Zhang YL, Peng GL, Leng WL, Lian Y, Cheng LQ, Li X, Wang YL, Zhou L, Long M. Association between serum retinol-binding protein and lower limb atherosclerosis risk in type 2 diabetes mellitus. World J Diabetes 2025; 16(3): 98590 [DOI: 10.4239/wjd.v16.i3.98590]
Corresponding Author of This Article
Min Long, Associate Chief Physician, Associate Professor, Department of Endocrinology, Southwest Hospital, Army Medical University (The Third Military Medical University), No. 30 Gaotanyan Main Street, Shapingba District, Chongqing 400038, China. longmin@tmmu.edu.cn
Research Domain of This Article
Endocrinology & Metabolism
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Yu-Ling Zhang, Gui-Liang Peng, Wei-Ling Leng, Li-Qing Cheng, Yu-Lin Wang, Ling Zhou, Min Long, Department of Endocrinology, Southwest Hospital, Army Medical University (The Third Military Medical University), Chongqing 400038, China
Yu-Ling Zhang, Yu Lian, Li-Qing Cheng, Department of Endocrinology, Southwest Hospital Jiangbei Area (The 958th Hospital of Chinese People’s Liberation Army), Chongqing 400000, China
Xing Li, Department of Endocrinology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210093, Jiangsu Province, China
Xing Li, Department of Endocrinology, Jinling Hospital, Nanjing Medical University, Nanjing 210093, Jiangsu Province, China
Xing Li, Department of Endocrinology, Jinling Hospital, School of Medicine, Southeast University, Nanjing 210093, Jiangsu Province, China
Co-first authors: Yu-Ling Zhang and Gui-Liang Peng.
Author contributions: Zhang YL and Peng GL performed study concept and design and data analysis, and they contributed equally to this work as co-first authors; Zhou L, Lian Y, Cheng LQ, and Wang YL performed data collection; Leng WL performed data verification; Long M and Li X revised the manuscript and make final approval of the version; and all authors read and approved the final version of manuscript.
Supported by Chongqing Young and Middle-aged Medical High-end Talents Project; Chongqing Young and Middle-aged Medical High-end Talents Studio Project; and Southwest Outstanding Youth and Talents Project.
Institutional review board statement: The study was approved by the ethics committee of Southwest Hospital, the First Affiliated Hospital of Army Medical University of Chinese People's Liberation Army (No. KY2024007).
Informed consent statement: Given the retrospective nature of this study and the anonymity of participant data, the institutional reviewer waived the requirement for informed consent.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The data underlying this article will be shared on reasonable request to the corresponding author.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Min Long, Associate Chief Physician, Associate Professor, Department of Endocrinology, Southwest Hospital, Army Medical University (The Third Military Medical University), No. 30 Gaotanyan Main Street, Shapingba District, Chongqing 400038, China. longmin@tmmu.edu.cn
Received: June 30, 2024 Revised: November 13, 2024 Accepted: December 30, 2024 Published online: March 15, 2025 Processing time: 205 Days and 1.9 Hours
Abstract
BACKGROUND
Serum retinol-binding protein (RBP) is the primary transport protein of circulating vitamin A. RBP has a crucial role in maintaining nutrient metabolism and physiologic homeostasis. Several studies have indicated that serum RBP participates in the progression of diabetes and diabetes-related complications. However, the impact of serum RBP on lower limb atherosclerosis has not been determined in individuals with type 2 diabetes mellitus (T2DM).
AIM
To determine the association between serum RBP and lower limb atherosclerosis in individuals with T2DM.
METHODS
This retrospective study enrolled 4428 eligible T2DM patients and divided the patients into non-lower limb atherosclerosis (n = 1913) and lower limb atherosclerosis groups (n = 2515) based on lower limb arterial ultrasonography results. At hospital admission, baseline serum RBP levels were assessed, and all subjects were categorized into three groups (Q1-Q3) based on RBP tertiles. Logistic regression, restricted cubic spline regression, subgroup analysis, and machine learning were used to assess the association between RBP levels and lower limb atherosclerosis risk.
RESULTS
Among 4428 individuals with T2DM, 2515 (56.80%) had lower limb atherosclerosis. Logistic analysis showed that lower limb atherosclerosis risk increased by 1% for every 1 unit rise in serum RBP level (odds ratio = 1.01, 95% confidence interval: 1.00-1.02, P = 0.004). Patients in the highest tertile group (Q3) had a higher lower limb atherosclerosis risk compared to the lowest tertile group (Q1) (odds ratio = 1.36, 95% confidence interval: 1.12-1.67, P = 0.002). The lower limb atherosclerosis risk gradually increased with an increase in RBP tertile (P for trend = 0.005). Restricted cubic spline analysis indicated a linear correlation between serum RBP levels and lower limb atherosclerosis risk (non-linear P < 0.05). Machine learning demonstrated the significance and diagnostic value of serum RBP in predicting lower limb atherosclerosis risk.
CONCLUSION
Elevated serum RBP levels correlate with an increased lower limb atherosclerosis risk in individuals with T2DM.
