
==== Front
World J Psychiatry
WJP
World Journal of Psychiatry
2220-3206
Baishideng Publishing Group Inc

jWJP.v14.i9.pg1308
10.5498/wjp.v14.i9.1308
97046
Retrospective Cohort Study
Predictive effect of lipopolysaccharide-stimulated inflammatory cytokines on symptoms of generalized anxiety disorder
Wang WY et al. Predictive effect of lipopolysaccharide-stimulated inflammatory cytokines
Wang Wen-Yuan Department of Neurology, The First Hospital of Hebei Medical University, Shijiazhuang 050000, Hebei Province, China
Department of Neurology, Hebei Hospital, Xuanwu Hospital, Capital Medical University, Shijiazhuang 050000, Hebei Province, China

Liu Na Department of Neurology, The First Hospital of Hebei Medical University, Shijiazhuang 050000, Hebei Province, China
Department of Neurology, Hebei Hospital, Xuanwu Hospital, Capital Medical University, Shijiazhuang 050000, Hebei Province, China

Qi Xiao-Xiao Department of Neurological Examination at Treatment Center, The First Hospital of Hebei Medical University, Shijiazhuang 050000, Hebei Province, China

Han Bing Department of Neurology, The First Hospital of Hebei Medical University, Shijiazhuang 050000, Hebei Province, China
Department of Neurology, Hebei Hospital, Xuanwu Hospital, Capital Medical University, Shijiazhuang 050000, Hebei Province, China

Sun Jing-Na Department of Clinical Laboratory, The First Hospital of Hebei Medical University, Shijiazhuang 050000, Hebei Province, China

Chen Zheng-Li Department of Clinical Laboratory, The First Hospital of Hebei Medical University, Shijiazhuang 050000, Hebei Province, China

Wang Ming-Wei Department of Neurology, The First Hospital of Hebei Medical University, Shijiazhuang 050000, Hebei Province, China
Department of Neurology, Hebei Hospital, Xuanwu Hospital, Capital Medical University, Shijiazhuang 050000, Hebei Province, China

Wang Yan-Yong Department of Neurology, The First Hospital of Hebei Medical University, Shijiazhuang 050000, Hebei Province, China
Department of Neurology, Hebei Hospital, Xuanwu Hospital, Capital Medical University, Shijiazhuang 050000, Hebei Province, China. 57600267@hebmu.edu.cn

Author contributions: Wang WY made significant contributions to research design, specific experimental process management, data analysis, and manuscript writing; Liu N, Qi XX, and Han B made significant contributions to research design and data analysis; Wang WY, Han B, and Sun JN made significant contributions to research support and results section preparation; Chen ZL, Wang MW, and Wang YY contributed to research design; Liu N and Qi XX contributed to data collection; Wang YY made significant contributions to research design and manuscript review; all authors have read and approved the final manuscript.

Supported by The 2023 Scientific Research Fund Project of Hebei Provincial Health and Family Planning Commission, No. 20231081 ; and The "Spark" Youth Research Project, The First Hospital of Hebei Medical University, No. XH202302.

Corresponding author: Yan-Yong Wang, MD, Chief Doctor, Department of Neurology, The First Hospital of Hebei Medical University, No. 89 Donggang Road, Shijiazhuang 050000, Hebei Province, China. 57600267@hebmu.edu.cn

19 9 2024
19 9 2024
14 9 13081318
21 5 2024
9 8 2024
20 8 2024
©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
2024
https://creativecommons.org/licenses/by-nc/4.0/ 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.
BACKGROUND

Generalized anxiety disorder (GAD) is a relatively common mental disorder. Recently, inflammation, an important factor for the development of depression, has attracted increasing attention. Several studies have shown that inflammatory cytokines can affect the pathophysiological processes of several nervous system diseases. We hypothesized that there is a correlation between the levels of lipopolysaccharide (LPS)-stimulated inflammatory cytokines and the clinical symptoms of GAD.

AIM

To investigate the predictive effect of LPS-stimulated inflammatory cytokines on symptoms of GAD.

