Published online Nov 19, 2026. doi: 10.5498/wjp.124037
Revised: July 13, 2026
Accepted: August 28, 2026
Published online: November 19, 2026
Processing time: 147 Days and 10.6 Hours
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder prevalent worldwide, often accompanied by exacerbated symptoms of depression and an
To investigate the association between the systemic immune-inflammation index (SII) and depressive and anxiety symptoms, as well as their comorbidity, in pa
A cross-sectional study was conducted using consecutive sampling, enrolling 402 hospitalized patients with T2DM. The SII was calculated as platelet count × neutrophil count/lymphocyte count. Depressive and anxiety symptoms were screened using the validated Chinese versions of the 9-item Patient Health Questionnaire and 7-item Generalized Anxiety Disorder scale, with a score ≥ 5 defined as elevated symptoms. Multivariable logistic regression, subgroup in
The prevalence of elevated depressive symptoms, elevated anxiety symptoms, and their comorbidity increased significantly with ascending SII tertiles (all P < 0.001). In fully adjusted models, the highest SII tertile was associated with higher odds of elevated depressive symptoms [odds ratio (OR) = 3.93, 95% confidence interval (95%CI): 2.18–7.08, P < 0.001], elevated anxiety symptoms (OR = 9.21, 95%CI: 4.16–20.39, P < 0.001), and their comorbidity (OR = 5.41, 95%CI: 3.21–9.11, P < 0.001) compared with the lowest tertile. Subgroup analysis identified significant interactions between alcohol consumption and the SII on depressive symptoms (P for interaction = 0.010) and between stroke history (P for interaction = 0.018) and BMI (P for interaction = 0.024) and the SII on anxiety symptoms. Restricted cubic spline analysis confirmed a significant nonlinear dose–response relationship between the SII and elevated depressive and anxiety symptoms (all P for nonlinearity < 0.05).
An elevated SII is independently associated with a higher prevalence of elevated depressive symptoms, elevated anxiety symptoms, and their comorbidity in hospitalized patients with T2DM in a nonlinear pattern.
Core Tip: Chronic inflammation is implicated in the psychological comorbidities of type 2 diabetes mellitus. This cross-sectional study enrolling 402 hospitalized patients with type 2 diabetes mellitus reveals that an elevated systemic immune-inflammation index is independently associated with a higher prevalence of elevated depressive symptoms, anxiety symptoms, and their comorbidity, presenting a significant nonlinear dose-response pattern. The systemic immune-inflammation index may act as an auxiliary inflammatory biomarker for psychological symptom stratification in hospitalized patients with type 2 diabetes mellitus.
- Citation: Pan XY, Wang YK, Ding YQ, Wang NJ, Pan TR, Zhong X. Association between systemic immune-inflammation index and symptoms of depression and anxiety in patients with type 2 diabetes mellitus. World J Psychiatry 2026; 16(11): 124037
- URL: https://www.wjgnet.com/2220-3206/full/v16/i11/124037.htm
- DOI: https://dx.doi.org/10.5498/wjp.124037
Type 2 diabetes mellitus (T2DM) is a highly prevalent chronic metabolic disease worldwide. In addition to typical microvascular and macrovascular complications, the condition is frequently accompanied by a significantly increased prevalence of psychological issues, including depression and anxiety. These conditions have been shown to have a detrimental effect on patients’ treatment adherence and quality of life and to further exacerbate blood glucose fluctuations and insulin resistance, creating a vicious cycle. A review of global epidemiological data indicates that the pre
The prevailing consensus within the academic community is that chronic, low-grade systemic inflammation constitutes a pivotal pathophysiological pathway linking T2DM to emotional symptoms. Hyperglycemia and insulin resistance have been demonstrated to activate inflammatory pathways, such as nuclear factor-κB, which in turn promote the activation of neutrophils and macrophages, as well as the release of various inflammatory cytokines[7,8]. These cytokines have the capacity to cross the blood–brain barrier, thereby activating microglia, disrupting neurotransmitter metabolism, and reducing neural plasticity. It is therefore possible that they may contribute to the onset and progression of depressive and anxiety symptoms. A substantial body of research has demonstrated that disruptions in the cytokine network in patients with T2DM are independently associated with an increased incidence of depressive and anxiety symptoms. This association remains statistically significant even after adjusting for confounding factors such as a history of mental illness[9-11]. However, the majority of previous studies have concentrated on individual circulating cytokines, such as C-reactive protein (CRP) and interleukin-6 (IL-6). Such markers are not included in routine clinical testing and have limited discriminatory power for emotional symptoms in the diabetic population. Consequently, the identification of cost-effective inflammatory biomarkers that reflect systemic inflammatory status is of significant clinical value for the psychological risk stratification of patients with diabetes.
The systemic immune-inflammation index (SII) is a novel composite inflammatory marker that integrates the levels of platelets, neutrophils, and lymphocytes in peripheral blood. The SII is calculated using the following formula: SII = platelet count × neutrophil count/lymphocyte count. In comparison with individual inflammatory markers, the SII provides a more comprehensive reflection of the imbalance between the body’s pro-inflammatory and anti-inflammatory systems. The SII has been validated in a variety of conditions, including cardiovascular disease, metabolic disorders, cancer, and stroke. Elevated SII levels are typically indicative of an increased systemic inflammatory burden and a poor prognosis[12-14]. However, there remains a paucity of systematic discussion regarding the clinical significance, reference thresholds, and influencing factors of SII in individuals with diabetes and co-occurring psychological symptoms.
Despite preliminary investigations into the association between inflammatory markers and emotional symptoms in diabetes, a number of significant research gaps persist within this domain. First, the majority of studies have focused exclusively on depressive symptoms as a solitary outcome, with inadequate consideration given to anxiety symptoms and the comorbidity of depression and anxiety. However, comorbid phenotypes are more prevalent in clinical practice and are associated with inferior metabolic outcomes. Second, the evidence base remains inconclusive with regard to the existence of a non-linear dose-response relationship between the SII and psychological symptoms, which hinders the establishment of clinically applicable risk thresholds. Third, the moderating effects of demographic and clinical factors, such as alcohol consumption, smoking, and comorbidities, on the aforementioned associations have not yet been systematically verified. Fourth, there remains a paucity of high-quality studies in China focusing on hospitalized patients with T2DM that adequately adjust for the burden of comorbidities. It is important to note that the present study utilized a cross-sectional design, which precludes the ability to establish causality or temporal sequence. Unmeasured confounding factors, such as socioeconomic status, sleep quality, dietary patterns, and physical activity, may also influence the observed associations.
In consideration of the preceding research, the present study adopted a cross-sectional design and recruited 402 hospitalized patients with T2DM. The objective of this study was to examine the independent associations between the SII and elevated symptoms of depression and anxiety, as well as the comorbidity of these conditions. Furthermore, potential effect-modifying factors were identified through subgroup interaction analysis, and dose–response relationships were explored using restricted cubic spline (RCS) analysis. The findings of this study provide evidence in support of the use of the SII as a simple inflammatory biomarker for screening psychological risk in patients with diabetes and offer a reference for the implementation of integrated metabolic and psychological management in clinical practice.