Core Tip: This cross-sectional study determined the association between the serum retinol-binding protein (RBP) level and lower limb atherosclerosis risk in individuals with type 2 diabetes mellitus (T2DM). The lower limb atherosclerosis risk increased with each unit increase in serum RBP level. Individuals with T2DM in the highest tertile group (Q3) had a higher lower limb atherosclerosis risk compared to the lowest tertile group (Q1) and there was a linear association between the serum RBP level and the lower limb atherosclerosis risk in T2DM. Therefore, clinical attention should be focused on the serum RBP level in T2DM patients.
Citation: Zhang YL, Peng GL, Leng WL, Lian Y, Cheng LQ, Li X, Wang YL, Zhou L, Long M. Association between serum retinol-binding protein and lower limb atherosclerosis risk in type 2 diabetes mellitus. World J Diabetes 2025; 16(3): 98590
With the improvement in living standards and changes in dietary patterns, the incidence of type 2 diabetes mellitus (T2DM) is increasing significantly worldwide[1,2]. T2DM is characterized by persistent hyperglycemia, which can impair vascular endothelial function and result in dyslipidemia, thereby increasing the risk of various microvascular and macrovascular complications[3]. Peripheral artery disease (PAD), as an important vascular complication, has high morbidity and mortality rates[4,5]. PAD is common in DM[6], and PAD risk is 2-4 times greater in DM patients compared to individuals without diabetes[7]. T2DM patients with PAD tend to progress rapidly, leading to a higher amputation and major adverse cardiovascular events risk[6,8]. Lower limb PAD is usually caused by atherosclerotic plaque deposition in the lower limb vasculature, which leads to occlusion of the lower limb vessels and further increases the risk of foot ulcers, gangrene, and amputation[6,9,10]. Therefore, the formation of atherosclerosis is a crucial factor leading to PAD in the lower limbs. At present, ultrasonography and angiography are the main methods by which to identify lower limb atherosclerosis when atherosclerotic plaque is formed[11]. Currently, there are no specific biomarkers for lower limb atherosclerosis in T2DM patients. Therefore, exploring the factors that influence lower limb atherosclerosis in T2DM could facilitate early identification and intervention to prevent and slow the progression of lower limb atherosclerosis, perhaps delaying the progression of PAD and reducing the risk of severe clinical outcomes.
Serum retinol-binding protein 4 (RBP4), previously known as RBP[12,13], a specific transport protein, is primarily synthesized by the liver[14]. The main function of RBP4 is to transport retinol (vitamin A) in the circulation from the liver to target tissues to exert physiologic effects[15]. Currently, circulating RBP4 has been proven to be a powerful biomarker for the early detection of renal tubular dysfunction and assessing early hepatic impairment[16]. Additionally, RBP4 has been reported as a novel adipokine[17]. Several clinical studies have identified a significant association of elevated circulating RBP4 levels with a range of metabolic disorders, which include T2DM, insulin resistance, obesity, and metabolic syndrome[18-22], suggesting that circulating RBP4 may serve as a potentially important biomarker in metabolic disease progression.
Recently, the association between circulating RBP4 and atherosclerosis has gradually been acknowledged. Exogenous recombinant RBP4 treatment and overexpression of the RBP4 gene have been shown in animal studies to contribute to atherosclerosis through macrophage-derived foam cell formation[23]. Moreover, elevated RBP4 levels may be linked to atherosclerosis in diabetic rats[24]. Several cross-sectional studies indicated a positive association between circulating RBP4 levels and atherosclerosis formation in obese patients with rheumatoid arthritis[25] and in patients with T2DM[26]. However, an association between the serum RBP level and atherosclerosis in the lower limb has not been established in T2DM patients. We hypothesized that elevated serum RBP levels maybe increase lower limb atherosclerosis risk in T2DM. Therefore, this study primarily investigated the association between the serum RBP level and lower limb atherosclerosis in T2DM patients to offer a reference for understanding the pathogenesis, diagnosis, and treatment of this condition.
MATERIALS AND METHODS
Study population
This retrospective study included individuals with T2DM diagnosed based on American Diabetes Association (2020) criteria[1] who were treated in the Department of Endocrinology of Southwest Hospital from September 2018 to September 2022. The exclusion criteria were: (1) Individuals < 18 years old; (2) Pregnancy; (3) Acute diabetes complications at the time of hospitalization; (4) Use of vitamin A drugs and rosiglitazone within 6 months; (5) Patients who were previously diagnosed with cancer, severe infection, severe heart failure, or severe liver insufficiency, and those who had undergone major surgery or had major trauma; (6) Patients undergoing dialysis; and (7) Incomplete clinical data. A total of 4428 T2DM patients were enrolled based on the above criteria, including 1913 without lower limb atherosclerosis and 2515 with lower limb atherosclerosis. This study received authorization from the ethics committee of Southwest Hospital, the First Affiliated Hospital of Army Medical University of Chinese People’s Liberation Army (No. KY2024007). Due to patient concealment, informed consent was exempted.
Clinical data collection
Baseline clinical data were taken from the hospital medical record system, which consisted of age, gender, height, weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), co-morbidities [hypertension, hyperlipidemia, and coronary heart disease (CHD)], and cigarette smoking and alcohol consumption histories. Body mass index (BMI) is equal to weight (kg) divided by height (m) squared. The following laboratory biochemical indicators were measured: Glycated hemoglobin (HbA1c); fasting blood glucose (FBG); white blood cell (WBC) count; C-reactive protein (CRP); lipid profile, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein-cholesterol (HDL-C), and low-density lipoprotein-cholesterol (LDL-C); alanine aminotransferase (ALT) and aspartate aminotransferase; uric acid (UA); RBP; and estimated glomerular filtration rate (eGFR). The blood sample was obtained in the morning after fasting for at least 8 hours. Detailed detection instruments and methods for all biochemical indicators are provided in Supplementary Table 1.
