This work is licensed under a Abstract
Objective
The aim of this study was to determine serum I-309 levels in type 2 diabetes mellitus (T2DM) patients, as well as the association with clinical/laboratory phenotypes and disease complications.
Methods
A total of 155 T2DM patients and 30 healthy controls (HC) were enrolled. The concentrations of serum I-309, interleukin-4 (IL-4), IL-6, IL-10, IL-12, IL-17, IL-23, tumor necrosis factor-α (TNF-α), and interferon (IFN)-γ were measured. The relationships between I-309 and various clinical and laboratory variables were analyzed.
Results
The serum concentrations of I-309 were significantly higher in T2DM patients than in HC (P < 0.001). The serum I-309 levels were significantly elevated in T2DM patients with diabetic kidney disease (DKD), hypertension, coronary artery disease, peripheral neuropathy, peripheral artery disease, and diabetic ketosis (all P < 0.05), but reduced in drinkers (P = 0.018). The Spearman analysis showed that serum I-309 correlated positively with age, disease duration, CKD stages, urea, creatinine, urinary albumin-to-creatinine ratio, C-reactive protein, red blood cell distribution width, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, IL-6, IL-12, and IFN-γ, but negatively with estimated glomerular filtration rate (eGFR), fasting blood glucose, total bilirubin, albumin, lymphocyte count, red blood cell count, and hemoglobin. The multiple linear regression analysis indicated that serum I-309 was independently correlated only with eGFR and IFN-γ. The multivariate logistic regression analysis demonstrated that serum I-30 and IL-17A remained independently associated with DKD.
Conclusion
Serum I-309 is markedly elevated in T2DM patients and is associated with increased DKD risk, suggesting its potential role as both a promising biomarker and a pathogenic mediator in the progression of T2DM, particularly DKD.
Keywords: I-309, type 2 diabetes mellitus, diabetic kidney disease
Introduction
According to the International Diabetes Federation (IDF) Diabetes Atlas (2021), 10.5% of the adult population between the ages of 20 and 79 years has diabetes mellitus (DM). Furthermore, the prevalence and incidence of this disease are increasing rapidly worldwide. IDF projects indicate that 12.5% adults will be living with DM by 2045, an increase of 46% (https://idf.org). Without question, the DM burden has become a serious public health problem. Type 2 DM (T2DM), accounting for over 90% of all diabetes cases globally, is a chronic progressive disorder characterized by a gradual loss of insulin secretion from the pancreas due to peripheral insulin resistance and progressive β-cell dysfunction, leading to impaired glucose homeostasis (1, 2). Accumulating evidence indicates that chronic low-grade inflammation, characterized by elevated acute-phase proteins, pro-inflammatory cytokines, and chemokines, alongside diminished anti-inflammatory mediators, mechanistically contributes to the development of T2DM and its complications (3, 4, 5).
Microvascular (e.g., nephropathy, retinopathy, and neuropathy) and macrovascular (e.g., coronary artery disease (CAD)) complications of DM, combined with its non-classical comorbidities, collectively drive excess morbidity and mortality. Diabetic kidney disease (DKD) is a major microvascular complication of DM and occurs in about 20–40% of DM patients (6), which progresses to end-stage renal disease (ESRD) without intervention, necessitating dialysis or transplantation. Therefore, early diagnosis and intervention are of great importance for delaying the progression of DKD and improving prognosis. Some comorbidities of T2DM are closely linked to DKD progression, including hypertension, atherosclerosis, and insulin resistance (6). In addition, activation of pro-inflammatory factors may exert a crucial role in renal damage of T2DM (7).
I-309, also known as ligand 1 (CCL1) or T-cell activation-3 (TCA-3), belongs to the CC chemokine subfamily. I-309 is an inducible glycoprotein cytokine produced by various cells such as monocytes/macrophages, T lymphocytes, and natural killer cells, which recruits and activates immune cells through binding to C–C motif chemokine receptor 8 (CCR8) (8, 9, 10). A number of studies have reported elevated levels of I-309 in T2DM patients. Among these, Mir et al. found that T2DM subjects exhibited a significant increase in serum I-309 concentrations related to obesity (11). Lu et al. observed increased serum I-309 levels in T2DM patients with DKD, whereas their study had a limited sample size, including only 30 DKD patients and 30 T2DM patients without DKD, and potential confounding factors were not adequately addressed (12). Therefore, further investigation into the association between serum I-309 and T2DM, as well as its morbidity and complications, particularly DKD, is necessary.
