Abstract
Objective
This study aimed to investigate the potential value of serum hypoxia-inducible factor-1α (HIF-1α) concentrations as a biomarker in patients with sepsis.
Methods
The enrolled patients were divided into the following four groups: the intensive care unit (ICU) control group (n = 33), infection group (n = 29), septic nonshock group (n = 40), and septic shock group (n = 94). An enzyme-linked immunosorbent assay was used to measure serum HIF-1α concentrations on ICU admission. Clinical parameters and laboratory test results were also collected.
Results
Serum HIF-1α concentrations were significantly higher in the infection group, septic nonshock group, and septic shock group than in the ICU control group. Moreover, HIF-1α concentrations were associated with a better predictive ability for diagnosing sepsis than the Acute Physiology and Chronic Health Evaluation II score, procalcitonin concentrations, and lactate concentrations. Patients with sepsis and HIF-1α concentrations >161.14 pg/mL had a poor prognosis.
Conclusions
Serum HIF-1α concentrations are a useful biomarker for the diagnosis of sepsis and predicting the prognosis of patients.
Keywords: Hypoxia-inducible factor-1α, sepsis, septic shock, biomarker, lactate, Acute Physiology and Chronic Health Evaluation II, intensive care unit
Introduction
Sepsis is currently defined as life-threatening organ dysfunction due to a dysregulated host response to infection. 1 Sepsis is one of the most common diseases leading to the death of critically ill patients, with a mortality rate of approximately 25% to 30%.2,3 When sepsis progresses to septic shock, the mortality rate increases to approximately 50%.4,5 Recent studies have shown that an early diagnosis and intervention of sepsis can considerably reduce patients’ mortality.6,7 Unfortunately, there is still a lack of recognized biomarkers for the diagnosis of sepsis. Therefore, identifying a biomarker with high specificity and sensitivity is important for the early diagnosis of sepsis and predicting the prognosis of patients.
Patients with sepsis or septic shock usually experience long-term and severe tissue hypoxia, which is one mechanism leading to further exacerbation of this disease.8,9 Hypoxia-inducible factor (HIF) is the primary transcription factor activated by hypoxia, and HIF-1α is an essential subtype. 10 HIF-1α is also closely related to angiogenesis, regulation of the internal environment, cell autophagy, and programmed cell death. In addition, HIF-1α plays an important role in cell metabolism and adaptation to hypoxic stress in physiological and pathophysiological contexts.11,12 Previous studies have shown increased expression of HIF-1α in patients with shock, and bioinformatics analysis tools have shown that HIF-1α messenger RNA levels are different between septic and nonseptic patients. 13 However, whether these results in patients with sepsis or septic shock need to be confirmed and the potential relationship between HIF-1α and sepsis need to be clarified. 14
Therefore, this study aimed to examine the predictive value of serum HIF-1α concentrations in patients with sepsis or septic shock to provide the theoretical basis for whether serum HIF-1α concentrations can be used as a biomarker for sepsis.
Methodology
Patients
This prospective study was performed at the Peking Union Medical College Hospital (PUMCH) and Xiamen Zhongshan Hospital between June 2019 and August 2020. Patients were enrolled within 24 hours after admission to the intensive care unit (ICU). All patients diagnosed with sepsis at the ICU were evaluated using the inclusion criteria. Patients who met the sepsis 3.0 criteria (defined according to consensus international guidelines 1 ) were prospectively recruited. After being recruited, the patients with sepsis were divided into the septic nonshock and septic shock groups. Patients in the septic shock group needed to meet the following criteria at the same time: (1) age ≥18 years, (2) persistent hypotension requiring vasopressors to maintain a mean arterial blood pressure ≥65 mmHg, and (3) serum lactate concentrations >2 mmol/L, despite adequate volume resuscitation. Patients with sepsis who did not meet these criteria were assigned to the septic nonshock group. Patients with infection, but who had a Sequential Organ Failure Assessment (SOFA) score <2, were assigned to the infection group. Patients who underwent elective surgery were assigned to the ICU control group. The exclusion criteria were as follows: (1) age <18 years, (2) patients with massive bleeding or pulmonary embolism, (3) a heart attack or acute exacerbation of previous heart disease in the last week, (4) heart surgery in the last week, and (5) refusal to provide written informed consent.