This was a single-center cross-sectional study. Consecutive sampling was used to recruit hospitalized patients with T2DM admitted to the Department of Endocrinology, the Second Affiliated Hospital of Anhui Medical University, between May 2024 and April 2025. All patients were hospitalized for suboptimal glycemic control, standardized diabetes management, or follow-up evaluation of chronic complications.
The inclusion criteria comprised the following: (1) Fulfillment of the 1999 World Health Organization diagnostic criteria for T2DM, (2) Age of ≥ 18 years, and (3) The ability to independently complete questionnaire assessments with complete clinical data. The exclusion criteria comprised the following: (1) Type 1 diabetes or other specific types of diabetes; (2) Severe hepatic or renal failure, malignant tumors, hematological disorders, autoimmune diseases, or use of glucocorticoids, immunosuppressants, antipsychotics, granulocyte colony-stimulating factor, or other medications affecting leukocyte counts within the past 6 months; (3) Clinically diagnosed depression or anxiety disorder requiring psychiatric medication or psychotherapy; (4) Cognitive or communication impairment preventing cooperation with the investigation; and (5) Acute infection (fever or acute respiratory or urinary tract infection) within 7 days before admission. In total, 516 hospitalized patients with T2DM were screened consecutively. Among them, 114 patients were excluded according to the above-described criteria: 29 with an inconsistent diabetes diagnosis, 47 with severe com
Demographic information was collected via structured questionnaires, including age, sex, smoking and drinking history, and diabetes duration. Height and body weight were measured with calibrated instruments to calculate body mass index (BMI). Blood pressure was measured after 15 minutes of rest in a seated position, and systolic blood pressure (SBP) and diastolic blood pressure (DBP) were recorded.
Fasting venous blood samples were collected from all patients between 8:00 and 10:00 a.m. on the second day after admission. Complete blood counts were determined using an automated hematology analyzer, and biochemical indicators included fasting blood glucose (FBG), glycated hemoglobin (HbA1c), total cholesterol, triglycerides, aspartate aminotransferase, alanine aminotransferase, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, serum creatinine (Scr), serum uric acid, and blood urea nitrogen (BUN). White blood cell (WBC), neutrophil, lymphocyte, and platelet counts were also determined. Diagnoses of hypertension, coronary artery disease (CAD), stroke, chronic kidney disease (CKD), and metabolic dysfunction-associated steatotic liver disease (MASLD) were based on hospital records and laboratory test results. All tests followed standard laboratory operating procedures with qualified internal quality control.
Smoking was defined as current regular smoking (≥ 1 cigarette per day for ≥ 1 year). Drinking was defined as current regular alcohol consumption (≥ 3 times per week for ≥ 1 year). Hypertension was defined as SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg, or a confirmed diagnosis with ongoing antihypertensive treatment. CKD was defined as estimated glomerular filtration rate < 60 mL/minute/1.73 m2 or urinary albumin/creatinine ratio ≥ 30 mg/g, lasting for ≥ 3 months. MASLD was diagnosed by abdominal ultrasound combined with metabolic risk factors, in line with international MASLD diagnostic criteria. CAD was confirmed by coronary angiography or previous myocardial infarction/coronary revascularization. Stroke was defined as a confirmed history of ischemic or hemorrhagic stroke by cranial imaging.
The samples were used to determine the platelet, neutrophil, and lymphocyte counts and to calculate the SII. The index was calculated using the following formula: Platelet count (× 109/L) multiplied by neutrophil count (× 109/L) and divided by lymphocyte count (× 109/L). All participants were divided into 3 groups (Q1, Q2, and Q3) according to SII tertiles ranked from low to high. The exact cutoff values were as follows: Q1 (SII ≤ 172.3), Q2 (172.3 < SII ≤ 301.6), and Q3 (SII > 301.6).
Depressive symptoms were assessed using the Chinese version of the 9-item Patient Health Questionnaire (PHQ-9), and anxiety symptoms were assessed using the Chinese version of the 7-item Generalized Anxiety Disorder scale (GAD-7). Both scales have been well validated for reliability and validity in the Chinese population. All questionnaires were completed independently by patients under the guidance of uniformly trained investigators and were checked for completeness immediately after collection.
According to validation studies in Chinese populations and widely used screening thresholds, a total score ≥ 5 on the PHQ-9 was defined as elevated depressive symptoms, and a total score ≥ 5 on the GAD-7 was defined as elevated anxiety symptoms. Participants meeting both criteria were defined as having comorbid elevated depressive and anxiety sym
All statistical analyses were performed using R software version 4.3.1. A 2-sided P value < 0.05 was considered statistically significant. Normally distributed continuous variables are expressed as mean ± SD, and intergroup comparisons were conducted using the independent-samples t-test or 1-way analysis of variance. Non-normally distributed continuous variables are expressed as median (interquartile range), and comparisons were performed using the Mann–Whitney U test or Kruskal–Wallis H test. Categorical variables are presented as n (%), and the χ2 test was applied for intergroup comparisons. Missing data were handled using multiple imputation by chained equations for variables with a missing rate below 1%. Complete-case analysis was also conducted as a sensitivity analysis, and consistent results were observed.
Multivariable logistic regression models were constructed to examine the independent associations between the SII and elevated depressive symptoms, elevated anxiety symptoms, and their comorbidity. Four sequentially adjusted models were established to verify the stability of the associations: Model 1: Crude model with no covariate adjustment; Model 2: Adjusted for demographic and lifestyle factors, including sex, age, diabetes duration, BMI, smoking status, and drinking status; Model 3: Further adjusted for comorbidities based on Model 2, including hypertension, CAD, stroke, CKD, and MASLD; and Model 4: Fully adjusted model, with additional adjustment for biochemical indicators, including HbA1c, FBG, total cholesterol, triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, Scr, uric acid, and BUN.
Covariates were selected based on clinical significance and previously published evidence regarding psychological symptoms in patients with diabetes. The events-per-variable ratio was calculated to evaluate potential overfitting risk. Firth penalized logistic regression and a parsimonious model with core covariates were additionally performed as sensitivity analyses to mitigate overfitting bias. Furthermore, sensitivity analyses using alternative cutoff values for the PHQ-9 (≥ 8 and ≥ 10) and GAD-7 (≥ 8 and ≥ 10) were conducted to verify the robustness of the primary findings; the direction and statistical significance of the associations remained consistent across all alternative cutoff specifications. Multicollinearity among covariates was assessed using the variance inflation factor; all variance inflation factor values were below 3, indicating no significant multicollinearity. To avoid mathematically derived collinearity, only the composite SII was included in the final regression models, while individual neutrophil, lymphocyte, and platelet counts were not entered simultaneously. Odds ratios (ORs) and corresponding 95% confidence intervals (95%CIs) were calculated for all regression analyses.
Subgroup analyses stratified by sex, age (< 60/≥ 60 years), BMI (< 28/≥ 28 kg/m2), smoking status, drinking status, hypertension, MASLD, CKD, CAD, and stroke were performed to explore potential effect modifiers. Interaction terms were introduced into the regression models to test the statistical significance of effect modification. For clinical interpretability, the SII was scaled per 100-unit increase in all subgroup analyses, and the results were visualized using forest plots.
