Wang WY, Wu Y, Zhang JQ, Li B. Expression differences and relationships of endothelin-1, interleukin-6 and c-kit in hypertensive patients with and without depression. World J Psychiatry 2025; 15(7): 106733 [DOI: 10.5498/wjp.v15.i7.106733]
Corresponding Author of This Article
Bin Li, Chief Physician, The Clinical Research Center for Acute Myocardial Infarction of Hubei Province, Xianning Central Hospital, First Affiliated Hospital of Hubei University of Science and Technology, No. 228 Jingui Road, Xianning 437000, Hubei Province, China. 17807238940@163.com
Research Domain of This Article
Psychiatry
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Wei-Yi Wang, Yi Wu, Jing-Qi Zhang, Bin Li, The Clinical Research Center for Acute Myocardial Infarction of Hubei Province, Xianning Central Hospital, First Affiliated Hospital of Hubei University of Science and Technology, Xianning 437000, Hubei Province, China
Wei-Yi Wang, Jing-Qi Zhang, Laboratory of Cardiovascular Internal Medicine Department, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, Heilongjiang Province, China
Author contributions: Wang WY, Wu Y designed the research study; Zhang JQ performed the research; Li B conducted experiments, analyzed the data. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript.
Institutional review board statement: This study was approved by the Medical Ethics Committee of The First Affiliated Hospital of Harbin Medical University and strictly adhered to the ethical guidelines of the Declaration of Helsinki.
Informed consent statement: Informed consent was obtained from all study participants.
Conflict-of-interest statement: The authors declare that they have no competing interests
Data sharing statement: No additional data are available.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Bin Li, Chief Physician, The Clinical Research Center for Acute Myocardial Infarction of Hubei Province, Xianning Central Hospital, First Affiliated Hospital of Hubei University of Science and Technology, No. 228 Jingui Road, Xianning 437000, Hubei Province, China. 17807238940@163.com
Received: March 28, 2025 Revised: April 17, 2025 Accepted: May 21, 2025 Published online: July 19, 2025 Processing time: 103 Days and 19.9 Hours
Abstract
BACKGROUND
Hypertension is a chronic cardiovascular disease characterized by persistently elevated arterial blood pressure. It is not only a significant risk factor for cardiovascular and cerebrovascular diseases (such as myocardial infarction and stroke) but also closely related to multiple organ damages (such as kidney disease and retinopathy), imposing a heavy health and economic burden on individuals and society.
AIM
To investigate the expression differences and relationships of endothelin-1 (ET-1), interleukin-6 (IL-6), stem cell factor (SCF), and its receptor (c-kit) in hypertensive patients with or without depression.
METHODS
A retrospective analysis was conducted on the clinical data of 163 hypertensive patients admitted to our hospital from March 2022 to January 2024. Based on the presence of depression, patients were divided into Group A (n = 77, with depression) and Group B (n = 86, without depression). Serum levels of ET-1 and IL-6 were measured using radioimmunoassay, while serum levels of SCF and c-kit were measured using ELISA. The differences in ET-1, IL-6, SCF, and c-kit levels between Groups A and B were compared. Additionally, the differences in these biomarkers among patients with varying degrees of depression in Group A were analyzed. Pearson correlation analysis was used to examine the relationship between ET-1, IL-6, SCF, c-kit levels, and Hamilton depression rating scale (HAMD) scores. Multivariate logistic regression analysis was performed to identify factors influencing hypertension with depression. The diagnostic efficacy of individual and combined biomarkers was analyzed using receiver operating characteristic (ROC) curves. Comparative statistical analysis of the area under the curve (AUC) values was performed using DeLong’s test to assess the superiority of combined biomarker detection.