The present study was designed to determine the serum levels of I-309 in T2DM patients and to comprehensively investigate its association with clinical and laboratory phenotypes, particularly DKD.
Patients and methods
Subjects
Between January and December, 2021, a total of 156 T2DM patients were enrolled, of whom one patient had an invalid serum test result for I-309, leaving 155 patients included in the present study. The mean age of eligible patients was 59 (SD, 14) years and 41.9% were women. Diagnosis of T2DM was based on the Standards of Medical Care for Type 2 Diabetes in China 2019 (13). DKD was defined by low estimated glomerular filtration rate (eGFR) (eGFR <60 mL/min/1.73 m2) or albuminuria (urinary albumin-to-creatinine ratio (uACR) ≥30 mg/g or proteinuria >500 mg over a 24 h period) in the setting of T2DM (14, 15). Key exclusion criteria were a history of cancers, liver diseases, or connective tissue diseases; a diagnosis of acute kidney injury or known renal diseases other than DKD; and presence of infectious diseases. A total of 20 healthy individuals with no histories of DM, who had matching sex and age (11 males and nine females, mean (SD) age 63 ± 8 years), were randomly selected as healthy controls (HCs). The study was approved by the institutional ethics committee of Taizhou First People’s Hospital (Number: 2021-KY004-01). Given residual samples used and few harm risks in the present study, informed consent exemptions or broad informed consent obtained from the subjects were also approved by the ethics committee.
Serological measurements
Serum specimens were obtained at enrollment and stored at −80°C. Serum levels of I-309, interleukin-4 (IL-4), IL-6, IL-10, IL-12, IL-17A, IL-23, tumor necrosis factor-α (TNF-α), and interferon (IFN)-γ were measured on the Meso Scale Discovery (MSD) multiplex immunoassay system (MSD SCALE DISCOVERY, USA). Other laboratory parameters were routinely determined in our laboratory.
Data extraction
The electronic medical record was used to obtain demographic, clinical, and laboratory information, including age, gender, body mass index (BMI), smoking, drinking, hypertension, CAD, DM-related complications, medications, routine blood count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein (CRP), fasting blood glucose, C-peptide and insulin, hemoglobin A1c (HbA1c), serum total bilirubin (TB), albumin (ALB), triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), creatinine, and urea. BMI was calculated as weight in kilograms divided by height in meters squared. Hypertension was defined as systolic and diastolic blood pressure values over 140/90 mmHg. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation was used for eGFR calculation (16). Characteristics of T2DM patients are showed in Table 1.
Table 1.
Demographic, clinical, and laboratory characteristics of T2DM patients.
| T2DM patients (n = 155) | |
|---|---|
| Age (y) | 59 ± 14 |
| Gender (F/M) | 65/90 |
| T2DM duration (y) | 8 (2–10) |
| BMI (kg/m2) | 25 ± 4 |
| Current smoker, n | 21 (14%) |
| Current drinker, n | 19 (12%) |
| Hypertension, n | 78 (50%) |
| CAD, n | 11 (7%) |
| PN, n | 100 (65%) |
| PAD, n | 86 (55%) |
| DR, n | 15 (10%) |
| Diabetic foot ulcers, n | 6 (4%) |
| DK, n | 25 (16%) |
| DKD, n | 53 (34%) |
| eGFR (ml/min/(1.73m)2) | 96 ± 28 |
| Fasting blood glucose (mmol/L) | 8.72 ± 3.76 |
| HbA1c (%) | 10.19 ± 2.25 |
| Fasting insulin (μIU/mL) | 12.10 (7.24–16.68) |
| Fasting C-peptide (ng/mL) | 1.67 (0.96–2.75) |
| TB (μmol/L) | 10.5 (8.2–14.4) |
| ALB (g/L) | 37 ± 5 |
| TG (mmol/L) | 1.55 (1.07–2.33) |
| TC (mmol/L) | 4.86 ± 1.19 |
| HDL-C (mmol/L) | 1.07 ± 0.31 |
| LDL-C (mmol/L) | 2.79 ± 0.97 |
