Association Between VEGF Gene Polymorphism and Diabetic Neuropathy Susceptibility

By Lequan Wen^1,2,3, Changsen Yang^1,2,3, Tiangang Song^1,2,3, Nan Guo^4,5, Lirui Tang^1,2,3, Haokun Tian^1,2,3

Affiliations

1. Joint Programme of Nanchang University and Queen Mary University of London, Nanchang University, Nanchang, China
2. Queen Mary School, Nanchang University, Nanchang, China
3. Nanchang Joint Programme, School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
4. The Third Affiliated Hospital of Nanchang University, Nanchang, China
5. The Third Clinical Medical College, Nanchang University, Nanchang, China

doi: 10.29271/jcpsp.2025.08.1028

ABSTRACT
Diabetic neuropathy is a common complication of diabetes, characterised by peripheral nerve damage that manifests as sensory loss and pain. Vascular endothelial growth factor (VEGF) plays a crucial role in angiogenesis and microvascular function. The association between the rs3025039 polymorphism in the VEGF gene and susceptibility to diabetic neuropathy remains controversial. Therefore, the meta-analysis searched databases for relevant articles published from the database establishment to March 1, 2023. Case-control studies examining VEGF gene polymorphisms in relation to diabetic neuropathy susceptibility, providing genotype/allele frequency data, and involving human subjects were included. Studies with incomplete data, non-human subjects research, or duplicate publications were excluded. RevMan 5.4 and StataMP 17 were used for the meta-analysis, and TSA 0.9.5.10 Beta was used for trial sequential analysis. The pooled analysis of CC vs. CT+TT genotypes, CC vs. CT genotypes, and C vs. T alleles showed an odds ratio >1 and p <0.05 based on the seven identified original studies. Sensitivity analysis and publication bias analysis supported the credibility of the meta-analysis’ results. These findings provide statistical evidence supporting the association between the rs3025039 polymorphism and diabetic neuropathy susceptibility, with the C allele conferring a higher risk than the T allele.

Key Words: Diabetic neuropathy, Vascular endothelial growth factor, Single-nucleotide polymorphism, Meta-analysis, Trial sequential analysis.

INTRODUCTION

Diabetes is a widespread chronic disease affecting populations worldwide. Over the past three decades, its incidence rate has increased from 4.7 to 8.5%, remaining at an alarmingly high level. The global diabetic population is projected to reach 693 million by 2045.¹ The rising prevalence of diabetes has raised public concern over its complications, including diabetic neuropathic pain, diabetic peripheral neuropathy (DPN), and diabetic autonomic neuropathy.² Diabetic neuropathy represents a major risk to patient’s health and well-being. Statistics suggest that approximately 25% of diabetic patients experience neuropathic pain, which often contributes to dep- ressive behaviours.^3,4 Studies show that approximately 10-34% of Type I Diabetes patients and 8-25% of Type II Diabetic patients develop DPN, adversely affecting their quality of life.^5,6

However, the pathophysiology of diabetic neuropathy is highly complex. Recent studies have suggested that diabetes and its complications are influenced not only by metabolic dysfunction but also by distinct genetic factors.⁷

Vascular endothelial growth factor (VEGF) plays a crucial role in tissue growth and repair by regulating both angiogenesis (the germination of new blood vessels from existing vascular structures) and vasculogenesis (vascular regrowth).⁸ VEGF enhances microvascular permeability by transmitting survival signals to endothelial cells, playing a key role in microvascular remodelling, particularly in the development of diabetic retinopathy.^8,9 Ropper et al. identified microvascular ischaemia as a critical factor in diabetic neuropathy and suggested VEGF gene therapy via intramuscular plasmid transfer as a potential treatment strategy.¹⁰ Furthermore, diabetic neuropathic pain has been closely associated with VEGF-mediated spinal cord vascular degeneration.¹¹ In conclusion, these findings suggest that VEGF is a pivotal player in the pathophysiology of diabetic neuropathy.

