Neutrophil-to-lymphocyte ratio associated with renal function in type 2 diabetic patients

Abstract

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a leading risk factor for the development and progression of chronic kidney disease (CKD). However, an accurate and convenient marker for early detection and appropriate management of CKD in individuals with T2DM is limited. Recent studies have demonstrated a strong correlation between the neutrophil-to-lymphocyte ratio (NLR) and CKD. Nonetheless, the predictive value of NLR for renal damage in type 2 diabetic patients remains understudied.

AIM

To investigate the relationship between NLR and renal function in T2DM patients.

METHODS

This study included 1040 adults aged 65 or older with T2DM from Shanghai's Community Health Service Center. The total number of neutrophils and lymphocytes was detected, and NLR levels were calculated. CKD was defined as an estimated glomerular filtration rate ≤ 60 mL/min/1.73 m². Participants were divided into four groups based on NLR levels. The clinical data and biochemical characteristics were compared among groups. A multivariate logistic regression model was used to analyze the association between NLR levels and CKD.

RESULTS

Significant differences were found in terms of sex, serum creatinine, blood urea nitrogen, total cholesterol, and low-density lipoprotein cholesterol among patients with T2DM in different NLR groups (P < 0.0007). T2DM patients in the highest NLR quartile had a higher prevalence of CKD (P for trend = 0.0011). Multivariate logistic regression analysis indicated that a high NLR was an independent risk factor for CKD in T2DM patients even after adjustment for important clinical and pathological parameters (P = 0.0001, odds ratio = 1.41, 95% confidence intervals: 1.18-1.68).

CONCLUSION

An elevated NLR in patients with T2DM is associated with higher prevalence of CKD, suggesting that it could be a marker for the detection and evaluation of diabetic kidney disease.

Key Words: Type 2 diabetes mellitus, Neutrophil-to-lymphocyte ratio, Chronic kidney disease, Logistic regression, Diabetes mellitus

Core Tip: In elderly type 2 diabetes mellitus (T2DM) patients, elevated neutrophil-to-lymphocyte ratio (NLR) is strongly linked to an increased risk of chronic kidney disease (CKD), uncovering NLR as a potential independent biomarker for early detection of renal damage. This finding holds significant promise for addressing the current challenge of delayed CKD diagnosis in T2DM, signifying the potential utility of NLR as a convenient and sensitive detection method for identifying CKD in diabetic patients.

INTRODUCTION

Diabetes is a prevalent metabolic disease with significant implications for global health, and type 2 diabetes mellitus (T2DM) represents the predominant form of diabetes in China, accounting for over 90% of cases[1]. T2DM is one of the leading risk factors for the development and progression of chronic kidney disease (CKD)[2]. In Asia, it is estimated that > 60% of patients with diabetes will develop kidney complications, compared with 30%-40% in Europeans despite having a similar duration of diabetes[3,4]. Furthermore, CKD in diabetic individuals is associated with increased morbidity and premature mortality, which impose a substantial economic burden on healthcare systems[5,6]. Given the continuous increase in the number of people with diabetes, early detection and appropriate management of CKD in individuals with T2DM are crucial to prevent or delay the progression of kidney disease. However, since CKD is a complex multifactorial disease and the pathogenesis of the disease remains unclear, along with limited access to medical resources and the high cost of testing in some regions, patients are hindered from obtaining routine renal function screening and timely diagnosis. Therefore, the identification of an accurate and convenient marker for promptly detecting and assessing kidney function is essential to improve patient outcomes.

Recent studies have shown that the neutrophil-to-lymphocyte ratio (NLR), an inflammatory marker, strongly correlates with acute ischemic stroke, tumors, sepsis, and CKD[7-10]. However, prior research has mostly examined hospitalized patients with more severe conditions, overlooking diabetic patients in the general population. This article mainly explored the relationship between NLR and renal function in patients with T2DM, aiming to establish a theoretical framework for evaluating the predictive value of NLR in the early detection of renal damage in T2DM patients.