Lower limb arterial ultrasound examination
All participants with stable respirations were positioned supine and underwent ultrasound evaluation of the lower limb arteries using high-resolution ultrasound equipment (Philips EPIQ5, Philips, United States) performed by ultrasound-certified physicians. The evaluation included the bilateral common femoral, superficial femoral, deep femoral, popliteal, anterior tibial, posterior tibial, and dorsalis pedis arteries. Lower limb atherosclerosis was characterized by the formation of plaques.
Feature selection
Machine learning algorithms for feature selection were used to determine the association of the RBP levels with lower limb atherosclerosis risk in T2DM. A random forest algorithm was utilized to construct an interpretable machine learning model for predicting lower limb atherosclerosis risk in T2DM. Additionally, a Shapley Additive Explanations (SHAP) algorithm was employed to evaluate feature importance, elucidate and visualize the average contribution of each feature to the predicted outcome, and represent the relative importance numerically. All procedures were implemented using scikit-learn (version 0.24.2), SHAP (version 0.40.0), and Python (version 3.11.5).
Statistical analysis
R-Studio software (version: 2023.09.1+494) was utilized for data statistics. The Shapiro-Wilk test was used to determine the continuous variable distribution. The results are presented as the mean ± SD when continuous variables conformed to a normal distribution, while a t-test was utilized for comparing differences between groups. Variables that did not follow a normal distribution are presented as the median and interquartile range. Group differences were assessed by the Mann-Whitney U test or the Kruskal-Wallis test. Categorical variables are displayed as absolute numbers (n) and proportions (%). Intergroup comparisons were calculated by the χ2-test. A small proportion of individual indicators in the raw analyzed data were missing (< 5% missing rate) and were imputed using the random forest imputation method in R-Studio software. The box plot method was used to identify RBP outliers effectively. Spearman correlation analysis was used to assess the correlation between RBP levels and various parameters in T2DM individuals. The relationship between the serum RBP level and lower limb atherosclerosis risk was assessed using multivariate logistic regression analysis, while the non-linear association between the RBP level and lower limb atherosclerosis risk was assessed via restricted cubic spline (RCS). Factors that may confound results, including age, cigarette smoking and alcohol consumption histories, SBP, DBP, gender, hypertension, hyperlipidemia, CHD, TC, TG, HDL-C, LDL-C, FBG, HbA1c, UA, CRP, WBC count, aspartate aminotransferase, ALT, and eGFR were adjusted. Statistically significant findings were identified with P values < 0.05.
RESULTS
Baseline characteristics
A total of 4428 eligible participants (60.77% males) were ultimately enrolled, with the median age being 56 years. Among them, 2515 had lower limb atherosclerosis. T2DM patients with lower limb atherosclerosis were older, had higher prevalence of hypertension, hyperlipidemia, and CHD, and had higher HbA1c, WBC, CRP, and FBG levels but lower HDL levels compared to non-lower limb atherosclerosis patients (Table 1).
Table 1 Baseline characteristics in the study participants.
Characteristic
Overall (n = 4428)
Non-lower limb atherosclerosis (n = 1913)
Lower limb atherosclerosis (n = 2515)
P value
RBP, mg/L
31.90 [26.15, 38.90]
30.96 [25.50, 36.95]
32.76 [26.80, 40.50]
< 0.001
Age, years
56.00 [48.00, 65.00]
50.00 [40.00, 58.00]
59.00 [52.00, 68.00]
< 0.001
Male, n (%)
2691 (60.77)
1051 (54.94)
1640 (65.21)
< 0.001
Cigarette smoking history, n (%)
1786 (40.33)
649 (33.93)
1137 (45.21)
< 0.001
Alcohol consumption history, n (%)
1722 (38.89)
671 (35.08)
1051 (41.79)
< 0.001
Hypertension, n (%)
2765 (62.44)
995 (52.01)
1770 (70.38)
< 0.001
Hyperlipidemia, n (%)
2521 (56.93)
1102 (57.61)
1419 (56.42)
0.449
CHD, n (%)
838 (18.93)
227 (11.87)
611 (24.29)
< 0.001
SBP, mmHg
129.00 [116.00, 143.00]
126.00 [114.00, 139.00]
132.00 [119.00, 145.00]
< 0.001
DBP, mmHg
80.50 [73.00, 89.00]