Data collection, definitions, and outcome measures
Laboratory tests and clinical history evaluations were performed in all patients who were admitted. Patients were included if the exclusion criteria were not met. After obtaining written informed consent, blood samples were collected to measure biomarker levels. Lactate, procalcitonin (PCT), cardiac troponin I (cTnI), and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels were tested in the biochemical laboratory of the hospital by chemiluminescence detection. The Acute Physiology and Chronic Health Evaluation (APACHE) II scores and SOFA scores were derived from existing medical records and ICU routine examination results. The Ethical Committee of PUMCH (approval number: JS-2421) and Xiamen Zhongshan Hospital (approval number: ky2019055, 5 May 2019) approved this study. Informed consent from all patients’ relatives was obtained before inclusion. We have de-identified all patients’ details.
Blood sample collection
Peripheral blood samples were collected within 24 hours of ICU admission. All of the samples were centrifuged immediately (3000 rpm [∼1006×g] for 10 minutes), and the serum was withdrawn and stored at −80°C.
Enzyme-linked immunosorbent assay for HIF-1α
Serum HIF-1α concentrations were determined by enzyme-linked immunosorbent assay (ELISA) measurements according to the manufacturer’s protocol using the Human HIF-1α ELISA kit (Catalog No. CSB-E12112h; Cusabio, Houston, TX, USA).
Statistical analysis
The normality of the data was tested by the Kolmogorov–Smirnov test. Normally distributed data are expressed as the mean and standard deviation and were compared using Students’ t-test or one-way analysis of variance. Non-normally distributed data are expressed as the median and interquartile range, and differences were analyzed with the Kruskal–Wails H test. The diagnostic and predictive value of HIF-1α for sepsis was analyzed by calculating the area under the receiver operating characteristic curve, and its cut-off value was obtained by calculating the Youden index. Risk factors were identified by binary logistic regression analysis. Survival analysis was performed by the Kaplan–Meier method, and statistical analysis was performed by the log-rank test. All statistical analyses were performed with SPSS 26.0 (IBM Corp., Armonk, NY, USA), and two-tailed P values <0.05 were considered significant. The reporting of this study conforms to the STROBE guidelines. 15
Results
Patients’ characteristics
The study flowchart is provided in Figure 1. We assessed 214 patients for inclusion. Of these patients, 3 had a heart attack in the previous week, 11 refused to sign the consent form, 4 had incomplete data, and no patients were lost to follow-up (Figure 1). As a result, 196 patients were selected for the study population. A total of 196 patients were included in the 4 groups, with 33 in the ICU control group, 29 in the infection group, 40 in the septic nonshock group, and 94 in the septic shock group.
Figure 1.
Flowchart of screening patients in the study.
The characteristics of the study population are shown in Table 1. The patients in the septic shock group had significantly higher SOFA scores, APACHE II scores, heart rate, and norepinephrine dosage, and higher ratios of abdominal infection, bloodstream infection, and pulmonary infection than those in the infection group (all P < 0.05). The patients in the septic shock group also had significantly higher SOFA scores, APACHE II scores, heart rate, norepinephrine dosage, and duration of mechanical ventilation and higher ratios of abdominal infection, bloodstream infection, and pulmonary infection than those in the ICU control group (all P < 0.05). The patients in the septic nonshock group had significantly higher SOFA and APACHE II scores, and higher ratio abdominal infection, bloodstream infection, compared with the infection group (all P < 0.05). In addition, the patients in the septic shock group had significantly higher SOFA scores, APACHE II scores, norepinephrine dosage than those in the septic nonshock group (all P < 0.05). There was no significant difference in age, sex, corticoid use, or body mass index between the infection and septic shock groups (Table 1).
Table 1.