MATERIALS AND METHODS

Population

This study involved 1040 adults aged 65 years old or above diagnosed with T2DM from the health examination platform of the Community Health Service Center in Songnan Town, Baoshan District, Shanghai, China from June to August 2021. The investigation focused on three medical service stations located in the community health service center and affiliated institutes of Songnan Town. The diagnosis of T2DM was in accordance with Chinese guidelines for the prevention and treatment of T2DM (2020 edition)[11], namely, a fasting plasma glucose (FPG) level ≥ 7.0 mmol/L or a previous diagnosis of T2DM and currently receiving oral medication. Participants were excluded if they had incomplete or uncertain basic information, type 1 DM, a history of hormone therapy within a year, any type of malignancy, a current acute infection, or an established hematologic disease. Oral consent was obtained from all participants, and the study was approved by the central ethics committee.

Implant procedure

Demographics (sex and age) and disease history, such as hypertension, were self-reported by all participants through comprehensive questionnaires completed by trained general practitioners and volunteers. Height and weight were measured using an electronic height scale, and body mass index (BMI) was calculated as the weight in kilograms divided by the height in meters squared. Waist and hip circumferences were measured using a soft skin caliper, and blood pressure was measured using an Omron sphygmomanometer (HBP-1120u).

For laboratory testing, the participants’ whole blood was drawn into an EDTA vacuum anticoagulant tube and mixed by inversion several times. Additionally, 6 mL of fasting venous blood was obtained in the early morning, and the supernatant was collected after centrifugation. FPG, serum creatinine (Scr), blood urea nitrogen (BUN), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels were detected using an automatic biochemical analyzer (Hitachi 7080). The total number of neutrophils and lymphocytes were detected using a Mairui 5100 automatic hematology analyzer, and NLR levels were calculated. All blood samples were collected by the Department of Laboratory Medicine in the Community Health Service Center, Songnan Town, Baoshan District, Shanghai, China. The laboratory received quality control from the standardized protocol for blood biochemical testing from the Shanghai Centers for Disease Control and Prevention.

Outcome definition

The estimated glomerular filtration rate (eGFR), expressed in ml/min/1.73 m², was calculated with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation on the basis of Scr[12]. The formula was as follows: (1) if female: Scr ≤ 0.7 mg/dL, eGFR = 144 × (Scr/0.7)^-0.329 × (0.993)^age; Scr > 0.7 mg/dL, eGFR = 144 × (Scr/0.7)^-1.209 × (0.993)^age; and (2) if male: Scr ≤ 0.9 mg/dL, eGFR = 141 × (Scr/0.9)^-0.411 × (0.993)^age; Scr > 0.9 mg/dL, eGFR = 141 × (Scr/0.9)^-1.209 × (0.993)^age. CKD was defined as an eGFR of 60 mL/min/1.73 m² or less[13].

Other definitions

(1) Hypertension was defined according to the Chinese guidelines for the prevention and treatment of hypertension (2018 Revision)[14], with systolic blood pressure (SBP) ≥ 140 mmHg and/or diastolic blood pressure (DBP) ≥ 90 mmHg, or with a previous diagnosis of hypertension and currently being treated with oral antihypertensive drugs; (2) Smoking referred to those who smoked ≥ 1 cigarette per day on average, continuously or cumulatively for the past 6 months; (3) Drinking was defined as consuming alcohol at least once a week at a dose of ≥ 50 g of ethanol per occasion, continuously or cumulatively over the past 6 months; and (4) Regular exercise referred to participation in physical activity at least 5 d per week, cumulatively for ≥ 30 min per day, for 6 consecutive months or more.

Statistical analysis

Continuous variables were expressed as the mean ± SD or median with interquartile range and were analyzed by an independent Student’s t test or one-way analysis of variance test for normally and nonnormally distributed variables (the Kolmogorov–Smirnov test). Categorical data were analyzed using the chi-square test and are presented as frequencies (percentages). The NLR level was analyzed as a continuous variable and divided by quartiles. Multivariate logistic regression analyses were conducted to assess the independent association between NLR and diabetic kidney disease (DKD). After adjusting for age, sex, BMI, FPG, TG, LDL-C, and lifestyle factors, odds ratios (ORs) with 95% confidence intervals (CIs) were reported. The predictive value of NLR for renal dysfunction in different eGFR groups was tested by the area under the receiver operating characteristic curve (AUROC), and the optimal cutoff point of the NLR was obtained by calculating the Youden index. The Youden index is a method of evaluating the authenticity of a screening test, which represents the total ability of the screening method to detect true patients and nonpatients. A higher index is associated with a better effect and greater authenticity of the screening test. The NLR that corresponded to the maximum Youden index was then determined to be the optimal cutoff NLR in this study.