81.00 [73.00, 90.00]
80.00 [73.00, 89.00]
0.196
BMI, kg/m2
24.20 [21.80, 26.60]
24.20 [21.70, 26.90]
24.10 [21.90, 26.40]
0.132
HbA1c, %
8.40 [7.00, 10.30]
8.30 [6.80, 10.45]
8.50 [7.10, 10.20]
0.020
FBG, mmol/L
8.49 [6.56, 11.40]
8.29 [6.38, 11.59]
8.62 [6.70, 11.29]
0.054
TC, mmol/L
4.59 [3.87, 5.39]
4.62 [3.92, 5.34]
4.58 [3.82, 5.42]
0.67
LDL, mmol/L
2.86 [2.35, 3.41]
2.86 [2.37, 3.35]
2.87 [2.33, 3.46]
0.383
TG, mmol/L
1.56 [1.11, 2.35]
1.57 [1.10, 2.43]
1.56 [1.13, 2.27]
0.351
HDL, mmol/L
1.10 [0.92, 1.30]
1.11 [0.94, 1.32]
1.09 [0.92, 1.29]
0.004
WBC count, 109/L
6.30 [5.24, 7.64]
6.10 [5.10, 7.41]
6.46 [5.35, 7.86]
< 0.001
CRP, mg/L
2.93 [1.19, 11.58]
2.62 [1.08, 9.14]
3.20 [1.26, 14.24]
< 0.001
AST, IU/L
20.67 [17.00, 26.10]
21.10 [17.20, 27.40]
20.40 [16.85, 25.10]
< 0.001
ALT, IU/L
19.45 [14.10, 28.80]
20.90 [15.00, 32.75]
18.65 [13.70, 26.62]
< 0.001
UA, μmol/L
326.20 [265.00, 398.00]
326.00 [265.10, 396.00]
327.00 [264.00, 399.50]
0.850
eGFR, mL/minute/1.73 m2
97.66 [77.73, 113.18]
104.67 [88.91, 120.20]
91.16 [69.40, 107.07]
< 0.001
Serum RBP levels were markedly higher in the lower limb atherosclerosis group compared to the non-lower limb atherosclerosis group (Figure 1A). The trend was consistent after removing outliers (Supplementary Figure 1A). Furthermore, the patients were stratified into three groups (Q1: 4.30-28.24 mg/L, Q2: 28.25-36.30 mg/L, and Q3: 36.31-129.80 mg/L) based on serum RBP tertiles. As depicted in Table 2, participants in the higher RBP tertile had elevated SBP, DBP, BMI, TC, TG, LDL, WBC, and UA levels, and HbA1c, FBG, CRP, and eGFR levels were decreased compared to the lower RBP tertile group. Moreover, the incidence of hypertension, hyperlipidemia, and CHD was higher in the highest tertile of serum RBP group than the lowest tertile group. Additionally, the risk of lower limb atherosclerosis increased with escalating RBP tertiles (Figure 1B). This trend persisted even after removing RBP outliers (Supplementary Figure 1B).
Figure 1 Serum retinol-binding protein levels and retinol-binding protein tertile proportions in lower limb atherosclerosis and non-lower limb atherosclerosis patients with type 2 diabetes mellitus.
A: Comparison of serum retinol-binding protein levels in the non-lower limb atherosclerosis and lower limb atherosclerosis group type 2 diabetes mellitus patients; B: Percentage of type 2 diabetes mellitus patients with lower limb atherosclerosis in different serum retinol-binding protein tertiles. RBP: Retinol-binding protein.
Table 2 Baseline characteristics in the study participants based on serum retinol-binding protein tertiles.
Characteristic
Q1 (n = 1474)
Q2 (n = 1478)
Q3 (n = 1476)
P value
lower limb atherosclerosis, n (%)
759 (51.49)
794 (53.73)
962 (66.18)
< 0.001
Age, years
56.00 [47.00, 64.00]
55.00 [47.25, 64.75]
56.00 [49.00, 65.00]
0.130
Male, n (%)
775 (52.58)
893 (60.42)
1023 (69.31)
< 0.001
Cigarette smoking history, n (%)
501 (33.99)
595 (40.26)
690 (46.75)
< 0.001
Alcohol consumption history, n (%)
469 (31.82)
578 (39.11)
675 (45.73)
< 0.001
Hypertension, n (%)
727 (49.32)
912 (61.71)
1126 (76.29)
< 0.001
CHD, n (%)
207 (14.04)
279 (18.88)
352 (23.85)
< 0.001
Hyperlipidemia, n (%)
598 (40.57)
905 (61.23)
1018 (68.97)
< 0.001
SBP, mmHg
126.00 [113.00, 139.00]
129.00 [117.00, 142.00]
132.00 [119.00, 148.00]
< 0.001
DBP, mmHg
79.00 [71.00, 87.00]
81.00 [73.00, 89.75]
83.00 [75.00, 92.00]
< 0.001
BMI, kg/m2
23.20 [20.70, 26.00]
24.20 [22.10, 26.40]
24.90 [22.60, 27.20]
< 0.001
RBP, mg/L
23.80 [20.40, 26.15]
31.90 [30.07, 33.90]
42.61 [38.90, 48.16]
< 0.001
HbA1c, %
9.00 [7.20, 10.90]
8.30 [7.00, 10.20]
8.05 [6.80, 9.70]
< 0.001
FBG, mmol/L
8.93 [6.52, 12.57]
8.37 [6.52, 11.19]
8.23 [6.59, 10.78]
< 0.001
TC, mmol/L
4.38 [3.68, 5.12]
4.66 [3.92, 5.42]
4.80 [4.00, 5.63]
< 0.001
LDL, mmol/L
2.74 [2.23, 3.25]
2.88 [2.41, 3.46]
2.96 [2.39, 3.52]
< 0.001
TG, mmol/L
1.27 [0.94, 1.80]
1.57 [1.15, 2.32]
1.95 [1.37, 2.91]
< 0.001
HDL, mmol/L
1.10 [0.90, 1.34]
1.11 [0.94, 1.30]
1.08 [0.94, 1.28]
0.440
WBC count, 109/L
6.17 [4.99, 7.56]
6.18 [5.22, 7.44]
6.58 [5.46, 7.89]
< 0.001
CRP, mg/L
3.87 [1.32, 21.64]
2.37 [1.08, 7.73]
2.74 [1.19, 9.30]
< 0.001
AST, IU/L
20.60 [16.36, 27.80]
20.50 [17.21, 25.30]