RESULTS
The levels of ET-1 and IL-6 in Group A were significantly higher than those in Group B, while the levels of SCF and c-kit were significantly lower in Group A compared to Group B (P < 0.05). In the severe depression subgroup, ET-1 and IL-6 levels were higher than those in the mild-to-moderate depression subgroup, while SCF and c-kit levels were lower (P < 0.05). Pearson correlation analysis showed that ET-1 and IL-6 levels were positively correlated with HAMD scores (r = 0.442, 0.463, P < 0.05), while SCF and c-kit levels were negatively correlated with HAMD scores (r = -0.429, -0.394, P < 0.05). Multivariate logistic regression analysis revealed that high ET-1, high IL-6, low SCF, and low c-kit were independent influencing factors for hypertension with depression (P < 0.05). ROC analysis revealed AUCs of 0.746 (ET-1), 0.801 (IL-6), 0.732 (SCF), 0.779 (c-kit), and 0.884 (combination). The combined diagnosis demonstrated significantly higher AUC than individual markers (DeLong's test, P < 0.01), with superior sensitivity (90.24%) and specificity (85.37%).
CONCLUSION
Compared to patients with hypertension alone, patients with hypertension and depression exhibited higher serum levels of ET-1 and IL-6 and lower levels of SCF and c-kit. High ET-1, high IL-6, low SCF, and low c-kit were independent influencing factors for hypertension with depression. The combination of ET-1, IL-6, SCF, and c-kit demonstrated significant diagnostic value for hypertension with depression.
Core Tip: Compared to patients with hypertension alone, patients with hypertension and depression exhibited higher serum levels of endothelin-1 (ET-1) and interleukin-6 (IL-6) and lower levels of stem cell factor (SCF) and c-kit. High ET-1, high IL-6, low SCF, and low c-kit were independent influencing factors for hypertension with depression. The combination of ET-1, IL-6, SCF, and c-kit demonstrated significant diagnostic value for hypertension with depression.
Citation: Wang WY, Wu Y, Zhang JQ, Li B. Expression differences and relationships of endothelin-1, interleukin-6 and c-kit in hypertensive patients with and without depression. World J Psychiatry 2025; 15(7): 106733
Hypertension is a chronic cardiovascular disease characterized by persistently elevated arterial blood pressure. It is not only a significant risk factor for cardiovascular and cerebrovascular diseases (such as myocardial infarction and stroke) but also closely related to multiple organ damages (such as kidney disease and retinopathy), imposing a heavy health and economic burden on individuals and society[1,2]. Although modern medicine has made significant progress in the diagnosis and treatment of hypertension, its pathogenesis remains complex, involving genetic, environmental, metabolic, neuroendocrine, and immune regulatory factors, leaving many questions unanswered. Recent studies[3,4] have shown a close association between hypertension and mental health disorders, particularly depression. Depression is a mental disorder characterized by persistent low mood, loss of interest, and cognitive decline[5]. Globally, the prevalence of depression is approximately 4.4%, but this rate is significantly higher among hypertensive patients, ranging from 20% to 30%[6]. The comorbidity of hypertension and depression not only exacerbates the complexity and treatment difficulty of the conditions but also significantly increases the risk of cardiovascular events and all-cause mortality.
At present, the interaction mechanisms between hypertension and depression are not fully understood. However, studies[7,8] suggest that the two conditions may influence each other through shared pathophysiological pathways, such as chronic inflammation, endothelial dysfunction, neuroendocrine dysregulation, and oxidative stress. Endothelin-1 (ET-1) is a potent vasoconstrictor peptide involved in blood pressure regulation and endothelial dysfunction[9]. Elevated levels of ET-1 may be associated with the development of both hypertension and depression. Interleukin-6 (IL-6), as a pro-inflammatory cytokine, plays a central role in systemic inflammatory responses. Elevated levels of IL-6 have been shown to be closely associated with both hypertension and depression. Several recent systematic reviews and meta-analyses have demonstrated that IL-6 levels are significantly higher in patients with depression compared to non-depressed individuals, and are positively correlated with the severity of depressive symptoms[10,11]. Stem cell factor (SCF) and its receptor c-kit play important roles in cell proliferation, differentiation, and tissue repair. Reduced levels of SCF/c-kit may lead to impaired endothelial function and decreased neural regeneration capacity[12], thereby exacerbating the conditions of hypertension and depression. Although existing studies have revealed the potential roles of ET-1, IL-6, SCF, and c-kit in hypertension and depression, the expression differences of these biomarkers in hypertensive patients with or without depression and their relationship with the severity of depression have not been systematically studied. Furthermore, whether these biomarkers can serve as diagnostic indicators for hypertension with depression and the value of their combined diagnosis remain to be further validated.
