| Literature DB >> 35337004 |
Geum-Young Lee1, Won-Keun Kim2,3, Jin Sun No4, Yongjin Yi5, Hayne Cho Park6, Jaehun Jung7, Seungchan Cho1, Jingyeong Lee1, Seung-Ho Lee8, Kyungmin Park1,9, Jongwoo Kim1,9, Jin-Won Song1,9.
Abstract
The ability to accurately predict the early progression of hemorrhagic fever with renal syndrome (HFRS) is crucial for reducing morbidity and mortality rates in severely affected patients. However, the utility of biomarkers for predicting clinical outcomes remains elusive in HFRS. The aims of the current study were to analyze the serum levels of immune function-related proteins and identify novel biomarkers that may help ascertain clinical outcomes of HFRS. Enzyme-linked immunosorbent assay, Luminex, and bioanalyzer assays were used to quantitatively detect 15 biomarkers in 49 serum samples of 26 patients with HFRS. High hemoglobin (HGB) and low urine output (UO) levels were identified as potential biomarkers associated with the acute HFRS. The serum soluble urokinase plasminogen activator receptor (suPAR) and C-X-C motif chemokine ligand 10 (CXCL10) values increased in the early phase of diseases. Elevated suPAR, interleukin-10 (IL-10), CXCL10, and decreased transforming growth factor-beta 3 (TGF-β3) were representative predictors of the disease severity. Upregulation of the HGB showed a significant correlation with high levels of suPAR and CXCL10. Reduced UO positively correlated with increased suPAR, CXCL10, and TGF-β2, and decreased vascular endothelial growth factor and TGF-β3. The changing HGB and UO criteria, high suPAR, IL-10, CXCL10, and low TGF-β3 of HFRS raise significant awareness for physicians regarding prospective biomarkers for monitoring early warning signs of HFRS. This study provides critical insights into the clinical and immunological biomarkers for disease severity and progression in patients with HFRS to identify early predictions of fatal outcomes.Entities:
Keywords: biomarker; early phase; hemorrhagic fever with renal syndrome; prognosis; severity
Mesh:
Substances:
Year: 2022 PMID: 35337004 PMCID: PMC8954228 DOI: 10.3390/v14030595
Source DB: PubMed Journal: Viruses ISSN: 1999-4915 Impact factor: 5.048
Clinical manifestations and outcomes of patients with hemorrhagic fever with renal syndrome.
| n (%) | |
|---|---|
| Symptoms | |
| Fever | 25/26 (96) |
| Nausea | 8/26 (31) |
| Headache | 5/26 (19) |
| Diarrhea | 3/26 (12) |
| Myalgia | 1/26 (4) |
| Flank pain | 1/26 (4) |
| Chest pain | 1/26 (4) |
| Sore throat | 1/26 (4) |
| Dizziness | 1/26 (4) |
| Dyspnea | 1/26 (4) |
| Weakness | 1/26 (4) |
|
| |
| Acute kidney injury | 25/26 (96) |
| Pulmonary edema | 9/26 (35) |
| Hypotension | 8/26 (31) |
|
| |
| ICU admission | 20/26 (77) |
| Transfusion | 3/26 (12) |
| Mechanical ventilation | 1/26 (4) |
| Hemodialysis | 1/26 (4) |
| Mortality | 1/26 (4) |
Abbreviations: ICU, intensive care unit.
Demographic and clinical characteristics of Hantaan virus (HTNV)-infected hemorrhagic fever with renal syndrome patients.
| Mild (n = 1 a) | Moderate (n = 14) | Severe (n = 11) | |
|---|---|---|---|
| Demographics | |||
| Age, years a | 23 | 21–23 | 21–23 |
| Hospital stay, days a | 5 | 9–11 | 11–15 |
| Actual treatment, days a | 4 | 10–12 | 13–17 |
| ICU treatment, days a | 2 | 2–4 | 3–5 |
| Laboratory tests | |||
| Anti-HTNV IgM positivity | 0 | 4 (29%) | 1 (9%) |
| Anti-HTNV IgG positivity, titers b | 0 | 12 (86%), 1:3904 ± 1598 | 9 (82%), 1:1844 ± 1458 |
| HTNV RT-PCR positivity | 0 | 11 (79%) | 10 (91%) |
Abbreviations: ICU = intensive care unit. IgG = immunoglobulin G. IgM = immunoglobulin M. RT-PCR = reverse transcription-polymerase chain reaction. a ROKA15-5, one of the mild patients, was negative for both anti-HTNV IgG and RT-PCR at the initial phase (collection date: 25 December 2015). Then, the patient was diagnosed with HTNV infection by RT-PCR at the diuretic phase (collection date: 26 December 2015). b Each parameter is presented as the mean ± standard deviation.
Figure 1Levels of clinical and laboratory parameters during early and late phases in patients with hemorrhagic fever with renal syndrome (HFRS).
Figure 2Levels of inflammatory markers, cytokines, and chemokines during early and late phases in patients with hemorrhagic fever with renal syndrome (HFRS). * p < 0.05; ** p < 0.01; *** p < 0.0002; **** p < 0.0001.
Figure 3Levels of inflammatory markers, cytokines, and chemokines for disease severity in the patients with hemorrhagic fever with renal syndrome (HFRS). * p < 0.05; ** p < 0.01; *** p < 0.0002; **** p < 0.0001.
Figure 4Correlation of hemoglobin (HGB) and urine output (UO) with immunological biomarkers in patients with hemorrhagic fever with renal syndrome (HFRS).
Figure 5Correlation of TGF-β3 with suPAR, IL-10, and CXCL10 in patients with hemorrhagic fever with renal syndrome.
Figure 6A schematic model summarizing the predictors of clinical progression and outcome in patients with hemorrhagic fever with renal syndrome (HFRS).