20.98 [17.30, 25.75]
0.466
ALT, IU/L
18.65 [13.11, 30.30]
19.73 [14.61, 27.90]
19.90 [14.75, 29.10]
0.027
UA, μmol/L
277.00 [227.00, 333.00]
325.00 [270.89, 384.00]
380.00 [321.00, 441.12]
< 0.001
eGFR, mL/minute/1.73 m2
105.85 [90.95, 120.70]
100.24 [85.50, 114.03]
81.76 [53.80, 101.49]
< 0.001
Correlation between serum RBP levels and T2DM patients’ clinical indicators
The correlation between the serum RBP level and T2DM patient clinical parameters was determined using Spearman correlation analysis (Figure 2). The results indicated a positive correlation between the serum RBP level and BMI, DBP, SBP, WBC, TG, TC, LDL-C, and UA, while an inverse correlation existed with HbA1c, FBG, CRP, ALT, and eGFR (P < 0.05).
Figure 2 Correlation between serum retinol-binding protein level and type 2 diabetes mellitus patient clinical indicators.
Orange indicates a positive correlation, whereas blue indicates a negative correlation. aP < 0.05; bP < 0.01; cP < 0.001. RBP: Retinol-binding protein; BMI: Body mass index; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; HbA1c: Glycated hemoglobin; FBG: Fasting blood glucose; TC: Total cholesterol; LDL-C: Low-density lipoprotein cholesterol; TG: Triglycerides; HDL-C: High-density lipoprotein cholesterol; WBC: White blood cell; CRP: C-reactive protein; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase; UA: Uric acid; eGFR: Estimated glomerular filtration rate.
Association between serum RBP level and lower limb atherosclerosis risk
The association of the serum RBP level with lower limb atherosclerosis risk was further evaluated using multivariate logistic regression analysis (Table 3). All potential confounding factors were adjusted in model 3. The lower limb atherosclerosis risk increased by 1% for each unit increase in the serum RBP level (odds ratio = 1.01, 95% confidence interval: 1.00-1.02, P = 0.004). As compared to the lowest tertile group (Q1), patients within the highest serum RBP tertile group (Q3) exhibited a 36% increased risk of lower limb atherosclerosis (odds ratio = 1.36, 95% confidence interval: 1.12-1.67, P = 0.002). Also, the lower limb atherosclerosis risk gradually increased with increasing serum RBP levels (trend test P = 0.005). Additionally, RCS analysis demonstrated a linear association between the serum RBP level and lower limb atherosclerosis risk among T2DM patients (non-linear P < 0.05) (Figure 3). After removing the outliers for RBP, the association of serum RBP level with lower limb atherosclerosis remained significant (Supplementary Table 2, Supplementary Figure 2).
Figure 3 Dose-response relationship between serum retinol-binding protein level and lower limb atherosclerosis risk in type 2 diabetes mellitus patients.
OR: Odds ratio; CI: Confidence interval; RBP: Retinol-binding protein.
Table 3 Association between serum retinol-binding protein levels and lower limb atherosclerosis risk in type 2 diabetes mellitus patients.
Serum RBP levels
Model 1, OR (95%CI)
Model 1, P value
Model 2, OR (95%CI)
Model 2, P value
Model 3, OR (95%CI)
Model 3, P value
Continuous
1.02 (1.02, 1.03)
< 0.001
1.01 (1.01, 1.02)
< 0.001
1.01 (1.00, 1.02)
0.004
Tertiles
Q1
Reference
Reference
Reference
Q2
1.09 (0.95, 1.26)
0.200
1.00 (0.84, 1.18)
0.900
1.00 (0.84, 1.19)
0.900
Q3
1.76 (1.52, 2.04)
< 0.001
1.44 (1.21, 1.71)
< 0.001
1.36 (1.12, 1.67)
0.002
P for trend
< 0.001
< 0.001
0.005
Subgroup analysis
Subgroup analyses further explored the association of the serum RBP level with lower limb atherosclerosis risk, stratified by age, gender, BMI, eGFR, hypertension, hyperlipidemia, and history of CHD. As presented in Table 4, a more significant correlation was observed between serum RBP level and lower limb atherosclerosis in younger individuals, males, overweight or obese patients, and patients with histories of hyperlipidemia and CHD in the fully adjusted model. The interaction analysis revealed that the relationship between the serum RBP level and lower limb atherosclerosis risk varied significantly across different age groups (P for interaction < 0.05).
Table 4 Subgroup analysis of relationship between serum retinol-binding protein level and lower limb atherosclerosis risk in type 2 diabetes mellitus patients.