Based on the above background, this study investigated the expression differences of ET-1, IL-6, SCF, and its receptor c-kit in hypertensive patients with or without depression, analyzed their relationship with the severity of depression, and evaluated the diagnostic value of these biomarkers for hypertension with depression. The aim is to provide new insights into the comorbidity mechanisms of hypertension and depression and to offer a theoretical basis for clinical diagnosis and treatment.
MATERIALS AND METHODS
Study subjects
A retrospective analysis was conducted on the clinical data of 163 hypertensive patients admitted to our hospital from March 2022 to January 2024. The data included gender, age, body mass index (BMI), smoking status, alcohol consumption, duration of hypertension, blood pressure indicators [systolic blood pressure (SBP), diastolic blood pressure (DBP)], lipid profiles [total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C)], fasting blood glucose (FBG) levels, blood urea nitrogen (BUN) levels, creatinine (Cr) levels, uric acid (UA) levels, and the use of amlodipine. Based on the presence of depression, patients were divided into Group A (n = 77, with depression) and Group B (n = 86, without depression). This study was approved by the Medical Ethics Committee of The First Affiliated Hospital of Harbin Medical University (Approval No.: FZJC240015) and strictly adhered to the ethical guidelines of the Declaration of Helsinki.
Inclusion and exclusion criteria
Inclusion criteria: (1) All patients met the diagnostic criteria for hypertension by the International Society of Hypertension[13], defined as SBP ≥ 140 mmHg (1 mmHg = 0.133 kPa) and/or DBP ≥ 90 mmHg, or currently receiving antihypertensive medication; and (2) Patients with depression met the diagnostic criteria for depression according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)[14] and were confirmed by the Hamilton depression rating scale (HAMD)[15]. DSM-5 diagnostic criteria for major depressive disorder: Patients were required to exhibit at least five of the following symptoms during the same two-week period, representing a change from previous functioning. At least one of the symptoms must be either depressed mood or loss of interest or pleasure: (1) Depressed mood most of the day, nearly every day; (2) Markedly diminished interest or pleasure in all, or almost all, activities; (3) Significant weight loss or gain, or decrease/increase in appetite; (4) Insomnia or hypersomnia; (5) Psychomotor agitation or retardation; (6) Fatigue or loss of energy; (7) Feelings of worthlessness or excessive/inappropriate guilt; (8) Diminished ability to think or concentrate, or indecisiveness; and (9) Recurrent thoughts of death, suicidal ideation, or suicide attempt. These symptoms must cause clinically significant distress or impairment in social, occupational, or other important areas of functioning and not be attributable to the physiological effects of a substance or another medical condition. The total HAMD score is 96, with scores < 8 defined as no depressive symptoms, 8-19 as possible depression, 20-35 as mild to moderate depression, and > 35 as severe depression; patients aged between 18 and 75 years, regardless of gender; all patients or their legal representatives signed informed consent forms and voluntarily participated in the study; and patients' clinical data (including general information, medical history, laboratory test results, imaging data, etc.) were complete and traceable.
Exclusion criteria: (1) Comorbidities with other severe mental disorders, such as schizophrenia, bipolar disorder, or severe anxiety disorder; (2) Comorbidities with severe organic diseases, such as malignant tumors, severe liver or kidney dysfunction (Child-Pugh class C liver function or glomerular filtration rate < 30 mL/min/1.73m²), or severe heart failure (NYHA class III-IV); (3) Recent use of antidepressants, immunosuppressants, or anti-inflammatory drugs may interfere with the study results; (4) Pregnant or lactating women; (5) Patients who underwent major surgery or suffered severe trauma within the past 6 months; (6) History of drug abuse or alcohol dependence; and (7) Patients with cognitive impairment or language communication barriers who were unable to complete the relevant scale assessments.