VEGF polymorphisms have been implicated in a range of diseases, including cancer, depression, endometriosis, and diabetic microvascular complications.^12-15 The VEGF gene, located on chromosome 6p12, consists of eight exons. The expression variability of the VEGF protein is linked to the 936C/T (rs3025039) single-nucleotide polymorphism in the untranslated region.¹⁶ Previous studies have linked the 936C/T (rs3025039) single-nucleotide polymorphism in VEGF with conditions such as leukaemia and rheumatoid arthritis.^17,18 In addition, case-control studies investigating the relationship between the VEGF 936C/T (rs3025039) polymorphism and diabetic neuropathy have increased in recent years. However, discrepancies in findings may be attributed to ethnic variations, limited sample sizes, or methodological inconsistencies, raising concerns about the credibility of the results.¹⁹

To overcome these limitations, meta-analysis functions as a statistical method that systematically integrates data from multiple independent studies, thereby enhancing the precision and reliability of results. By synthesising the available literature, this meta-analysis can identify commonalities and discrepancies across studies, providing stronger evidence for the underlying mechanisms of the disease. Furthermore, trial sequential analysis (TSA) complements meta-analysis by evaluating the risk of random errors and determining the required sample size to draw definitive conclusions. TSA helps to ensure that the findings are not false positives or false negatives, thereby increasing the robustness of the conclusions. Therefore, this study aimed to perform a meta-analysis and TSA of case-control studies, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline, to evaluate the association between the 936C/T (rs3025039) polymorphism of the VEGF gene and diabetic neuropathy, ultimately yielding high-level evidence.

METHODOLOGY

A systematic literature search was conducted across Web of Science, PubMed, Embase, CNKI, VIP, and Wanfang Data. The search covered publications from the inception of each database up to March 1, 2023. Additionally, reference lists of included studies were manually screened to identify potentially relevant articles. Inclusion criteria were published case- control studies examining the relationship between VEGF gene polymorphisms and diabetic neuropathy susceptibility; a case group comprising individuals diagnosed with diabetic neuropathy and a control group of healthy subjects; and complete data on sample sizes for both control and case groups, along with allele or genotype frequency distributions. Exclusion criteria included studies with missing or incomplete data, when attempts to contact the original authors were unsuccessful, non-human subject studies, duplicate publications or studies reporting overlapping data. The search strategy incorporated the keywords such as VEGF, vascular endothelial growth factor, diabetic neuropathy, diabetic polyneuropathy, diabetic peripheral neuropathy, diabetic microvascular complications, gene polymorphisms, and gene variants.
 

Two independent researchers reviewed the publications, extracted data, and cross-verified the results. Discrepancies were resolved either through discussion or by a third reviewer. Research title was screened to eliminate irrelevant articles. Subsequently, the abstracts and full-texts were assessed to determine the final determination. In cases where further information was required, the corresponding authors were contacted via email or telephone.

Risk of bias in the included studies was assessed using the Newcastle–Ottawa Scale (NOS).¹⁹ The NOS assesses study quality based on criteria such as case definition and diagnosis, selection and definition of control group, representativeness of the cases, comparability of study groups, consistency in exposure assessment, similarity of investigation methods, and response rate.²⁰ Two independent reviewers assessed each study, and discrepancies were resolved through discussion or with the assistance of a third reviewer.

The meta-analysis was conducted using RevMan 5.4 (The Cochrane Collaboration, London, UK) and StataMP 17 (StataCorp LLC, Texas, USA). Odds ratios (ORs), p-values, and 95% confidence intervals (CIs) for each outcome were reported. Study heterogeneity was assessed using the Chi-square test, with a significance threshold of α = 0.10. In instances of low statistical heterogeneity (p >0.10), a fixed-effects model was used for the meta-analysis. Conversely, when significant statistical heterogeneity was present (p <0.10), a random-effects model was used. Sensitivity analysis was performed by systematically excluding each study, one at a time, to assess its impact on the overall results.¹⁹ Begg’s and Egger’s tests were used to detect publication bias, with a value of p >0.05 signifying low risk of bias. Finally, TSA 0.9.5.10 Beta (Copenhagen Trial Unit, Copenhagen, Denmark) was used to evaluate the risk of random errors and to determine the necessary sample size for a definitive conclusion.²¹

RESULTS

After a thorough screening of the 200 initially retrieved articles, seven case-control studies that met the inclusion criteria were ultimately identified. These studies included 869 controls and 627 cases, spanning from 2009 to 2022, and covered individuals from Asia, Africa, and the America.^22-28 Figure 1 shows the flow diagram of article searching and screening process. All of the included articles were of high methodological quality, meeting the predefined inclusion criteria. Table I summarises the extracted data from these studies.