RCS analysis was conducted to explore the nonlinear dose–response relationship between the continuous SII and elevated psychological symptoms. Four knots were placed at the 5th, 35th, 65th, and 95th percentiles of the SII distribution, with the median SII value set as the reference. No truncation was applied to extreme values, and the overall observed range of the SII was 42.6–721.9. Of note, the RCS curve is plotted with an extended x-axis range to visualize the complete fitted curve; nevertheless, all statistical inferences are restricted to the observed data range. All covariates included in the fully adjusted model were adjusted for in the spline analysis. The significance of nonlinearity was tested via a likelihood ratio test.
The present study comprised a total of 402 hospitalized patients with T2DM, who were divided into 3 groups according to SII levels (Q1: SII ≤ 172.3, n = 134; Q2: 172.3 < SII ≤ 301.6, n = 134; and Q3: SII > 301.6, n = 134). As the SII increased across the tertiles, the duration of diabetes gradually lengthened (P = 0.049), SBP and BUN levels gradually rose, and the prevalence of CKD gradually increased (all P < 0.05). With regard to drinking status, hematological parameters, the WBC, neutrophil count, and platelet count showed a gradual increase with rising SII, while the lymphocyte count showed a gradual decrease (all P < 0.05). With regard to mood symptom scores and detection rates, PHQ-9 and GAD-7 scores increased significantly as the SII rose through the 3 tertiles; the detection rates for elevated depressive symptoms and elevated anxiety symptoms both showed a significant upward trend with increasing SII (all P < 0.001). No statistically significant differences were observed among the 3 groups for other demographic indicators, liver and kidney function parameters, or comorbidities (P > 0.05; Table 1).
| Variables | Total (n = 402) | Q1 (n = 134) | Q2 (n = 134) | Q3 (n = 134) | P value |
| Age (years) | 55.15 ± 13.09 | 54.87 ± 12.20 | 53.75 ± 13.55 | 56.84 ± 13.39 | 0.146 |
| Diabetes duration (years) | 6.48 ± 6.92 | 6.01 ± 6.97 | 5.75 ± 6.04 | 7.66 ± 7.55 | 0.049 |
| Sex (male) | 249 (61.94) | 81 (60.45) | 89 (66.42) | 79 (58.96) | 0.412 |
| Smoking | 97 (24.13) | 39 (29.10) | 35 (26.12) | 23 (17.16) | 0.059 |
| Drinking | 119 (29.60) | 49 (36.57) | 43 (32.09) | 27 (20.15) | 0.010 |
| SBP (mmHg) | 133.02 ± 17.61 | 130.58 ± 18.48 | 132.20 ± 16.83 | 136.28 ± 17.10 | 0.024 |
| DBP (mmHg) | 80.77 ± 12.26 | 79.37 ± 11.88 | 81.51 ± 12.47 | 81.43 ± 12.39 | 0.267 |
| BMI (kg/m2) | 25.61 ± 4.08 | 25.98 ± 3.90 | 25.43 ± 4.27 | 25.43 ± 4.08 | 0.448 |
| HbA1c (%) | 8.72 ± 2.17 | 8.71 ± 1.98 | 8.89 ± 2.29 | 8.56 ± 2.22 | 0.467 |
| FBG (mmol/L) | 8.32 ± 2.91 | 8.39 ± 2.79 | 8.64 ± 3.19 | 7.95 ± 2.70 | 0.145 |
| ALT (U/L) | 27.46 ± 22.05 | 26.72 ± 20.42 | 27.29 ± 19.09 | 28.37 ± 26.16 | 0.826 |
| AST (U/L) | 23.77 ± 15.09 | 23.37 ± 16.11 | 23.56 ± 13.64 | 24.39 ± 15.51 | 0.841 |
| TC (mmol/L) | 4.66 ± 1.35 | 4.59 ± 1.33 | 4.74 ± 1.54 | 4.64 ± 1.17 | 0.647 |
| TG (mmol/L) | 1.97 ± 1.89 | 2.04 ± 1.82 | 1.91 ± 1.51 | 1.96 ± 2.27 | 0.848 |
| LDL-C (mmol/L) | 2.91 ± 1.01 | 2.90 ± 0.91 | 3.02 ± 1.08 | 2.80 ± 1.04 | 0.215 |
| HDL-C (mmol/L) | 1.13 ± 0.31 | 1.14 ± 0.34 | 1.14 ± 0.29 | 1.10 ± 0.30 | 0.392 |
| Scr (µmol/L) | 65.94 ± 29.54 | 61.95 ± 25.21 | 66.10 ± 24.92 | 69.78 ± 36.64 | 0.096 |
| UA (µmol/L) | 321.45 ± 89.29 | 310.59 ± 83.26 | 325.99 ± 90.18 | 327.74 ± 93.78 | 0.229 |
| BUN (mmol/L) | 6.50 ± 2.21 | 6.14 ± 1.83 | 6.48 ± 1.82 | 6.88 ± 2.78 | 0.024 |
| WBC (× 109/L) | 6.36 ± 1.58 | 5.86 ± 1.55 | 6.35 ± 1.59 | 6.88 ± 1.46 | < 0.001 |
| Neutrophil (× 109/L) | 3.58 ± 1.12 | 2.86 ± 0.84 | 3.48 ± 0.91 | 4.39 ± 1.02 | < 0.001 |
| Lymphocyte (× 109/L) | 2.14 ± 0.85 | 2.47 ± 0.96 | 2.16 ± 0.75 | 1.78 ± 0.67 | < 0.001 |
| PLT (× 109/L) | 199.94 ± 60.02 | 165.83 ± 45.11 | 203.15 ± 48.61 | 230.85 ± 65.72 | < 0.001 |
| CKD | 77 (19.15) | 17 (12.69) | 26 (19.40) | 34 (25.37) | 0.031 |
| Hypertension | 187 (46.52) | 58 (43.28) | 61 (45.52) | 68 (50.75) | 0.454 |
| MASLD | 191 (47.51) | 67 (50.00) | 67 (50.00) | 57 (42.54) | 0.369 |
| CAD | 37 (9.20) | 13 (9.70) | 14 (10.45) | 10 (7.46) | 0.679 |
| Stroke | 46 (11.44) | 15 (11.19) | 15 (11.19) | 16 (11.94) | 0.976 |
| PHQ-9 | 4.31 ± 2.80 | 3.28 ± 2.34 | 4.39 ± 2.79 | 5.27 ± 2.89 | < 0.001 |
| GAD-7 | 3.19 ± 2.59 | 1.99 ± 1.59 | 3.57 ± 2.75 | 4.01 ± 2.80 | < 0.001 |
| Depression | 197 (49.00) | 42 (31.34) | 66 (49.25) | 89 (66.42) | < 0.001 |
| Anxiety | 106 (26.37) | 9 (6.72) | 41 (30.60) | 56 (41.79) | < 0.001 |
In comparisons between groups stratified by depressive symptoms (no depression, n = 205; depression, n = 197), the group with depressive symptoms was significantly older (P = 0.019) and had higher prevalences of hypertension (P = 0.023), CKD (P = 0.004), and stroke (P = 0.019). SBP (P = 0.008), HbA1c (P = 0.009), Scr (P = 0.012), and BUN (P < 0.001) were significantly higher, while FBG (P = 0.027) was significantly lower. Furthermore, the neutrophil count (P = 0.008) was significantly higher, while the lymphocyte count (P < 0.001) was significantly lower. The proportion of participants in the highest SII tertile was higher in the group with elevated depressive symptoms (P < 0.001). No statistically significant differences were observed between the groups with respect to disease duration, sex distribution, smoking/drinking status, liver function, or lipid profiles (P > 0.05; Table 2).