Serum indicator detection methods
Venous blood (5 mL) was collected from fasting patients who had not taken any medications using vacuum negative pressure dry tubes. Immediately after collection, 3 mL of blood was evenly distributed into pre-prepared heparin anticoagulant tubes and EDTA anticoagulant tubes. The anticoagulated blood samples were centrifuged at 3000 rpm for 10 minutes to separate the plasma. The plasma was aliquoted into three Eppendorf tubes, and aprotinin (final concentration of 500 KIU/mL) was added to the EDTA-anticoagulated plasma to prevent protein degradation. The aliquoted plasma samples were immediately stored at -20 °C for later use: (1) Detection of ET-1 and IL-6 levels: EDTA-anticoagulated plasma was thawed and gently mixed to avoid repeated freeze-thaw cycles. The levels of ET-1 and IL-6 were measured using radioimmunoassay. The kits were purchased from Beijing North Biotechnology Research Institute, and all procedures were strictly followed according to the kit instructions. The standards were diluted in a gradient and added to the standard wells, while the plasma samples to be tested were added to the sample wells, with 100 μL added to each well. The plates were incubated at 37 °C for 2 hours, washed three times to remove unbound substances, and then radioactive-labeled antibodies were added. The plates were further incubated for 1 hour, and the radioactive intensity of each well was measured using a gamma counter. The concentrations of ET-1 and IL-6 were calculated based on the standard curve; (2) Detection of Lipid and Biochemical Indicators: Serum samples from the dry tubes were thawed and gently mixed. The levels of TC, TG, LDL-C, HDL-C, FBG, BUN, Cr, and UA were measured using the DuPont Dimension RxL multifunctional fully automated biochemical analyzer (United States). The reagents for each indicator were prepared according to the instrument manual. The serum samples were added to the sample tray, and the detection program was set. The instrument automatically completed the sample detection and generated results, and the concentrations of each indicator were recorded; and (3) Detection of SCF and c-kit Levels: Heparin-anticoagulated plasma was thawed and gently mixed. The expression levels of SCF and c-kit were measured using ELISA. The kits were purchased from R&D Systems (United States). The pre-coated enzyme-labeled plates were taken out, and 100 μL of the specified diluent was added to all wells. Then, 100 μL of standards and plasma samples to be tested were added to the standard and sample wells, respectively. The plates were incubated at room temperature for 2 hours, washed three times to remove unbound substances, and 200 μL of enzyme conjugate was added to each well. The plates were further incubated for 2 hours, washed three times, and 200 μL of chromogenic substrate was added. The plates were incubated at room temperature in the dark for 20 minutes, and 50 μL of stop solution was added to terminate the reaction. Within 30 minutes, the absorbance of each well was read at 450 nm using a BIORAD EVOLIS fully automated microplate reader. A standard curve was generated based on the standards, and the concentrations of SCF and c-kit in each sample were calculated.
Statistical analysis
GraphPad Prism 8 was used for graphing. SPSS 25.0 was used for statistical analysis. Categorical data were expressed as percentages (%) and analyzed using the χ2 test. Continuous data were expressed as mean ± SD, and comparisons between two groups were performed using independent sample t-tests. Pearson correlation analysis was used to examine the relationship between ET-1, IL-6, SCF, c-kit levels, and HAMD scores. Multivariate logistic regression analysis was performed to identify factors influencing hypertension with depression. Receiver operating characteristic (ROC) curves were plotted to evaluate the diagnostic value of ET-1, IL-6, SCF, c-kit, and their combination for hypertension with depression; Comparative statistical analysis of the area under the curve (AUC) values was performed using DeLong’s test to assess the superiority of combined biomarker detection. A P-value < 0.05 was considered statistically significant.