Table II provides an overview of the pooled meta-analysis results. Individuals carrying the CC genotype exhibited a significantly higher risk of developing diabetic neuropathy than those with the CT + TT genotype (OR = 1.61, 95% CI [1.28, 2.03], p <0.0001; Figure 2A). Similarly, individuals with the CC genotype demonstrated an elevated risk of diabetic neuropathy relative to those with the CT genotype (OR = 1.55, 95% CI [1.20, 2.00], p = 0.0008; Figure 2B).

Table I: Characteristics of included studies.

First Author	Years	Countries	Case			Control
			CC	CT	TT	CC	CT	TT
Kim HW26	2009	Korea	69	34	3	190	88	15
Yang-Xin D23	2011	China	80	19	3	58	29	5
Zhang X25	2014	China	159	39	6	115	59	10
Ghisleni MM27	2015	Brazil	25	4	1	9	2	0
Barus J24	2018	Indonesia	59	10 (CT+TT)		56	27 (CT+TT)
Arredondo-Garcia VK28	2019	Mexico	46	32	12	50	66	12
El-Deeb22	2022	Egypt	13	8	5	42	25	11
C = Cytosine; T = Thymine.

Table II: Summary of meta-analysis results.

Outcomes	OR	95% CIs	p-values
CC vs. TT	1.35	[0.83, 2.21]	0.23
CC+CT vs. TT	1.14	[0.71, 1.83]	0.59
CC vs. CT+TT	1.61	[1.28, 2.03]	0.0001*
CC vs. CT	1.55	[1.20, 2.00]	0.0008*
CT vs. TT	0.87	[0.53, 1.44]	0.59
C vs. T	1.36	[1.11, 1.66]	0.002*
C = Cytosine; T = Thymine; OR: Odds ratios; 95% CI: 95% Confidence intervals. Table III: Publication bias analysis results.

Outcomes	Begg’s tests		Egger’s tests
	Z	p-values	t	p-values
CC vs. TT	0.00	1.000	0.14	0.892
CC+CT vs. TT	0.00	1.000	0.52	0.630
CC vs. CT+TT	0.00	1.000	-0.14	0.895
CC vs. CT	0.38	0.707	-0.19	0.862
CT vs. TT	0.00	1.000	0.51	0.634
C vs. T	0.38	0.707	-0.59	0.589
C = Cytosine; T = Thymine.

Figure 1: Flow diagram of article searching and screening.

Additionally, individuals with the C allele had a greater probability of developing diabetic neuropathy than those with the T allele (OR = 1.36, 95% CI [1.11, 1.66], p = 0.002; Figure 2C). No statistically significant associations were found for the remaining three genetic comparisons (Table II).

To conduct the sensitivity analysis, a one-by-one exclusion method was used.¹⁹ For instance, in the CC vs. CT + TT geno-type comparison, the highest OR value was 1.87 (95% CI [1.44, 2.44], p <0.0001) after excluding the study by Kim et al.²⁶ Conversely, the lowest OR value was 1.46 (95% CI [1.11, 1.91], p = 0.006) after excluding the study of Zhang et al.²⁵ Across all individual study exclusions, the OR consistently remained above 1, with p-values below 0.05, confirming the robustness of the findings. For the CC vs. CT genotype compari-son, the highest OR value was 1.88 (95% CI [1.39, 2.55], p <0.0001) after excluding the study by Kim et al.²⁶ The lowest OR value was 1.37 (95% CI [1.01, 1.85], p = 0.04) after excluding the study by Zhang et al.²⁵ For the C vs. T allele comparison, the highest OR value was 1.47 (95% CI [1.17, 1.85], p = 0.001) after excluding the study by Kim et al.²⁶ The lowest OR value was 1.20 (95% CI [0.95, 1.52], p = 0.13) after excluding the study by Zhang et al.²⁵ The sensitivity analysis confirmed the stability of the meta-analysis results, as excluding any single study did not substantially alter the overall findings.