| Variables | Depression | Anxiety | ||||
| No (n = 205) | Yes (n = 197) | P value | No (n = 296) | Yes (n = 106) | P value | |
| Age (years) | 53.65 ± 13.04 | 56.72 ± 12.99 | 0.019 | 55.01 ± 12.96 | 55.56 ± 13.52 | 0.711 |
| Diabetes duration (years) | 6.10 ± 6.42 | 6.87 ± 7.39 | 0.268 | 6.29 ± 6.73 | 7.00 ± 7.41 | 0.362 |
| Sex (male) | 133 (64.88) | 116 (58.88) | 0.216 | 192 (64.86) | 57 (53.77) | 0.044 |
| Smoking | 55 (26.83) | 42 (21.32) | 0.197 | 83 (28.04) | 14 (13.21) | 0.002 |
| Drinking | 67 (32.68) | 52 (26.40) | 0.167 | 102 (34.46) | 17 (16.04) | < 0.001 |
| SBP (mmHg) | 130.75 ± 18.16 | 135.38 ± 16.73 | 0.008 | 131.48 ± 17.92 | 137.32 ± 16.01 | 0.003 |
| DBP (mmHg) | 80.15 ± 12.95 | 81.42 ± 11.49 | 0.298 | 80.16 ± 11.82 | 82.47 ± 13.33 | 0.096 |
| BMI (kg/m2) | 25.81 ± 3.99 | 25.41 ± 4.18 | 0.329 | 25.91 ± 3.84 | 24.77 ± 4.63 | 0.024 |
| HbA1c (%) | 8.44 ± 1.98 | 9.01 ± 2.32 | 0.009 | 8.78 ± 2.07 | 8.55 ± 2.41 | 0.386 |
| FBG (mmol/L) | 8.64 ± 2.89 | 8.00 ± 2.90 | 0.027 | 8.48 ± 2.86 | 7.90 ± 3.00 | 0.078 |
| ALT (U/L) | 26.20 ± 19.75 | 28.78 ± 24.20 | 0.242 | 26.76 ± 20.04 | 29.41 ± 26.93 | 0.292 |
| AST (U/L) | 23.10 ± 15.03 | 24.47 ± 15.16 | 0.365 | 23.42 ± 15.46 | 24.76 ± 14.02 | 0.434 |
| TC (mmol/L) | 4.66 ± 1.33 | 4.65 ± 1.38 | 0.942 | 4.68 ± 1.42 | 4.59 ± 1.15 | 0.556 |
| TG (mmol/L) | 1.98 ± 1.97 | 1.97 ± 1.80 | 0.965 | 1.99 ± 1.96 | 1.92 ± 1.66 | 0.748 |
| LDL-C (mmol/L) | 2.96 ± 1.03 | 2.86 ± 0.99 | 0.316 | 2.91 ± 1.01 | 2.91 ± 1.03 | 0.994 |
| HDL-C (mmol/L) | 1.14 ± 0.31 | 1.12 ± 0.31 | 0.517 | 1.12 ± 0.31 | 1.14 ± 0.30 | 0.613 |
| Scr (µmol/L) | 62.30 ± 25.97 | 69.71 ± 32.46 | 0.012 | 65.23 ± 29.37 | 67.92 ± 30.03 | 0.423 |
| UA (µmol/L) | 315.90 ± 92.93 | 327.15 ± 85.27 | 0.210 | 320.81 ± 89.01 | 323.22 ± 90.45 | 0.812 |
| BUN (mmol/L) | 6.08 ± 1.62 | 6.94 ± 2.62 | < 0.001 | 6.43 ± 2.10 | 6.70 ± 2.48 | 0.280 |
| WBC (× 109/L) | 6.35 ± 1.67 | 6.38 ± 1.50 | 0.876 | 6.25 ± 1.53 | 6.69 ± 1.69 | 0.015 |
| Neutrophil (× 109/L) | 3.43 ± 1.07 | 3.73 ± 1.15 | 0.008 | 3.46 ± 1.08 | 3.90 ± 1.15 | < 0.001 |
| Lymphocyte (× 109/L) | 2.29 ± 0.93 | 1.97 ± 0.72 | < 0.001 | 2.19 ± 0.86 | 1.99 ± 0.82 | 0.034 |
| PLT (× 109/L) | 196.31 ± 60.41 | 203.72 ± 59.53 | 0.216 | 196.98 ± 60.87 | 208.23 ± 57.05 | 0.098 |
| CKD | 28 (13.66) | 49 (24.87) | 0.004 | 51 (17.23) | 26 (24.53) | 0.101 |
| Hypertension | 84 (40.98) | 103 (52.28) | 0.023 | 135 (45.61) | 52 (49.06) | 0.541 |
| MASLD | 105 (51.22) | 86 (43.65) | 0.129 | 148 (50.00) | 43 (40.57) | 0.095 |
| CAD | 19 (9.27) | 18 (9.14) | 0.964 | 26 (8.78) | 11 (10.38) | 0.626 |
| Stroke | 16 (7.80) | 30 (15.23) | 0.019 | 29 (9.80) | 17 (16.04) | 0.083 |
| SII | < 0.001 | < 0.001 | ||||
| Q1 | 92 (44.88) | 42 (21.32) | 125 (42.23) | 9 (8.49) | ||
| Q2 | 68 (33.17) | 66 (33.50) | 93 (31.42) | 41 (38.68) | ||
| Q3 | 45 (21.95) | 89 (45.18) | 78 (26.35) | 56 (52.83) | ||
A comparison was made between the groups stratified by anxiety symptoms (no anxiety, n = 296; anxiety, n = 106). The group without anxiety symptoms had a significantly higher proportion of male patients (P = 0.044), higher rates of smoking (P = 0.002) and alcohol consumption (P < 0.001), and a higher BMI (P = 0.024). The group with anxiety symptoms demonstrated a significantly higher SBP (P = 0.003). Within the group with anxiety symptoms, the WBC (P = 0.015) and neutrophil count (P < 0.001) were significantly higher, while the lymphocyte count (P = 0.034) was significantly lower. The proportion of participants in the highest SII tertile was higher in the group with elevated anxiety symptoms (P < 0.001). No significant differences were observed in age, disease duration, HbA1c, FBG, hepatic and renal function, or lipid profiles (P > 0.05; Table 2).
