Association Between Systemic Immune-Inflammation Index and Diabetic Depression

Introduction

Diabetes mellitus (DM) is one of the most prevalent chronic diseases in recent decades.¹ In patients with DM, 64% experience psychological distress and 8% to 35% are diagnosed with depression.^2–5 Patients with DM and depression tend to be less adherent to their therapy and have a higher rate of death.⁶ The complications associated with diabetes can also increase the risk of depression. Approximately 51% of depression cases are not correctly diagnosed in patients with DM, and only 31% received adequate antidepressants.⁷ Therefore, it is both urgent and necessary to identify depression in patients with DM.

Preclinical and clinical studies have shown a causal link between sterile low-grade inflammation and depression in patients with DM.^8–12 Study showed that a high-fat diet leads to an increase in inflammatory cytokine levels and to anxiety and depressive behaviors.^13,14 Antidepressant administration decreased the inflammatory cytokine levels and reversed the behavioral deficits caused by a high-fat diet.¹⁵ Inflammatory biomarkers could potentially be used to predict depression in diabetic patients. Abnormal increases in inflammatory blood cell parameters including neutrophil count, neutrophil-to-lymphocyte ratio,^16,17 monocyte-to-lymphocyte ratio,¹⁸ and platelet-to-lymphocyte ratio^19,20 serve as simple markers of inflammation and their ability to predict depression has been assessed. But these biomarkers involve only two types of immune-inflammatory cells and might not accurately reflect the inflammation status.

The systemic immune-inflammation index (SII) is an integrated and novel inflammatory biomarker^21,22 based on neutrophil, lymphocyte, and platelet counts. The SII index was initially used to assess the prognosis of patients with solid cancers²² and coronary heart disease (CHD)²³ and is now considered to accurately reflect inflammation status.²⁴ However, the role of SII in depression in patients with DM remains unclear. We hypothesized that patients with DM and higher levels of inflammation, as measured by SII, are at a higher risk of developing depression. Therefore, we performed a cross-sectional study to assess the relationship between diabetic depression and SII levels to determine the value of SII in predicting diabetic depression.

Methods

Data and Sample Sources

The study was a two-year cross-sectional, stratified, multistage probability cluster survey. Data were obtained from the National Health and Nutrition Examination Survey (NHANES),²⁵ which is designed to collect a wide variety of information on the potential risk factors and nutrition of the non-institutionalized, civilian, US population. The protocols for the conduct of NHANES were approved by the National Center for Health Statistics institutional review board (NCHS IRB/ERB), and informed consent was obtained from all participants (NCHS IRB/ERB protocols #2011–17). The Ethics Review Board for the National Center for Health Statistic (NCHS ERB) approved the NHANES (NCHS ERB protocols #2011–17), and all participants gave written informed consent. Following an in-home interview, NHANES participants receive a health examination at mobile examination centers. The medical and physiological status of participants is assessed, and laboratory tests conducted. Four cycles of the NHANES survey were selected to assess the association between SII and diabetic depression. The exclusion criteria were: (a) patients with missing SII data and incomplete Patient Health Questionnaire-9 (PHQ-9),²⁶ and (b) corticosteroid, and nonsteroidal anti-inflammatory drug use.

Assessment of Depression Symptoms

In NHANES, depression was assessed using the PHQ-9.²⁶ The PHQ-9 form was completed during the face‐to‐face mobile exam center interview and was designed to evaluate any depression symptoms in the preceding 2 weeks. Each item on the form was scored on a scale of 0 to 3, and total scores ranged from 0 to 27. In this study, PHQ‐9 score ≥ 10 was considered to indicate depression, with a specificity and sensitivity of 88%.^27,28

Study Variables

Lymphocyte, neutrophil, and platelet counts were evaluated using automated hematology analyzing devices and were expressed as ×10³ cells/µL. The SII level was measured as platelet count x neutrophil count/lymphocyte count.²¹ Details of methods about blood are described in the Supporting Methods section. Demographic characteristics included age, sex, race, marital status, education level, body mass index (BMI), smoking status, and ratio of family income to poverty (PIR); DM-related characteristics glycated hemoglobin A1c (HbA1c), diabetes duration, diabetic retinopathy (DR) and insulin use; health factors included stroke, heart failure (HF), and CHD.