RESULTS
Comparison of clinical data between group A and group B
The comparison of gender, age, BMI, smoking status, alcohol consumption, duration of hypertension, SBP, DBP, TC, TG, LDL-C, HDL-C, FBG, BUN, Cr, UA, and the use of amlodipine between Group A and Group B showed no significant differences (P > 0.05), indicating comparability (Table 1).
Table 1 Comparison of clinical data between group a and group B, n (%).
Clinical data
Group A (n = 77)
Group B (n = 86)
t/χ2
P value
Gender (male)
42 (54.55)
45 (52.33)
0.080
0.776
Age (years)
53.74 ± 11.79
54.32 ± 10.85
0.327
0.744
BMI (kg/m²)
23.18 ± 3.73
22.76 ± 3.95
0.695
0.487
Smoking status
28 (36.36)
34 (39.53)
0.173
0.677
Alcohol consumption
12 (15.58)
11 (12.79)
0.261
0.609
Duration of hypertension (years)
4.92 ± 1.43
5.17 ± 1.79
0.977
0.329
SBP (mmHg)
152.39 ± 7.87
153.48 ± 8.12
0.868
0.386
DBP (mmHg)
94.19 ± 9.93
94.35 ± 10.21
0.101
0.919
TC (mmol/L)
4.73 ± 1.15
4.62 ± 1.28
0.574
0.566
TG (mmol/L)
1.33 ± 0.72
1.39 ± 0.82
0.493
0.622
LDL-C (mmol/L)
2.78 ± 0.74
2.85 ± 0.72
0.611
0.541
HDL-C (mmol/L)
1.41 ± 0.73
1.32 ± 0.77
0.763
0.446
FBG (mmol/L)
4.97 ± 0.38
5.09 ± 0.52
1.665
0.097
BUN (mmol/L)
5.12 ± 1.33
4.94 ± 1.45
0.822
0.411
Cr (μmol/L)
69.74 ± 11.45
70.37 ± 12.16
0.339
0.734
UA (μmol/L)
311.78 ± 76.95
316.43 ± 80.52
0.375
0.707
Use of amlodipine
6 (7.79)
5 (5.81)
0.252
0.615
Comparison of serum ET-1, IL-6, SCF, and c-kit levels between group A and group B
The levels of ET-1 (166.84 ± 21.29 vs 150.36 ± 17.45 ng/L) and IL-6 (98.27 ± 12.14 vs 85.32 ± 9.79 ng/L) in Group A were significantly higher than those in Group B, while the levels of SCF (846.39 ± 22.43 vs 918.65 ± 32.37 ng/L) and c-kit (11.76 ± 3.63 vs 13.44 ± 4.21 μg/L) were significantly lower (P < 0.05), as shown in Figure 1.
Figure 1 Comparison of serum endothelin-1, interleukin-6, stem cell factor, and c-kit levels between group A and group B.
A: Endothelin-1; B: Interleukin-6; C: Stem cell factor; D: c-kit. aP < 0.05. ET-1: Endothelin-1; IL-6: Interleukin-6; SCF: Stem cell factor.
Comparison of serum ET-1, IL-6, SCF, and c-kit levels among patients with different depression severity in group A
Among the 77 patients in Group A, 60 cases had HAMD scores of 20-35 (mild to moderate depression group), and 17 cases had HAMD scores > 35 (severe depression group). Compared with the mild to moderate subgroup, the severe depression subgroup had higher levels of ET-1 (171.49 ± 16.86 vs 159.53 ± 17.62 ng/L) and IL-6 (99.36 ± 10.17 vs 92.15 ± 7.98 ng/L), and lower levels of SCF (840.34 ± 15.57 vs 856.42 ± 16.89 ng/L) and c-kit (10.31 ± 2.44 vs 12.46 ± 3.68 μg/L) (P < 0.05), as shown in Figure 2.
Figure 2 Comparison of serum endothelin-1, interleukin-6, stem cell factor, and c-kit levels among patients with different depression severity in group A.