Subgroups
OR (95%CI)
P value
P for interaction
Age
0.019
< 60 years
1.01 (1.00, 1.02)
0.016
≥ 60 years
1.01 (0.99, 1.02)
0.400
Sex
0.700
Male
1.02 (1.01, 1.03)
0.003
Female
1.01 (0.99, 1.02)
0.500
BMI
0.900
< 25 kg/m2
1.01 (1.00, 1.02)
0.110
≥ 25 kg/m2
1.02 (1.00, 1.03)
0.011
Hypertension
0.800
Yes
1.01 (1.00, 1.02)
0.037
No
1.02 (1.00, 1.03)
0.036
Hyperlipidemia
0.700
Yes
1.01 (1.00, 1.02)
0.022
No
1.01 (1.00, 1.02)
0.091
CHD
0.200
Yes
1.03 (1.01, 1.06)
0.003
No
1.01 (1.00, 1.02)
0.069
eGFR
0.800
≤ 60 mL/minute/1.73 m2
1.02 (1.00, 1.03)
0.046
> 60 mL/minute/1.73 m2
1.01 (1.00, 1.02)
0.027
Importance of serum RBP level in predicting lower limb atherosclerosis risk in individuals with T2DM
The clinical importance of the serum RBP level in predicting lower limb atherosclerosis risk in individuals with T2DM patients was determined utilizing a machine learning algorithm based on a random forest model, which also assessed the significance of each clinical feature using SHAP. The impact of each clinical feature on the random forest-based prediction model is summarized in the SHAP summary plot (Figure 4A). The results indicated that with the increase of serum RBP level, there was a higher lower limb atherosclerosis risk in T2DM. In Figure 4B, the SHAP force plot further demonstrates that the serum RBP level was positively associated with the lower limb atherosclerosis risk, with a SHAP value > 0 indicating an increased lower limb atherosclerosis risk.
Figure 4 Shapley Additive Explanations analysis results of the random forest model.
A: Shapley Additive Explanations (SHAP) summary plot. The X-axis represents the SHAP value and the Y-axis represents the feature contributions ranked by importance. The higher the SHAP value, the greater the risk of lower limb atherosclerosis. A pink dot indicates a higher predicted value and a blue dot indicates a lower predicted value; B: SHAP force plot. eGFR: Estimated glomerular filtration rate; WBC: White blood cell count; SBP: Systolic blood pressure; RBP: Retinol-binding protein; BMI: Body mass index; ALT: Alanine aminotransferase; AST: Aspartate aminotransferase; HbA1c: Glycated hemoglobin; LDL-C: Low-density lipoprotein cholesterol; HDL-C: High-density lipoprotein cholesterol; CHD: Coronary heart disease; FBG: Fasting blood glucose; CRP: C-reactive protein; TG: Triglycerides; DBP: Diastolic blood pressure; UA: Uric acid; SHAP: Shapley Additive Explanations.
DISCUSSION
This study is the initial investigation into the association between changes in serum RBP levels and lower limb atherosclerosis risk in individuals with T2DM. The findings indicated that a higher serum RBP level was significantly linked to a heightened risk of atherosclerosis in the lower limbs among individuals with T2DM. Furthermore, RCS analysis indicated that serum RBP levels had a positive linear association with lower limb atherosclerosis risk, which remained significant even after controlling for various confounding variables. In addition, the findings linked the serum RBP level with lower limb atherosclerosis and revealed its potential value in early prevention and intervention of lower limb atherosclerosis, which is expected to bring new perspectives and strategies for diagnosis and treatment.
In recent years, changes in serum RBP levels have been significantly linked to the progression of various diseases, such as inflammatory, metabolic, and immune system disorders[27-30]. In addition, clinical research has indicated a connection between serum RBP levels and disorders associated with diabetes. Huang et al[31] reported that RBP4 is a biomarker and potential therapeutic target for non-alcoholic fatty liver disease development. Huang et al[32] found that elevated serum RBP levels can be associated with T2DM progression to diabetic nephropathy. Chen et al[33] concluded that the serum RBP levels are a promising predictor to evaluate diabetic foot severity and progression. Zhang et al[34] showed that low levels of serum RBP are related to cognitive function of diabetic patients. However, knowledge about the potential link between the serum RBP levels and lower limb atherosclerosis risk of T2DM is lacking. This study found a statistically significant increase in the serum RBP levels among patients in the lower limb atherosclerosis group compared to the non-lower limb atherosclerosis group. As the serum RBP tertile level increased, there was a corresponding gradual increase in the incidence of lower limb atherosclerosis. Furthermore, logistic regression indicated that the serum RBP levels were significantly linked to lower limb atherosclerosis risk. Additionally, RCS analysis demonstrated that serum RBP levels had a positive linear association with lower limb atherosclerosis risk, a relationship that persisted after controlling for various potential confounders. Overall, these findings indicated that the serum RBP levels have a crucial role in lower limb atherosclerosis progression in T2DM.