Statistical Analyses

Differences in baseline characteristics in the depressive and the non-depressive-symptoms groups were compared using an independent sample t-test for continuous variables and χ2 tests for categoric variables. For the current study, the optimal cutoff value for the SII level was determined using receiver operating characteristics curve analysis. We performed multivariate logistic regression analysis to examine the association between SII and diabetic depression, with 95% confidence intervals (CI) and odds ratio (OR) calculated. In model 1, any confounding factors were not adjusted for, and age, sex, race, education, marital status, body mass index, HbA1c, insulin use, poverty income ratio, smoking status, diabetes duration, chronic conditions including stroke (yes/no), CHD (yes/no), and HF (yes/no), were adjusted for in model 2. To avoid potential bias, and because of differences in baseline characteristics, the propensity score matching (PSM) was determined.²⁹ The study was used to ensure all reported depression selection factors were included as covariates in the model to further reduce potential confounding. Final covariates were age, sex, race, education, marital status, body mass index, HbA1c, insulin use, poverty income ratio, smoking status, diabetes duration, diabetic retinopathy, chronic conditions including stroke (yes/no), CHD (yes/no), and HF (yes/no). PSM was performed at a ratio of 1:1 using a caliper width of 0.01 of the SD of the logit of the propensity score. After PSM, model 3 was analyzed. Subgroup analysis was performed to explore if the association differed for subgroups classified using different parameters including age, sex, BMI, HbA1c, and insulin use. We conducted linear regression analyses to examine the association of SII (independent variable) and high sensitive c-reactive protein (hs-CRP), neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio (dependent variable) to examine whether SII level were associated with inflammation levels.

All analyses were performed using R (version 4.00) “MatchIt” package for PSM. P < 0.05 (two-sided) indicated significant difference.

Results

Subject Characteristics

We identified 2566 patients with DM who met our inclusion criteria. The eligible participants included 1252 women and 1314 men with a mean age of 61.4 ± 13.1 years, and a mean SII of 557.4. The number of patients diagnosed with diabetic depression was 370 (14.4%). Baseline characteristics are shown in Table 1. Depression in patients was associated with higher levels of BMI, heart failure, stroke, and SII. They were also less likely to have been married, and more likely to be in the lower age group and have a lower PIR rate (p < 0.05). Education, diabetic retinopathy, and CHD did not differ between patients with and without depression.

Table 1 Characteristics of Participants in the NHANES (2009–2016) by Depression Statusa

SII is an Independent Risk Factor for Diabetic Depression

We constructed various models to assess the independent effects of SII on diabetic depression, after adjusting for other potential confounding factors. In univariate analysis, age, sex, race, education, BMI, PIR, smoking status, marital status, and chronic conditions were associated with a higher risk of depression (p < 0.05, Supplementary Materials Table S1). High SII levels were a risk factor for diabetic depression in univariate analysis (OR = 1.687, 95% CI: 1.351–2.107, P < 0.00001, Table 2). After adjusting for age, sex, race, education, marital status, body mass index, HbA1c, insulin use, poverty income ratio, smoking status, diabetes duration, chronic conditions including stroke (yes/no), CHD (yes/no), and HF (yes/no), high SII levels were an independent risk factor for diabetic depression (OR = 1.347, 95% CI: 1.031–1.760, P =0.02882). We excluded participants who had a diagnosis of coronary heart disease, stroke, and heart failure, a significant relationship between SII and depression still present (Supplementary Materials Table S2).

Table 2 Association Between SII and Diabetic Depression

PSM Analysis

PSM analysis was conducted to assess the relationship between SII and diabetic depression. The baseline characteristics of patients in different SII groups did not significantly differ (Table 3). Logistic regression analysis revealed that high SII levels were independently related to diabetic depression (OR = 1.452, 95% CI: 1.104–1.908, p = 0.00755).

Table 3 Characteristics of Patients Before and After PSMa

Subgroup Analysis

Subgroup analysis results are shown in Table 4. In patients with diabetic depression, there were no differences in SII levels in most pre-specified subgroups, with the exception of sex. High SII levels were independently related to depression in male patients (OR = 1.686, 95% CI: 1.162–2.447, p = 0.0059), but not in female patients.