A: Endothelin-1; B: Interleukin-6; C: Stem cell factor; D: c-kit. aP < 0.05. MMDG: Mild to moderate depression group; SDG: Severe depression group; ET-1: Endothelin-1; IL-6: Interleukin-6; SCF: Stem cell factor.
Relationship between ET-1, IL-6, SCF, c-kit levels and HAMD scores
Pearson correlation analysis showed that ET-1 and IL-6 levels were positively correlated with HAMD scores (r = 0.442, 0.463, P < 0.05), while SCF and c-kit levels were negatively correlated with HAMD scores (r = -0.429, -0.394, P < 0.05) (Figure 3).
Figure 3 Relationship between endothelin-1, interleukin-6, stem cell factor, c-kit levels and Hamilton depression rating scale scores.
A: Endothelin-1; B: Interleukin-6; C: Stem cell factor; D: c-kit. ET-1: Endothelin-1; IL-6: Interleukin-6; SCF: Stem cell factor; HAMD: Hamilton depression rating scale.
Multivariate logistic regression analysis of factors influencing hypertension with depression
Using the presence of hypertension with depression as the dependent variable (no = 0, yes = 1) and the potential influencing factors obtained from Figure 1 and Table 1 as independent variables (Table 2 for assignment), a multivariate logistic regression analysis model was established. The results showed that high ET-1, high IL-6, low SCF, and low c-kit were independent influencing factors for hypertension with depression (P < 0.05) (Table 3).
Table 3 Multivariate logistic regression analysis of factors influencing hypertension with depression.
Factor
β
SE
Wald χ2
P value
OR
95%CI
ET-1
1.086
0.372
8.674
< 0.001
2.893
1.281-6.519
IL-6
1.148
0.411
7.657
< 0.001
1.775
1.216-4.158
SCF
-1.153
0.364
9.481
< 0.001
0.715
0.463-0.972
c-kit
-1.224
0.537
10.752
< 0.001
0.643
0.368-0.835
Diagnostic value of ET-1, IL-6, SCF, c-kit, and their combination for hypertension with depression
ROC analysis revealed AUCs of 0.746 (ET-1), 0.801 (IL-6), 0.732 (SCF), 0.779 (c-kit), and 0.884 (combination). The combined diagnosis demonstrated significantly higher AUC than individual markers (DeLong's test, P < 0.01), with superior sensitivity (90.24%) and specificity (85.37%) (Table 4 and Figure 4).
Figure 4 Receiver operating characteristic curves of endothelin-1, interleukin-6, stem cell factor, c-kit, and their combination for predicting hypertension with depression.
ET-1: Endothelin-1; IL-6: Interleukin-6; SCF: Stem cell factor.
Table 4 Diagnostic value of endothelin-1, interleukin-6, stem cell factor c-kit, and their combination for hypertension with depression.
Indicator
Optimal cutoff value
AUC
95%CI
P value
Sensitivity (%)
Specificity (%)
ET-1
165.73 ng/L
0.746
0.675-0.832
< 0.05
72.56
75.38
IL-6
96.04 ng/L
0.801
0.743-0.889
< 0.05
75.43
67.62
SCF
847.36 ng/L
0.732
0.654-0.817
< 0.05
70.85
74.19
c-kit
11.53 μg/L
0.779
0.707-0.876
< 0.05
77.62
70.57
Combined
-
0.884
0.813-0.957
< 0.05
90.24
85.37
DISCUSSION
The comorbidity of hypertension and depression has emerged as a significant issue warranting heightened attention in the realm of global public health. Recent epidemiological evidence suggests that the prevalence of depressive symptoms among patients with hypertension is markedly higher than in the general population[16,17]. Depression not only compromises treatment adherence in hypertensive individuals but also substantially elevates the risk of cardiovascular complications and all-cause mortality[18]. Although the exact causal mechanisms underlying this comorbidity remain to be fully elucidated, growing evidence indicates that various pathological processes-including chronic low-grade inflammation, endothelial dysfunction, neuroendocrine disturbances, oxidative stress, and autonomic nervous system dysregulation-may play crucial and interrelated roles[19,20].