| Urea (μmol/L) | 5.66 (4.65–7.40) |
| Creatinine (μmol/L) | 60 (48–76) |
| uACR (mg/g) | 17 (9–52) |
| WBC (×1012/L) | 6.9 ± 2.3 |
| Neutrophil (×1012/L) | 3.8 (2.9–4.9) |
| Monocyte (×1012/L) | 0.6 ± 0.2 |
| Lymphocyte (×1012/L) | 1.8 (1.5–2.4) |
| RBC (×1012/L) | 4.47 ± 0.69 |
| HB (g/L) | 136 ± 21 |
| RDW | 12.5 ± 0.9 |
| PLT (×109/L) | 227 ± 86 |
| NLR | 1.92 (1.38–2.91) |
| PLR (×10−3) | 113 (86–147) |
| CRP (mg/L) | 2.66 (1.00–7.77) |
| IL-4 (pg/mL) | 0.4 (0.3–0.7) |
| IL-6 (pg/mL) | 3.07 (1.78–6.58) |
| IL-10 (pg/mL) | 0.34 (0.22–0.51) |
| IL-12 (pg/mL) | 0.24 (0.19–0.33) |
| IL-17A (pg/mL) | 4.05 (3.06–6.22) |
| IL-23 (pg/mL) | 1.00 (0.62–1.82) |
| IFN-γ (pg/mL) | 22.72 (16.16–37.33) |
| TNF-α (pg/mL) | 16.16 (7.66–30.08) |
| Medications when enrolled | |
| Sulfonylureas, n | 31 (20%) |
| Metformin, n | 51 (33%) |
| Insulin, n | 46 (30%) |
| Acarbose, n | 32 (21%) |
| Repaglinide, n | 16 (10%) |
| Sitagliptin, n | 13 (8%) |
| Pioglitazone, n | 6 (4%) |
| Aspirin, n | 9 (6%) |
| Antihypertensives, n | 10 (6%) |
T2DM, type 2 diabetes mellitus; y, years; F, female; M, male; BMI, body mass index; CAD, coronary artery disease; PN, peripheral neuropathy; PAD, peripheral artery disease; DR, diabetic retinopathy; DK, diabetic ketosis; DKD, diabetic kidney disease; eGFR, estimated glomerular filtration rate; HbA1c, hemoglobin A1c; TB, total bilirubin; ALB, albumin; TG, triglyceride; TC, total cholesterol; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein-cholesterol; uACR, urinary albumin-to-creatinine ratio; WBC, white blood cell; RBC, red blood cell; HB, hemoglobin; RDW, RBC distribution width; PLT, platelet; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; CRP, C-reactive protein; IL, interleukin; IFN, interferon; TNF, tumor necrosis factor.
Statistical analysis
Statistical analyses were performed with the use of SPSS 17.0 software. Frequencies, mean ± standard deviation (SD), median, and interquartile ranges (IQR) were estimated for categorical, normally distributed, and skewedly distributed variables, respectively. Differences in serum I-309 between groups were tested for statistical significance using the Mann–Whitney U test. Spearman’s rank correlation coefficients were calculated to evaluate the correlation between groups. Receiver operating characteristic (ROC) curve was used to assess the ability of serum I-309 to distinguish DKD, and the optimal cutoff value was calculated by Youden’s Index. Univariate and multivariate linear regression analyses were performed to examine the correlation of serum I-309 with other variables. Univariate or multivariate logistic regression models were used to evaluate the relationships between various variables and DKD. Two-tailed P values < 0.05 were considered statistically significant.
Results
Serum I-309 levels in T2DM patients and HC
The levels of serum I-309 were significantly increased in T2DM patients (median, IQR, 15.11, 11.74–20.53, pg/mL) compared with HCs (median, IQR, 11.57, 10.3–13.73, pg/mL) (P = 0.001). Moreover, the patients both with and without DKD had significantly higher serum I-309 levels (median, IQR, T2DM with DKD: 20.47, 13.58–26.47; T2DM without DKD: 13.59, 11.14–16.50, pg/mL) than HC (P < 0.001 for DKD vs HC, P = 0.016 for non-DKD vs HC) (Fig. 1). ROC analysis showed a moderate performance of serum I-309 to identify patients with T2DM, with an AUC of 0.735 (95% CI: 0.648–0.823, P < 0.001) (Fig. 2). When the optimal cutoff value of 12.53 pg/mL was used, sensitivity and specificity were 70.3 and 70.0%, respectively.
Figure 1.
Serum levels of I-309 in T2DM patients and HC.
Figure 2.
The ROC analysis for diagnostic performance of serum I-309 for T2DM.
