Immune biomarkers as early indicators of renal damage in type 1 diabetic children: A step toward translational medicine

Abstract

An article recently published in the World Journal of Diabetes, provides valuable insights into using immune biomarkers to identify renal damage in pediatric patients with newly diagnosed type 1 diabetes (T1D). Although these findings are promising, clinical translation of these immune markers into routine diagnostics and preventive care remains challenging. In this letter, we propose building on the authors’ work by exploring the integration of immune biomarkers into a more comprehensive dynamic risk stratification model for early renal injury. Combining immune system indicators with metabolic and genetic factors could enhance the predictive accuracy and support more personalized interventions. Longitudinal studies are needed to evaluate temporal changes in immune biomarkers and their association with long-term renal outcomes in children with T1Ds. Immunomodulatory therapies targeting early immune dysfunction can prevent or slow the progression of diabetic nephropathy. By incorporating these aspects, we hope to translate immune biomarkers from research into practical clinical tools, ultimately improving patient outcomes and reducing the burden of kidney-related complications in pediatric diabetes.

Key Words: Type 1 diabetes; Immune biomarkers; Renal damage; Risk stratification; Translational medicine

Core Tip: Immune biomarkers play a crucial role in the early detection of renal damage in children with type 1 diabetes. This letter highlights the need for integrating immune indicators into a dynamic risk stratification model, combining metabolic and genetic factors for improved predictive accuracy. Additionally, we emphasize the importance of longitudinal studies to assess biomarker temporal dynamics and explore immunomodulatory strategies for early intervention. Advancing these approaches could enhance the clinical utility of immune biomarkers, facilitating their translation into routine diagnostics and personalized treatment strategies for diabetic nephropathy prevention.

TO THE EDITOR

Diabetic nephropathy (DN) is a progressive complication of type 1 diabetes (T1D) that begins in childhood; however, its early detection remains challenging[1,2]. A recent article, “Systemic immune indicators for predicting renal damage in newly diagnosed type 1 diabetic children”[3], published in the World Journal of Diabetes, provided valuable insights into the role of immune biomarkers in identifying renal impairment at an early stage. The authors highlighted the systemic inflammatory markers that correlate with renal dysfunction, underscoring the involvement of immune dysregulation in DN pathogenesis.

Although this study represents a significant step forward, further research is required to translate these findings into clinical practice. Key areas of exploration include integrating immune biomarkers into routine risk stratification, conducting longitudinal studies to assess biomarker dynamics, and investigating immunomodulatory interventions. Understanding the evolution of immune dysregulation over time and the potential for targeted interventions to mitigate renal damage in patients with T1D remains a critical research avenue. In this letter, we build on these perspectives, emphasizing the translational potential of immune biomarkers in guiding early intervention strategies for DN prevention.

POTENTIAL OF IMMUNE BIOMARKERS IN EARLY RISK STRATIFICATION

The early identification of children with T1D who are at high risk of developing DN is crucial for implementing timely interventions[4,5]. Cao et al[3] provided compelling evidence that systemic immune markers such as the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) correlate with early renal impairment. These findings align with growing evidence suggesting that immune dysregulation plays a pivotal role in DN pathogenesis, even before traditional markers such as albuminuria appear. In addition to NLR and PLR, other immune-related indicators, such as the monocyte-to-lymphocyte ratio, systemic immune-inflammation index, and specific cytokine levels (e.g., TIMP-1, MMP-9, CD4, and CD8), have been proposed as early predictors of renal injury in diabetes[6-8].

Despite their potential, immune biomarkers have yet to be fully integrated into routine clinical risk assessments for DN. Their predictive value can be enhanced by combining with other established indicators, such as estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR), to develop a more comprehensive risk stratification model[9,10]. Additionally, machine learning approaches can refine the predictive power of immune markers, enabling personalized risk assessments and early intervention strategies[11,12].

Longitudinal studies are required to assess these biomarkers' stability and temporal evolution in patients with T1D. Fluctuations in immune markers preceding renal function decline may offer a critical window for early therapeutic interventions. Investigating the interactions of these markers with other inflammatory pathways, oxidative stress markers, and metabolic parameters may reveal novel therapeutic targets.

Incorporating immune biomarkers into clinical practice could transform DN management by shifting the focus from late-stage detection to proactive prevention. Future studies should validate these biomarkers in larger multicenter cohorts and explore their roles in guiding individualized treatment strategies.

LONGITUDINAL STUDIES AND TEMPORAL DYNAMICS OF IMMUNE MARKERS

Understanding the temporal evolution of immune biomarkers in T1D and their relationship with renal deterioration is critical for establishing clinical utility[13]. Although Cao et al[3] identified systemic immune indicators as potential early predictors of DN, cross-sectional data alone cannot capture the dynamic interplay between immune dysregulation and progressive renal impairment. Longitudinal studies are essential to determine whether fluctuations in markers such as NLR[14,15] and PLR[16] consistently precede measurable declines in kidney function, providing an opportunity for timely intervention.