The present study found that levels of ET-1 were significantly elevated in patients suffering from both hypertension and depression. Moreover, ET-1 levels showed a positive correlation with depression severity, suggesting that ET-1 is not only a hallmark of vascular dysfunction but may also serve as an independent risk factor in this patient population. This finding is in agreement with prior studies[21], which indicate that ET-1, beyond its well-established vasoconstrictive role in hypertension, can cross the blood-brain barrier and influence central nervous system activity. Specifically, ET-1 is capable of acting on neurons and glial cells, thereby affecting the synthesis, release, and transmission of monoamine neurotransmitters such as serotonin and dopamine[22]-two key modulators implicated in the pathophysiology of depression. Additionally, ET-1 can induce cerebral endothelial dysfunction and reduce cerebral perfusion, particularly in emotion-regulating regions such as the prefrontal cortex, amygdala, and hippocampus[23]. Experimental animal studies further demonstrate that ET-1 activates pro-inflammatory signaling pathways such as NF-κB and NADPH oxidase, thereby promoting oxidative stress and neuroinflammation, which in turn impairs neural plasticity and synaptic function[24].
Parallel to ET-1, IL-6 levels were also significantly elevated in patients with comorbid hypertension and depression, showing a strong positive association with HAMD scores. IL-6, as a classic pro-inflammatory cytokine, reflects systemic inflammation and plays a pivotal role in neuroinflammatory processes within the central nervous system[25]. Several studies have shown that IL-6 can cross the blood-brain barrier, activate microglia and astrocytes, and trigger inflammatory cascades that lead to synaptic degradation, diminished neuroplasticity, and ultimately mood dysregulation[26,27]. Of particular interest is the potential bidirectional positive feedback loop between IL-6 and ET-1, wherein IL-6 can upregulate ET-1 expression and enhance its vasoconstrictive effects, while ET-1 can simultaneously stimulate IL-6 production. This creates a vicious cycle of inflammation and vascular dysfunction that may synergistically exacerbate both hypertensive and depressive symptoms[28]. Furthermore, IL-6 has been implicated in disrupting blood-brain barrier integrity, thereby promoting inflammatory infiltration and exacerbating damage to brain tissue-an immunological perspective that further reinforces the biological plausibility of hypertension-depression comorbidity.
Interestingly, this study also identified a distinct pattern in the expression of SCF and its receptor c-kit. Specifically, these markers were significantly downregulated in patients with more severe depression, suggesting a potential neuroprotective and vasoprotective role. The SCF/c-kit signaling axis is known to participate in vascular repair, hematopoietic homeostasis, and neuroregenerative processes. Emerging evidence[29] highlights the protective potential of this pathway in neuropsychiatric disorders. On the vascular side, SCF/c-kit promotes endothelial regeneration and counteracts the vascular dysfunction commonly seen in hypertensive states[30]. In the central nervous system, this pathway activates downstream neurotrophic factors such as BDNF, which supports hippocampal neuroplasticity and may contribute to the alleviation of depressive symptoms[31]. Additionally, SCF has demonstrated antioxidant and anti-inflammatory properties by inhibiting reactive oxygen species production and suppressing NF-κB activation, thereby reducing the release of inflammatory mediators and protecting neural and vascular tissues from further injury[32]. The inverse relationship observed between SCF/c-kit levels and depression severity in this study lends support to the hypothesis that this signaling pathway may serve as a compensatory protective mechanism, potentially offsetting the detrimental effects of inflammation and oxidative stress in hypertensive patients with coexisting depression.
