Sensing Biomechanical Alterations in Red Blood Cells of Type 1 Diabetes Patients: Potential Markers for Microvascular Complications

Abstract

In physiological conditions, red blood cells (RBCs) demonstrate remarkable deformability, allowing them to undergo considerable deformation when passing through the microcirculation. However, this deformability is compromised in Type 1 diabetes mellitus (T1DM) and related pathological conditions. This study aims to investigate the biomechanical properties of RBCs in T1DM patients, focusing on identifying significant mechanical alterations associated with microvascular complications (MCs). We conducted a case-control study involving 38 T1DM subjects recruited from the Diabetes Care Unit at Fondazione Policlinico Gemelli Hospital, comprising 22 without MCs (control group) and 16 with MCs (pathological group). Atomic Force Microscopy was employed to assess RBC biomechanical properties in a liquid environment. We observed significant RBC stiffening in individuals with MCs, particularly during large indentations that mimic microcirculatory deformations. Univariate analysis unveiled significant differences in RBC stiffness (median difference 0.0006 N/m, p = 0.012) and RBC counts (median difference -0.39 × 10¹²/L, p = 0.009) between the MC and control groups. Bivariate logistic regression further demonstrated that combining these parameters could effectively discriminate between MC and non-MC conditions, achieving an AUC of 0.82 (95% CI: 0.67-0.97). These findings reveal the potential of RBC biomechanical properties as diagnostic and monitoring tools in diabetes research. Exploring RBC mechanical alterations may lead to the development of novel biomarkers, which, in combination with clinical markers, could facilitate the early diagnosis of diabetes-related complications.

Keywords: Atomic Force Microscopy; biomarkers; biomechanics; blood biochemistry; diabetes; microvascular complications; red blood cells.

Figure 1

Representative force–distance (FD) cycles (blue: approach phase; black: retraction phase) acquired on a red blood cell obtained from a pathological subject (A). The cyan shaded area represents dissipated energy and hysteresis, while the red continuous line represents the best fit of the curve using the Sneddon model. The dashed black oblique line represents the slope (S) measured in N/m of the FD approach curve, which also provides information on the cell stiffness. A schematic view of the AFM tip indenting the cell is shown in the upper right corner. Schematic representation of the design of the experiment (B).

Figure 2

Heatmap of clinical (duration), biochemical (red blood cell indices, hematocrit, lipid, liver, glucose, and renal panel), and mechanical parameters. To enable a simultaneous visualization of all parameters, the measured values are normalized in terms of z-scores. The gray color indicates missing values, which can be considered random. Statistical significance is indicated as follows: * p < 0.05, ** p < 0.01, ∙ p < 0.1 and ns (not significant).

Figure 3

Box plot analysis of the significant variables including plasma triglyceride levels (A), red blood cell count (B), mean corpuscular volume (C), and AFM stiffness (D).

Figure 4

Cullen and Frey Plot showing the potential distribution shape of E values for RBCs extracted from complicated (green) and non-complicated subjects (gold). The dotted line indicates the plot region corresponding to a log-normal distribution, the dashed line corresponds to the Gamma distribution, and the shaded gray region corresponds to the family of beta distributions.

Figure 5

Receiver Operating Characteristic (ROC) curves illustrating the diagnostic performance of selected clinical, biochemical, and mechanical variables (left). The corresponding values of the area under the curve (AUC) with 95% confidence intervals are presented on the (right), providing a comprehensive assessment of each biomarker’s classification performance in predicting microvascular complications in patients with Type 1 diabetes mellitus.

Figure 6

ROC and AUC analysis corresponding to the combination of the RBC stiffness and count (A); bivariate logistic probability function of MC occurrence according to the value of the two selected circulating biomarkers (B).

Figure 7

Correlation analysis between mechanical (x-axis) and demographic, clinical, and biochemical parameters in T1DM patients with MCs (A), without MCs (B), and in all patients recruited in the study (C).

Figure 8

Scatter plot of selected circulating lipid markers in MC patients as a function of mechanical parameters. Triglycerides show a positive correlation with stiffness (A) and negative correlations with both dissipation (B) and hysteresis (C). HDL displays a positive correlation with hysteresis (D). The shaded areas represent the 95% confidence intervals, and the dashed lines indicate the best-fit regression lines. Data points correspond to individual MC patients.