Relationships between serum I-309 and clinical and laboratory variables in T2DM patients
The serum levels of I-309 were significantly increased in T2DM patients with DKD, hypertension, CAD, peripheral neuropathy (PN), peripheral artery disease (PAD), and diabetic ketosis (DK), compared to those without these complications (all P < 0.05), but decreased in drinkers (T2DM patients currently drinking) compared to non-drinkers (those who never drank or former drinkers) (P = 0.018). The serum levels of I-309 were slightly higher in T2DM patients who were receiving repaglinide medication than in those who were not (P = 0.047). See Table 2.
Table 2.
Associations between I-309 and categorized variables in T2DM patients.
| I-309 (pg/mL) | P value | |
|---|---|---|
| Gender | ||
| Male (n = 90) | 14.20 (11.36–19.94) | |
| Female (n = 65) | 16.08 (12.93–20.86) | 0.095 |
| Smoking | ||
| Yes (n = 21) | 14.15 (9.96–15.88) | |
| No (n = 134) | 15.42 (12.20–20.98) | 0.126 |
| Drinking | ||
| Yes (n = 19) | 13.47 (10.45–14.51) | |
| No (n = 136) | 15.57 (12.17–21.52) | 0.018 |
| Hypertension | ||
| Yes (n = 78) | 16.28 (13.34–23.25) | |
| No (n = 77) | 13.47 (10.73–17.18) | <0.001 |
| CAD | ||
| Yes (n = 11) | 23.17 (19.13–27.93) | |
| No (n = 144) | 14.39 (11.55–19.84) | 0.002 |
| DKD | ||
| Yes (n = 53) | 20.47 (13.58–26.47) | |
| No (n = 102) | 13.59 (11.14–16.50) | <0.001 |
| PN | ||
| Yes (n = 100) | 16.22 (12.86–22.19) | |
| No (n = 55) | 13.17 (10.45–16.36) | 0.002 |
| PAD | ||
| Yes (n = 86) | 16.15 (13.17–20.98) | |
| No (n = 69) | 13.34 (11.12–19.30) | 0.020 |
| DR | ||
| Yes (n = 15) | 20.52 (11.50–26.15) | |
| No (n = 140) | 15.01 (11.81–20.14) | 0.171 |
| Diabetic foot ulcers | ||
| Yes (n = 6) | 17.11 (12.14–21.78) | |
| No (n = 149) | 15.11 (11.71–20.50) | 0.742 |
| DK | ||
| Yes (n = 25) | 12.43 (10.12–14.89) | |
| No (n = 130) | 15.57 (12.39–21.78) | 0.002 |
| Medications when enrolled | ||
| Sulfonylureas | ||
| Yes (n = 31) | 14.10 (12.43–18.81) | |
| No (n = 124) | 15.19 (11.70–22.02) | 0.403 |
| Metformin | ||
| Yes (n = 51) | 15.26 (11.51–20.24) | |
| No (n = 104) | 14.83 (12.03–21.94) | 0.655 |
| Insulin | ||
| Yes (n = 46) | 16.27 (12.39–23.59) | |
| No (n = 109) | 14.07 (11.71–19.77) | 0.056 |
| Acarbose | ||
| Yes (n = 32) | 16.29 (11.39–22.19) | |
| No (n = 123) | 15.10 (11.99–19.86) | 0.567 |
| Repaglinide | ||
| Yes (n = 16) | 20.52 (13.60–25.85) | |
| No (n = 139) | 14.74 (11.68–19.79) | 0.047 |
| Sitagliptin | ||
| Yes (n = 13) | 16.08 (12.90–18.63) | |
| No (n = 142) | 15.10 (11.64–20.64) | 0.799 |
| Pioglitazone | ||
| Yes (n = 6) | 15.07 (11.78–24.11) | |
| No (n = 149) | 15.11 (11.71–20.52) | 0.856 |
| Aspirin | ||
| Yes (n = 9) | 19.86 (14.68–21.27) | |
| No (n = 146) | 14.83 (11.64–20.57) | 0.236 |
| Antihypertensives | ||
| Yes (n = 10) | 20.45 (10.17–23.99) | |
| No (n = 145) | 15.10 (11.87–20.35) | 0.444 |
T2DM, type 2 diabetes mellitus; CAD, coronary artery disease; DKD, diabetic kidney disease; PN, peripheral neuropathy; PAD, peripheral artery disease; DR, diabetic retinopathy; DK, diabetic ketosis.