Subgroup analyses were conducted to investigate the influence of demographic factors (age, sex, BMI, alcohol consumption, and smoking status) and comorbidities (hypertension, MASLD, CKD, stroke, and CAD) on the associations. A 100-unit increase in the SII was used as the exposure variable. With regard to depressive symptoms, a significant association was found between the SII and the presence of depressive symptoms, particularly among patients who consumed alcohol (P for interaction = 0.01; Figure 1). With regard to anxiety symptoms, a statistically significant association was observed between the SII and the presence of anxiety symptoms. Subgroup interaction analysis identified significant effect modification by stroke history (P for interaction = 0.018) and BMI (P for interaction = 0.024). Specifically, the association between the SII and anxiety symptoms was more pronounced in patients with a history of stroke (OR = 2.15, 95%CI: 1.24–3.73) than in those without a history of stroke (OR = 1.16, 95%CI: 1.06–1.28) and in patients with BMI ≥ 28 kg/m2 (OR = 1.69, 95%CI: 1.19–2.40) than in those with BMI < 28 kg/m2 (OR = 1.14, 95%CI: 1.04–1.26; Figure 2).
Multivariable logistic regression analysis was employed to investigate the associations between the SII and depressive and anxiety symptoms. The stability of the findings was evaluated using 4 progressively adjusted models. The findings demonstrated robust associations between an elevated SII and depressive and anxiety symptoms. These associations remained statistically significant even after adjustment for various confounding factors (Table 3). Specifically, using the lowest tertile (Q1) of the SII as the reference, the OR for Q2 in Model 1 was 2.13 (95%CI: 1.29–3.50, P = 0.003). In Model 4, adjusted for all confounders, the OR was 2.02 (95%CI: 1.16–3.54, P = 0.014). The OR for the highest tertile (Q3) of the SII ranged from 3.93 to 4.33 across models, with an OR of 3.93 (95%CI: 2.18–7.08, P < 0.001) in Model 4. With regard to anxiety symptoms, the strength of the association was greater than that for depressive symptoms. The SII Q2 yielded ORs ranging from 6.12 to 6.30 (95%CIs: 2.80–14.04, all P < 0.001) across models, with an OR of 6.30 (95%CI: 2.83–14.04, P < 0.001) in Model 4. Similarly, the SII Q3 yielded ORs ranging from 9.15 to 9.97 (95%CIs: 4.16–21.29, all P < 0.001) across models, with an OR of 9.21 (95%CI: 4.16–20.39, P < 0.001) in Model 4.
| Variables | Model 1 | Model 2 | Model 3 | Model 4 | |||||
| OR (95%CI) | P value | OR (95%CI) | P value | OR (95%CI) | P value | OR (95%CI) | P value | ||
| Depression | Q1 | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | ||||
| Q2 | 2.13 (1.29–3.50) | 0.003 | 2.19 (1.32–3.62) | 0.002 | 2.13 (1.27–3.55) | 0.004 | 2.02 (1.16–3.54) | 0.014 | |
| Q3 | 4.33 (2.60–7.23) | < 0.001 | 4.25 (2.52–7.17) | < 0.001 | 4.09 (2.39–6.97) | < 0.001 | 3.93 (2.18–7.08) | < 0.001 | |
| Anxiety | Q1 | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | ||||
| Q2 | 6.12 (2.84–13.22) | < 0.001 | 6.22 (2.84–13.61) | < 0.001 | 6.16 (2.80–13.55) | < 0.001 | 6.30 (2.83–14.04) | < 0.001 | |
| Q3 | 9.97 (4.67–21.29) | < 0.001 | 9.20 (4.24–19.93) | < 0.001 | 9.15 (4.19–19.98) | < 0.001 | 9.21 (4.16–20.39) | < 0.001 | |
To further investigate the nonlinear relationship between the SII and depressive and anxiety symptoms in patients with T2DM, an RCS analysis was conducted. The results demonstrated significant nonlinear associations between the SII and the prevalence of depressive and anxiety symptoms. In univariable models, both the overall associations (P for overall < 0.001 for both depressive and anxiety symptoms) and nonlinearity (P for nonlinearity = 0.002 for depressive symptoms, P for nonlinearity = 0.031 for anxiety symptoms; Figure 3A and B, respectively) reached statistical significance. Following adjustment for multiple confounding factors, both the overall associations (P for overall < 0.001 for both) and nonlinearity (P for nonlinearity < 0.001 for depressive symptoms, P for nonlinearity < 0.001 for anxiety symptoms; Figure 3C and D, respectively) remained statistically significant. Because of the limited sample size, the CI for high SII values was considerably broader. Consequently, results obtained within this interval should be interpreted with caution.
The participants were grouped and compared according to the co-occurrence of anxiety and depressive symptoms. Group 1 comprised participants with no anxiety or depressive symptoms (n = 180), Group 2 comprised participants with anxiety symptoms only or depressive symptoms only (n = 141), and Group 3 comprised participants with co-occurring anxiety and depressive symptoms (n = 81). No statistically significant differences were observed among the 3 groups in terms of age, disease duration, sex distribution, DBP, BMI, liver function, or blood lipids (all P > 0.05; Table 4). Statistically significant differences were observed in smoking prevalence, alcohol consumption prevalence, SBP, HbA1c, FBG, BUN, neutrophil count, lymphocyte count, CKD, stroke history, and the SII (all P < 0.05). Furthermore, the SII exhibited a gradient-like trend with increasing symptom comorbidity (Table 4).