METHODS

This was a cross-sectional study in which 89 patients with GAD diagnosed at The First Hospital of Hebei Medical University from January 2022 to December 2022 and 70 individuals without anxiety and depression (controls) during the same period were included. Fasting venous blood was collected from all the subjects in heparin tubes, and another 3 ml of blood was supplemented with LPS (10 ng/ml). The plasma levels of 12 cytokines [Interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, tumor necrosis factor (TNF)-α, interferon (IFN)-γ, IL-17A, IL-12p70, and IFN-α] were detected.

RESULTS

Post-LPS stimulation, the levels of IL-1β, IL-6, IL-8, IL-10, and TNF-α in both the control and GAD groups were significantly elevated above those in the nonstimulated groups, with IL-6 and IL-8 showing marked increases. Increases in IL-8 and TNF-α were statistically significant in the GAD group (P < 0.05). IL-1β, IL-6, IL-8, IL-10, and TNF-α were found to be significantly correlated with Hamilton Anxiety Rating Scale (HAMA) scores (P < 0.05). A negative correlation was observed between IL-10 levels and HAMA scores. Further analysis revealed that TNF-α was associated with mental anxiety, whereas IL-1β, IL-8, and IL-10 were associated with physical anxiety symptoms, with IL-10 showing a negative correlation with physical anxiety. IL-6 was associated with both mental and physical aspects of anxiety.

CONCLUSION

The physical symptoms of GAD are related to inflammatory factors. IL-1β, IL-8, IL-10, and TNF-a can be used as predictors of physical or mental anxiety in patients with GAD.

Lipopolysaccharide
Cytokine
Generalized anxiety disorder
Inflammatory cytokines
Anxiety
==== Body
pmc Core Tip: In this study, the physical symptoms of generalized anxiety disorder (GAD) were found to be related to inflammatory factors and the innate ability of the body to produce inflammation in vivo. Interleukin (IL)-1β, IL-8, IL-10, and tumor necrosis factor-α can be used as predictors of physical or mental anxiety in patients with GAD. This study provides evidence that lipopolysaccharide-induced inflammatory cytokines can be used to monitor the mental state of GAD patients. Strategies for generalized anxiety disorder that can benefit from personalized treatment with anti-inflammatory drugs may be promising.

INTRODUCTION

Generalized anxiety disorder (GAD) is a relatively common mental disorder characterized by persistent and widespread anxiety and stress, with an unclear pathogenesis. Health facilities at all levels frequently encounter patients with a variety of symptoms. These patients often experience pain in different parts of the body, fatigue, and dysfunction of the head, heart, and gastrointestinal or other organs. Many patients even experience multiple symptoms at the same time. Pain is not limited to physical pain; it also includes psychological and behavioral aspects, especially for some patients. Physical disease is mild or even nonexistent, but patients are highly sensitive to health anxiety and examination behavior. In most patients, most pain is caused by physical pain, but in others, the pain in their own bodies is caused by mental illness, in which anxiety is at the heart of their suffering[1]. However, most patients have physical distress problems or types of illness that are not properly identified and acknowledged at the time of visit. Consequently, prolonged and ultimately unsuccessful treatments often lead to depression. As a result, doctors frequently find such disorders or patients more challenging to treat and requiring higher costs and more time compared to those without anxiety disorders. These health problems significantly contribute to the increasing global burden of disease. At present, it is generally believed that functional somatic symptoms can cause more depression and anxiety disorders. Studies have shown that people with anxiety and depression have different neurobiological correlations compared to people without, such as a stronger thalamic-pituitary-adrenal axis and increased neural activation and activation deficits in working memory due to hypervigilance during magnetic resonance imaging cognitive control tasks[2]. In recent years, inflammation, an important factor for the development of depression, has garnered increasing attention. Several meta-analyses have identified inflammation as a key pathophysiological mechanisms of anxiety disorders. Inflammatory cytokines such as interleukin (IL)-1, IL-6, and tumor necrosis factor (TNF)-α can affect the pathophysiological processes of several nervous system diseases[3].