All statistical analyses were performed using SAS software (version 9.4). A two-tailed P value < 0.05 was considered statistically significant.

RESULTS

Implant data

Table 1 shows the general characteristics of the study population. A total of 1040 participants diagnosed with T2DM were included in the analysis and divided into four groups according to their NLR: quartile 1 (NLR < 1.38, 261 patients), quartile 2 (1.38 ≤ NLR < 1.76, 258 patients), quartile 3 (1.76 ≤ NLR < 2.30, 262 patients), and quartile 4 (NLR ≥ 2.30, 259 patients). No significant difference was observed among the groups concerning age, BMI, SBP, DBP, FPG, TG, platelet counts, smoking, drinking, regular exercise, and hypertension (Table 1). However, significant differences were found in terms of sex, BUN, Scr, eGFR, TC, LDL-C, HDL-C, neutrophil, lymphocyte and white blood cell (WBC) counts among the four groups (P < 0.05).

Table 1 Characteristics of all type 2 diabetes mellitus patients categorized by the neutrophil-to-lymphocyte ratio quartiles.

Variables	Total	Quartile 1 (NLR < 1.38)	Quartile 2 (1.38 ≤ NLR < 1.76)	Quartile 3 (1.76 ≤ NLR < 2.30)	Quartile 4 (NLR ≥ 2.30)
N	1040	261	258	262	259
Male1, n (%)	490 (47.1)	99 (37.9)	119 (46.1)	130 (49.6)	142 (54.8)
Age (yr)	71.9 ± 5.5	71.5 ± 5.5	72.0 ± 5.7	71.9 ± 5.4	72.3 ± 5.5
BMI (kg/m2)	25.0 ± 4.0	25.1 ± 3.6	25.3 ± 4.6	25.1 ± 3.7	24.7 ± 4.2
SBP (mmHg)	145.3 ± 20.3	144.8 ± 19.7	144.4 ± 19.4	146.5 ± 20.2	145.3 ± 22.0
DBP (mmHg)	78.7 ± 11.7	77.8 ± 11.5	79.0 ± 10.8	78.9 ± 11.0	79.2 ± 13.5
FPG (mmol/L)	7.8 ± 2.4	7.6 ± 1.8	8.0 ± 2.8	7.8 ± 2.4	8.0 ± 2.3
BUN1 (mmol/L)	6.8 ± 2.1	6.4 ± 1.6	6.9 ± 2.2	6.6 ± 2.0	7.1 ± 2.3
Scr1 (mmol/L)	74.1 ± 21.8	68.2 ± 16.1	73.1 ± 19.4	75.3 ± 22.1	79.8 ± 26.8
eGFR1 (mL/min/1.73 m2)	80.2 ± 15.7	83.6 ± 12.9	80.7 ± 15.0	79.3 ± 16.0	77.7 ± 17.0
TC1 (mmol/L)	4.7 ± 1.2	5.0 ± 1.2	4.8 ± 1.3	4.7 ± 1.1	4.6 ± 1.1
TG (mmol/L)	1.7 ± 1.5	1.6 ± 1.2	1.8 ± 2.0	1.7 ± 1.5	1.5 ± 1.1
LDL-C1 (mmol/L)	3.0 ± 0.9	3.2 ± 1.0	3.0 ± 1.0	2.9 ± 0.9	2.9 ± 0.9
HDL-C1 (mmol/L)	1.5 ± 0.4	1.5 ± 0.3	1.4 ± 0.3	1.5 ± 0.4	1.5 ± 0.4
Neutrophil1	3.7 ± 1.0	2.9 ± 0.7	3.5 ± 0.8	3.9 ± 0.9	4.5 ± 1.0
Lymphocyte1	2.1 ± 0.6	2.6 ± 0.7	2.2 ± 0.5	1.9 ± 0.4	1.5 ± 0.4
WBC1	6.3 ± 1.4	6.1 ± 1.3	6.3 ± 1.4	6.3 ± 1.4	6.5 ± 1.4
Platelet	189.1 ± 48.5	187.6 ± 46.3	191.7 ± 46.2	191.2 ± 52.0	185.8 ± 49.4
Smoking, n (%)	174 (16.7)	36 (13.8)	48 (18.6)	47 (17.9)	43 (16.6)
Drinking, n (%)	179 (17.2)	36 (13.8)	54 (20.9)	48 (18.3)	41 (15.8)
Regular exercise, n (%)	197 (18.9)	53 (20.3)	52 (20.2)	51 (19.5)	41 (15.8)
Hypertension, n (%)	714 (68.7)	171 (65.5)	182 (70.5)	187 (71.4)	174 (67.2)

¹Means a significant difference (P < 0.05) between four neutrophil-to-lymphocyte ratio quartile groups for corresponding variable.