| Variables | No anxiety or depression | Anxiety or depression | Anxiety and depression | P value |
| Age (years) | 53.86 ± 12.81 | 55.96 ± 13.42 | 56.62 ± 13.02 | 0.192 |
| Diabetes duration (years) | 6.01 ± 6.52 | 6.73 ± 6.83 | 7.08 ± 7.88 | 0.445 |
| Sex (male) | 121 (67.22) | 83 (58.87) | 45 (55.56) | 0.129 |
| Smoking | 54 (30.00) | 30 (21.28) | 13 (16.05) | 0.032 |
| Drinking | 65 (36.11) | 39 (27.66) | 15 (18.52) | 0.013 |
| SBP (mmHg) | 129.91 ± 18.22 | 134.43 ± 17.15 | 137.48 ± 15.84 | 0.003 |
| DBP (mmHg) | 80.30 ± 12.68 | 79.79 ± 11.29 | 83.53 ± 12.68 | 0.071 |
| BMI (kg/m2) | 25.89 ± 3.81 | 25.82 ± 4.14 | 24.64 ± 4.47 | 0.054 |
| HbA1c (%) | 8.37 ± 1.95 | 9.31 ± 2.13 | 8.44 ± 2.48 | < 0.001 |
| FBG (mmol/L) | 8.48 ± 2.78 | 8.69 ± 3.10 | 7.33 ± 2.62 | 0.002 |
| ALT (U/L) | 26.85 ± 20.85 | 25.72 ± 17.40 | 31.89 ± 30.23 | 0.120 |
| AST (U/L) | 23.34 ± 15.87 | 23.15 ± 13.74 | 25.82 ± 15.58 | 0.394 |
| TC (mmol/L) | 4.65 ± 1.35 | 4.73 ± 1.47 | 4.55 ± 1.14 | 0.626 |
| TG (mmol/L) | 2.04 ± 2.08 | 1.85 ± 1.65 | 2.04 ± 1.84 | 0.642 |
| LDL-C (mmol/L) | 2.91 ± 1.00 | 2.98 ± 1.06 | 2.79 ± 0.95 | 0.407 |
| HDL-C (mmol/L) | 1.12 ± 0.30 | 1.15 ± 0.34 | 1.10 ± 0.27 | 0.462 |
| Scr (µmol/L) | 62.56 ± 26.93 | 67.76 ± 30.55 | 70.22 ± 32.62 | 0.102 |
| UA (µmol/L) | 317.95 ± 94.89 | 320.93 ± 79.36 | 329.95 ± 93.42 | 0.605 |
| BUN (mmol/L) | 6.00 ± 1.57 | 7.01 ± 2.49 | 6.72 ± 2.65 | < 0.001 |
| WBC (× 109/L) | 6.30 ± 1.64 | 6.27 ± 1.47 | 6.67 ± 1.65 | 0.150 |
| Neutrophil (× 109/L) | 3.38 ± 1.06 | 3.62 ± 1.12 | 3.93 ± 1.16 | < 0.001 |
| Lymphocyte (× 109/L) | 2.31 ± 0.93 | 2.05 ± 0.75 | 1.91 ± 0.76 | < 0.001 |
| PLT (× 109/L) | 194.69 ± 60.34 | 201.84 ± 61.46 | 208.31 ± 56.23 | 0.214 |
| CKD | 23 (12.78) | 33 (23.40) | 21 (25.93) | 0.012 |
| Hypertension | 76 (42.22) | 67 (47.52) | 44 (54.32) | 0.185 |
| MASLD | 97 (53.89) | 59 (41.84) | 35 (43.21) | 0.069 |
| CAD | 15 (8.33) | 15 (10.64) | 7 (8.64) | 0.763 |
| Stroke | 13 (7.22) | 19 (13.48) | 14 (17.28) | 0.039 |
| SII | < 0.001 | |||
| Q1 | 89 (49.44) | 39 (27.66) | 6 (7.41) | |
| Q2 | 57 (31.67) | 47 (33.33) | 30 (37.04) | |
| Q3 | 34 (18.89) | 55 (39.01) | 45 (55.56) |
Multivariable logistic regression analysis indicated that with the lowest tertile (Q1) of the SII as the reference, elevated SII levels were significantly and robustly associated with increased odds of comorbid depressive and anxiety symptoms. In Model 1, Q2 demonstrated an OR of 3.03 (95%CI: 1.88–4.89), and Q3 exhibited an OR of 6.15 (95%CI: 3.78–10.01). In Model 2, Q2 demonstrated an OR of 3.04 (95%CI: 1.87–4.94), and Q3 exhibited an OR of 5.86 (95%CI: 3.57–9.61). In Model 3, Q2 demonstrated an OR of 3.02 (95%CI: 1.85–4.93), and Q3 exhibited an OR of 5.67 (95%CI: 3.43–9.36). In Model 4, Q2 demonstrated an OR of 3.03 (95%CI: 1.82–5.05), and Q3 exhibited an OR of 5.41 (95%CI: 3.21–9.11) (all P < 0.001; Table 5).
| Variables | Model 1 | Model 2 | Model 3 | Model 4 | |||||
| OR (95%CI) | P value | OR (95%CI) | P value | OR (95%CI) | P value | OR (95%CI) | P value | ||
| SII | Q1 | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | ||||
| Q2 | 3.03 (1.88–4.89) | < 0.001 | 3.04 (1.87–4.94) | < 0.001 | 3.02 (1.85–4.93) | < 0.001 | 3.03 (1.82–5.05) | < 0.001 | |
| Q3 | 6.15 (3.78–10.01) | < 0.001 | 5.86 (3.57–9.61) | < 0.001 | 5.67 (3.43–9.36) | < 0.001 | 5.41 (3.21–9.11) | < 0.001 | |
The present study utilized cross-sectional data from 402 hospitalized patients with T2DM, systematically analyzing the association between the SII and elevated depressive symptoms, anxiety symptoms, and the comorbidity of both. The study identified several key findings. First, an elevated SII was found to be independently and positively associated with all 3 types of emotional symptoms. Second, the magnitude of the associations varied across symptom phenotypes, with the strongest association observed for elevated anxiety symptoms, followed by comorbid depressive and anxiety symptoms and elevated depressive symptoms. Third, a significant nonlinear dose–response relationship between the SII and emotional symptoms was identified. Finally, there were significant interaction effects of alcohol consumption status on the association with depressive symptoms and of stroke history and BMI on the association with anxiety symptoms. It is important to note that the present study adopted a cross-sectional design, which is capable of discerning only con
The findings of this study are largely consistent with extant evidence from research on inflammatory markers and mood disorders in the field of diabetes. A substantial body of previous cross-sectional studies and longitudinal cohorts has demonstrated that in individuals diagnosed with T2DM, the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and classical inflammatory markers such as CRP and IL-6 are all significantly associated with the severity of depressive and anxiety symptoms[15-18]. In comparison with individual inflammatory markers, the SII integrates information from 3 types of blood cells (neutrophils, lymphocytes, and platelets) and thus provides a more comprehensive reflection of the overall imbalance in the body’s pro-inflammatory and anti-inflammatory systems. This may also explain why the association between the SII and mood symptoms was more pronounced in this study. However, because this study did not measure traditional markers such as CRP and IL-6 simultaneously, it was unable to directly verify the incremental discriminatory value of the SII. A comparison of their clinical efficacy still requires confirmation through subsequent head-to-head studies.
The exploratory results of the subgroup analysis have certain clinical implications. The present study identified a significant interaction between alcohol consumption status and the SII in relation to depressive symptoms, with a stronger association between the 2 observed in individuals who consume alcohol. This finding is consistent with the conclusions of previous studies suggesting that alcohol amplifies inflammatory responses and synergistically increases the risk of mood disorders. Alcohol has been demonstrated to exacerbate the systemic inflammatory burden by inducing damage to the intestinal barrier, dysbiosis, and the release of endotoxins[19]. In addition, it has been shown to directly interfere with the regulation of central nervous system neurotransmitters, thereby forming a synergistic effect with the inflammatory response to jointly increase the risk of depressive symptoms. However, in individuals with a history of stroke, the association between the SII and anxiety symptoms was significantly stronger. This finding may be attributed to the heightened systemic inflammatory burden following stroke, which can synergistically amplify neuroinflammatory pathways implicated in anxiety. Post-stroke neuroinflammation, characterized by activated microglia and increased pro-inflammatory cytokine release, may compromise blood–brain barrier integrity and lower the threshold for anxiety manifestation, thereby augmenting the detectability of the inflammation–anxiety association in this vulnerable subgroup[20,21]. Furthermore, a significant interaction was observed between BMI and the SII in relation to anxiety symptoms, with a stronger association noted in patients with BMI ≥ 28 kg/m2. This may be explained by the additive inflammatory burden conferred by obesity, wherein adipose tissue-derived cytokines and SII-related systemic inflammation may act synergistically to increase anxiety risk. It is important to emphasize that subsequent to stratification, the sample sizes within each group were limited; consequently, these interaction effects constitute exploratory findings, and their stability requires validation in studies employing larger sample sizes.
