4. Platelet to Lymphocyte Ratio (P/L)
Platelets to lymphocytes ratio (PLT/Ly), simultaneously with neutrophiles to lymphocytes ratio (Neu/Ly), together with complete blood count (CBC), are bioparameters proposed in the routine laboratory practice [
16,
22].
The same authors proposed the reference intervals for PLTs: PLT (count) – 142-424; MPV: 6.8 – 10.8 (fl.). In the further routine laboratory practice, simultaneous anisocytosis for PLTs and RBCs could be determined, improving the prognostic biomarkers for DM2.
Table 1.
Thrombocytes (Platelets - PTs) reference data.
Table 1.
Thrombocytes (Platelets - PTs) reference data.
PLTs – platelets count |
140 - 440 x 109 /L |
MPV - mean platelet volume (MPV) |
7.80 – 11.0 fL |
PDW - platelet distribution width |
15,5% - 30,5% |
The precise studies of DM2 pathological states (at the level of morphological, cytochemical and ultrastructural methods), might be useful for creation and development of new DM2 treatment medicines and strategies, leading to reduced PLTs hyperactivation in development of DM2 (e.g. treatment of PLTs hyperactivity with oleic acid (OA); [
4,
23,
24].
The physiological mechanisms that underline PLTs homeostasis under the influence of OA remain unclear. OA has potential antithrombotic effects, suppressing the PLTs hyperactivation. OA also inhibits PLTs aggregation, thrombocyte granule release and calcium “mobilization”. Additionally, OA suppresses the spread of the PLTs on fibrinogen, delaying further the development of arterial thrombosis. New studies (Zhou et al., 2023) on OA as a probable antiplatelet activation “hyperactivation” drug of clinical significance for prevention and treatment of DM2, could be further useful in diabetology.
5. Hematological/Hematometrical Investigations, Related to Metabolic/Glycemic Control of DM2
Some authors teams pointed out that the parameter of mean platelet volume (MPV) is a cost-effective tool in primary health care of diabetic patients. The same authors obtained interesting results related to the metabolic/glycemic control of DM: as the glycemic control of DM2 improves, MPV and HbA1c in patients decrease. Improving PLTs activities and functions, the regular glycemic control of diabetics may delay the vascular complications of DM.
The hematometrical laboratory results obtained could be further explored in the clinical practice, as well as in creation of new computational modelling of platelets.
The MPV in diabetics was 11.3 ± 1.0 fl, compared to 9 ± 0.6 fl in non-diabetics, with
p value 0.004 [
21].
The mean PDW in diabetic patients was 14.2 ± 2.5 fl, where it was 10.7 ± 0.7 fl in healthy individuals (controls). The same authors observed
p values of MPV and PDW to be highly significant in diabetic patients (
p<0.05). Additionally, a positive statistical Pearson correlation was obtained between MPV and PDW with HbA1c in the group of diabetic patients [
12,
13,
14,
15].
Platelet indices MPV and PDW in the diabetic group were higher in diabetics with chronic vascular complications than in patients without blood vessels’ injuries, but data were not statistically significant.
Recently, the clinicians pointed out that a MPV significantly increases in diabetic patients during development of retinopathy (
p=0.006) [
25]. Performing correlation analysis, the same authors obtained positive correlation between HbA1c and PDW, HbA1c and MPV, as well as HbA1c and PCT.
PDW levels were found to be independently associated with diagnosis of DM2, while MPV – with PLTs activation and impaired glucose regulation [
25].
Therefore, the conclusion arises that the regular monitoring of all easily acceptable and inexpensive platelet hematological/hematometrical indices are of clinical importance in diagnosis and prevention of micro- and macrovascular complications of DM2: cardiovascular- and brain- vascular diseases, blood hyper-coagulation, combined with defective fibrinolysis, dysregulated vasodilation and increased risk of vascular clot occlusion.
PLT anisocytosis (elevated MPV and PDW), simultaneously combined with RBC anisocytosis (elevated MCV and RDW), could appear as a tool predicting serious DM2 complications (inflammation, vascular thromboses, endothelial dysfunction, etc.) [
26,
27,
28,
29,
30].