While the hypothesis linking immune dysregulation to anxiety disorders is compelling, the evidence supporting it is not uniform. A crucial consideration in earlier research was the measurement of basal inflammatory markers in circulation, which are significantly impacted by lifestyle choices and health conditions[4,5]. A comprehensive meta-analysis revealed that the correlation between anxiety and inflammation becomes less pronounced when body mass index (BMI) is taken into account[3]. It appears that baseline inflammation is more closely related to various lifestyle and health factors, including alcohol consumption, BMI, chronic illnesses, and the use of certain medications. At present, few studies have investigated the relationships between various anxiety disorders, especially GAD, and inflammatory responses. It has been reported that ILs and inflammatory chemokines play important roles in the immune regulatory response in GAD[6,7]. On the other hand, studies have shown that inflammatory cytokines can affect cognitive function[8]. In most patients, the association between underlying inflammation and anxiety largely disappeared after adjusting for lifestyle and health factors.

Investigating the response of inflammatory markers to in vitro lipopolysaccharide (LPS) stimulation in blood samples may offer deeper insights into immune regulatory mechanisms. This approach closely mirrors the natural physiological environment, is influenced by strong genetic factors, and elicits an inflammatory reaction that mirrors the body's inherent capacity for inflammatory marker production[9,10,11]. Recent research has indicated that the variability observed in baseline inflammatory level assessments could be mitigated by evaluating markers of inflammation in blood samples stimulated with LPS[12].

Therefore, this study has three main objectives: (1) To observe the basal levels of inflammatory factors in GAD patients and analyze whether there is a correlation between basal inflammatory factors and the clinical symptoms of GAD; (2) To determine whether there is a correlation between the levels of LPS-stimulated cytokines and the clinical symptoms of GAD, given that basic inflammatory factors are influenced by multiple factors; and (3) To examine the relationship between the levels of LPS-stimulated inflammatory factors and mental or physical anxiety as measured by the Hamilton Anxiety Rating Scale (HAMA).

MATERIALS AND METHODS

Clinical data

This investigation employed a cross-sectional approach. The subject pool comprised 89 individuals diagnosed with GAD, recruited from the outpatient and inpatient units of the neurology and psychiatry departments at The First Hospital of Hebei Medical University between January 2022 and December 2022. Seventy individuals who did not exhibit anxiety or depression symptoms during the same timeframe were included as controls. The study protocol received ethical approval from the hospital's ethics committee (approval No. 20220581).

GAD group

The inclusion criteria were as follows: (1) Patients aged 20–70 years; (2) Patients met the International Classification of Disease-10 (ICD-10) version of the diagnostic criteria for GAD; and (3) Patients signed an informed consent form.

The exclusion criteria were as follows: (1) Patients with physical symptoms caused by physical diseases; (2) Patients with language, writing, or reading difficulties; (3) Patients with cognitive dysfunction; (4) Patients diagnosed with other mental illnesses (including bipolar disorder, schizophrenia, and mania); (5) Patients with a strong suicidal tendency; (6) Patients who currently suffer from acute or chronic inflammatory diseases; (7) Patients who have taken antidepressant or antianxiety drugs within 1 mo; and (8) Patients who reported any inflammatory events or ingesting any drugs known to have immunomodulatory effects (such as glucocorticoids) within 2 wk before testing.

Control group

The inclusion criteria were as follows: (1) Patients aged 20–70 years; (2) Patients diagnosed according to the ICD-10 version and used the GAD 7-item (GAD-7) scale and Patient Health Questionnaire-9 (PHQ-9) to rule out anxiety and depression; (3) Patients matched the age and sex of the experimental group; and (4) Patients signed an informed consent form.

The exclusion criteria were as follows: (1) Patients had language, writing, or reading difficulties; (2) Patients had cognitive dysfunction; (3) Patients had suffered from mental illness in the past; (4) Patients had acute or chronic inflammatory diseases; and (5) Patients reported any inflammatory events or ingestion of any drugs known to have immunomodulatory effects (such as glucocorticoids) within 2 wk before testing.

General information

The demographic questionnaire included questions about gender, age, race, place of residence and living conditions, marital status, education level, and occupation. Lifestyle questionnaire data included height, weight, smoking history, and drinking history. The presence of chronic diseases such as diabetes, hypertension, cardiovascular and cerebrovascular diseases, triglycerides, and cholesterol was recorded.