As shown in Table 3, the Spearman’s correlation analysis indicated that serum I-309 levels correlated positively with age, disease duration, CKD stages, urea, creatinine, uACR, CRP, RDW, NLR, PLR, IL-6, IL-12, and IFN-γ, but negatively with eGFR, fasting blood glucose, TB, ALB, lymphocyte count, RBC count, and HB (all P < 0.05). No significant correlation was observed between serum I-309 levels and other clinical or laboratory variables. The multiple linear regression analysis suggested that serum I-309 levels were independently correlated only with eGFR and IFN-γ, after adjusting for various confounding factors (Table 4).
Table 3.
Correlations between I-309 and continuous variables in T2DM patients.
| T2DM patients | ||
|---|---|---|
| r | P value | |
| Age | 0.400 | <0.001 |
| T2DM duration | 0.309 | <0.001 |
| BMI | 0.019 | 0.812 |
| eGFR | −0.565 | <0.001 |
| CKD stage | 0.484 | <0.001 |
| Fasting blood glucose | −0.189 | 0.018 |
| HbA1c | −0.144 | 0.074 |
| Fasting insulin | 0.080 | 0.322 |
| Fasting C-peptide | −0.006 | 0.943 |
| TB | −0.197 | 0.014 |
| ALB | −0.227 | 0.005 |
| TG | −0.084 | 0.302 |
| TC | −0.155 | 0.054 |
| HDL-C | −0.066 | 0.418 |
| LDL-C | −0.141 | 0.082 |
| Urea | 0.375 | <0.001 |
| Creatinine | 0.422 | <0.001 |
| uACR | 0.424 | <0.001 |
| CRP | 0.212 | 0.008 |
| WBC | 0.006 | 0.946 |
| Neutrophil | 0.097 | 0.228 |
| Monocyte | 0.067 | 0.410 |
| Lymphocyte | −0.205 | 0.010 |
| RBC | −0.356 | <0.001 |
| HB | −0.385 | <0.001 |
| RDW | 0.207 | 0.010 |
| PLT | 0.079 | 0.328 |
| NLR | 0.233 | 0.004 |
| PLR | 0.253 | 0.001 |
| IL-4 | 0.045 | 0.579 |
| IL-6 | 0.257 | 0.001 |
| IL-10 | 0.098 | 0.227 |
| IL-12 | 0.171 | 0.033 |
| IL-17A | 0.077 | 0.338 |
| IL-23 | −0.011 | 0.896 |
| IFN-γ | 0.245 | 0.002 |
| TNF-α | 0.051 | 0.526 |
T2DM, type 2 diabetes mellitus; F, female; M, male; BMI, body mass index; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; HbA1c, hemoglobin A1c; TB, total bilirubin; ALB, albumin; TG, triglyceride; TC, total cholesterol; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein-cholesterol; uACR, urinary albumin-to-creatinine ratio; CRP, C-reactive protein; WBC, white blood cell; RBC, red blood cell; HB, hemoglobin; RDW, RBC distribution width; PLT, platelet; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; IL, interleukin; IFN, interferon; TNF, tumor necrosis factor.
Table 4.
Multiple linear regression analysis of correlation between serum I-309 and various variables in T2DM patients.