Characteristics of the patients at ICU admission.
| ICU control group (n = 33) | Infection group (n = 29) | Septic nonshock group (n = 40) | Septic shock group (n = 94) | P value | |
|---|---|---|---|---|---|
| Mean age (years) | 63 (46–70) | 57 (47–67) | 66 (54–76) | 66 (56–72) | 0.060 |
| Male sex (n, %) | 18 (54.5) | 23 (79.3) | 23 (57.5) | 66 (70.2) | 0.190 |
| APACHE II score | 13 (10–15) | 14 (8–17) | 17 (16–24)a,c | 20 (17–29)a,b,c | <0.001 |
| SOFA score | 0 (0–0) | 0 (0–2) | 9 (4–12)a,c | 13 (10–15)a,b,c | <0.001 |
| BMI (kg/m2) | 23 (21–27) | 24 (22–26) | 23 (21–24) | 23 (20–25) | 0.264 |
| Life-support | |||||
| MV (hour) | 11 (4–73) | 22 (10–116) | 42 (8–157) | 65 (12–216)c | 0.026 |
| NE (μg/kg/minute) | 0 (0–0) | 0 (0–0) | 0 (0–0) | 0.22 (0.09–0.56)a,b,c | <0.001 |
| Inotropes (n, %) | 3 (9.1 | 4 (13.8) | 10 (25.6) | 24 (25.5) | 0.324 |
| CRRT (n, %) | 3 (9.1) | 3 (10.3) | 7 (17.5) | 20 (21.3) | 0.519 |
| Corticoids (n, %) | 5 (15.2% | 4 (13.8) | 4 (13.79) | 21 (22.3) | 0.253 |
| HR (beats/minute) | 85 (70–94) | 90 (80–101) | 95 (83–110) | 105 (90–118)a,c | <0.001 |
| MAP (mmHg) | 95 (87–101) | 92 (86–102) | 85 (79–95)c | 82 (72–94)c | <0.001 |
| Infection source (n, %) | |||||
| Abdominal | 10 (14.9) | 11 (16.4) | 12 (17.9) | 34 (50.7%)a,c | 0.030 |
| Pulmonary | 6 (12.2) | 6 (12.2) | 5 (10.2%a,c | 32 (65.3%)a,b,c | 0.020 |
| Blood (including catheter related) | 2 (13.3) | 0 (0) | 7 (46.7)a | 6 (40)a,b,c | <0.001 |
| Skin, bone, or soft tissue | 0 (0) | 1 (12.5) | 2 (25)a,,c | 5 (62.5)a,b,c | 0.011 |
| Others | 2 (8.7) | 6 (26.1) | 7 (30.4) | 8 (34.8) | 0.370 |
The data are shown as the mean ± standard deviation, n (%), or median (interquartile range). aP < 0.05 compared with the infection group; bP < 0.05 compared with the sepsis nonshock group; cP < 0.05 compared with the ICU control group.
ICU, intensive care unit; APACHE II, Acute Physiology and Chronic Health Evaluation II; SOFA, Sequential Organ Failure Assessment; BMI, body mass index; MV, mechanical ventilation; NE, norepinephrine; CRRT, continuous renal replacement therapy; HR, heart rate; MAP, mean arterial blood pressure.
Clinical characteristics
The clinical characteristics of patients admitted into the ICU are shown in Table 2. The patients in the septic shock group had significantly higher serum concentrations of lactate, PCT, cTnI, and NT-proBNP than those in the infection and ICU control groups (all P < 0.05). The septic shock group had a significantly higher 28-day mortality and longer ICU stay than the infection group (both P < 0.05). The septic shock group also had significantly higher serum concentrations of lactate, PCT, cTnI, and NT-proBNP and higher 28-day mortality than the septic nonshock group (all P < 0.05). The septic nonshock group had a significantly higher 28-day mortality than the infection group (P < 0.05). However, there was no significant difference in the arteriovenous carbon dioxide partial pressure difference or central venous blood oxygen saturation between the septic nonshock and septic shock groups.
Table 2.