NLR: Neutrophil-to-lymphocyte ratio; BMI: Body mass index; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; FPG: Fasting plasma glucose; BUN: Blood urea nitrogen; Scr: Serum creatinine; TC: Total cholesterol; TG: Triglyceride; LDL-C: Low-density lipoprotein cholesterol; HDL-C: High-density lipoprotein cholesterol.

Using the definition of CKD, there were 132 cases in total. As shown in Figure 1, patients in the higher NLR quartile group had a greater prevalence of CKD (P for trend = 0.0011).

Figure 1 Comparison of chronic kidney disease prevalence in different neutrophil-to-lymphocyte ratio quartiles. The numbers above the bars and in brackets represent the cases and corresponding proportions of chronic kidney diseases in each neutrophil-to-lymphocyte ratio quartile group. CKD: Chronic kidney diseases.

Association between NLR and CKD in T2DM patients

As shown in Table 2, we found that high NLR was associated with a higher prevalence of CKD in T2DM patients in multivariate regression models even after adjustment for important clinical parameters, including age, sex, smoking, drinking, regular exercise, BMI, SBP, FPG, TG and LDL-C (P value < 0.0001). With an SD increase in the NLR, the prevalence of CKD increased by 44%. Furthermore, when NLR was categorized into quartiles, the association between NLR and CKD remained, and there was a 3.3-fold increased prevalence of CKD in T2DM patients in the highest quartile of NLR (OR 3.30, 95%CI: 1.78-6.12, P = 0.0001) compared to those in the lowest quartile. AUROC was analyzed to determine the predictive value of the NLR for the risk stratification of renal dysfunction. As shown in Figure 2, compared with the higher eGFR group (< 90 mL/min/1.73 m² and < 60 mL/min/1.73 m²), the NLR had the highest AUROC (0.902) when eGFR was < 30 mL/min/1.73 m² (P = 0.005, 95%CI: 0.840-0. 959). The AUROC for eGFR < 90 mL/min/1.73 m² and eGFR < 60 mL/min/1.73 m² was 0.553 (P = 0.019, 95%CI: 0.515-0.591) and 0.606 (P = 0.026, 95%CI: 0.556-0.657), respectively (Figure 2). The cutoff values (sensitivity and specificity) for different eGFR groups (< 90 mL/min/1.73 m², < 60 mL/min/1.73 m², and < 30 mL/min/1.73 m²) were 1.525 (69.1%, 40.9%), 1.605 (78.8%, 41.0%) and 2.525 (approximately 100%, 81.1%), respectively.

Figure 2 Predictive value of neutrophil-to-lymphocyte ratio for estimated glomerular filtration rate decline. ROC: Receiver operating characteristic curve; AUC: Area under the curve; eGFR: Estimated glomerular filtration rate.

Table 2 Association between neutrophil-to-lymphocyte ratio and chronic kidney disease in type 2 diabetic patients.

Exposure	Age-and-sex adjusted model		Multivariate model
	OR (95%CI)	P value	OR (95%CI)	P value
NLR (per SD)	1.39 (1.17-1.65)	0.0002	1.44 (1.21-1.72)	< 0.0001
Quartile 1 (< 1.38)	Reference		Reference
Quartile 2 (1.38–1.76)	1.69 (0.89-3.22)	0.1100	1.57 (0.81-3.04)	0.1785
Quartile 3 (1.76–2.30)	2.42 (1.30-4.50)	0.0052	2.52 (1.35-4.73)	0.0039
Quartile 4 (≥ 2.30)	3.07 (1.68-5.62)	0.0003	3.30 (1.78-6.12)	0.0001
P for trend		0.0001		< 0.0001

SD = 0.76; P values were calculated from univariate or multivariate regression tests, and the bold typeface indicates significance (P < 0.05). The multivariate model was further adjusted for age, sex, smoking, drinking, regular exercise, body mass index, systolic blood pressure, fasting plasma glucose, triglyceride, and low-density lipoprotein cholesterol. OR: Odds ratio; CI: Confidence interval; SD: Standard deviation; NLR: Neutrophil-to-lymphocyte ratio.