| Unstandardized coefficients | Standardized coefficients | P value | ||
|---|---|---|---|---|
| Β | Standard error | β | ||
| Age | −0.060 | 0.061 | −0.102 | 0.322 |
| Duration of T2DM | 0.127 | 0.093 | 0.116 | 0.175 |
| Drinking | −0.557 | 1.795 | −0.022 | 0.757 |
| Hypertension | 1.617 | 1.296 | 0.095 | 0.215 |
| CAD | 0.244 | 2.369 | 0.007 | 0.918 |
| PN | −0.247 | 1.378 | −0.014 | 0.858 |
| PAD | 0.302 | 1.331 | 0.018 | 0.821 |
| DK | −2.321 | 1.781 | −0.101 | 0.195 |
| Repaglinide | −0.228 | 1.987 | −0.008 | 0.909 |
| Urea | 0.194 | 0.276 | 0.070 | 0.484 |
| eGFR | −0.118 | 0.040 | −0.393 | 0.004 |
| uACR | 0.001 | 0.001 | 0.098 | 0.250 |
| Fasting blood glucose | 0.117 | 0.173 | 0.052 | 0.501 |
| TB | 0.017 | 0.126 | 0.011 | 0.893 |
| ALB | −0.170 | 0.163 | −0.097 | 0.301 |
| CRP | 0.007 | 0.030 | 0.021 | 0.817 |
| Lymphocyte | −0.140 | 0.295 | −0.033 | 0.636 |
| RBC | 0.789 | 2.447 | 0.065 | 0.748 |
| HB | 0.000 | 0.084 | 0.000 | 0.998 |
| RDW | 0.482 | 0.822 | 0.048 | 0.558 |
| IFN-γ | 0.043 | 0.015 | 0.243 | 0.006 |
| IL-12 | 0.964 | 0.801 | 0.089 | 0.231 |
| IL-6 | −0.039 | 0.046 | −0.065 | 0.404 |
T2DM, type 2 diabetes mellitus; CAD, coronary artery disease; PN, peripheral neuropathy; PAD, peripheral artery disease; DK, diabetic ketosis; eGFR, estimated glomerular filtration rate; uACR, urinary albumin-to-creatinine ratio; TB, total bilirubin; ALB, albumin; CRP, C-reactive protein; RBC, red blood cell; HB, hemoglobin; RDW, RBC distribution width; IFN, interferon; IL, interleukin.
Association between serum I-309 and DKD
As mentioned above, serum I-309 levels were significantly elevated in T2DM patients with DKD and were significantly correlated with eGFR and uACR. Therefore, we employed ROC analysis to explore the performance of the chemokine for identifying DKD in T2DM patients. The results demonstrated an acceptable performance, with an AUC of 0.722 (95% CI: 0.635–0.810, P < 0.001) (Fig. 3). In addition, logistic regression analysis was further employed to investigate whether serum I-309 was independently associated with the risk of DKD in T2DM patients. The univariate regression analysis revealed that serum I-309, along with age, disease duration, hypertension, CAD, PN, DR, fasting C-peptide, CRP, monocyte count, RBC, HB, RDW, IL-17A, IFN-γ, TB, and ALB, was associated with increased DKD risk in T2DM patients (all P < 0.05). However, the multivariate regression analysis including these significant variables demonstrated that only serum I-309 (OR: 1.113, 95% CI: 1.014–1.221), hypertension, DR, fasting C-peptide, and IL-17A remained independently associated with increased DKD risk. See Table 5.
Figure 3.
The ROC analysis for identification of DKD in T2DM patients.
Table 5.
Association of various variables with DKD risk in T2DM patients.
| OR | 95% CI | P value | OR | 95% CI | P value | |
|---|---|---|---|---|---|---|
| Age | 1.031 | 1.004–1.058 | 0.023 | 0.976 | 0.926–1.029 | 0.373 |
| Gender | 1.231 | 0.630–2.407 | 0.543 | |||
| T2DM duration | 1.090 | 1.041–1.141 | <0.001 | 1.046 | 0.968–1.130 | 0.259 |
| BMI | 0.995 | 0.908–1.090 | 0.910 | |||
| Current smoker | 1.534 | 0.601–3.913 | 0.370 | |||
| Current drinker | 0.473 | 0.149–1.506 | 0.205 | |||
| Hypertension | 3.441 | 1.696–6.981 | 0.001 | 3.437 | 1.122–10.526 | 0.031 |
| CAD | 3.728 | 1.039–13.375 | 0.043 | 0.689 | 0.068–6.991 | 0.753 |
| PN | 4.016 | 1.775–9.084 | 0.001 | 2.365 | 0.661–8.463 | 0.186 |
| PAD | 1.944 | 0.977–3.870 | 0.058 | |||
| DR | 9.659 | 2.589–36.029 | 0.001 | 6.697 | 1.045–42.928 | 0.045 |