To assess the clinical utility of these biomarkers, the study conducted a ROC curve analysis. Results demonstrated that the combined detection of ET-1, IL-6, SCF, and c-kit yielded an AUC value of 0.884-significantly outperforming any single marker (DeLong’s test, P < 0.01). This underscores the value of a multi-biomarker approach for the early identification and risk stratification of hypertension accompanied by depression, and it may facilitate the implementation of individualized treatment strategies. Additionally, correlation analysis revealed that the coefficients between these four biomarkers ranged from 0.442 to 0.463, representing moderate positive correlations. Although statistically significant, these findings suggest that while these biomarkers reflect important aspects of the underlying pathophysiology, their individual predictive power may be limited. However, their combined application shows promise in enhancing the accuracy of clinical decision-making, particularly when integrated into a multi-dimensional risk assessment framework. Further large-scale studies are needed to validate these associations and determine optimal thresholds for clinical use, paving the way for the development of precise, biomarker-based screening and intervention protocols tailored to this high-risk population.
Although this study identified a distinct biomarker profile in hypertensive patients with depression and explored the relationship between ET-1, IL-6, SCF, and c-kit with the disease, there are still several limitations, and several future research directions warrant further investigation: (1) Limitations: This study was based primarily on single-center retrospective data. While our sample size was sufficient, the limited data source may introduce sample selection bias. Additionally, the retrospective design cannot fully eliminate potential confounding factors, and thus, it is difficult to rule out the influence of other factors on the results. Future multi-center prospective studies will help validate the generalizability and reliability of our findings. Moreover, this study did not include mechanistic experiments. Although we explored the association between biomarker levels and the severity of hypertension combined with depression, the exact mechanistic roles of ET-1, IL-6, SCF, and c-kit in this comorbidity remain unclear. The changes in these biomarkers could be a reflection of complex pathological processes, but their specific regulatory mechanisms still need to be elucidated further; and (2) Future directions: In light of the above limitations, we propose the following future research directions to deepen the understanding of hypertension combined with depression and promote clinical applications: (1) Animal model studies: To verify the role of ET-1, IL-6, and SCF in hypertension combined with depression, animal models can be used for further experimental research. Using hypertensive rat models, we can examine whether inhibition of ET-1 and IL-6 or supplementation of SCF can alleviate depressive behaviors induced by hypertension. This would not only help clarify the specific roles of these biomarkers in the pathological process but also provide theoretical support for the development of new therapeutic strategies; (2) Multi-omics integration studies: While this study focused on four biomarkers (ET-1, IL-6, SCF, and c-kit), the changes in these biomarkers may involve complex molecular regulatory networks. Future research could integrate multiple omics approaches (such as transcriptomics, proteomics, and metabolomics) to explore upstream regulators of these biomarkers. By utilizing high-throughput technologies and bioinformatics analysis, additional potential regulatory pathways can be uncovered, further refining the biomarker model for hypertension combined with depression and offering new targets for early diagnosis and personalized treatment; and (3) Mechanistic studies and personalized treatment: The mechanism of hypertension combined with depression is still not fully understood, and future research should focus on the molecular mechanisms of this comorbidity. Investigating how inflammation, endothelial damage, and neurovascular repair interact to contribute to disease onset and progression will be crucial. By uncovering these mechanisms, personalized treatment strategies can be developed, leading to the application of “precision medicine” for hypertensive patients with depression.
This study highlights the potential clinical significance of the identified biomarkers-ET-1, IL-6, SCF, and c-kit-in hypertensive patients with depression. The results suggest that these biomarkers could serve as valuable tools for the early identification of high-risk patients, enabling the development of personalized intervention strategies. By incorporating these biomarkers into clinical practice, healthcare providers may be able to detect comorbid hypertension and depression at an earlier stage, allowing for more effective management and tailored therapeutic approaches. Moreover, these biomarkers may also facilitate more precise risk stratification, improving patient outcomes through targeted interventions.
CONCLUSION
Thus, the clinical application of this biomarker panel holds great promise for enhancing both diagnostic accuracy and the effectiveness of individualized treatments for patients with hypertension and depression.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Psychiatry
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade B, Grade C
Novelty: Grade B, Grade B
Creativity or Innovation: Grade C, Grade C
Scientific Significance: Grade B, Grade C
P-Reviewer: Bakolis I; Provenzi L S-Editor: Qu XL L-Editor: A P-Editor: Yu HG
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