Introduction: The Growing Need for Predictive Biomarkers in Diabetic Eye Care

Diabetic retinopathy (DR) remains the leading cause of preventable vision loss among working-age adults worldwide. Despite advances in glycemic control and systemic disease management, the prevalence of DR continues to climb in parallel with the global diabetes epidemic. The International Diabetes Federation projects that the number of adults with diabetes will reach 783 million by 2045, and a significant proportion of these individuals will develop retinal complications. Early detection is critical because the most severe, vision-threatening stages—proliferative diabetic retinopathy (PDR) and diabetic macular edema (DME)—often develop without noticeable symptoms until irreversible damage has occurred. Traditional screening relies on fundus photography and clinical examination, which detect structural changes only after they are already present. There is an urgent need for molecular biomarkers that can stratify risk years before visible pathology appears. Among the most promising candidates is circulating vascular endothelial growth factor (VEGF), a key driver of the aberrant angiogenesis that characterizes advanced DR. This article examines the evidence linking circulating VEGF to DR risk, explores its potential integration into routine assessment, and discusses the implications for personalized treatment strategies. Additionally, we consider how combining VEGF with other emerging biomarkers and imaging modalities could reshape screening protocols.

Understanding Diabetic Retinopathy: Pathophysiology and Progression

Diabetic retinopathy is a neurovascular complication of diabetes mellitus. Chronic hyperglycemia triggers a cascade of metabolic insults to the retinal microvasculature: accumulation of advanced glycation end-products (AGEs), activation of the polyol pathway, oxidative stress, and chronic low-grade inflammation. These processes lead to pericyte loss, endothelial cell dysfunction, and thickening of the capillary basement membrane. As the blood-retinal barrier becomes compromised, microaneurysms, dot-blot hemorrhages, and hard exudates appear—hallmarks of non-proliferative diabetic retinopathy (NPDR). Over time, progressive capillary occlusion creates areas of retinal ischemia. In response to hypoxia, the retina upregulates hypoxia-inducible factor-1α (HIF-1α), which in turn stimulates the production of VEGF and other angiogenic factors. This drives the formation of fragile, abnormal new blood vessels—the defining feature of proliferative diabetic retinopathy (PDR). These vessels are prone to leakage and hemorrhage, leading to vitreous hemorrhage, tractional retinal detachment, and neovascular glaucoma. Concurrently, VEGF-mediated hyperpermeability can cause fluid accumulation in the macula, resulting in diabetic macular edema (DME), the most common cause of vision loss in DR. Recent research has also highlighted the role of neurodegeneration—retinal ganglion cell loss and thinning of the nerve fiber layer—as an early event in DR, preceding visible vascular changes. This neurovascular unit dysfunction underscores the complexity of the disease and the need for biomarkers that capture both vascular and neural damage.

Epidemiology and Risk Factors

According to the International Diabetes Federation, approximately 537 million adults had diabetes in 2021, a number projected to reach 783 million by 2045. Of these, about one-third will develop some form of DR, and up to 10% will progress to vision-threatening stages. Major risk factors include duration of diabetes, poor glycemic control (elevated HbA1c), hypertension, dyslipidemia, and nephropathy. However, these clinical variables alone have limited predictive power. Two patients with identical HbA1c levels and disease duration can have dramatically different DR trajectories, highlighting the need for more granular biomarkers that capture individual variation in angiogenic and inflammatory pathways. For instance, the Diabetes Control and Complications Trial (DCCT) demonstrated that intensive glycemic control reduced the risk of DR progression by 76%, yet some patients in the intensive group still developed advanced retinopathy. This variability suggests that genetic predisposition and molecular mediators—such as circulating VEGF—play a crucial role in determining individual risk.

The Role of Vascular Endothelial Growth Factor (VEGF) in Diabetic Retinopathy

Vascular endothelial growth factor is a homodimeric glycoprotein that plays a central role in both physiological and pathological angiogenesis. The VEGF family includes VEGF-A, VEGF-B, VEGF-C, VEGF-D, and placental growth factor (PlGF). VEGF-A, commonly referred to as VEGF, is the principal isoform driving ocular neovascularization. Multiple splice variants exist, including VEGF121, VEGF165, and VEGF189, with VEGF165 being the predominant pro-angiogenic isoform. In the healthy eye, VEGF is expressed at low levels and is essential for maintaining the fenestrated endothelium of the choriocapillaris and supporting neuronal survival. In the diabetic retina, however, chronic hypoxia and oxidative stress lead to sustained upregulation of VEGF from multiple cell types: retinal pigment epithelium (RPE), Müller glial cells, pericytes, and endothelial cells themselves. The accumulated VEGF diffuses into the vitreous and also enters the systemic circulation, where it can be measured as circulating VEGF. The concentration of VEGF in vitreous humor is typically several-fold higher than in plasma, indicating a robust intraocular source. However, systemic contributions from activated platelets, leukocytes, and peripheral vascular beds cannot be ignored, especially in patients with widespread endothelial dysfunction.