The exact pathophysiologic mechanism between RBP and lower limb atherosclerosis risk has not been fully elucidated. Atherosclerosis is widely recognized as a lipid-driven vascular disease[35]. Diabetic patients often have lipid metabolism disorders, such as hypercholesterolemia and hypertriglyceridemia, which further promote the formation of atherosclerosis[36]. This study found that serum RBP levels were positively correlated with the TC, TG, and LDL-C levels in T2DM patients. Therefore, elevated serum RBP levels in patients with T2DM complicated by lower limb atherosclerosis may indicate a severe lipid metabolic disorder. Diabetic patients frequently have renal insufficiency[37]. Because RBP is primarily metabolized and excreted through the kidneys, renal insufficiency may lead to the accumulation of RBP[38]. A notable inverse relationship was observed between the serum RBP and eGFR levels in T2DM patients in the current study, suggesting that renal insufficiency may be an important factor linking RBP and lower limb atherosclerosis. However, T2DM patients exhibited an inverse relationship between serum RBP levels and FBG and HbA1c levels, which may be related to long-term malnutrition and chronic inflammatory states leading to insulin dysfunction[39,40]. Further investigation is warranted to elucidate the specific mechanisms. Overall, the relationship between the serum RBP levels and lower limb atherosclerosis risk in individuals with T2DM may be closely related to lipid metabolism and renal insufficiency.
It has been reported that the lower limb atherosclerosis severity and the adverse outcomes risk are strongly dependent on factors, such as gender[41], age[42], and BMI[43]. Generally, elderly patients are more susceptible to atherosclerosis[44-47], which increases their hospitalization rates and cardiovascular events. Recently, there has been a noticeable rise in young individuals diagnosed with T2DM and atherosclerosis[45], which emphasizes the critical need for early evaluations of atherosclerosis in this age group. Our subgroup analysis by age revealed that young T2DM patients with elevated RBP levels have a higher lower limb atherosclerosis risk, which may emphasize the necessity for intensified monitoring of circulating RBP levels in young T2DM patients. Gender differences have an impact on the incidence of atherosclerosis. Multiple studies have showed that the overall vascular plaque burden tends to be higher in males than females[48], which may be related to variations in male testosterone levels[49]. We observed that male T2DM patients who have elevated RBP levels were more likely to have lower limb atherosclerosis, suggesting that RBP may be involved in atherosclerosis in males, although these underlying mechanisms require further exploration. It is well-known that hyperlipidemia, obesity, and atherosclerosis are all considered risk factors for cardiovascular disease, and various diseases affect each other[50]. In our subgroup analysis, elevated RBP levels have been linked to an elevated risk of lower limb atherosclerosis in patients with T2DM who were overweight or obese, had hyperlipidemia, and had CHD. Overall, the overall trend remained consistent with the main findings of this study. In addition, machine learning demonstrated that the serum RBP levels are also a promising potential biomarker for diagnosing the lower limb atherosclerosis risk in T2DM patients.
Acknowledging the limitations of the current study is important. This retrospective study inevitably had selection bias. First, all patients were selected from those hospitalized with T2DM at Southwest Hospital from 2018-2022, which may introduce time- and location-related biases because patient characteristics and disease conditions may differ across time periods and geographic regions. Second, patients with incomplete clinical data were excluded during the data-cleaning process, potentially impacting the experimental results. Third, to ensure the integrity of clinical data, all T2DM patients were recruited from the inpatient department, implying that their conditions might be relatively severe compared to those of outpatients. Therefore, the population may not fully represent unselected and mildly ill T2DM outpatients. However, to minimize these biases as much as possible, we used a series of rigorous statistical methods to derive robust and reliable results, as well as a relatively large sample size to mitigate this effect. In addition, in a cross-sectional observational study, it was impossible to dynamically observe a causal link between changes in serum RBP levels and lower limb atherosclerosis incidence. Thus, large-scale longitudinal clinical investigations are essential to ascertain the potential link between RBP levels and clinical lower limb atherosclerosis progression in T2DM. Additionally, more basic research in animals is required to investigate whether RBP can provide assistance in targeted therapy for lower limb atherosclerosis in T2DM.
CONCLUSION
Elevated serum RBP levels are strongly associated with an increased lower limb atherosclerosis risk in T2DM patients. Our findings suggest that serum RBP levels are expected to assist in the detection of lower limb atherosclerosis early in patients with T2DM, thereby enhancing risk assessment and early prevention. Indeed, the detection of serum RBP levels may be more economical, convenient, and safe compared to vascular ultrasound and angiography. However, RBP levels may be affected by multiple factors, including diseases, medications, and physiologic states, which require long-term dynamic detection. Furthermore, there is no available targeted therapy related to serum RBP, further restricting its clinical utility. Therefore, there is demand for more prospective and mechanistic investigations to validate this finding.
ACKNOWLEDGEMENTS
The authors would like to acknowledge the support of Professor Sen Fang from Nanjing Shensen Technology for the contributions to data processing and analysis.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, Stein C, Basit A, Chan JCN, Mbanya JC, Pavkov ME, Ramachandaran A, Wild SH, James S, Herman WH, Zhang P, Bommer C, Kuo S, Boyko EJ, Magliano DJ. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045.Diabetes Res Clin Pract. 2022;183:109119.
[PubMed] [DOI][Cited in This Article: ][Cited by in Crossref: 3033][Cited by in F6Publishing: 3685][Article Influence: 1228.3][Reference Citation Analysis (36)]
Mahé G, Aboyans V, Cosson E, Mohammedi K, Sarlon-Bartoli G, Lanéelle D, Mirault T, Darmon P. Challenges and opportunities in the management of type 2 diabetes in patients with lower extremity peripheral artery disease: a tailored diagnosis and treatment review.Cardiovasc Diabetol. 2024;23:220.