| Diabetic foot ulcers | 4.082 | 0.723–23.056 | 0.111 | |||
| DK | 1.099 | 0.450–2.687 | 0.835 | |||
| Medications when enrolled | ||||||
| Sulfonylureas | 1.279 | 0.567–2.885 | 0.554 | |||
| Metformin | 0.828 | 0.405–1.692 | 0.604 | |||
| Insulin | 1.772 | 0.869–3.610 | 0.115 | |||
| Acarbose | 1.675 | 1.756–3.710 | 0.203 | |||
| Repaglinide | 1.572 | 0.551–4.489 | 0.398 | |||
| Sitagliptin | 0.324 | 0.069–1.521 | 0.153 | |||
| Pioglitazone | 0.373 | 0.042–3.278 | 0.374 | |||
| Aspirin | 1.584 | 0.407–6.164 | 0.507 | |||
| Antihypertensives | 2.0021 | 0.558–7.319 | 0.284 | |||
| Fasting blood glucose | 1.016 | 0.931–1.109 | 0.723 | |||
| HbA1c | 0.891 | 0.766–1.038 | 0.138 | |||
| Fasting insulin | 1.020 | 0.992–1.049 | 0.161 | |||
| Fasting C-peptide | 1.259 | 1.030–1.538 | 0.024 | 1.538 | 1.101–2.149 | 0.012 |
| CRP | 1.053 | 1.019–1.087 | 0.002 | 1.023 | 0.980–1.069 | 0.299 |
| WBC | 1.156 | 0.995–1.343 | 0.059 | |||
| Neutrophil | 1.008 | 0.950–1.069 | 0.793 | |||
| Monocyte | 8.935 | 1.755–45.479 | 0.008 | 5.556 | 0.291–105.969 | 0.254 |
| Lymphocyte | 0.949 | 0.776–1.159 | 0.606 | |||
| RBC | 0.280 | 0.155–0.508 | <0.001 | 1.017 | 0.115–8.982 | 0.988 |
| HB | 0.950 | 0.930–0.970 | <0.001 | 0.961 | 0.890–1.037 | 0.309 |
| RDW | 2.024 | 1.295–3.162 | 0.002 | 1.486 | 0.792–2.791 | 0.218 |
| NLR | 1.056 | 0.937–1.189 | 0.372 | |||
| PLR | 1.005 | 1.000–1.011 | 0.050 | |||
| IL-4 | 2.218 | 0.701–14.778 | 0.133 | |||
| IL-6 | 1.026 | 0.999–1.054 | 0.055 | |||
| IL-17A | 1.110 | 1.028–1.197 | 0.007 | 1.218 | 1.059–1.402 | 0.006 |
| IFN-γ | 1.013 | 1.002–1.024 | 0.025 | 0.990 | 0.975–1.006 | 0.225 |
| TNF-α | 0.988 | 0.970–1.007 | 0.225 | |||
| TB | 0.920 | 0.853–0.991 | 0.028 | 1.025 | 0.917–1.146 | 0.658 |
| ALB | 0.852 | 0.785–0.924 | <0.001 | 0.977 | 0.853–1.118 | 0.731 |
| TG | 0.918 | 0.738–1.141 | 0.441 | |||
| TC | 0.783 | 0.586–1.047 | 0.099 | |||
| HDL-C | 0.500 | 0.153–1.632 | 0.251 | |||
| LDL-C | 0.718 | 0.500–1.030 | 0.072 | |||
| I-309 | 1.141 | 1.076–1.210 | <0.001 | 1.113 | 1.014–1.221 | 0.024 |
DKD, diabetic kidney disease; T2DM, type 2 diabetes mellitus; OR, odds ratio; CI, confidence interval; BMI, body mass index; CAD, coronary artery disease; PN, peripheral neuropathy; PAD, peripheral artery disease; DR, diabetic retinopathy; DK, diabetic ketosis; HbA1c, hemoglobin A1c; CRP, C-reactive protein; WBC, white blood cell; RBC, red blood cell; HB, hemoglobin; RDW, RBC distribution width; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; IL, interleukin; IFN, interferon; TNF, tumor necrosis factor; TB, total bilirubin; ALB, albumin; TG, triglyceride; TC, total cholesterol; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein-cholesterol.
Discussion
The present study represents a comprehensive and in-depth attempt to investigate the relationship between serum levels of I-309 and various clinical/laboratory phenotypes in T2DM patients. We found that serum I-309 levels are markedly elevated in T2DM patients compared to healthy individuals, with a moderate diagnostic accuracy for T2DM (AUC of 0.735 in ROC analysis). Furthermore, through comprehensive univariate and multivariate analyses, we demonstrated that serum I-309 is independently associated with impaired renal function and increased risk of DKD progression, suggesting its potential as a biomarker and implicating its involvement in DKD progression among T2DM patients. In addition, we found no independent association between serum I-309 and other T2DM complications.