Clinical characteristics of the patients.
| ICU control group (n = 33) | Infection group (n = 29) | Septic nonshock group (n = 40) | Septic shock group (n = 94) | P value | |
|---|---|---|---|---|---|
| Lac (mmol/L) | 1.01 (0.85–1.67) | 0.95 (0.70–1.50) | 1.10 (0.85–1.80) | 3.00 (2.45–4.45)a,b,c | <0.001 |
| Pv-aCO2 (mmHg) | 3.9 (2.7–5.1) | 4.4 (3.1–5.5) | 2.8 (1.2–4.3) | 3.8 (2.4–6.7) | 0.128 |
| ScvO2 (%) | 77.60 (74.80–86.20) | 72.30 (64.00–74.20) | 76.50 (71.10–83.80) | 75.25 (66.75–79.95) | 0.390 |
| PCT (ng/mL) | 0.10 (0.07–0.260) | 0.44 (0.21–1.20) | 1.65 (0.63–2.80)c | 7.30 (1.90–26.00)a,b,c | <0.001 |
| cTnI (μg/mL) | 0.01 (0.01–0.03) | 0.01 (0.01–0.05) | 0.01 (0.017–0.24) | 0.34 (0.07–1.32)a,b,c | <0.001 |
| NT-proBNP (pg/mL) | 168.3 (60–384) | 193.5 (86–862) | 770 (512.5–1379.5)c | 3063 (1159–7330)a,b,c | <0.001 |
| Prognostic parameters | |||||
| ICU stay (days) | 1 (1–1) | 1 (1–5) | 8 (3–23)c | 8 (5–22)a,c | <0.001 |
| 28-day mortality (n, %) | 0 (0) | 0 (0) | 2 (5)a,c | 22(23.4)a,b,c | <0.001 |
The data are shown as the mean ± standard deviation, n (%), or median (interquartile range). aP < 0.05 compared with the infection group; bP < 0.05 compared with the sepsis nonshock group; cP < 0.05 compared with the ICU control group.
ICU, intensive care unit; Lac, lactate; Pv-aCO2, arteriovenous carbon dioxide partial pressure difference; ScvO2, central venous blood oxygen saturation; PCT, procalcitonin; cTnI, cardiac troponin I; NT-ProBNP, N-terminal pro-brain natriuretic peptide.
Serum HIF-1α concentrations in each group of patients
The mean serum HIF-1α concentration was lowest in patients in the ICU control group, but it progressively increased in those in the infection group, septic nonshock group, and septic shock group (Figure 2). The mean serum HIF-1α concentrations in the septic shock group (160.39 ± 19.68 pg/mL) and septic nonshock group (135.24 ± 20.34 pg/mL) were significantly higher than that in the ICU control group (113.37 ± 15480 pg/mL, both P < 0.001). The mean serum HIF-1α concentration in the septic shock group was significantly higher than that in the septic nonshock group (P < 0.01). In addition, the mean serum HIF-1α concentration in the septic shock group was significantly higher than that in the infection group (114.34 ± 15.50 pg/mL, P < 0.01). However, there was no significant difference in serum HIF-1α concentrations between the ICU control and infection groups.
Figure 2.
Serum HIF-1α concentrations in each group of patients. HIF-1α concentrations were significantly increased sequentially in the ICU control group, infection group, and septic nonshock group or septic shock group. There was no significant difference in HIF-1α concentrations between the septic nonshock and septic shock groups. *P < 0.05 compared with the ICU control group; #P < 0.05 compared with the infection group; @P < 0.05 compared with the septic nonshock group.
HIF-1α, hypoxia-inducible factor-1α; ICU, intensive care unit.
Diagnostic and predictive value of HIF-1α in sepsis
We found that HIF-1α and SOFA score were significant contributing factors to the diagnosis of sepsis by binary logistic regression analysis (both P < 0.05). However, PCT, lactate, and the APACHE II score did not significantly contribute to the diagnosis of sepsis (Table 3). We used the receiver operating characteristic curve to calculate the cut-off value of HIF-1α as a biomarker for the diagnosis of sepsis (Figure 3). Serum HIF-1α concentrations showed a higher area under curve than the APACHE II score, PCT concentrations, and lactate concentrations, but were inferior to the SOFA score (Table 4). In addition, the cut-off value of 131.96 pg/mL for HIF-1α was calculated on the basis of the Youden index.
Table 3.