Scale evaluation

The study utilized three critical scales for mental health evaluation: The PHQ-9, the GAD-7, and the HAMA, with a specific focus on the HAMA. In accordance with the criteria set by the Local Scale Collaboration Group, HAMA scores are interpreted as follows: A total score exceeding 29 points signifies severe anxiety, a score above 21 points indicates notable anxiety, a score over 14 points suggests moderate anxiety, a score greater than 7 points denotes mild anxiety, and a score less than 7 points indicates no apparent anxiety symptoms. HAMA's comprehensive analysis, which includes both physical and psychological elements, serves to depict a patient's emotional state and identify any physical symptoms requiring medical attention.

Additionally, the study employed the GAD-7, which was formulated by Kroenke et al[13]. This scale, a segment of the Patient Health Questionnaire, is pivotal for detecting generalized anxiety and measuring the intensity of symptoms. The Chinese version of the GAD-7 has a sensitivity of 86.2%, specificity of 95.5%, and kappa value of 0.825, highlighting its high reliability and validity. This meticulous approach in scale selection and interpretation aligns with the rigorous standards of Science Citation Index journal publications, ensuring a thorough and credible evaluation of psychological health.

Methods for detecting plasma inflammatory factors

Venous blood from all the subjects was collected in heparin tubes, left at room temperature for 30 min, and centrifuged at 4000 r/min for 10 min to obtain the plasma. Another 3 mL of blood was collected, and LPS (10 ng/mL) was added for stimulation[9,11,14]. The mixture was incubated with slow rotation at 37 °C for 5-6 h and centrifuged at 4000 r/min for 10 min. The plasma was then frozen at -80 °C. Plasma levels of cytokines [IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, TNF-α, interferon (IFN)-γ, IL-17A, IL-12p70, and IFN-α] were detected[11].

Statistical analysis

After meticulous validation and editing, the data were organized into a database compatible with Statistical Package for the Social Sciences (SPSS) software, and the analyses were performed via SPSS version 21.0. Proportional data are expressed as percentages. Numerical data are presented as the mean with standard deviation (mean ± SD). To compare average values between two groups, the t test was applied. Categorical variables were tested using the χ² test. Pearson correlation was used to analyze the relationship between two continuous variables, and Spearman correlation was used to evaluate associations between dichotomous and continuous variables. Statistical significance was indicated by a P value less than 0.05.

RESULTS

Comparison of demographic and clinical characteristics of the two groups

The demographic and clinical data of participants in the GAD group vs those in the control group are shown in Table 1. The GAD group included 89 individuals, whereas the control group included 70 individuals. In terms of sex distribution, age, BMI, smoking habits, alcohol consumption, and the prevalence of diabetes, hypertension, hyperlipidemia, coronary artery disease, or cerebrovascular accidents, no significant differences were observed between the two cohorts (P > 0.05).

Table 1 Demographic and clinical characteristics, n (%)

Index	Control group	Generalized anxiety disorder group	t/χ2	P value	
Age (yr)	53.79 ± 16.23	58.30 ± 13.70	1.863	0.065	
Sex (male/female)	25/45	39/50	1.812	0.178	
Body mass index (kg/m2)	24.55 ± 2.06	24.46 ± 3.24	0.291	0.760	
Smoking history	19 (27.14)	18 (20.22)	1.050	0.305	
Drinking history	9 (12.85)	8 (8.99)	0.001	0.529	
Diabetes	10 (14.29)	13 (14.60)	0.030	0.954	
Hypertension	33 (47.14)	46 (51.69)	0.323	0.570	
Coronary heart disease	8 (11.42)	18 (20.22)	2.216	0.137	
Hyperlipidemia	7 (10.00)	10 (11.23)	0.063	0.802	
Cerebral infarction	10 (14.28)	15 (16.85)	0.195	0.659	

Basic inflammatory factors in the peripheral blood

Flow cytometry was used to measure the levels of inflammatory cytokines in the blood. The comparative analysis of these cytokine levels in the peripheral blood of the GAD and control groups is illustrated in Table 2 and Figure 1. Notably, the levels of IL-4 and IL-5 were significantly elevated in the GAD group compared with those in the control group (P < 0.05), whereas the IL-17A levels were significantly lower in the GAD group (P < 0.05).

