tetano
Editor, Senior Moderator
J Transl Med
. 2024 Jul 4;22(1):626.
doi: 10.1186/s12967-024-05342-0. Dysregulated proteasome activity and steroid hormone biosynthesis are associated with mortality among patients with acute COVID-19
Fengjiao Liu[SUP] #[/SUP][SUP] 1 2 [/SUP], Huqin Yang[SUP] #[/SUP][SUP] 1 [/SUP], Tingyu Yang[SUP] 2 [/SUP], Zhijin Zhang[SUP] 1 [/SUP], Lujia Guan[SUP] 1 [/SUP], Leyi Gao[SUP] 1 [/SUP], Haomiao Ma[SUP] 1 [/SUP], Haifan Zhang[SUP] 1 [/SUP], Nan Song[SUP] 3 4 [/SUP], Zhaohui Tong[SUP] 5 [/SUP], Jieqiong Li[SUP] 6 7 [/SUP]
Affiliations
The persistence of coronavirus disease 2019 (COVID-19)-related hospitalization severely threatens medical systems worldwide and has increased the need for reliable detection of acute status and prediction of mortality. We applied a systems biology approach to discover acute-stage biomarkers that could predict mortality. A total 247 plasma samples were collected from 103 COVID-19 (52 surviving COVID-19 patients and 51 COVID-19 patients with mortality), 51 patients with other infectious diseases (IDCs) and 41 healthy controls (HCs). Paired plasma samples were obtained from survival COVID-19 patients within 1 day after hospital admission and 1-3 days before discharge. There were clear differences between COVID-19 patients and controls, as well as substantial differences between the acute and recovery phases of COVID-19. Samples from patients in the acute phase showed suppressed immunity and decreased steroid hormone biosynthesis, as well as elevated inflammation and proteasome activation. These findings were validated by enzyme-linked immunosorbent assays and metabolomic analyses in a larger cohort. Moreover, excessive proteasome activity was a prominent signature in the acute phase among patients with mortality, indicating that it may be a key cause of poor prognosis. Based on these features, we constructed a machine learning panel, including four proteins [C-reactive protein (CRP), proteasome subunit alpha type (PSMA)1, PSMA7, and proteasome subunit beta type (PSMB)1)] and one metabolite (urocortisone), to predict mortality among COVID-19 patients (area under the receiver operating characteristic curve: 0.976) on the first day of hospitalization. Our systematic analysis provides a novel method for the early prediction of mortality in hospitalized COVID-19 patients.
Keywords: Acute phase; COVID-19; Mortality; Omics; Prediction.
. 2024 Jul 4;22(1):626.
doi: 10.1186/s12967-024-05342-0. Dysregulated proteasome activity and steroid hormone biosynthesis are associated with mortality among patients with acute COVID-19
Fengjiao Liu[SUP] #[/SUP][SUP] 1 2 [/SUP], Huqin Yang[SUP] #[/SUP][SUP] 1 [/SUP], Tingyu Yang[SUP] 2 [/SUP], Zhijin Zhang[SUP] 1 [/SUP], Lujia Guan[SUP] 1 [/SUP], Leyi Gao[SUP] 1 [/SUP], Haomiao Ma[SUP] 1 [/SUP], Haifan Zhang[SUP] 1 [/SUP], Nan Song[SUP] 3 4 [/SUP], Zhaohui Tong[SUP] 5 [/SUP], Jieqiong Li[SUP] 6 7 [/SUP]
Affiliations
- PMID: 38965561
- DOI: 10.1186/s12967-024-05342-0
The persistence of coronavirus disease 2019 (COVID-19)-related hospitalization severely threatens medical systems worldwide and has increased the need for reliable detection of acute status and prediction of mortality. We applied a systems biology approach to discover acute-stage biomarkers that could predict mortality. A total 247 plasma samples were collected from 103 COVID-19 (52 surviving COVID-19 patients and 51 COVID-19 patients with mortality), 51 patients with other infectious diseases (IDCs) and 41 healthy controls (HCs). Paired plasma samples were obtained from survival COVID-19 patients within 1 day after hospital admission and 1-3 days before discharge. There were clear differences between COVID-19 patients and controls, as well as substantial differences between the acute and recovery phases of COVID-19. Samples from patients in the acute phase showed suppressed immunity and decreased steroid hormone biosynthesis, as well as elevated inflammation and proteasome activation. These findings were validated by enzyme-linked immunosorbent assays and metabolomic analyses in a larger cohort. Moreover, excessive proteasome activity was a prominent signature in the acute phase among patients with mortality, indicating that it may be a key cause of poor prognosis. Based on these features, we constructed a machine learning panel, including four proteins [C-reactive protein (CRP), proteasome subunit alpha type (PSMA)1, PSMA7, and proteasome subunit beta type (PSMB)1)] and one metabolite (urocortisone), to predict mortality among COVID-19 patients (area under the receiver operating characteristic curve: 0.976) on the first day of hospitalization. Our systematic analysis provides a novel method for the early prediction of mortality in hospitalized COVID-19 patients.
Keywords: Acute phase; COVID-19; Mortality; Omics; Prediction.