Figure 2: Forest plots of overall meta-analysis results: (A) CC vs. CT+TT; (B) CC vs. CT; and (C) C vs. T comparisons.

The publication bias assessment, conducted using StataMP 17, is summarised in Table III. Taking the outcome of CC vs. CT + TT genotype as an example, Begg’s test yielded Z = 0.00 and p = 1.000, and Egger’s test yielded t = -0.14 and p = 0.895, respectively, indicating that there was no significant publication bias. These results are consistent with those shown in Table III. The funnel plot demonstrated a symmetrical distribution of the studies, suggesting the absence of substantial publication bias (Figure 3A). For the outcomes of CC vs. CT genotype and C vs. T allele, the results were the same (Figure 3B, C). This shows that publication bias was not likely to have affected the dependability of the meta-analysis results.

TSA was conducted using TSA 0.9.5.10 Beta. Taking the CC vs. CT + TT genotype outcome as an example, Figure 4A illustrates that the Z-curve did not reach the required information size (RIS) and approached the boundary line but did not cross it. A similar pattern was noted in the TSA results for CC vs. CT and C vs. T comparisons, suggesting a residual possibility of false-positive or false-negative results (Figure 4B, C). Further large-scale, well-designed case-control studies are warranted to validate the findings of this meta-analysis.

DISCUSSION

This study investigated the relationship between the VEGF 936C/T (rs3025039) polymorphism in the VEGF gene and susceptibility to diabetic neuropathy. Comparisons of the CC vs. CT + TT genotype, CC vs. CT genotype, and C vs. T allele revealed statistically significant associations, demonstrating a differential risk of diabetic neuropathy based on VEGF genotypes. Carriers of the C allele exhibited an increased risk of developing diabetic neuropathy compared to those with the T allele.

Diabetic neuropathy is a progressive neurodegenerative disorder caused by diabetes-induced damage to the autonomic nervous system. It is primarily characterised by sensory impairment and pain. The pathophysiology of diabetic neuropathy compared has been extensively studied. Microcirculatory dysfunction has been implicated as a key contributor to peripheral nerve damage.²⁹

VEGF is a pro-angiogenic factor that plays a critical role in vascular regulation by modulating permeability, facilitating endothelial cell migration, promoting pro-inflammatory cell aggregation, and sustaining wound healing respon-ses.³⁰ Numerous studies have demonstrated the involvement of VEGF in experimental diabetic neuropathy, showing its role in angiogenic inflammatory and oxidative pathways, both in vitro and in vivo.^31,32 As a dimeric glycoprotein, VEGF binds heparin and plays a crucial role in endothelial homeo-stasis under normal physiological conditions. However, a dysregulated VEGF expression can cause abnormal angio-genesis.³³

Figure 3: Funnel plots of publication bias analysis results. (A) CC vs. CT+TT; (B) CC vs. CT; and (C) C vs. T comparisons.

The VEGF gene, located on chromosome 6 (6p21.3), harbours significant polymorphisms, particularly in the promot, 5', and 3' untranslated region.³⁴ Among the various VEGF polymor-phisms, rs3025039 is located within the untranslated region.^16,35 A hypoxia-induced glycoprotein can bind to VEGF mRNA, prolonging its half-life and enhancing VEGF expression levels.

Figure 4: Trial sequential analysis results: (A) CC vs. CT+TT; (B) CC vs. CT; and (C) C vs. T comparisons.

The rs3025039 polymorphism may alter the binding affinity, leading to modifications in VEGF expression.³⁶ Another study has shown that the rs3025039 polymorphism may affect hypoxia-induced transcription and activation by altering the binding site of the nuclear transcription activating factor, AP-4.³⁷ In this case, the rs3025039 polymorphism in the VEGF gene may affect the susceptibility to diabetic neuro-pathy by tempering VEGF gene expression.