Figure 1 Violin plot comparing levels of inflammation-related cytokines. bP < 0.01; dP < 0.0001. GAD: Generalized anxiety disorder; NS: Not significant; IFN: Interferon; IL: Interleukin; TNF: Tumor necrosis factor.

Table 2 Comparison of levels of inflammation-related cytokines between the two groups

Inflammatory factor (normal range)	Control group (mean ± SD)	Generalized anxiety disorder group (mean ± SD)	t value	P value	
IL-1β (0-12.4 pg/mL)	1.69 ± 1.04	1.96 ± 2.21	1.024	0.308	
IL-2 (0-5.71 pg/mL)	1.45 ± 0.98	1.78 ± 1.40	1.684	0.094	
IL-4 (0-3 pg/mL)	1.68 ± 1.14	2.19 ± 1.82	2.040	0.043	
IL-5 (0-3.10 pg/mL)	1.27 ± 0.58	2.18 ± 1.80	4.044	0.001	
IL-6 (0-7 pg/mL)	5.03 ± 3.11	5.06 ± 3.98	-0.40	0.968	
IL-8 (0-20.60 pg/mL)	30.59 ± 41.33	57.53 ± 230.29	1.081	0.336	
IL-10 (0-4.91 pg/mL)	2.30 ± 0.82	3.66 ± 5.86	2.163	0.056	
TNF-α (0-4.60 pg/mL)	2.05 ± 1.25	2.42 ± 2.67	1.069	0.287	
IFN-γ (0-7.42 pg/mL)	1.77 ± 1.29	2.02 ± 1.59	1.056	0.292	
IL-17A (0-20.6 pg/mL)	7.23 ± 4.84	4.27 ± 4.42	-3.749	0.001	
IL-12p70 (0-3.4 pg/mL)	2.07 ± 1.40	2.55 ± 2.54	1.443	0.151	
IFN-α (0-8.5 pg/mL)	1.80 ± 1.20	3.42 ± 10.42	1.460	0.148	
IFN: Interferon; IL: Interleukin; TNF: Tumor necrosis factor.

Changes in inflammatory factors after LPS stimulation

LPS-stimulated inflammatory factors represent a patient's innate ability to produce inflammatory factors. Inflammatory factors are affected by various factors, such as diabetes, BMI, and other factors. When we compared the levels of inflammatory factors between the two groups, we assessed whether there was a difference in the ability to produce inflammatory factors. In our analysis, we excluded the effects of BMI, diabetes, hypertension, hyperlipidemia, coronary heart disease, and cerebral infarction on inflammatory factors.

Since LPS is involved in nonspecific immunity and different individuals have varying immune capabilities, we further selected inflammatory factors stimulated by LPS and observed differences between the two groups. After LPS stimulation, flow cytometry was used to compare the levels of inflammatory factors (Table 3 and Figure 2). Compared to the baseline levels (Table 1), the levels of the inflammatory factors IL-1β, IL-6, IL-8, IL-10, TNF-α, and IFN-γ significantly increased in both the control group and the GAD group after stimulation (P < 0.05). Among these, the expression of IL-6 and IL-8 showed the most pronounced increase. The levels of IL-8 and TNF-α in the GAD group after stimulation were significantly higher than those in the control group after stimulation (P < 0.05). However, there were no significant differences in the basic inflammatory factors IL-4, IL-5, and IL-17A which were previously distinct, suggests that GAD is related to the innate production ability of IL-8 and TNF-α in the body.

Figure 2 Violin plot comparing levels of inflammation-related cytokines between groups after lipopolysaccharide stimulation. aP < 0.05; bP < 0.01; dP < 0.0001. GAD: Generalized anxiety disorder; NS: Not significant; IFN: Interferon; IL: Interleukin; TNF: Tumor necrosis factor.