Binary logistic regression analysis in patients diagnosed with sepsis.
| β | SE | Wald | OR | P value | |
|---|---|---|---|---|---|
| HIF-1α | 0.135 | 0.043 | 9.788 | 1.145 | 0.002 |
| SOFA score | 0.687 | 0.197 | 12.130 | 1.987 | <0.001 |
| APACHE II score | 0.271 | 0.161 | 2.847 | 1.312 | 0.092 |
| PCT | 0.684 | 0.369 | 3.431 | 1.982 | 0.064 |
| Lac | 0.944 | 0.518 | 3.321 | 0.389 | 0.068 |
SE, standard error; OR, odds ratio; HIF-1α, hypoxia-inducible factor-1α; SOFA, Sequential Organ Failure Assessment; APACHE II, Acute Physiology and Chronic Health Evaluation II; PCT, procalcitonin; Lac, lactate.
Figure 3.
ROC curves show that serum HIF-1α concentrations have a better diagnostic value than the APACHE II score, PCT, and lactate
ROC, receiver operating characteristic; PCT, procalcitonin; Lac, lactate; SOFA, Sequential Organ Failure Assessment; HIF-1α, hypoxia-inducible factor-1α; APACHE-II, Acute Physiology and Chronic Health Evaluation II.
Table 4.
Receiver operating characteristic curve analysis for the diagnosis of sepsis.
| AUC ± SE | P value | Cut-off value | Sensitivity (%) | Specificity (%) | Negative predictive value (%) | Positive predictive value (%) | |
|---|---|---|---|---|---|---|---|
| HIF-1α | 0.92 ± 0.02 | <0.001 | 131.96 pg/mL | 79.9 | 91.9 | 89.5 | 90.5 |
| PCT | 0.89 ± 0.03 | <0.001 | 0.79 ng/mL | 83.3 | 80.0 | 87.4 | 75.6 |
| Lac | 0.64 ± 0.04 | 0.001 | 0.75 mmol/L | 93.1 | 31.1 | 78.5 | 86.5 |
| SOFA score | 0.98 ± 0.01 | <0.001 | 2.5 | 97.7 | 90.3 | 98.5 | 99.5 |
| APACHE-II score | 0.84 ± 0.03 | <0.001 | 15 | 82.4 | 70.0 | 86.5 | 96.4 |
AUC, area under the curve; HIF-1α, hypoxia-inducible factor-1α; PCT, procalcitonin; Lac, lactate; SOFA, Sequential Organ Failure Assessment; APACHE II, Acute Physiology and Chronic Health Evaluation II.
We further examined the predictive value for the prognosis of HIF-1α in patients with sepsis or septic shock. HIF-1α was divided into four groups according to the interquartile range (0, 1, 2, and 3 groups). The HIF-1α (3) group significantly contributed to the death of patients as shown by binary logistic regression analysis of predictors of 28-day mortality (odds ratio = 4.26, P = 0.04, Table 5). In addition, we divided the patients in the HIF-1α (3) group into two subgroups of HIF-1α concentrations ≥161.14 pg/mL and HIF-1α concentrations <161.14 pg/mL. Kaplan–Meier survival analysis used the HIF-1α cut-off value of 161.14 pg/mL in patients (Figure 4). Patients with serum HIF-1α concentrations >161.14 pg/mL had a significantly poor prognosis (95% confidence interval 51.94–82.57 vs. 100.05–116.28, P = 0.03).
Table 5.
Binary logistic regression analysis of predictors of 28-day mortality in patients.
| Death (n, %) | Unadjusted OR | Unadjusted P value | Adjusted OR | Adjusted P value | |
|---|---|---|---|---|---|
| HIF-1α 0 group | 3 (6.00) | 1 | – | 1 | – |
| HIF-1α 1 group | 3 (6.38) | 1.09 | 0.92 | 1.01 | 0.99 |
| HIF-1α 2 group | 8 (16.33) | 3.06 | 0.12 | 2.61 | 0.18 |
| HIF-1α 3 group | 11 (22.45) | 4.54 | 0.03 | 4.26 | 0.04 |
HIF-1α, hypoxia-inducible factor-1α.
Figure 4.
Kaplan–Meier survival curves show that patients with sepsis and those with septic shock with serum HIF-1α concentrations >142.42 pg/mL have a significantly poor prognosis
HIF-1α, hypoxia-inducible factor-1α.