Table 4 Subgroup Analysis of the Associations Between SII and Diabetic Depression

Associations Between SII and Inflammatory Markers

Correlations between SII and inflammatory markers are summarized in Table 5. The SII levels were significantly correlated with the inflammatory markers (hs-CRP, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio) in the diabetes mellitus (P<0.001), and these correlations were stronger in depressive symptoms (hs-CRP, r = 0.6073, P <0.001)

Table 5 Correlations Between SII vs Different Variables in All Subjects and Depressive Symptoms

Discussion

To the best of our knowledge, this is the first study that demonstrates the close association between SII and depression in people with DM. Our results show that patients with DM suffering from depression had significantly higher SII levels than did those without depression. Additionally, high SII levels were an independent risk factor for diabetic depression.

As a major mental illness, depression is an important chronic comorbidity of DM.³⁰ Multiple meta-analyses show that DM is a risk factor for depression, and a bi-directional relationship has been shown between the two.^6,31–33 Studies show that 20% to 40% of individuals with diabetes experienced symptoms of depression.³³ Depression is associated with poor health behaviors, including smoking, physical inactivity, and caloric intake, that increase the risk of diabetes.³⁴ Depression is associated with macrovascular complications,³⁵ all of which cause mortality in patients with diabetes.³⁶ It is important to identify biomarkers for early detection of depression in patients with diabetes. A potential link between chronic inflammatory states and depression has also been proposed.³⁷

SII was determined based on the counts of three types of circulating immune cells: neutrophils, lymphocytes, and platelets. The SII level reflects the inflammatory state and could serve as a readily detectable biomarker for systemic inflammatory activity.³⁸ Our results show that patients with diabetes suffering from depression had significantly higher SII levels than did those without depression and that high SII levels are an independent risk factor for diabetic depression. After matching the possible confounding factors, we found that SII, the neutrophil to lymphocyte ratio, and platelet to lymphocyte ratio were associated with depression, but that SII had the highest risk. The SII level provides more clinical information than do NLR and PLR. Patients with high SII levels often have thrombocytosis, neutrophilia, or lymphopenia.³⁹ Lymphocytes and neutrophils mediate adaptive and innate immunity. Neutrophils, which constitute the largest proportion of white blood cells, are important for initiating and modulating immune processes⁴⁰ and secrete neutrophil elastase to mediate chronic inflammation.⁴¹ Patients with increased neutrophil activity release reactive oxygen species, which may be involved in the development of depression. Lymphocytes are an important component of leukocytes, mediate adaptive immunity, and function in innate immunity. Lymphocytes are specific inflammatory mediators with regulatory or protective effects.

Platelets can be considered an aspecific first line inflammatory marker that can bind to leukocytes and the endothelium, influencing the function of inflammatory elements of these cells. Inflammatory elements including cytokines, epinephrine, serotonin, glutamate, dopamine, and P-selectin can activate platelets.⁴² Serotonin, glutamate, and other proinflammatory molecules such as IL-1, CD40L, and P-selectin originate from activated platelets and modulate platelet function in the pathophysiology of depression.^43,44 The dense granules within platelets also contain glutamate^42,45 and platelets are activated in patients with depression. Our results show that high SII levels are an independent risk factor for diabetic depression.

A single study that analyzed inflammation and CHD risk in patients with depression found that SII was significantly higher in patients with major depressive disorder than in the control group.⁴⁶ However, further analysis was not performed, and the researchers did not adjust for potential confounding factors.

Our study had several strengths. The sample size in this study was large enough to identify a significant association between SII and depression in patients with diabetes. Moreover, the analysis of detailed covariate data allowed us to adjust for potential confounding factors that might influence the association between SII and depression. However, there are some limitations to our study. Firstly, the cross-sectional study design means that causality cannot be established. Prospective studies are needed to establish causality. Secondly, data used in this study were extracted from one blood test only. Serial testing may be more informative than a single test on admission because of the short life span of blood cells. Thirdly, SII is easy to measure in clinical practice but the loss of neutrophils, lymphocytes, and platelet counts is common and may lead to selection bias.

Conclusion

Here, we provide the first evidence that SII levels are associated with an increased risk of depression in patients with diabetes. This should be confirmed in prospective studies.