The application of an RCS analysis confirmed a nonlinear dose–response relationship between the SII and elevated emotional symptoms. This finding suggests the possible existence of an inflammatory threshold effect. When the SII is at low to moderate levels, the odds of elevated emotional symptoms rise rapidly as inflammation levels increase. Once the SII exceeds a certain threshold, this upward trend tends to level off. However, it should be noted that the sample size in the high SII range is relatively small and the CIs are wide. The clinical cutoff value for this threshold still requires further confirmation through studies involving larger sample sizes.
From the perspective of pathophysiological hypotheses, the association between the SII and elevated emotional symptoms in patients with diabetes can be explained by neurobiological pathways mediated by chronic inflammation. Preliminary studies have demonstrated that hyperglycemia and insulin resistance can trigger inflammatory pathways, such as nuclear factor-κB, which in turn activates myeloid cells and leads to the release of pro-inflammatory factors[22,23]. Inflammatory factors have been shown to cross the blood–brain barrier, where they can activate central microglia. This, in turn, has been demonstrated to disrupt neural plasticity and the metabolism of monoamine neurotransmitters in brain regions involved in emotional regulation, such as the hippocampus and prefrontal cortex. This disruption, in turn, has been linked to the development of emotional disturbances[24-26]. The 3 components of the SII offer a multifaceted perspective on this process: Elevated neutrophil counts signify peripheral pro-inflammatory activation, lymphocytopenia indicates inadequate anti-inflammatory immune capacity, and platelet dysfunction may influence central neurotransmitter equilibrium via pathways such as 5-hydroxytryptamine transport. However, it should be noted that the aforementioned pathways are theoretical inferences based on previous literature; because this study did not measure downstream inflammatory factors or central nervous system-related indicators, it is unable to confirm specific molecular mechanisms, and the relevant inferences should be interpreted with caution.
The clinical value of this study lies in the fact that the SII is a derivative indicator of routine blood tests; it incurs no additional testing costs and can be readily obtained in hospitalized patients with diabetes. The findings of this study indicate that the SII can function as an auxiliary inflammatory marker for the preliminary screening of emotional risk in hospitalized patients with diabetes. This can assist clinicians in rapidly identifying those at high risk of emotional symptoms, thereby enabling the initiation of standardized scale assessments and psychological interventions. However, it must be acknowledged that the SII, when utilized in isolation, possesses only moderate discriminatory power for emotional symptoms. Its role is best suited to serving as a reference tool for clinical stratification. It cannot, by itself, substitute for assessments employing standardized psychological scales such as the PHQ-9 or GAD-7. Nor can it be equated with a psychiatric clinical diagnosis. Furthermore, the present study observed that the magnitude of the association between the SII and psychological symptoms varied across symptom phenotypes. Specifically, the association was most pronounced for elevated anxiety symptoms (OR = 9.21), followed by comorbid depressive and anxiety symptoms (OR = 5.41), and elevated depressive symptoms (OR = 3.93). Notably, the comorbid group exhibited a stronger association than depressive symptoms, although it did not exceed that observed for anxiety symptoms. This finding suggests that anxiety symptoms may be particularly sensitive to systemic inflammatory burden in hospitalized patients with T2DM. Consequently, clinical management should place greater emphasis on inflammatory biomarker monitoring and integrated metabolic-psychological interventions in patients presenting with elevated anxiety symptoms, whether or not they occur in combination with depressive symptoms.
The present study is subject to several limitations. First, given that the study was conducted as a single-center cross-sectional investigation, it was not possible to establish a causal relationship or temporal sequence between the SII and emotional symptoms. Furthermore, the study was unable to rule out a bidirectional effect whereby emotional abnor
In the context of hospitalized patients with T2DM, an elevated SII was found to be independently associated with an increased prevalence of symptoms of depression and anxiety, as well as comorbidity between the two. Furthermore, the SII demonstrated a nonlinear dose–response relationship with these symptoms. The cross-sectional design of the study suggests a concurrent association but does not allow for the establishment of a causal relationship. Emotional symptoms were measured using screening scales and should not be equated with clinical diagnoses. The SII may serve as an auxiliary reference indicator for stratifying patients according to emotional risk, although its clinical value requires further validation through prospective studies.
We sincerely thank every patient who participated in this study.
| 1. | Xu H, He DJ, Luo C, Yu XM, Duan CZ, Sun D, Wu DJ, Mao XQ, Jiang WF. Association between uric acid to high-density lipoprotein ratio and mental health symptoms in people with type 2 diabetes. World J Diabetes. 2025;16:110211. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Reference Citation Analysis (3)] |
| 2. | Lu X, Yang H, Ying X, Lin S. Enhancing outcomes in type 2 diabetes: the role of psychological interventions within multidisciplinary rehabilitation care. BMC Nurs. 2025;24:1221. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 1] [Cited by in RCA: 2] [Article Influence: 2.0] [Reference Citation Analysis (0)] |
| 3. | Fu W, Xu J, Jiang C, Liu S, Yang C, Qiu X. Associations among personality traits, emotional states, and self-management behaviors with quality of life in type 2 diabetes: a structural equation modeling approach examining emotional mediation. Front Psychol. 2025;16:1629825. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 3] [Cited by in RCA: 5] [Article Influence: 5.0] [Reference Citation Analysis (0)] |
| 4. | Liu X, Li Y, Guan L, He X, Zhang H, Zhang J, Li J, Zhong D, Jin R. A Systematic Review and Meta-Analysis of the Prevalence and Risk Factors of Depression in Type 2 Diabetes Patients in China. Front Med (Lausanne). 2022;9:759499. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 5] [Cited by in RCA: 22] [Article Influence: 5.5] [Reference Citation Analysis (0)] |
| 5. | Zhang Y, Cui Y, Li Y, Lu H, Huang H, Sui J, Guo Z, Miao D. Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus. Front Psychiatry. 2024;15:1328857. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 23] [Cited by in RCA: 23] [Article Influence: 11.5] [Reference Citation Analysis (1)] |
| 6. | Sun N, Lou P, Shang Y, Zhang P, Wang J, Chang G, Shi C. Prevalence and determinants of depressive and anxiety symptoms in adults with type 2 diabetes in China: a cross-sectional study. BMJ Open. 2016;6:e012540. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 91] [Cited by in RCA: 73] [Article Influence: 7.3] [Reference Citation Analysis (1)] |