[PubMed] [DOI][Cited in This Article: ][Cited by in Crossref: 1][Reference Citation Analysis (0)]
Saely CH, Schindewolf M, Zanolin D, Heinzle CF, Vonbank A, Silbernagel G, Leiherer A, Drexel H, Baumgartner I. Single and combined effects of peripheral artery disease and of type 2 diabetes mellitus on the risk of cardiovascular events: A prospective cohort study.Atherosclerosis. 2018;279:32-37.
[PubMed] [DOI][Cited in This Article: ][Cited by in Crossref: 10][Cited by in F6Publishing: 10][Article Influence: 1.4][Reference Citation Analysis (0)]
Wang L, Ma Q, Fang B, Su Y, Lu W, Liu M, Li X, Liu J, He L. Shift work is associated with an increased risk of type 2 diabetes and elevated RBP4 level: cross sectional analysis from the OHSPIW cohort study.BMC Public Health. 2023;23:1139.
[PubMed] [DOI][Cited in This Article: ][Cited by in F6Publishing: 3][Reference Citation Analysis (0)]
Kilicarslan M, de Weijer BA, Simonyté Sjödin K, Aryal P, Ter Horst KW, Cakir H, Romijn JA, Ackermans MT, Janssen IM, Berends FJ, van de Laar AW, Houdijk AP, Kahn BB, Serlie MJ. RBP4 increases lipolysis in human adipocytes and is associated with increased lipolysis and hepatic insulin resistance in obese women.FASEB J. 2020;34:6099-6110.
[PubMed] [DOI][Cited in This Article: ][Cited by in Crossref: 22][Cited by in F6Publishing: 35][Article Influence: 7.0][Reference Citation Analysis (0)]
Patel N, Penkert RR, Sealy RE, Surman SL, Jones BG, Ringwald-Smith K, Ross AC, Hurwitz JL. Retinol Binding Protein, Sunlight Hours, and the Influenza Virus-Specific Immune Response.Biomedicines. 2022;10:2322.
[PubMed] [DOI][Cited in This Article: ][Reference Citation Analysis (0)]
Agustinho BC, Ramsey KC, Moore C, Tsai CY, Scholte CM, McGuire MA, Rezamand P. Effect of Different Combinations of Dietary Vitamin A, Protein Levels, and Monensin on Inflammatory Markers and Metabolites, Retinol-Binding Protein, and Retinoid Status in Periparturient Dairy Cows.Animals (Basel). 2021;11:2605.
[PubMed] [DOI][Cited in This Article: ][Cited by in F6Publishing: 1][Reference Citation Analysis (0)]
Huang J, Liu J, Liu W. Correlations of Serum Retinol-Binding Protein and Stromal Cell-Derived Factor-1 with Renal Function in Patients with Diabetic Kidney Disease.Clin Lab. 2024;70.
[PubMed] [DOI][Cited in This Article: ][Reference Citation Analysis (0)]
Chen X, Xu Y, Meng X, Geng R, Wang X, Zhang G, Bai L. RETRACTED: Analysis of the association between serum levels of 25(OH)D, retinol binding protein, and Cyclooxygenase-2 and the disease severity in patients with diabetic foot ulcers.Int Wound J. 2024;21:e14502.
[PubMed] [DOI][Cited in This Article: ][Cited by in Crossref: 1][Cited by in F6Publishing: 2][Article Influence: 2.0][Reference Citation Analysis (0)]
Zhang W, Yuan Y, Cui X, Chen S, Zhuang X. The level of serum retinol-binding protein is associated with diabetic mild cognitive impairment.Brain Res. 2024;1822:148670.
[PubMed] [DOI][Cited in This Article: ][Reference Citation Analysis (0)]
Guardiola M, Rehues P, Amigó N, Arrieta F, Botana M, Gimeno-Orna JA, Girona J, Martínez-Montoro JI, Ortega E, Pérez-Pérez A, Sánchez-Margalet V, Pedro-Botet J, Ribalta J; Cardiovascular Disease Group of the Spanish Society of Diabetes. Increasing the complexity of lipoprotein characterization for cardiovascular risk in type 2 diabetes.Eur J Clin Invest. 2024;54:e14214.
[PubMed] [DOI][Cited in This Article: ][Reference Citation Analysis (0)]
De Matteis G, Biscetti F, Della Polla DA, Serra A, Burzo ML, Fuorlo M, Nicolazzi MA, Novelli A, Santoliquido A, Gambassi G, Gasbarrini A, Flex A, Franceschi F, Covino M. Sex-Based Differences in Clinical Characteristics and Outcomes among Patients with Peripheral Artery Disease: A Retrospective Analysis.J Clin Med. 2023;12:5094.
[PubMed] [DOI][Cited in This Article: ][Reference Citation Analysis (0)]
Almohtasib Y, Fancher AJ, Sawalha K. Emerging Trends in Atherosclerosis: Time to Address Atherosclerosis From a Younger Age.Cureus. 2024;16:e56635.
[PubMed] [DOI][Cited in This Article: ][Reference Citation Analysis (0)]