Several prior studies have examined the role of VEGF gene polymorphisms in diabetic microvascular complications. For instance, Han et al. conducted a meta-analysis on VEGF gene variants and diabetic retinopathy, suggesting a strong association between VEGF polymorphisms and microvascular dysfunction.³⁸ Similarly, a meta-analysis by Zhou et al. investigated VEGF genetic variants in Type II Diabetes complications, demonstrating that VEGF polymorphisms play a crucial role in the susceptibility to diabetic complications.³⁹ In addition, previous meta-analyses have explored the role of VEGF polymorphisms in other diseases, such as cancer, diabetic foot, and chronic immune-mediated inflammatory diseases, confirming the regulatory role of VEGF genetic variations in pathological angiogenesis and inflammation.^40-42 This study complements these findings by providing an evidence that the rs3025039 polymorphism in VEGF is significantly associated with diabetic neuropathy risk.

Moreover, findings of this study align with those of Deguchi et al. who reported that serum VEGF concentrations are significantly elevated in diabetic patients with neuropathy.⁴³ VEGF affects nerves by altering the endothelial structure of capillaries to make them more permeable, causing vascular endothelial cell hypertrophy and proliferation. Simultan-eously, extracellular matrix production increases with a thickened vascular basement membrane. These alterations compromise vascular function, obstruct blood flow, and increase oxygen diffusion distance, leading to nerve ischaemia, hypoxia, and subsequent neuropathy.⁴⁴ However, VEGF can also protect neurons from ischaemia and hypoxia by interacting with VEGFR2, which has neurotrophic effects.^24,45,46 The role of VEGF in endothelial dysfunction and neuronal damage, as discussed in studies by Cameron and Cotter and Sondell et al., further supports the conclusion.^47,48 The findings suggest that VEGF plays a complex role in modifying the risk of diabetic neuropathy.

Beyond VEGF, other meta-analyses have examined polymorphisms in genes such as methylenetetrahydrofolate reductase (MTHFR), angiotensin-converting enzyme (ACE), and catalase (CAT), all of which have been implicated in the pathogenesis of diabetic neuropathy.^49,50 For example, Zhao et al. conducted a meta-analysis on the CAT -262C/T, demonstrating its role in inflammation and neuronal damage associated with diabetes-related complications.⁴⁹ Similarly, a meta-analysis by Wu et al. on MTHFR and ACE gene polymor-phisms found a strong correlation between the MTHFR 677 C >T and ACE I/D polymorphisms and increased susceptibility to diabetic neuropathy, highlighting the complex genetic basis of this condition.⁵⁰

However, this meta-analysis has certain limitations. First, the number of primary studies evaluating the rs3025039 polymorphism of the VEGF gene and its impact on diabetic neuropathy remains limited. Consequently, the sample size of this meta-analysis was relatively small, as reflected in the TSA results. Furthermore, the geographical diversity of the included studies precluded race-based subgroup analyses. Thus, additional follow-up case-control studies are required to confirm the findings of this meta-analysis.

CONCLUSION

This meta-analysis provides a robust statistical evidence supporting the relationship between the rs3025039 polymorphism in VEGF and an increased risk of diabetic neuropathy. Individuals with the C allele are at a greater risk of developing diabetic neuropathy. Sensitivity analysis confirmed the stability of the present study’s conclusions, indicating minimal susceptibility to changes from individual studies. Publication bias analysis suggested that the reliability of this meta-analysis’ findings was largely unaffected. TSA revealed that due to the limitation of the quantity of the included original studies, the Z-curve did not cross the boundary, and the required information size was not met. Therefore, high-quality, multicentre, large-sample, case-control studies are recommended to verify the conclusions of this study.

COMPETING INTEREST:
The authors declared no conflict of interest.

AUTHORS’ CONTRIBUTION:
LW: Conceptualisation, methodology, investigation, data curation, formal analysis, and editing.
CY: Methodology, investigation, data curation, formal analysis, validation, and software.
TS: Investigation, formal analysis, validation, writing of the original draft, and visualisation.
NG: Investigation and writing of the original draft.
LT: Formal analysis and writing of the original draft.
HT: Resources, investigation, formal analysis, validation, writing – review, editing, visualisation, supervision, and project administration.
All authors approved the final version of the manuscript to be published.
 

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