Association of increased MPV and PDW, related to impaired glucose regulation in DM2 has been described in the different clinical stages of disease: pre-diabetes, diabetes, vascular diabetic complications. As the elevated MPV, the increased levels of PDW are reported in the medical literature to be closely associated with DM2 and its vascular complications [
18].
The complex of hematological/hematometrical results, obtained as discussed by different study groups are of great importance in assessing early DM2 diagnosis, prognosis, clinical management and improved outcome of disease [
31].
Conflicting results have been also reported – e.g., on the probable relationships between PLTs count and DM development: some authors propose “association”, but several studies supported the opinion “no relationships”. Beside the thrombo-embolic disorders, association of PLTs indices with inflammatory states has been also examined. The large scale of further studies need to be evaluated.
6. Computational Platelets Modeling in DM2
The shear rate of blood is an important factor controlling platelet distribution in the blood vessels [
18,
32,
33,
34,
35].
Chang et al., (2018), simulate blood with hematocrit at 20% (for controlling different blood cells suspensions) [
18,
36]. The results indicated that “larger platelets” are more likely to migrate towards the vessel wall. It was suggested that there is roughly 6-10% decrease in the platelet migration rate when the wall shear rate is decreased from 1000 s
-1 to 600 s
-1.
The weakened platelet migration at lower wall shear rates is probably due to the reduced collision between platelets and RBSs [
32].
In order to present and simulate the micro-scale interactions between different types of blood cells, numerous mathematical and computational models have been developed [
33,
34,
35]. Lattice Boltzmann and lattice kinetic Monte Carlo models have been developed to simulate platelet activation and aggregation by treating PLTs as particles under flow [
37]. However, applications of these hybrid models are mostly limited to two-dimensions, due to the model complexity and the significant computational costs.
In the further created modelling systems, a multiscale approach could be proposed, facilitating a patient-specific simulation of thrombosis/thrombogenesis in different hemodynamic conditions and under different pharmacological treatments.
Yazdani and Karniadakis (2016) [
38] have performed a systematic study on the RBCs and PLTs transport by considering different levels constriction, controlling hematocrit and flow rates. In this work, normal and diabetic RBCs and PLTs models are employed to simulate normal and diabetic blood flow in a rectangular channel. In the numerical framework, the four ket sub-processes of blood clotting were combined: hydrodynamics, PLTs-micromechanics, transport of PLTs coagulation factors and the registration of resulting coagulation reactions. To consider the coagulation cascade, the authors implement the mathematical model of Anand et al., (2008) [
39].
Yazdani and Karniadakis (2016) [
38] concluded that a higher levels of blood vessel constriction (stenosis) and elevated vessel wall shear rates lead to significantly enhanced migration of platelets. This model – with modifications, could explain the experimental data of active PLTs aggregation in a post-vascular stenosis segment of vessel wall in different pathological states (DM2, atherosclerosis, etc.).
Computational modelling has emerged as a powerful tool for investigating of pathological processes in DM2, but there are still many unexplored areas and different experimental conditions that could be targeted in the future researches on the topic.
In the cellular, tissue and organ-specific modelling of diabetic blood cells and of injured microvasculature (complications as retinopathy, nephropathy, microangiopathy, etc.), the micro-aneurisms could be obtained simultaneously with oedema and/or hemorrhages, directly affecting the organ functions [
16,
35,
40,
41].
Instead of the great advantages in bioinformatics and biomechanics, there is a lack of computational models in the medical scientific literature – to connect the prediction of blood glucose levels in diabetic patients by the aid of PLTs hematological and hemorheological biomarkers [
17,
18].
Altered structure and architecture, as well as the functions of fibrin clots have been reported in patients with DM2, as well as in cases of coronary artery disease (CAD). DM2 affects unfavorably plasma fibrin by lowering its permeability and susceptibility to lysis and simultaneously increasing fibrinogen plasma levels leading to hyperfibrinogenemia. Specifically, changes are attributed to glycation of fibrinogen and fibrin in diabetic patients.
Platelets activation in DM2 is a well-known modifier of fibrin clot properties. In the presence of activated PLTs fibrin clot has specific architecture with local increase in fibrin fiber diameter and density [
9]. P-selectin, expressed in alpha-granules of activated platelets of DM2 patients also increases. The role of vWF in the altered plasma fibrin network properties remains to be established, which is closely related to the phenomenon fibrinolysis/thrombolysis [
5].
