Introduction: The Growing Need for Non‑Invasive Biomarkers in Diabetic Nephropathy

Diabetic nephropathy (DN) remains one of the most serious microvascular complications of diabetes mellitus and the leading cause of end‑stage renal disease (ESRD) worldwide. Despite major advances in glycemic control and renin‑angiotensin‑aldosterone system (RAAS) blockade, many patients continue to progress toward kidney failure at an alarming rate. Early detection and accurate monitoring of disease progression are critical to guide therapeutic interventions and improve long‑term outcomes. Traditional markers such as estimated glomerular filtration rate (eGFR) and urinary albumin excretion (UAE) have well‑known limitations—they lack sensitivity for early fibrotic changes and may not adequately reflect ongoing tissue damage. In recent years, the search for reliable, non‑invasive biomarkers has intensified. Among the many candidates, circulating transforming growth factor‑beta 1 (TGF‑β1) has emerged as a particularly promising indicator of renal fibrotic activity. TGF‑β1 is a multifunctional cytokine that plays a central role in extracellular matrix (ECM) accumulation and fibrosis—the hallmark pathological process underlying DN. Accumulating evidence strongly suggests that elevated circulating TGF‑β1 levels correlate with declining renal function and may serve as an early warning signal before irreversible structural damage occurs. This article reviews the biological rationale, clinical evidence, practical advantages, limitations, and future prospects of using circulating TGF‑β1 as a biomarker for diabetic nephropathy progression, with the aim of providing clinicians and researchers with a comprehensive, up‑to‑date perspective.

Pathophysiology of TGF‑β1 in Diabetic Nephropathy: From Signaling to Fibrosis

To understand why TGF‑β1 may serve as a useful biomarker, it is essential to first appreciate its multifaceted pathophysiological role in the kidney. Under normal physiological conditions, TGF‑β1 is a key regulator of cell proliferation, differentiation, apoptosis, and immune homeostasis. It exists in three isoforms (TGF‑β1, TGF‑β2, TGF‑β3), with TGF‑β1 being the most abundant and best studied in renal fibrosis. In the healthy kidney, TGF‑β1 is produced by glomerular mesangial cells, tubular epithelial cells, podocytes, and resident immune cells at low levels, maintaining ECM turnover in a balanced state. However, in the diabetic milieu—characterized by hyperglycemia, advanced glycation end‑products (AGEs), oxidative stress, mechanical stretch from hyperfiltration, and activation of the RAAS—TGF‑β1 expression becomes chronically and pathologically upregulated. This sustained elevation drives the transformation of tubular epithelial cells and pericytes into myofibroblasts through processes known as epithelial‑to‑mesenchymal transition (EMT) and pericyte‑to‑myofibroblast transition. Myofibroblasts are hyper‑proliferative, highly contractile, and produce excessive amounts of ECM proteins such as collagen types I, III, and IV, fibronectin, and laminin. Over time, these matrix components accumulate in the glomerular mesangium and tubulointerstitium, leading to glomerulosclerosis and tubulointerstitial fibrosis—the structural lesions that define progressive DN.

Beyond direct matrix deposition, TGF‑β1 also orchestrates a broader fibrotic program. It suppresses matrix metalloproteinases (MMPs) and upregulates tissue inhibitors of metalloproteinases (TIMPs), further tipping the balance toward ECM accumulation rather than degradation. TGF‑β1 induces podocyte injury, detachment, and apoptosis—a key step in the development of proteinuria and loss of glomerular filtration barrier integrity. The cytokine also promotes inflammation by stimulating other pro‑fibrotic factors such as connective tissue growth factor (CTGF/CCN2) and platelet‑derived growth factor (PDGF), creating a self‑reinforcing cycle. Additionally, TGF‑β1 activates Smad‑dependent and Smad‑independent signaling pathways (e.g., MAPK, PI3K/Akt, Rho‑like GTPases) that converge on fibrotic gene expression. Given these pleiotropic effects, TGF‑β1 is considered a master switch in the fibrotic cascade. Measuring its concentration in the bloodstream may therefore offer a window into the ongoing fibrotic activity within the kidneys—potentially earlier than changes in eGFR or albuminuria become apparent.