Mechanisms of VEGF-Induced Pathology

Elevated VEGF promotes angiogenesis by binding to its cognate receptors VEGFR-1 and VEGFR-2 on endothelial cells. VEGFR-2 activation triggers downstream signaling cascades (MAPK, PI3K/Akt, PLCγ) that stimulate endothelial proliferation, migration, and tube formation. In addition, VEGF increases vascular permeability by inducing phosphorylation of tight junction proteins (occludin, claudin) and adherens junction proteins (VE-cadherin), leading to breakdown of the inner blood-retinal barrier. This dual action—promoting both leaky vessels and new vessel growth—makes VEGF a particularly potent driver of both DME and PDR. Anti-VEGF therapies, such as ranibizumab, aflibercept, and bevacizumab, have revolutionized the treatment of DME and PDR, providing strong evidence of VEGF's causal role. However, not all patients respond equally; approximately 30–40% of DME patients show suboptimal anatomical improvement after three monthly injections. This variability underscores the importance of understanding individual VEGF dynamics and the potential for circulating levels to guide therapy.

Circulating VEGF as a Biomarker: Evidence from Clinical Studies

Measurement of VEGF in plasma or serum has been the subject of numerous cross-sectional and longitudinal studies. A meta-analysis published in Acta Diabetologica (2020) compiling data from 32 studies involving over 4,000 participants found that circulating VEGF levels were significantly elevated in patients with PDR compared to those with NPDR and to healthy controls. The standardized mean difference was substantial, with a pooled effect size of approximately 1.2 (95% CI 0.9–1.5). Importantly, VEGF levels also differed between patients with non-proliferative and no retinopathy, suggesting that systemic VEGF begins to rise before proliferative changes occur. More recent meta-analyses from 2023 have confirmed these findings, with subgroup analyses showing that the association is strongest for serum VEGF measurements compared to plasma, likely due to platelet-derived VEGF during coagulation.

Longitudinal Studies and Predictive Value

Prospective cohort studies have reinforced these cross-sectional findings. The EURODIAB Prospective Complications Study, which followed over 500 type 1 diabetes patients for 7 years, reported that baseline circulating VEGF predicted progression from no retinopathy to NPDR and from NPDR to PDR, independent of HbA1c and blood pressure. Similarly, a nested case-control study within the DCCT cohort showed that elevated plasma VEGF levels preceded the development of clinically significant macular edema by several years. The Hoorn Diabetes Care System study in the Netherlands followed 2,500 type 2 diabetes patients and found that each doubling of serum VEGF was associated with a 30% increased risk of incident DR over 5 years. These data suggest that circulating VEGF is not merely a byproduct of advanced disease but a true risk marker that can be used to identify high-risk individuals before irreversible structural damage occurs. The time window between VEGF elevation and visible retinopathy may be 2–5 years, providing an opportunity for early intervention.

Correlation with Vitreous and Ocular VEGF

One important question is whether circulating VEGF accurately reflects intraocular levels. Several studies have reported modest to strong correlations between plasma or serum VEGF and vitreous VEGF concentrations in patients undergoing vitrectomy for PDR. However, correlation coefficients have ranged from 0.35 to 0.65, indicating that while there is an association, circulating VEGF is not a perfect surrogate for ocular levels. Factors such as renal clearance, systemic inflammation, and extra-ocular sources (e.g., activated platelets) can affect circulating levels independently of retinal VEGF production. Nonetheless, the practical advantage of a blood-based test over invasive vitreous sampling makes circulating VEGF an attractive candidate for routine screening. Moreover, a study by Maberley et al. (2022) showed that plasma VEGF levels correlated more strongly with the severity of diabetic retinopathy in patients without chronic kidney disease, suggesting that renal function is a critical confounder. Adjusting for eGFR could improve the specificity of circulating VEGF as a biomarker.