The dynamic changes in the platelet shape and morphology continue – from an “active” to a “procoagulant state” [
42,
43].
Correlation was found between MPV as a main biomarker of PLTs activation and metabolic status of type 2 diabetic patients [
10,
17,
21,
44,
45,
46]. Important hemogram parameters are: MPV, platelet count (PLT), PDW, PCT, HbA1c and the duration of disease. Some authors suggested that RDW is also an important predictor of vascular complications of DM2 [
28]. Prospective studies are needed to define and clarify all these relationsips between hematological/hematometrical indices. MPV and PDW can be easily determined on routine automated hemograms available and are significantly elevated in diabetics, compared to healthy persons; among the diabetics, the mean of MPV and PDW are higher in patients with complications (not statistically significant) [
21]. The authors pointed out that monitoring of DM2 and thus, preventing of vascular complications are needed. PDW is also main PLT index, significantly higher in diabetic patients, compared to healthy controls. PLTs indices are useful biomarkers for vascular risk in grading DM. This suggested a role of increased PLT activation in the pathogenesis of DM vascular complications.
Modelling glycemic control in DM2 patients, authors concluded that hematometrical indices MPV and PDW are precise biomarkers in DM2: MPV and PDW levels are significantly elevated in diabetics with HbA1c higher than 6.5% [
21].
Additionally, it may be pointed out that a regular glycemic control improves platelets biological activities and functions. Thus, the good glycemic control helps in DM2 treatment and management and could delay micro- and macrovascular complications, attributable to DM2 as a socially significant disease.
Vascular complications appearing in the protrombic/thrombic state of DM2 are mainly related to the risk factors for clot formation. In this stage of DM2, the presence of larger PLTs, as well as “giant paltelets” in the blood smears of patients, may provide simple, effortless and cost-effective diagnostic/prognostic tool, predicting the thrombotic state in the development of DM2 and in other pathological states.
Platelet activation plays important role in the development of vascular DM2 complications, MPV and PDW pathological levels increase, as precise biomarkers of platelets’ activation in DM. In their prospective study, Ulutas et al., 2014, found a statistically significant correlation between MPV and HbA1c values [
44].
First Hajek et al., 1979, showed that PLTs have insulin receptors, with density of about 500 receptors/thrombocyte [
46,
47]. By this way, insulin could regulate directly the functions of PLTs and has an inhibitory effect on platelets’ hyperactivity.
Recent studies [
48], provide insight on the potential role of platelet hematological/hematometrical parameters (PLT count, MPV and PDW), as biomarkers in diagnosis, management and prognosis of DM2. Utilizing of such easy and simple biomarkers of DM2 could have important role in the routine medical practice [
46,
49].
Today, mean platelet volume (MPV) is a commonly used marker of PLT size and indicator of PLT biological activity. The larger PLTs have increased protrombic potential than smaller ones. This conclusion is evaluated not only in routine clinical practice, but is confirmed by SEM and AFM microscopies [
5,
9,
10].
MPV could be indicator of bone marrow and spleen thrombocytogenesis and PLTs turnover rate. In the scientific literature, it has been proposed that MPV is directly related to PLTs aggregation: when aggregation PLT function weakens, the MPV level decreases. This conclusion is related to optimal management of DM2 and other diseases (cardio-vascular, brain-vascular, etc.), where prothrombotic situations correlate to the degree of PLTs activation. MPV is reduced in patients receiving better glycemic control. In state of improved glycemic management, the improvement is related to reduced PLTs activity and lower MPV, respectively.
The platelet distribution width (PDW) is a main hematometrical index – linked to DM2 and other socially-important diseases. PDW demonstrates the size diversity (anisocytosis) of PLTs.
7. Combined Properties of Diabetic RBCs and PLTs Indices
Chang et al., (2018) [
36] combined successfully the properties of diabetic RBCs and PLTs indices from the scientific literature. Novel contributions in this field are data on PLTs rolling near the endothelial cells in vessel walls. PLTs adhesion on vessel walls could demonstrate the process of platelets’ activation/hyperactivation [
18] - evaluating the blood vessel walls injury, as well as the coagulation cascade during thrombogenesis (clots formation).
