Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications
<p dir="ltr">COVID-19 complications still present a huge burden on healthcare systems and warrant predictive risk models to triage patients and inform early intervention. Here, we profile 893 plasma proteins from 50 severe and 50 mild-moderate COVID-19 patients, and 50 healthy contro...
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2022
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| _version_ | 1864513518627192832 |
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| author | Maryam A. Y. Al-Nesf (18426867) |
| author2 | Houari B. Abdesselem (14152827) Ilham Bensmail (12204845) Shahd Ibrahim (12204847) Walaa A. H. Saeed (18426870) Sara S. I. Mohammed (18426873) Almurtada Razok (12204854) Hashim Alhussain (9167136) Reham M. A. Aly (18426876) Muna Al Maslamani (12501671) Khalid Ouararhni (3145734) Mohamad Y. Khatib (11659459) Ali Ait Hssain (11264358) Ali S. Omrani (9590116) Saad Al-Kaabi (12204872) Abdullatif Al Khal (12024468) Asmaa A. Al-Thani (11264355) Waseem Samsam (12204880) Abdulaziz Farooq (5345384) Jassim Al-Suwaidi (12204883) Mohammed Al-Maadheed (12204886) Heba H. Al-Siddiqi (17733783) Alexandra E. Butler (6189536) Julie V. Decock (18426879) Vidya Mohamed-Ali (12204895) Fares Al-Ejeh (266674) |
| author2_role | author author author author author author author author author author author author author author author author author author author author author author author author author |
| author_facet | Maryam A. Y. Al-Nesf (18426867) Houari B. Abdesselem (14152827) Ilham Bensmail (12204845) Shahd Ibrahim (12204847) Walaa A. H. Saeed (18426870) Sara S. I. Mohammed (18426873) Almurtada Razok (12204854) Hashim Alhussain (9167136) Reham M. A. Aly (18426876) Muna Al Maslamani (12501671) Khalid Ouararhni (3145734) Mohamad Y. Khatib (11659459) Ali Ait Hssain (11264358) Ali S. Omrani (9590116) Saad Al-Kaabi (12204872) Abdullatif Al Khal (12024468) Asmaa A. Al-Thani (11264355) Waseem Samsam (12204880) Abdulaziz Farooq (5345384) Jassim Al-Suwaidi (12204883) Mohammed Al-Maadheed (12204886) Heba H. Al-Siddiqi (17733783) Alexandra E. Butler (6189536) Julie V. Decock (18426879) Vidya Mohamed-Ali (12204895) Fares Al-Ejeh (266674) |
| author_role | author |
| dc.creator.none.fl_str_mv | Maryam A. Y. Al-Nesf (18426867) Houari B. Abdesselem (14152827) Ilham Bensmail (12204845) Shahd Ibrahim (12204847) Walaa A. H. Saeed (18426870) Sara S. I. Mohammed (18426873) Almurtada Razok (12204854) Hashim Alhussain (9167136) Reham M. A. Aly (18426876) Muna Al Maslamani (12501671) Khalid Ouararhni (3145734) Mohamad Y. Khatib (11659459) Ali Ait Hssain (11264358) Ali S. Omrani (9590116) Saad Al-Kaabi (12204872) Abdullatif Al Khal (12024468) Asmaa A. Al-Thani (11264355) Waseem Samsam (12204880) Abdulaziz Farooq (5345384) Jassim Al-Suwaidi (12204883) Mohammed Al-Maadheed (12204886) Heba H. Al-Siddiqi (17733783) Alexandra E. Butler (6189536) Julie V. Decock (18426879) Vidya Mohamed-Ali (12204895) Fares Al-Ejeh (266674) |
| dc.date.none.fl_str_mv | 2022-02-17T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1038/s41467-022-28639-4 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Prognostic_tools_and_candidate_drugs_based_on_plasma_proteomics_of_patients_with_severe_COVID-19_complications/25671621 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biological sciences Bioinformatics and computational biology Biomedical and clinical sciences Cardiovascular medicine and haematology Medical biochemistry and metabolomics Health sciences Health services and systems COVID-19 Healthcare systems Predictive risk models Triage Early intervention Plasma proteins |
| dc.title.none.fl_str_mv | Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">COVID-19 complications still present a huge burden on healthcare systems and warrant predictive risk models to triage patients and inform early intervention. Here, we profile 893 plasma proteins from 50 severe and 50 mild-moderate COVID-19 patients, and 50 healthy controls, and show that 375 proteins are differentially expressed in the plasma of severe COVID-19 patients. These differentially expressed plasma proteins are implicated in the pathogenesis of COVID-19 and present targets for candidate drugs to prevent or treat severe complications. Based on the plasma proteomics and clinical lab tests, we also report a 12-plasma protein signature and a model of seven routine clinical tests that validate in an independent cohort as early risk predictors of COVID-19 severity and patient survival. The risk predictors and candidate drugs described in our study can be used and developed for personalized management of SARS-CoV-2 infected patients.</p><h2>Other Information</h2><p dir="ltr">Published in: Nature Communications<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/s41467-022-28639-4" target="_blank">https://dx.doi.org/10.1038/s41467-022-28639-4</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_2fb405bb669afd43b916d9c162b9d84d |