The significant elevation of serum I-309 in T2DM patients aligns with previous studies, implicating this chemokine in the pathogenesis of T2DM (11, 17). Unlike the prior study, which demonstrated that increased I-309 was associated with obesity among T2DM patients (11), the present study found no correlation of serum I-309 with BMI and blood fat. These inconsistencies might be explained by demographic divergences between the recruited population and the relatively small sample size, which may limit statistical power. Therefore, further in-depth investigation is warranted to clarify the interplay between I-309, obesity, and metabolic dysregulation under T2DM conditions.
In the current study, while the univariate analysis revealed significant associations between serum I-309 and multiple macrovascular and microvascular complications, as well as metabolic parameters (e.g., fasting blood glucose, albumin, bilirubin) and inflammatory markers (e.g., CRP, NLR, PLR, IL-6), the multivariate analysis demonstrated that only renal dysfunction, DKD, and serum IFN-γ levels remained independently associated with I-309. These findings delineate a specific pathological axis in T2DM, where I-309 emerges as a renal-selective mediator interacting with Th1-type inflammatory responses, while its broader systemic correlations appear mediated through confounding metabolic derangements. Our study extended the findings of Lu et al. (12), who initially demonstrated through small-scale univariate analysis that plasma I-309 concentrations were significantly elevated in T2DM patients with DKD compared to those without this renal complication.
The mechanistic contributions of I-309 to T2DM and its progression to DKD remain incompletely understood. Prior research has implicated the I-309/CCR8 axis in type 1 diabetes pathogenesis, specifically through CCR8+ monocyte-macrophage recruitment by pathogenic Th1 cells via CCL1 secretion, leading to pancreatic β-cell damage (17). The role of this chemokine in T2DM pathophysiology demands systematic investigation. Notably, while the univariate analysis demonstrated a significant association between serum IFN-γ and type 2 DKD, consistent with prior findings (18, 19, 20) in which the multivariate analysis was not performed, this association became non-significant upon multivariate adjustment for confounders. This analytical dissociation suggests that I-309 may exert more direct and pathophysiologically predominant effects compared to IFN-γ in DKD progression, potentially through CCR8-mediated macrophage activation pathways rather than secondary Th1-mediated inflammatory cascades.
Previous studies have suggested the possible pathogenic role of Th17 cells in DKD (18, 21, 22). Our current data indicated that serum IL-17A is independently associated with increased DKD risk in T2DM patients. Of note, no independent correlation between serum I-309 and IL-17A was observed in our study, revealing that during the pathogenesis of type 2 diabetes-related kidney disease, I-309 and IL-17A act through distinct pathways to participate in disease progression, with no significant reciprocal regulatory interaction between these two cytokines.
The limitations of this study need addressing. First, while our study establishes significant associations, its cross-sectional design precludes causal inferences between I-309 and β-cell dysfunction, or between I-309 and renal injury in T2DM, which warrants validation through prospective cohort studies and causal inference methodologies such as Mendelian randomization. Second, the detailed mechanisms by which I-309 interacts with IFN-γ and participates in T2DM and DKD pathogenic processes cannot be investigated in this study. Experimental models are needed to delineate the mechanistic role of I-309. Third, the AUC values of 0.735 and 0.722 demonstrate that serum I-309 exhibits moderate diagnostic accuracy for T2DM and DKD, respectively. Therefore, these findings warrant cautious interpretation and necessitate evidence-based conclusions. Nevertheless, our study represents the first systematic attempt to characterize the relationship between I-309 and both T2DM and DKD. The findings reveal robust associations, providing a valuable foundation for more in-depth exploration in this field.
In summary, serum I-309 emerges as a likely promising biomarker for T2DM, particularly in identifying T2DM-related DKD rather than other complications. Its integration into clinical practice could enhance early intervention strategies, while its pathophysiological role warrants exploration as a therapeutic target for T2DM and DKD.
Declaration of interest
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the work reported.
Funding
This study was supported by the Medical Health Science and Technology Project of Zhejiang Provincial Health Commission (2024KY532), Key Project of Science and Technology Co-construction in National Traditional Chinese Medicine Comprehensive Reform Demonstration Zone (GZY-KJS-ZJ-2025-097), and the Joint Funds of the Zhejiang Provincial Natural Science Foundation of China under Grant No. LKLZ25H030001.
Ethics statement
The study was approved by the institutional ethics committee of Taizhou First People’s Hospital (Number: 2021-KY004-01). Given residual samples used and few harm risks in the present study, informed consent exemptions or broad informed consent obtained from the subjects were also approved by the ethics committee.
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