Clinical Evidence Linking Circulating TGF‑β1 to DN Progression

Numerous cross‑sectional and longitudinal studies have examined the association between circulating TGF‑β1 levels and markers of DN severity. A seminal study by Sharma et al. (J Am Soc Nephrol, 1997) first demonstrated that patients with type 2 diabetes and overt nephropathy had significantly higher serum TGF‑β1 concentrations compared to those without nephropathy or healthy controls. Subsequent investigations across diverse ethnic populations confirmed that elevated TGF‑β1 correlates with increased UAE and reduced eGFR. A comprehensive meta‑analysis of 18 studies published in Diabetologia (2021) reported a pooled correlation coefficient of −0.43 between TGF‑β1 and eGFR, and +0.51 between TGF‑β1 and proteinuria, indicating a moderate but consistent relationship. More recent work has shown that circulating TGF‑β1 levels are elevated even in normoalbuminuric patients with diabetes who later develop microalbuminuria, suggesting a potential role in predicting early‑stage disease.

Longitudinal Data and Predictive Value

Longitudinal data further support a predictive role for TGF‑β1. In a prospective cohort of 245 patients with type 2 diabetes followed for 5 years, baseline TGF‑β1 levels independently predicted a >30% decline in eGFR after adjustment for traditional risk factors including HbA1c, blood pressure, baseline eGFR, and albuminuria. Similarly, a study by Wong et al. (Kidney Int, 2013) found that patients in the highest tertile of serum TGF‑β1 had a 2.4‑fold higher risk of progression to ESRD compared to the lowest tertile, even after multivariable adjustment. These associations were particularly strong in those with established macroalbuminuria. Importantly, TGF‑β1 levels also appear to change in response to interventions: RAAS blockers, sodium‑glucose cotransporter‑2 (SGLT2) inhibitors, and certain anti‑fibrotic agents have been shown to reduce circulating TGF‑β1 in parallel with improvements in renal outcomes. For instance, a randomized controlled trial of losartan in type 2 diabetic patients with nephropathy demonstrated a significant reduction in serum TGF‑β1 over 6 months that correlated with proteinuria reduction. This dynamic responsiveness strengthens the case for TGF‑β1 as a monitoring tool.

Association with Histological Severity

Beyond clinical parameters, TGF‑β1 levels have also been correlated with renal biopsy findings. In a study of 60 patients with type 2 diabetes who underwent kidney biopsy, serum TGF‑β1 positively correlated with mesangial expansion, glomerulosclerosis score, and tubulointerstitial fibrosis severity. Patients with higher TGF‑β1 levels had more advanced histological changes even when eGFR was still above 60 mL/min/1.73 m², highlighting the biomarker's potential to detect subclinical fibrosis. This histological correlation provides a strong link between the circulating biomarker and the underlying pathological process.

Advantages of Circulating TGF‑β1 as a Biomarker

  • Non‑invasive and readily accessible: TGF‑β1 can be measured in serum or plasma using commercially available enzyme‑linked immunosorbent assays (ELISAs), requiring only a standard venipuncture. This makes it suitable for routine clinical monitoring in primary care and nephrology settings without the need for invasive kidney biopsy, which carries risk and is infrequently repeated.
  • Early detection potential: Because TGF‑β1 elevation precedes overt histological fibrosis, it may detect incipient fibrotic activity before significant loss of renal function occurs. In normoalbuminuric patients with diabetes, higher TGF‑β1 has been associated with subsequent development of microalbuminuria over 2–4 years of follow‑up, suggesting a possible role in identifying early‑stage disease when interventions are most effective.
  • Monitoring therapeutic efficacy: Serial measurement of TGF‑β1 could help assess whether a given treatment is effectively dampening fibrotic pathways. A decline in TGF‑β1 after initiation of therapy may indicate a favorable response, while persistently elevated levels could signal the need for alternative or additional interventions. This pharmacodynamic application is particularly relevant as new anti‑fibrotic drugs enter clinical trials.
  • Risk stratification beyond traditional markers: Integrating TGF‑β1 into a multimarker panel could improve risk prediction beyond traditional metrics such as eGFR and albuminuria. Patients with high TGF‑β1 despite controlled blood pressure and glucose may represent a high‑risk phenotype that requires more aggressive management, including consideration of newer agents like SGLT2 inhibitors or finerenone.