| identifier_str_mv | 10.1038/s41467-022-28639-4 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25671621 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complicationsMaryam A. Y. Al-Nesf (18426867)Houari B. Abdesselem (14152827)Ilham Bensmail (12204845)Shahd Ibrahim (12204847)Walaa A. H. Saeed (18426870)Sara S. I. Mohammed (18426873)Almurtada Razok (12204854)Hashim Alhussain (9167136)Reham M. A. Aly (18426876)Muna Al Maslamani (12501671)Khalid Ouararhni (3145734)Mohamad Y. Khatib (11659459)Ali Ait Hssain (11264358)Ali S. Omrani (9590116)Saad Al-Kaabi (12204872)Abdullatif Al Khal (12024468)Asmaa A. Al-Thani (11264355)Waseem Samsam (12204880)Abdulaziz Farooq (5345384)Jassim Al-Suwaidi (12204883)Mohammed Al-Maadheed (12204886)Heba H. Al-Siddiqi (17733783)Alexandra E. Butler (6189536)Julie V. Decock (18426879)Vidya Mohamed-Ali (12204895)Fares Al-Ejeh (266674)Biological sciencesBioinformatics and computational biologyBiomedical and clinical sciencesCardiovascular medicine and haematologyMedical biochemistry and metabolomicsHealth sciencesHealth services and systemsCOVID-19Healthcare systemsPredictive risk modelsTriageEarly interventionPlasma proteins<p dir="ltr">COVID-19 complications still present a huge burden on healthcare systems and warrant predictive risk models to triage patients and inform early intervention. Here, we profile 893 plasma proteins from 50 severe and 50 mild-moderate COVID-19 patients, and 50 healthy controls, and show that 375 proteins are differentially expressed in the plasma of severe COVID-19 patients. These differentially expressed plasma proteins are implicated in the pathogenesis of COVID-19 and present targets for candidate drugs to prevent or treat severe complications. Based on the plasma proteomics and clinical lab tests, we also report a 12-plasma protein signature and a model of seven routine clinical tests that validate in an independent cohort as early risk predictors of COVID-19 severity and patient survival. The risk predictors and candidate drugs described in our study can be used and developed for personalized management of SARS-CoV-2 infected patients.</p><h2>Other Information</h2><p dir="ltr">Published in: Nature Communications<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/s41467-022-28639-4" target="_blank">https://dx.doi.org/10.1038/s41467-022-28639-4</a></p>2022-02-17T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1038/s41467-022-28639-4https://figshare.com/articles/journal_contribution/Prognostic_tools_and_candidate_drugs_based_on_plasma_proteomics_of_patients_with_severe_COVID-19_complications/25671621CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/256716212022-02-17T03:00:00Z |
| spellingShingle | Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications Maryam A. Y. Al-Nesf (18426867) Biological sciences Bioinformatics and computational biology Biomedical and clinical sciences Cardiovascular medicine and haematology Medical biochemistry and metabolomics Health sciences Health services and systems COVID-19 Healthcare systems Predictive risk models Triage Early intervention Plasma proteins |
| status_str | publishedVersion |
| title | Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications |
| title_full | Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications |
| title_fullStr | Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications |
| title_full_unstemmed | Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications |
| title_short | Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications |
| title_sort | Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications |
| topic | Biological sciences Bioinformatics and computational biology Biomedical and clinical sciences Cardiovascular medicine and haematology Medical biochemistry and metabolomics Health sciences Health services and systems COVID-19 Healthcare systems Predictive risk models Triage Early intervention Plasma proteins |