid‐19 prognosis |
| publisher |
Wiley |
| publishDate |
2021 |
| url |
https://doaj.org/article/f8eb078fb27a469bb4350f69d131fd6a |
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