Limitations and Challenges: Barriers to Routine Clinical Adoption

Despite its promise, several significant obstacles hinder the routine clinical adoption of circulating TGF‑β1 as a biomarker. First, TGF‑β1 is not kidney‑specific; it is produced by many cell types throughout the body, including platelets, macrophages, and various epithelial cells. Systemic inflammation, malignancy, liver fibrosis, pulmonary fibrosis, and infection can all elevate TGF‑β1 levels, confounding interpretation in a diabetic population that frequently has comorbid conditions. Proper patient selection, careful clinical assessment for concurrent diseases, and concomitant measurement of inflammatory markers (e.g., CRP, IL‑6, TNF‑α) may partially mitigate this issue but adds complexity.

Second, assay standardization remains a significant challenge. Circulating TGF‑β1 is primarily measured in its latent, inactive form bound to latency‑associated peptide (LAP) and latent TGF‑β binding proteins (LTBPs). Detection requires acid activation to release mature TGF‑β1, and different activation protocols—varying in acid type, pH, incubation time, and temperature—yield divergent results. Additionally, commercial ELISA kits from different manufacturers show variable sensitivity and specificity, making it difficult to establish universal cut‑off values. The pre‑analytical phase introduces further variability: platelet degranulation during venipuncture and sample handling can release large amounts of TGF‑β1 from platelet α‑granules, leading to falsely elevated readings. Strict protocols—such as using platelet‑poor plasma (preferably citrate‑anticoagulated), immediate centrifugation at 4°C within 30 minutes, and avoiding repeated freeze‑thaw cycles—are essential but are not uniformly applied across clinical laboratories or research studies. Without harmonization, comparing results across centers becomes problematic.

Third, the relationship between TGF‑β1 and kidney function is not linear across all disease stages. In very advanced DN (e.g., eGFR < 20 mL/min/1.73 m²), TGF‑β1 levels may plateau or even decline due to reduced renal clearance, altered systemic clearance, or changes in production as the kidney parenchyma is replaced by fibrotic tissue. This diminishes the biomarker's utility as a progression marker in late stages. Additionally, TGF‑β1 measured in the circulation may not fully reflect intrarenal TGF‑β1 activity, which is highly compartmentalized and subject to local regulation by binding proteins, receptors, and endogenous inhibitors such as decorin and BMP‑7. Urinary TGF‑β1—derived directly from renal tubular cells through both filtration and local secretion—has been proposed as a more kidney‑specific alternative. However, urinary measurements are challenged by dilution (requiring correction for creatinine) and degradation in the urine, and they correlate only moderately with serum levels. Some studies suggest that the urinary TGF‑β1/creatinine ratio may better reflect tubular injury, but standardization is even less advanced than for serum assays.

Finally, most clinical studies to date have been relatively small, cross‑sectional, or retrospective, with heterogeneous populations varying in diabetes type, duration, ethnicity, and renal function. Follow‑up periods have often been short, and few studies have assessed TGF‑β1 in large, diverse, prospective cohorts with rigorous exclusion of confounders. Large‑scale, multi‑center prospective studies using standardized assays are urgently needed to establish clinically meaningful thresholds, define reference ranges for different stages of kidney disease (including adjustment for age and sex), and validate the additive predictive value of TGF‑β1 over existing biomarkers such as eGFR, urinary albumin‑to‑creatinine ratio (UACR), and other emerging markers (e.g., kidney injury molecule‑1, neutrophil gelatinase‑associated lipocalin). The National Kidney Foundation’s Kidney Disease Outcomes Quality Initiative (KDOQI) and the FDA’s Biomarker Qualification Program have yet to endorse TGF‑β1 for DN, reflecting the need for more robust evidence before clinical implementation can be recommended.