A key question remains whether changes in immune markers reflect transient inflammatory states or a sustained pathogenic process leading to DN. Serial measurements of immune biomarkers coupled with traditional renal function tests (eGFR and UACR) can reveal distinct biomarker trajectories associated with the different stages of DN progression. For instance, a persistent elevation in NLR or PLR over time might be a stronger predictor of renal dysfunction than an isolated measurement. Furthermore, integrating these biomarkers with novel omics approaches such as transcriptomic or metabolomic profiling could improve our understanding of immune-mediated renal damage in patients with T1D.

Incorporating high-dimensional data such as genetic predispositions and metabolic profiles could allow for more nuanced risk modeling. Transcriptomic and metabolomic data may help identify the critical regulatory pathways underlying immune-mediated renal damage in T1D. Machine learning models applied to longitudinal and multimodal datasets can improve the identification of early disease phenotypes and inform adaptive monitoring strategies.

External factors, such as glycemic variability, infections, and pubertal hormonal changes, may influence the behavior of immune biomarkers over time. Therefore, longitudinal studies should control for these confounding factors to elucidate the actual predictive capacity of these markers. Future multicenter prospective studies are needed to validate these findings, establish standardized cutoff values, and assess responsiveness to interventions.

EXPLORING IMMUNOMODULATORY STRATEGIES FOR EARLY INTERVENTION

Given the emerging role of immune biomarkers in predicting renal damage in newly diagnosed patients with T1D, the next step is to explore immunomodulatory strategies that could mitigate inflammation-driven kidney injury. Systemic immune indicators such as the NLR and PLR serve as early warning signals. Targeted interventions that modulate immune responses can delay or prevent the onset of DN.

A promising approach involves the use of anti-inflammatory therapies to restore immune homeostasis. Agents targeting cytokine pathways, such as interleukin 6 or tumor necrosis factor alpha inhibitors, have shown efficacy in other inflammatory conditions and may offer renoprotective effects in T1D by reducing systemic inflammation[17,18]. Low-dose immunosuppressants such as mycophenolate mofetil have been investigated for their potential to preserve renal function in autoimmune kidney diseases[19,20]. However, identifying patients who would benefit the most from these treatments without compromising their immune defenses remains challenging.

Beyond pharmacological approaches, lifestyle modifications and metabolic interventions may influence immune-mediated kidney injury. Dietary interventions such as anti-inflammatory or ketogenic diets have been proposed to reduce oxidative stress and modulate immune responses in diabetes[21]. Emerging evidence indicates that gut microbiota composition significantly influences systemic inflammation and autoimmunity[22]. Probiotic and prebiotic therapies to restore the gut-immune balance may offer a novel approach to mitigating immune-driven renal damage.

Integrating immune biomarker profiling with metabolic, genetic, and microbiome data can provide a framework for precision medicine. This approach allows clinicians to identify high-risk individuals based on unique immunological signatures and tailor preventive strategies accordingly. Future randomized controlled trials should evaluate the efficacy of these interventions in modifying immune trajectories and improving renal outcomes in pediatric T1D.

CONCLUSION AND FUTURE PERSPECTIVES

The study of systemic immune indicators as predictors of renal damage in newly diagnosed children with T1D provides a significant step toward early risk stratification and precision medicine. Identifying immune markers such as the NLR and PLR is a promising approach for identifying high-risk individuals before irreversible kidney damage occurs. However, translating these findings into clinical practice requires further validation through longitudinal studies and mechanistic investigations.

Future research should focus on establishing standardized immune biomarker thresholds for risk assessment, integrating multi-omics data to refine predictive models, and exploring immunomodulatory interventions to mitigate renal complications. The interplay between immune dysregulation, metabolic stress, and genetic susceptibility in T1D-related DN remains critical. Prospective clinical trials should assess the efficacy of anti-inflammatory therapies, microbiota-targeted interventions, and personalized treatment strategies based on immune profiling. Ongoing early intervention studies in pediatric DN offer valuable opportunities to incorporate immune biomarker profiling into clinical trial designs. Evaluating how immune signatures change in response to early treatment could validate their prognostic value and facilitate more tailored and timely interventions for high-risk children.

However, translating immune biomarkers into routine clinical care faces several barriers, including variability in laboratory assays, limited cost-effectiveness data, and the absence of universally accepted thresholds. Overdiagnosis and overtreatment remain concerns, especially when considering the use of immunomodulatory agents in pediatric populations. Any clinical implementation must be guided by rigorous risk-benefit analysis and long-term safety monitoring to ensure that early interventions improve outcomes without introducing new harms. Collaborative efforts among researchers, clinicians, and healthcare systems are the key to optimizing the clinical utility of these promising biomarkers.