Table 3 Inflammation-related cytokine levels after lipopolysaccharide stimulation

Inflammatory factor (normal range)	Control group (mean ± SD)	Generalized anxiety disorder group (mean ± SD)	t value	P value	
IL-1β (0-12.4 pg/mL)	1592.06 ± 622.43	1538.99 ± 844.21	-0.440	0.660	
IL-2 (0-5.71 pg/mL)	1.12 ± 0.67	1.13 ± 0.85	0.082	0.935	
IL-4 (0-3 pg/mL)	1.44 ± 0.75	1.25 ± 0.77	-1.568	0.119	
IL-5 (0-3.10 pg/mL)	1.09 ± 0.68	1.04 ± 0.39	-0.625	0.534	
IL-6 (0-7 pg/mL)	14354.85 ± 1420.62	14657.66 ± 3347.42	0.173	0.443	
IL-8 (0-20.60 pg/mL)	9515.79 ± 3803.61	11351.12 ± 6349.79	2.306	0.025	
IL-10 (0-4.91 pg/mL)	1244.80 ± 2727.53	1049.45 ± 2877.97	-0.433	0.665	
TNF-α (0-4.60 pg/mL)	2666.29 ± 1272.87	3197.81 ± 1887.78	1.676	0.045	
IFN-γ (0-7.42 pg/mL)	34.72 ± 166.81	23.77 ± 74.81	-0.553	0.581	
IL-17 (0-20.6 pg/mL)	26.91 ± 22.767	28.78 ± 30.53	0.426	0.671	
IL-12p70 (0-3.4 pg/mL)	2.50 ± 2.84	1.94 ± 1.44	-1.633	0.104	
IFN-α (0-8.5 pg/mL)	2.42 ± 2.24	2.01 ± 2.21	-1.181	0.240	
IFN: Interferon; IL: Interleukin; TNF: Tumor necrosis factor.

Analysis of correlation between inflammatory factors and HAMA scores

Some previous studies[11,15] indicated that the correlation of anxiety with inflammation is driven mainly by anxiety symptoms. Herein, we investigated whether these inflammatory factors are related to certain clinical symptoms of GAD. First, we analyzed the correlations between the levels of inflammatory factors and HAMA scores before and after LPS stimulation (Table 4). The results showed that before LPS stimulation, HAMA scores were related to the level of IL-17A; after LPS stimulation, the levels of IL-17A and HAMA scores were not related. However, the levels of five inflammatory factors (IL-1β, IL-6, IL-8, IL-8, IL-8, and TNF-α) and HAMA scores were significantly increased (P < 0.05) after LPS stimulation. Among them, IL-1β, IL-6, IL-8, and TNF-α were positively related to HAMA scores, and IL-10 was negatively related to HAMA scores. This may be because only IL-10 is an anti-inflammatory factor (P < 0.05).

Table 4 Correlation between inflammatory factors and Hamilton Anxiety Rating Scale scores

Inflammatory factor	Correlation with HAMA scores before LPS stimulation	Correlation with HAMA scores after LPS- stimulation	
r value	P value	r value	P value	
IL-1β	0.118	0.271	0.219	0.039	
IL-2	0.131	0.220	-0.20	0.852	
IL-4	0.106	0.322	0.663	0.558	
IL-5	-0.087	0.420	-0.042	0.698	
IL-6	0.058	0.590	0.379	< 0.001	
IL-8	0.149	0.164	0.640	< 0.001	
IL-10	0.050	0.640	-2.92	0.005	
TNF-α	0.108	0.313	0.621	< 0.001	
IFN-γ	0.049	0.647	0.153	0.151	
IL-17A	0.245	0.021	0.138	0.197	
IL-12p70	0.118	0.270	0.091	0.399	
IFN-α	0.036	0.737	0.144	0.178	
IFN: Interferon; IL: Interleukin; TNF: Tumor necrosis factor; HAMA: Hamilton Anxiety Rating Scale; LPS: Lipopolysaccharide.

Correlations of IL-1β, IL-6, IL-8, IL-10, and TNF-α with different HAMA domains

The above results indicate that the correlations between IL-1β, IL-6, IL-8, IL-10, and TNF-α and HAMA score were greater than those between other factors and HAMA score. Therefore, we further analyzed the correlations between IL-1β, IL-6, IL-8, IL-10, and TNF-α and HAMA score. The HAMA was also used to assess both mental anxiety and physical anxiety. These five factors were more stronger related to the mental anxiety and physical anxiety. Therefore, we compared the correlations between the five inflammatory factors and the HAMA score (Table 5). The results revealed that TNF-α was more strongly correlated with mental anxiety, whereas IL-1β, IL-8, and IL-10 were more strongly correlated with physical anxiety (P < 0.05). IL-10 was negatively correlated with physical anxiety (r = -0.292, P < 0.05).