Discussion
This study aimed to determine whether serum HIF-1α concentrations can be used as a biomarker to evaluate the condition of patients with sepsis. We found that serum HIF-1α concentrations in patients with sepsis were significantly higher than those in ICU controls and in patients with infection. Moreover, HIF-1α had good value in the diagnosis of sepsis, and its specificity was even better than that for lactate, PCT, and the APACHE II score, but inferior to that of the SOFA score (Figure 3). Further analysis showed that serum HIF-1α concentrations were positively associated with 28-day mortality in patients with sepsis. Our study suggests that, if the serum HIF-1α concentration exceeds 161.14 pg/mL (cut-off value) on admission to the ICU, the prognosis of patients is poor.
Serum HIF-1α concentrations are related to cellular oxygen concentrations, which increase when tissue hypoxia is within a certain range. 16 Many previous studies showed an increase in serum HIF-1α concentrations in patients with non-infectious diseases with tissue hypoxia, such as acute myocardial infarction and mechanical ventilation-related diaphragm injury.17,18 As a typical representative of infectious diseases, sepsis is also often accompanied by tissue hypoxia. There have been few studies on the relationship between HIF-1α and patients with sepsis.14,19 We found that serum HIF-1α concentrations in patients with infection, septic nonshock, and septic shock were significantly higher than those in patients who underwent elective surgery (ICU control group). Furthermore, serum HIF-1α levels in patients with septic nonshock and septic shock were significantly higher than those in patients with infection. These results not only confirmed our speculation on the relationship between HIF-1α and sepsis, but also suggested that patients have the problem of tissue hypoxia at the microcirculatory level as early as the infection stage.
The early identification of patients with sepsis is crucial because it reduces the mortality of patients, optimizes treatment, and conserves medical resources. In this study, serum HIF-1α concentrations were increased in patients with sepsis, suggesting that HIF-1α may be a useful biomarker for diagnosing sepsis. Many studies have shown the application of HIF-1α in diagnosing diseases with tissue hypoxia. Kergert et al. 20 found that HIF-1α plays a vital role as a biomarker in the early diagnosis and disease risk stratification of pulmonary embolism. Other studies have also shown that HIF-1α may be a helpful indicator for the early diagnosis of acute decompensated heart failure or renal vascular diseases.21,22 To confirm the ability of HIF-1α in the early diagnosis of sepsis, we compared HIF-1α with lactate, PCT, and the APACHE II score by the receiver operating characteristic method. We found that high serum HIF-1α concentrations were significantly associated with a higher incidence of sepsis, and HIF-1α had a higher area under the curve value and specificity than lactate, PCT, and the APACHE II score. In addition, recent studies have shown that HIF-1α has an excellent ability to assess the prognosis of patients with tumor diseases, such as melanoma and colorectal cancer.23,24 However, whether HIF-1α can also be used as a biomarker to predict the prognosis of patients with sepsis is unclear. Therefore, we further examined and evaluated the ability of HIF-1α in predicting the prognosis of patients with sepsis, and found that the prognosis of patients with sepsis whose serum HIF-1α concentrations were >161.14 pg/mL was poor. This finding has several implications for clinicians as follows: (1) patients with suspected or confirmed infection sources in the ICU should be aware of the possibility of sepsis if they have high serum HIF-1α concentrations; (2) when serum HIF-1α concentrations in infected patients are further increased, they should be warned about the occurrence of sepsis; and (3) patients with sepsis and high serum HIF-1α concentrations should be vigilant for a poor prognosis.
Our study has several important clinical implications. (1) Serum HIF-1α concentrations have great potential value in the clinical management and treatment of patients with sepsis. Awareness of high serum HIF-1α concentrations may help medical workers to identify the occurrence of sepsis, diagnose sepsis, and predict the prognosis of patients with sepsis, which are beneficial to adjusting the treatment strategy in time. (2) The measurement of serum HIF-1α concentrations can be more rapidly obtained and more accurate in clinical practice by using an ELISA as performed in our study than using western blotting or reverse transcriptase-polymerase chain reaction, which is beneficial to determining the patient’s condition. (3) From a medico-economic point of view, the cost of an ELISA is also comparatively reasonable (approximately 25–30 RMB for one sample), which could considerably decrease the patient’s medical expenses. (4) If HIF-1α concentrations are abnormally elevated in patients with common infections, we may need to be vigilant regarding whether the patient is progressing to sepsis.
