Blood Cell Count-Based Inflammatory Markers Exhibit Superior Association with Diabetic Peripheral Neuropathy Compared to Protein-Based Markers.

BACKGROUND: Diabetic peripheral neuropathy (DPN) is a prevalent and disabling complication of type 2 diabetes mellitus, contributing to poor quality of life and increased healthcare burden. Chronic low-grade inflammation has been proposed as a key contributor to the pathogenesis of DPN. While various inflammatory markers have been studied, their diagnostic utility remains unclear, particularly when comparing protein-based markers and blood cell count-derived ratios. OBJECTIVE: This study aimed to investigate whether blood cell count-based inflammatory markers, such as the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), are more strongly associated with DPN compared to protein-based markers, including interleukin-1 receptor antagonist (IL-1Ra) and high-sensitivity C-reactive protein (hsCRP). METHODS: In this cross-sectional study, 137 patients with type 2 diabetes were recruited. DPN was defined as a Michigan Neuropathy Screening Instrument (MNSI) score ≥2. All participants underwent physical examinations, questionnaire assessments, and laboratory evaluation of inflammatory markers. RESULTS: NLR was significantly elevated in the DPN group compared to controls (P < 0.05), while IL-1Ra and hsCRP levels showed no significant differences. Participants in the highest NLR tertile exhibited a higher DPN prevalence (19.0%) than those in the lowest tertile (8.8%). Multivariate linear regression identified NLR and HbA1(c) as independent predictors of MNSI scores. CONCLUSION: Our findings demonstrate that the NLR, an inflammation-related marker derived from peripheral blood cell counts, is significantly associated with DPN, whereas protein-based markers did not demonstrate clear associations. These findings suggest that NLR may serve as a simple, cost-effective biomarker for identifying patients at risk for DPN. Further longitudinal studies are warranted to clarify causal relationships and evaluate its prognostic value.