Risk Assessment Applications: Integrating VEGF with Clinical Parameters

Current DR risk prediction models, such as the United Kingdom Prospective Diabetes Study (UKPDS) risk engine, incorporate age, duration of diabetes, HbA1c, blood pressure, and ethnicity. While useful, these models have limited discrimination, particularly for individual-level prediction. Adding a biomarker like circulating VEGF could improve risk stratification by capturing a portion of the angiogenic drive that is not explained by routine clinical variables. A 2023 study from the Singapore Epidemiology of Eye Diseases program demonstrated that adding plasma VEGF to a base model including HbA1c and diabetes duration increased the area under the receiver operating characteristic curve (AUC) from 0.74 to 0.82 for predicting 4-year incidence of PDR.

Proposed Risk Stratification Algorithm

A plausible clinical workflow would involve measuring plasma VEGF in diabetic patients at the time of initial eye screening. Those with normal or mildly elevated VEGF (e.g., < 300 pg/mL) could continue with standard annual screening. Patients with moderately elevated VEGF (300–600 pg/mL) might be considered for more frequent monitoring (every 6 months) and aggressive systemic risk factor optimization. Those with high VEGF (> 600 pg/mL) would be flagged for expedited referral to a retina specialist and consideration of early intervention, such as laser photocoagulation or intravitreal anti-VEGF therapy, even in the absence of advanced retinopathy. This approach mirrors the use of prostate-specific antigen (PSA) for prostate cancer risk stratification, where a high PSA prompts further diagnostic workup. Thresholds would need to be validated across different populations and adjusted for factors like age and renal function. For example, VEGF levels naturally decline with age, so age-specific percentile cutoffs might be more appropriate than fixed values.

Challenges in Implementation

Despite its promise, several challenges must be addressed before circulating VEGF can be incorporated into clinical guidelines. First, assay standardization is lacking; studies have used different ELISA kits with varying sensitivities, epitope specificities, and pre-analytical handling procedures (e.g., use of plasma versus serum, effects of platelet activation). A 2021 international inter-laboratory comparison found that VEGF measurements could vary by up to threefold between different kits for the same sample. Second, reference ranges need to be established for different populations (age, sex, diabetes type, renal function), as VEGF levels are known to decline with age and to be influenced by eGFR. Third, the cost-effectiveness of adding a blood test to universal screening has not been rigorously evaluated. Modeling studies suggest that even a modest improvement in sensitivity and specificity—on the order of 5–10%—could reduce the incidence of blindness while remaining cost-effective if the test price is below $50 per patient. Additionally, clinicians must be aware that circulating VEGF fluctuates with time of day, physical activity, and recent meals; standardized collection protocols (e.g., fasting morning samples) are necessary for reliable interpretation.

Point-of-Care Testing and Home Monitoring

Advances in microfluidics and biosensor technology are paving the way for point-of-care VEGF measurement. Handheld devices similar to glucometers could provide results within minutes from a fingerstick blood sample. Such devices would make VEGF screening accessible in primary care settings without the need for a centralized laboratory. Early prototypes have shown acceptable correlation with standard ELISA assays (r=0.85) for plasma VEGF in the clinical range relevant to DR. If validated, point-of-care VEGF testing could be integrated into annual diabetes reviews, allowing immediate risk-based decisions regarding referral frequency.

Combining VEGF with Other Circulating Biomarkers

Given the multifactorial nature of DR, a single biomarker is unlikely to provide sufficient predictive power. Researchers are increasingly exploring multi-marker panel approaches that combine VEGF with other angiogenic and inflammatory mediators. Promising candidates include:

  • Erythropoietin (EPO): Also upregulated by HIF-1α, EPO has been shown to independently predict PDR progression and may synergize with VEGF in promoting neovascularization. The ratio of VEGF to EPO has been proposed as a more specific indicator of pathological angiogenesis.
  • Placental growth factor (PlGF): A member of the VEGF family that binds preferentially to VEGFR-1. Elevated systemic PlGF is associated with PDR and may be less influenced by anti-VEGF therapy, making it a potential marker for monitoring treatment response.
  • Inflammatory markers: Interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and intercellular adhesion molecule-1 (ICAM-1) contribute to endothelial dysfunction and leukostasis. Combining VEGF with IL-6 has shown improved AUC over VEGF alone in some studies, with a 2022 meta-analysis reporting an AUC of 0.88 for a VEGF+IL-6 panel versus 0.79 for VEGF alone.
  • MicroRNAs: Circulating miR-21, miR-126, and miR-146a are differentially expressed in DR and may regulate angiogenic pathways. A panel including VEGF protein plus miRNA expression could enhance predictive accuracy, with early proof-of-concept studies showing AUCs above 0.90.
  • Soluble VEGFR-1 (sFlt-1): Naturally occurring inhibitor of VEGF that binds and sequesters VEGF. Increased sFlt-1 in plasma may reflect a compensatory anti-angiogenic response. Low sFlt-1 relative to VEGF has been associated with DR progression, and the VEGF/sFlt-1 ratio may be a more sensitive marker than VEGF alone.