| 7. | Al Qassab M, Mneimneh M, Jradi A, Derbas B, Dabboussi D, Khoury Baini J, Katrib N, Chaarani N, Attieh P, Kanaan A, Harb F, Azar S, Ghadieh HE. The Expanding Role of GLP-1 Receptor Agonists: Advancing Clinical Outcomes in Metabolic and Mental Health. Curr Issues Mol Biol. 2025;47:285. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 34] [Reference Citation Analysis (0)] |
| 8. | Luo C, Yu XM, Zeng MQ, Duan CZ, Xu SY, Zhu CY, Zheng ZG, Sun D, Fang J, He DJ. Breaking the diabetes-depression cycle: Exploring shared mechanisms, neuroinflammation, and emerging interventions for metabolic-mood comorbidities. World J Diabetes. 2025;16:107406. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 10] [Reference Citation Analysis (0)] |
| 9. | Mansour A, Dehghan Najm Abadi A, Etesam F, Danaei S, Abaszadeh Y, Torabi F, Murshed A, Nasli-Esfahani E, Vahabi Z, Sajjadi-Jazi SM. Association of antidiabetic medications with psychiatric disorders in patients with type 2 diabetes: a cross-sectional study. Eur J Med Res. 2025;30:654. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 3] [Reference Citation Analysis (0)] |
| 10. | Irandoost P, Firouzjaei A, Heshmati J, Sadeghi E, Ayati MH, Namazi N. The effects of an anti-inflammatory diet alone or in combination with acupuncture on mental health, anthropometric indices, and metabolic status in diabetic patients with depression: a randomized, controlled clinical trial. Nutr Diabetes. 2025;15:18. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 9] [Cited by in RCA: 7] [Article Influence: 7.0] [Reference Citation Analysis (0)] |
| 11. | He Y, Tan J, Chen M, Zhao Y, Yang C, Zhang H, Tian J, Huang G, Zhao Z, Yao Z, Zhao L. Individual morphological brain networks, systemic inflammation, and neurocognitive alterations in type 2 diabetes. Brain Res Bull. 2026;240:111903. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 1] [Reference Citation Analysis (0)] |
| 12. | Dong W, Jiang H, Li Y, Lv L, Gong Y, Li B, Wang H, Zeng H. Interpretable machine learning analysis of immunoinflammatory biomarkers for predicting CHD among NAFLD patients. Cardiovasc Diabetol. 2025;24:263. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 33] [Cited by in RCA: 25] [Article Influence: 25.0] [Reference Citation Analysis (0)] |
| 13. | Li Z, Ge S, Song C, Li Y, Xie X, Xu L, Liao S, Zhang K. Systemic immune-inflammation and prognostic immune nutritional index in oral squamous cell carcinoma patients. Biomark Med. 2024;18:759-770. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 5] [Cited by in RCA: 4] [Article Influence: 2.0] [Reference Citation Analysis (0)] |
| 14. | Ma F, Li L, Xu L, Wu J, Zhang A, Liao J, Chen J, Li Y, Li L, Chen Z, Li W, Zhu Q, Zhu Y, Wu M. The relationship between systemic inflammation index, systemic immune-inflammatory index, and inflammatory prognostic index and 90-day outcomes in acute ischemic stroke patients treated with intravenous thrombolysis. J Neuroinflammation. 2023;20:220. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 105] [Reference Citation Analysis (0)] |
| 15. | Zhou Y, Jiang X, Hu Y, Zheng Y, Yan J, Zhang B, Gao Q, Chen Y. The Relationship Between Neutrophil-to-Lymphocyte Ratio and the Prevalence and Clinical Outcomes of Depressive Disorders: A Systematic Review and Meta-Analysis. Harv Rev Psychiatry. 2025;33:289-304. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 2] [Reference Citation Analysis (0)] |
| 16. | Amitai M, Kaffman S, Kroizer E, Lebow M, Magen I, Benaroya-Milshtein N, Fennig S, Weizman A, Apter A, Chen A. Neutrophil to-lymphocyte and platelet-to-lymphocyte ratios as biomarkers for suicidal behavior in children and adolescents with depression or anxiety treated with selective serotonin reuptake inhibitors. Brain Behav Immun. 2022;104:31-38. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 8] [Cited by in RCA: 34] [Article Influence: 8.5] [Reference Citation Analysis (0)] |
| 17. | Zeng Y, Chourpiliadis C, Hammar N, Seitz C, Valdimarsdóttir UA, Fang F, Song H, Wei D. Inflammatory Biomarkers and Risk of Psychiatric Disorders. JAMA Psychiatry. 2024;81:1118-1129. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 105] [Cited by in RCA: 84] [Article Influence: 42.0] [Reference Citation Analysis (0)] |
| 18. | Shen SY, Liang LF, Shi TL, Shen ZQ, Yin SY, Zhang JR, Li W, Mi WL, Wang YQ, Zhang YQ, Yu J. Microglia-Derived Interleukin-6 Triggers Astrocyte Apoptosis in the Hippocampus and Mediates Depression-Like Behavior. Adv Sci (Weinh). 2025;12:e2412556. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 1] [Cited by in RCA: 41] [Article Influence: 41.0] [Reference Citation Analysis (0)] |
| 19. | Litwinowicz K, Gamian A. Microbiome Alterations in Alcohol Use Disorder and Alcoholic Liver Disease. Int J Mol Sci. 2023;24:2461. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 31] [Reference Citation Analysis (0)] |
| 20. | Scopelliti G, Mele F, Cova I, Masserini F, Cucumo V, Maestri G, Nicotra A, Forgione A, Bertora P, Pomati S, Salvadori E, Pantoni L. Depressive Symptoms Profiles and Cognitive Outcomes After Stroke. Brain Behav. 2025;15:e70801. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Reference Citation Analysis (0)] |
| 21. | Gu P, Ding Y, Ruchi M, Feng J, Fan H, Fayyaz A, Geng X. Post-stroke dizziness, depression and anxiety. Neurol Res. 2024;46:466-478. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 10] [Cited by in RCA: 15] [Article Influence: 7.5] [Reference Citation Analysis (1)] |
| 22. | Silveira ASA, Alves ACDA, Gimenes GM, Quessada PDS, Lobato TB, Dias BB, Pereira ACG, Iser-Bem PN, Pereira JNB, Hatanaka E, Masi LN, Pithon-Curi TC, Mattaraia VGM, Hirabara SM, Crisma AR, Gorjão R, Curi R. Evidence for a Pro-Inflammatory State of Macrophages from Non-Obese Type-2 Diabetic Goto-Kakizaki Rats. Int J Mol Sci. 2024;25:10240. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 6] [Reference Citation Analysis (1)] |
| 23. | Baek KR, Kim HK. All-Trans Retinoic Acid Attenuates Inflammation and Insulin Resistance Induced by Adipocyte-Macrophage Coculture. Molecules. 2025;30:4111. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 5] [Reference Citation Analysis (0)] |
| 24. | Liu Q, Nie B, Cui X, Wang W, Duan D. Inflammatory Factors: A Key Contributor to Stress-Induced Major Depressive Disorder. Cells. 2025;14:629. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 8] [Reference Citation Analysis (0)] |
| 25. | Chan KL, Cathomas F, Russo SJ. Central and Peripheral Inflammation Link Metabolic Syndrome and Major Depressive Disorder. Physiology (Bethesda). 2019;34:123-133. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 163] [Cited by in RCA: 160] [Article Influence: 22.9] [Reference Citation Analysis (2)] |
| 26. | Zhao G, Lu Z, Liao Y, Sun Y, Zhang Y, Kang Z, Feng X, Sun J, Yue W. Association of intestinal anti-inflammatory drug target genes with psychiatric Disorders: A Mendelian randomization study. J Adv Res. 2025;70:545-553. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 15] [Cited by in RCA: 12] [Article Influence: 12.0] [Reference Citation Analysis (0)] |