Future Directions: Combinatorial Panels and Technological Advances

Given the complexity of diabetic nephropathy, it is unlikely that a single biomarker will capture the full spectrum of disease progression. Instead, a panel of complementary markers may offer greater diagnostic and prognostic accuracy. TGF‑β1 could be combined with other fibrosis‑related molecules such as CTGF (CCN2), fibronectin, collagen IV fragments (e.g., P‑IV‑NP), and microRNAs known to regulate fibrosis (e.g., miR‑21, miR‑29, miR‑192). For instance, urinary exosomal TGF‑β1 mRNA has shown promise in early DN detection (J Diabetes Res, 2020). Similarly, circulating levels of bone morphogenetic protein‑7 (BMP‑7), a natural antagonist of TGF‑β1 signaling, may provide a more balanced view of fibrotic activity; a low TGF‑β1/BMP‑7 ratio could indicate a pro‑fibrotic state. Combining TGF‑β1 with markers of tubular injury (e.g., KIM‑1, NGAL) could capture both fibrotic and acute damage pathways.

Advancements in proteomics and metabolomics have also identified novel TGF‑β1‑related pathways. For example, the ratio of TGF‑β1 to its soluble receptor endoglin (sEng) has been proposed as a marker of endothelial‑mesenchymal transition, which contributes to peritubular capillary rarefaction in advanced DN. Additionally, measuring specific LTBP isoforms (e.g., LTBP‑1, LTBP‑4) may help distinguish between active and total TGF‑β1, providing a more functional readout. Emerging technologies such as single‑molecule arrays (Simoa) and digital ELISA offer improved sensitivity to detect low‑level changes, which may be particularly helpful in early‑stage disease. Machine learning algorithms that integrate TGF‑β1 with clinical variables (age, BMI, blood pressure, HbA1c, eGFR trajectory, UACR) and other biomarkers could produce dynamic risk models that update over time, enabling personalized treatment adjustments.

From a therapeutic standpoint, TGF‑β1 is not only a biomarker but also a potential therapeutic target. Several anti‑TGF‑β1 agents—including monoclonal antibodies (e.g., fresolimumab), small molecule inhibitors of TGF‑β receptor I kinase (e.g., galunisertib), and antisense oligonucleotides—have been evaluated in clinical trials for fibrotic diseases including diabetic kidney disease. Monitoring TGF‑β1 levels during such therapies could serve as a pharmacodynamic indicator, helping to guide dosing and identify responders early. A decline in TGF‑β1 within weeks of treatment initiation might predict long‑term renal protection, whereas a lack of decline could prompt dose escalation or therapy switch. However, systemic TGF‑β1 inhibition carries risks of immune dysregulation, autoimmunity, and potential tumor promotion, underscoring the need for carefully designed studies that monitor both efficacy and safety. Localized delivery strategies, such as peptide‑based inhibitors or gene therapy targeting the kidney, may eventually circumvent systemic effects.

Conclusion

Circulating TGF‑β1 offers a biologically plausible and clinically accessible window into the fibrotic processes that drive diabetic nephropathy progression. A substantial body of evidence links elevated serum TGF‑β1 to worsening albuminuria, declining eGFR, increased risk of ESRD, and more severe histological fibrosis. The cytokine’s ability to reflect early fibrotic remodeling before significant functional loss makes it a potentially valuable tool for early detection, risk stratification, and therapeutic monitoring. Nevertheless, important limitations—including non‑specificity, assay variability, pre‑analytical challenges, and the need for standardized protocols—must be addressed before TGF‑β1 can be integrated into routine clinical practice. Future efforts should focus on establishing harmonized measurement guidelines through consensus initiatives among professional societies, conducting large‑scale prospective validation studies in diverse populations, and exploring combinatorial biomarker panels that leverage TGF‑β1 alongside other fibrotic and inflammatory markers. With continued research and technological refinement, circulating TGF‑β1 may ultimately help identify high‑risk patients earlier, personalize treatment strategies, accelerate the development of targeted anti‑fibrotic therapies, and improve outcomes for the millions of patients worldwide living with diabetic nephropathy.