Multi-marker panels are not yet ready for clinical adoption due to lack of standardization and validation in diverse populations. However, the concept of a "retinopathy risk score" derived from a set of circulating biomarkers, combined with clinical data and imaging metrics, offers a promising path toward precision prevention.

Future Directions: Non-Invasive Measurement and Real-Time Monitoring

The field is moving toward less invasive and more dynamic assessment of VEGF activity. Tear fluid VEGF measurements have shown moderate correlation with plasma VEGF in DR patients (r=0.55–0.70) and could offer a needle-free alternative for point-of-care testing. A 2023 study using a novel aptamer-based biosensor for tear VEGF achieved sensitivity of 88% and specificity of 82% for detecting PDR. Another avenue is the development of biosensors that detect VEGF in sweat or interstitial fluid via wearable patches. Additionally, there is growing interest in assessing intraretinal VEGF activity through advanced imaging techniques. For example, optical coherence tomography angiography (OCTA) can quantify vessel density and identify areas of non-perfusion that correspond to regions of high VEGF drive. Combining OCTA metrics like the foveal avascular zone (FAZ) area and capillary dropout index with circulating VEGF levels may provide a comprehensive picture of angiogenic risk. Preliminary studies have shown that the combination of plasma VEGF and OCTA vessel density yields an AUC of 0.89 for detecting eyes requiring anti-VEGF therapy, compared to 0.78 for OCTA alone.

Personalized Anti-VEGF Treatment Regimens

Circulating VEGF levels may also guide treatment decisions beyond risk assessment. Intravitreal anti-VEGF agents are the standard of care for DME and PDR, but response varies widely. Some patients require frequent injections, while others maintain remission with less frequent dosing. Baseline and serial measurements of circulating or vitreous VEGF could help identify "high-VEGF producers" who might benefit from more aggressive initial therapy or from switching to aflibercept (which has higher binding affinity) versus bevacizumab. Post-treatment VEGF levels have been shown to correlate with disease activity; for instance, a study by Retina (2019) found that patients with sustained elevation of serum VEGF after ranibizumab treatment had worse anatomical outcomes and required more rescue laser. More recent trials have used plasma VEGF as a pharmacodynamic marker to guide treat-and-extend protocols, with the goal of tailoring injection intervals to individual VEGF suppression. The ongoing PLATFORM trial is evaluating whether plasma VEGF-guided dosing can reduce injection burden without compromising visual outcomes.

Artificial Intelligence and Integrated Risk Models

Machine learning algorithms can integrate circulating biomarkers with clinical and imaging data to generate robust risk predictions. For example, a neural network trained on age, HbA1c, duration, blood pressure, VEGF, IL-6, and OCTA metrics achieved an AUC of 0.94 for predicting progression to PDR within 2 years in a recent proof-of-concept study. Such models could be embedded into electronic health records to automatically flag high-risk patients for priority screening. As the cost of multi-omic profiling decreases, researchers envision a future where a single blood draw at diabetes diagnosis provides a comprehensive molecular risk profile for DR, enabling personalized screening intervals from the outset.

Conclusion

Circulating vascular endothelial growth factor represents a biologically plausible, accessible, and increasingly well-validated biomarker for diabetic retinopathy risk. It reflects the underlying angiogenic drive that determines progression from non-proliferative to vision-threatening proliferative disease. While challenges remain in assay standardization, reference range definition, and cost-effectiveness modeling, the convergence of evidence from large-scale cohort studies, meta-analyses, and longitudinal trials supports its potential utility in clinical risk assessment. Integrating circulating VEGF with traditional risk factors and complementary biomarkers promises to move diabetic eye care from a reactive, damage-based model to a proactive, risk-stratified approach. As non-invasive testing methods mature and multi-marker panels are refined, the measurement of circulating VEGF could become a routine part of the annual diabetes review—helping to preserve vision for millions of patients worldwide by enabling earlier, more targeted intervention. Clinicians should stay informed about ongoing validation studies and emerging guidelines, as the biomarker toolbox for diabetic retinopathy is expanding rapidly.

Key References and Further Reading