DISCUSSION

In this cross-sectional study comprising 1040 patients diagnosed with T2DM, we observed that higher NLR was significantly associated with an increased prevalence of CKD, even after adjusting for various confounding factors. These findings shed light on the possibility of utilizing NLR as a promising clinical marker, facilitating early detection and subsequent management of CKD among patients with T2DM.

CKD is a common and severe complication in individuals with diabetes, although its precise pathogenesis remains poorly understood. It is recognized that a sequence of pathological events, including parenchymal cell loss, chronic inflammation, renal fibrosis, and reduced regenerative capacity of the kidney, can contribute to the development and progression of CKD[15]. Metabolic disorders in diabetic patients activate inflammatory signals within the body, and elevated levels of inflammatory factors contribute to kidney injury[16]. Chronic inflammation has been implicated in the development of complications associated with T2DM, and various inflammatory molecules, such as adipokines, chemokines, adhesion molecules, and cytokines, have been identified as contributors to CKD development[17]. However, several of these markers, such as C-reactive protein, interleukin-6, and tumor necrosis factor-α, are expensive and not routinely measured in clinical practice.

NLR has recently emerged as a discerning inflammatory indicator that provides insights into the equilibrium between neutrophils and lymphocytes, two critical constituents of the immune system. While neutrophils function as nonspecific instigators of inflammation, lymphocytes play regulatory and protective roles in the context of inflammatory responses[18]. NLR has garnered recognition as a reliable metric for gauging the extent of systemic inflammation[19,20]. Previous studies have shown a positive association between NLR and well-established inflammation markers, such as interleukin-6 and C-reactive protein[21,22]. Notably, in comparison to other inflammatory markers, the NLR exhibits advantages in terms of stability, cost-effectiveness, and accessibility[23].

Growing evidence substantiates the connection between elevated NLR and progression and prognosis of CKD[24-28]. Although DKD is the most common cause of CKD, the relationship between NLR and CKD in T2DM patients is still relatively understudied[29]. Notably, a previous study showed a positive correlation between neutrophil levels and urinary albumin excretion in individuals with T2DM, while lymphocyte levels displayed a negative correlation[30]. Similarly, a hospital-based investigation involving 655 adult patients with T2DM elucidated the independent association of NLR with the risk of developing DKD[31]. Additionally, a cross-sectional survey conducted in seven communities in China involving 4813 diabetic adults revealed a positive relationship between a higher NLR and a higher prevalence of DKD[32]. Furthermore, elevated NLR not only manifested as a risk factor for DKD but also served as a prognostic indicator for early detection of DKD[33]. In a small case-control study, significant differences were observed in NLR among different groups of T2DM patients based on their albuminuria status[34]. A meta-analysis that included 48 studies demonstrated higher NLR values in patients with DKD than in those without DKD[35]. Last but not least, a longitudinal 3-year follow-up study underscored the potential of NLR as a robust predictor of deteriorating renal function in individuals with diabetes[36].

Limits of the study

Our study adds to the literature by providing compelling evidence of a significant association between NLR and CKD prevalence in patients with T2DM. However, it should be noted that this study had some limitations. First, as a cross-sectional study, a causal relationship between NLR and CKD could not be established. Second, the small sample might have introduced selection bias. Third, due to data constraints, our study population was not assessed for urine albumin and CRP, consequently relying on eGFR to evaluate kidney function and WBC counts to assess inflammatory markers as a control for NLR. Last, as this study was conducted at a single center and only included patients aged 65 years and older, the generalizability of our findings to other settings may be limited. Therefore, future investigations should consider larger sample sizes and adopt prospective study designs to further explore this association.

CONCLUSION

Our findings revealed a significant association between elevated NLR levels and reduced eGFR, as well as a higher prevalence of CKD in Chinese adults with T2DM. These results suggest that NLR has potential as a valuable biomarker for early detection of kidney damage in diabetes patients. However, it is crucial to emphasize the need for further research to validate these findings and elucidate the potential causal relationship between NLR and CKD.

ACKNOWLEDGEMENTS

The authors thank all team members and participants in the Community Health Service Center of Songnan Town, Baoshan District, Shanghai, China.