This study has several limitations. First, this was a single-center, relatively small-sample study. Therefore, a larger cohort in a multicenter study is required to ensure the random distribution of risk factors (e.g., treatment interventions, type of infection, and complications) that may affect the study results. Second, the circulating half-life and dynamic changes in HIF-1α concentrations in sepsis are still unclear. These issues should be examined in further research. Third, because this was an observational study, our results should be regarded only as a reference and must be further verified by more high-quality, large-sample, randomized trials. Fourth, we excluded patients with ischemic heart disease, cardiac arrest, pulmonary embolism, and bleeding, and HIF-1α should also not be excluded in the study of appellate diseases, such as ischemic heart disease, cardiac arrest, pulmonary embolism, and bleeding.
Conclusion
This study shows that serum HIF-1α concentrations on ICU admission are a useful biomarker for the diagnosis of sepsis, and high serum HIF-1α concentrations suggest that patients have a poor prognosis. These results provide evidence for the potential effect of HIF-1α in patients with sepsis. In the future, studies are still required to further investigate the potential clinical value of HIF-1α and its specific mechanisms.
Acknowledgements
We thank Dr. Lianhui and Su Longxiang for guidance and selection of the journal.
Footnotes
The authors declare that there is no conflict of interest.
Funding: This research was funded by the Central Health Key Project (2020ZD08).
ORCID iD: Xiaoting Wang https://orcid.org/0000-0001-8162-4787
References
- 1.Singer M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016; 315: 801–810. 2016/02/24. DOI: 10.1001/jama.2016.0287. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Rudd KE, Johnson SC, Agesa KM, et al. Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study. Lancet 2020; 395: 200–211. 2020/01/20. DOI: 10.1016/s0140-6736(19)32989-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Rhee C, Jones TM, Hamad Y, et al. Prevalence, Underlying Causes, and Preventability of Sepsis-Associated Mortality in US Acute Care Hospitals. JAMA Netw Open 2019; 2: e187571. 2019/02/16. DOI: 10.1001/jamanetworkopen.2018.7571. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Van der Poll T, Van de Veerdonk FL, Scicluna BP, et al. The immunopathology of sepsis and potential therapeutic targets. Nat Rev Immunol 2017; 17: 407–420. 2017/04/25. DOI: 10.1038/nri.2017.36. [DOI] [PubMed] [Google Scholar]
- 5.Weng L, Zeng XY, Yin P, et al. Sepsis-related mortality in China: a descriptive analysis. Intensive Care Med 2018; 44: 1071–1080. 2018/05/31. DOI: 10.1007/s00134-018-5203-z. [DOI] [PubMed] [Google Scholar]
- 6.Kim HI, Park S. Sepsis: Early Recognition and Optimized Treatment. Tuberc Respir Dis (Seoul) 2019; 82: 6–14. 2018/10/12. DOI: 10.4046/trd.2018.0041. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Baghdadi JD, Brook RH, Uslan DZ, et al. Association of a Care Bundle for Early Sepsis Management With Mortality Among Patients With Hospital-Onset or Community-Onset Sepsis. JAMA Intern Med 2020; 180: 707–716. 2020/04/07. DOI: 10.1001/jamainternmed.2020.0183. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Li M, Li G, Yu B, et al. Activation of Hypoxia-Inducible Factor-1α Via Succinate Dehydrogenase Pathway During Acute Lung Injury Induced by Trauma/Hemorrhagic Shock. Shock 2020; 53: 208–216. 2019/07/02. DOI: 10.1097/shk.0000000000001347. [DOI] [PubMed] [Google Scholar]