Table 5 Correlation between inflammatory factors and mental anxiety and somatic anxiety

Inflammatory factor	Correlation with mental anxiety	Correlation with somatic anxiety	
r value	P value	r value	P value	
IL-1β	0.148	0.166	0.236	0.026	
IL-6	0.374	< 0.0001	0.304	0.004	
IL-8	0.495	< 0.0001	0.587	< 0.0001	
IL-10	-0.224	< 0.035	-0.307	0.003	
TNF-α	0.644	< 0.0001	0.503	< 0.0001	
IL: Interleukin; TNF: Tumor necrosis factor.

The above results revealed that there were four inflammatory factors related to physical anxiety. Therefore, we used these four inflammatory factors and a more detailed factor division in the HAMA to perform a more specific correlation analysis (Table 6). The results showed that IL-1β was obviously correlated with symptoms of the cardiovascular system. Interestingly, IL-8 was related not only to urogenital system symptoms but also to symptoms of the autonomous nervous system. IL-10 was correlated with gastrointestinal symptoms (Table 6).

Table 6 Correlation between inflammatory factors and factors of somatic anxiety

Somatic anxiety factor (symptoms)	Correlation with inflammatory factors	
IL-1β	IL-8	IL- 10	
r value	P value	r value	P value	r value	P value	
Muscular system	0.26	0.808	0.175	0.101	-0.20	0.853	
Sensory system	0.143	0.182	0.114	0.288	-1.69	0.114	
Cardiovascular system	0.30	0.004	0.119	0.265	0.029	0.788	
Respiratory system	0.012	0.908	0.118	0.273	-0.092	0.392	
Gastrointestinal system	-0.052	0.630	0.027	0.801	-0.503	< 0.0001	
Genitourinary system	0.102	0.341	0.322	0.002	-0.124	0.245	
Autonomic nervous system	0.077	0.471	0.517	< 0.0001	-0.040	0.707	

DISCUSSION

The results of this study suggest that the physical symptoms of GAD are related to inflammatory factors and the innate ability of the body to generate inflammation. IL-1β, IL-8, IL-10, and TNF-α may serve as predictors of physical or mental anxiety in GAD. In the future, monitoring these inflammatory factors could improve the diagnosis of patients' mental status and facilitate symptomatic treatment.

However, doctors in general hospitals should be vigilant about potential psychological issues such as depression or anxiety in patients presenting with multiple symptoms or when emotional symptoms co-occur. The high prevalence of depression and anxiety disorders in general hospital patients underscores the importance of these institutions in providing mental health services. Yet, this role is often mismatched with their current service levels: The recognition rates for mental health problems, especially anxiety and depression, are low. One study revealed that only 8.5% of patients with depression and anxiety in general hospitals received advice from psychiatrists, and only 6.4% were prescribed psychiatric medications[13]. Misdiagnosis surveys have shown that common diseases like digestive, cardiovascular, endocrine, and neurological conditions are often mistaken for anxiety and depression, leading to repeated consultations and examinations, delayed diagnosis, and increased economic and psychological burdens[16].

A study by the National Institutes of Health found that physicians correctly diagnosed anxiety or depression in 77% of patients with psychological symptoms as the main complaint, but only 22% when physical symptoms were predominant[17]. This suggests that focusing on somatic symptoms may reduce the recognition rate of depression and anxiety disorders. In China, the recognition rate of these disorders by non-psychiatrists is particularly low[13].

In 1998, Maes et al[18] first reported a significant relationship between the inflammatory response and anxiety induced by stress. Individuals with anxiety had higher levels of IFN-γ and lower levels of IL-10 compared to non-anxious individuals. Low levels of IL-4 and IL-10 in patients with chronic pain and anxiety are linked to increased pain[19], suggesting a strong association between pain and anxiety[20,21]. Recently, the relationship between inflammatory cytokines and cognitive functions has gained attention. Studies have shown that newly diagnosed GAD patients have abnormal inflammatory cytokine levels and execution function, and there is a correlation between the two factors[22]. Another analysis revealed a bidirectional relationship between depression and inflammation[3]. These studies suggest that inflammatory cytokines and anxiety symptoms are correlated.