- 9.Yuan X, Lee JW, Bowser JL, et al. Targeting Hypoxia Signaling for Perioperative Organ Injury. Anesth Analg 2018; 126: 308–321. 2017/08/02. DOI: 10.1213/ane.0000000000002288. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Choudhry H, Harris AL. Advances in Hypoxia-Inducible Factor Biology. Cell Metab 2018; 27: 281–298. 2017/11/14. DOI: 10.1016/j.cmet.2017.10.005. [DOI] [PubMed] [Google Scholar]
- 11.Thomas LW, Ashcroft M. Exploring the molecular interface between hypoxia-inducible factor signalling and mitochondria. Cell Mol Life Sci 2019; 76: 1759–1777. 2019/02/16. DOI: 10.1007/s00018-019-03039-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Sokolova IM, Sokolov EP, Haider F. Mitochondrial Mechanisms Underlying Tolerance to Fluctuating Oxygen Conditions: Lessons from Hypoxia-Tolerant Organisms. Integr Comp Biol 2019; 59: 938–952. 2019/05/24. DOI: 10.1093/icb/icz047. [DOI] [PubMed] [Google Scholar]
- 13.Ruan H, Li YZ, Zhang Q, et al. Identification and clinical validation of hypoxia-inducible factor 1α protein as the potential biomarker in patients with sepsis. Shock 2023; 59: 855–863. 2023/04/01. DOI: 10.1097/shk.0000000000002122. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Ferreira BL, Leite GGF, Brunialti MKC, et al. HIF-1α and Hypoxia Responsive Genes are Differentially Expressed in Leukocytes From Survivors and Non-Survivors Patients During Clinical Sepsis. Shock 2021; 56: 80–91. 2021/07/02. DOI: 10.1097/shk.0000000000001694. [DOI] [PubMed] [Google Scholar]
- 15.Von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med 2007; 147: 573–577. 2007/10/17. DOI: 10.7326/0003-4819-147-8-200710160-00010. [DOI] [PubMed] [Google Scholar]
- 16.Schumacker PT. Hypoxia-inducible factor-1 (HIF-1). Crit Care Med 2005; 33: S423–S425. 2005/12/13. DOI: 10.1097/01.ccm.0000191716.38566.e0. [DOI] [PubMed] [Google Scholar]
- 17.Dölling M, Eckstein M, Singh J, et al. Hypoxia Promotes Neutrophil Survival After Acute Myocardial Infarction. Front Immunol 2022; 13: 726153. 2022/03/01. DOI: 10.3389/fimmu.2022.726153. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Li LF, Yu CC, Huang HY, et al. Suppression of Hypoxia-Inducible Factor 1α by Low-Molecular-Weight Heparin Mitigates Ventilation-Induced Diaphragm Dysfunction in a Murine Endotoxemia Model. Int J Mol Sci 2021; 22: 1702. 2021/02/12. DOI: 10.3390/ijms22041702. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Lotsios NS, Keskinidou C, Jahaj E, et al. Prognostic Value of HIF-1α-Induced Genes in Sepsis/Septic Shock. Med Sci (Basel) 2023; 11: 41. 2023/06/27. DOI: 10.3390/medsci11020041. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kerget B, Afşin DE, Aksakal A, et al. Could HIF-1α be a novel biomarker for the clinical course and treatment of pulmonary embolism? Turk J Med Sci 2020; 50: 963–968. 2020/05/19. DOI: 10.3906/sag-1908-93. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Li G, Lu WH, Wu XW, et al. Admission hypoxia-inducible factor 1α levels and in-hospital mortality in patients with acute decompensated heart failure. BMC Cardiovasc Disord 2015; 15: 79. 2015/08/01. DOI: 10.1186/s12872-015-0073-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Movafagh S, Raj D, Sanaei-Ardekani M, et al. Hypoxia Inducible Factor 1: A Urinary Biomarker of Kidney Disease. Clin Transl Sci 2017; 10: 201–207. 2017/02/10. DOI: 10.1111/cts.12445. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Dong S, Liang S, Cheng Z, et al. ROS/PI3K/Akt and Wnt/β-catenin signalings activate HIF-1α-induced metabolic reprogramming to impart 5-fluorouracil resistance in colorectal cancer. J Exp Clin Cancer Res 2022; 41: 15. 2022/01/10. DOI: 10.1186/s13046-021-02229-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Malekan M, Ebrahimzadeh MA, Sheida F. The role of Hypoxia-Inducible Factor-1alpha and its signaling in melanoma. Biomed Pharmacother 2021; 141: 111873. 2021/07/06. DOI: 10.1016/j.biopha.2021.111873. [DOI] [PubMed] [Google Scholar]