To evaluate the mental and physical symptoms of patients, this study utilized the scales PHQ-9, GAD-7, and HAMA. The GAD-7 and PHQ-9 are used for screening, while the HAMA was used to analyze the correlation with inflammatory cytokines. Studies have shown that these scales have strong reliability and high detection rates in diagnosing anxiety or depression[23,24].

In this study, significant differences were noted in the baseline inflammatory markers between the GAD group and the control group. Specifically, the GAD group had higher levels of IL-4 and IL-5 and lower levels of IL-17A (P < 0.05), contrasting with the typically reported increases in IL-6, IL-8, IL-1β, TNF-α, and IFN-γ in prior studies. Research has shown increased IL-6 levels in GAD patients compared to controls[25-28]. TNF-α's role in GAD has yielded mixed results, with some studies indicating elevated levels among GAD patients[27,29,30], whereas the most extensive TNF-α study (n = 1010) revealed no differences between GAD patients and controls or any link between TNF-α levels and anxiety symptoms[25]. This aligns with a study of 93 GAD patients with ischemic heart disease, where no significant differences were found using a combined inflammatory index[31]. A study on IL-4[30] found no significant differences between GAD patients and controls when adjusting for demographic and lifestyle factors. IL-10, known for its anti-inflammatory properties, was significantly decreased in GAD patients (odds ratio = 0.35, P = 0.003). Three studies assessed IFN-γ levels in GAD patients (n = 330)[25,29,30]. A domestic study with the largest number (n = 118) indicating elevated levels of IFN-γ even after adjustments for various factors[30]. Research on newly diagnosed GAD outpatients revealed elevated levels of IL-1α, IL-8, and IL-12p70, with IL-1α and IL-8 levels correlating with GAD severity[25].

Our investigation analyzed baseline inflammation and cytokine production in response to GAD in the same participants. Post-LPS stimulation, significant increases in IL-1β, IL-6, IL-8, IL-10, TNF-α, and IFN-γ were observed in both the control and GAD groups, with IL-6 and IL-8 showing particularly marked increases. The GAD group had significant increases in IL-8 and TNF-α levels, suggesting a link between GAD and the body's inherent ability to produce these cytokines.

Additionally, correlations were found between the levels of IL-1β, IL-6, IL-8, IL-10, and TNF-α and HAMA scores (P < 0.05). IL-1β, IL-6, IL-8, and TNF-α were positively correlated with HAMA scores, with IL-8 and TNF-α showing particularly strong correlations. Conversely, IL-10 levels were negatively correlated with HAMA scores. Baseline inflammation was only associated with IL-17A. Research has indicated that the levels of LPS-stimulated inflammatory markers, including IL-6, IL-8, IL-10, IL-18, MCP-1, MMP2, and TNF-β, are linked to the severity of anxiety symptoms[28].

This study highlights the distinct nature of basal inflammation levels compared to those post-LPS stimulation, representing different aspects of the immune system response. It also underscores the importance of cytokine production capacity in understanding anxiety disorders.

The limitations of this study, such as the cross-sectional design and insufficient sample size, should be acknowledged. Further research is needed to explore the potential causal effects of cytokine production capacity on anxiety symptom risk. Understanding the complex interplay between peripheral inflammation, neuroinflammatory responses, and anxiety symptoms could inform the development of targeted treatments for patients with high inflammation.

CONCLUSION

In general, this study has monitored the mental state of patients with GAD using LPS-induced inflammatory cytokines. Strategies for GAD that can benefit from (personalized) treatment with anti-inflammatory drugs may be promising.

Data sharing statement

The experimental data used to support the findings of this study are available from the corresponding author upon request.

Institutional review board statement: The study protocol received ethical approval from the hospital's ethics committee (approval No. 20220581).

Informed consent statement: Written informed consent was obtained from all participants.

Conflict-of-interest statement: The authors declared that they have no conflicts of interest regarding this work.

STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.

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

Novelty: Grade A

Creativity or Innovation: Grade A

Scientific Significance: Grade A

P-Reviewer: Ong H S-Editor: Luo ML L-Editor: Wang TQ P-Editor: Yu HG
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