Important for DM2 are alterations in the palsma levels of coagulatory proteins, pro-coagulatory particles, metal ions, lipids’ composition and metabolism, endothelial morphology and physiology and a degree of PLTs activation [
49].
In the last two decades, numerous computational models have been developed – to simulate the dynamics of all blood cells (RBCs, WBCs and PLTs), under static and dynamic (flow) conditions [
32]. It is very important to impact simultaneously on defects in hemostasis and a risk of cardio-vascular diseases [
50].
After contributions of Benjamin et al., (2018) [
51], in the precise biological and molecular mechanisms of DM2 actively participates the MPV size index.
Researchers observe association between MPV and several medications used to manage DM2: Insulin, Metformin and Sullphonylureas [
52]. For instance, Metformin has protective effects on PLTs mitochondria, inhibiting mitochondrial hyperpolarization (induced by hyperglycemia in diabetic patients). After six month treatment only with Metformin, a significant lower levels of MPV was observed in the treated patients [
52,
53]. The small levels of MPV could prove a useful variables in prediction models for DM2.
Furthermore, DM2 complications (micro- and macrovascular) are associated with elevated RDW and PLT/Ly ratios and thus, need precise glycemic control [
46,
49,
54].
Other main hemorheological parameters (as WBV whole blood viscosity, ED – erythrocyte deformability, EA – erythrocyte aggregability, are also applied in the Clinical diabetology. The hemorheological disorders in DM2 patients increase simultaneously with unfavorable alterations in their glycemic/carbonhydrate metabolism and depend on the intensity of oxidative stress (micro-hemodynamic index OSI – oxidative stress intensity). Micro-hemodynamic indices as ERDI (relative deformability of erythrocyte membrane), WBV (whole blood viscosity), blood plasma viscosity (BPV), erythrocyte aggregation index (EAI) are discussed in relationship to prevention of cardiovascular risks and other vascular complications during DM2 [
51,
54,
55].
Figure 1.
AFM Bruker images (3D topography), of the unfixed blood clot from DM2 patient. Erythrocytes / echinocytes (blue stars) fibrin fibers (blue triangles) , "activated" PLTs, (orange-brown stained; blue arrows) [
9,
56].
Figure 1.
AFM Bruker images (3D topography), of the unfixed blood clot from DM2 patient. Erythrocytes / echinocytes (blue stars) fibrin fibers (blue triangles) , "activated" PLTs, (orange-brown stained; blue arrows) [
9,
56].
(Echinocytes - blue arrows; fibrin fibers - blue triangles)
Figure 2.
AFM Bruker image (3D topography), of the surface of clot from blood of healthy donor. Erythrocyte /discocyte - white star, platelets - white arrows and fibrin fibers (white triangles) [
9,
56].
Figure 2.
AFM Bruker image (3D topography), of the surface of clot from blood of healthy donor. Erythrocyte /discocyte - white star, platelets - white arrows and fibrin fibers (white triangles) [
9,
56].
Figure 3.
AFM Bruker image (3D topogtaphy) of PLTs cluster, containing "activated" thrombocytes from the blood of DM2 patient. Abundant thick fibin fibers are organized in the fibrin network [
9,
56].
Figure 3.
AFM Bruker image (3D topogtaphy) of PLTs cluster, containing "activated" thrombocytes from the blood of DM2 patient. Abundant thick fibin fibers are organized in the fibrin network [
9,
56].
Figure 4.
SEM JSM 6390 image: "activated PLTs" on the fibrin network of a fixed blood clot from a patient with DM-2 ( at magnification x 10 000) [
9,
56].
Figure 4.
SEM JSM 6390 image: "activated PLTs" on the fibrin network of a fixed blood clot from a patient with DM-2 ( at magnification x 10 000) [
9,
56].
Figure 5.
SEM JSM 6390 image: parts of the surface of blood clot from blood of DM2 patient, including erythrocytes with atypical shapes, "activated" PLTs in fibrin fibers network (at magnification x 5000) [
9,
56].
Figure 5.
SEM JSM 6390 image: parts of the surface of blood clot from blood of DM2 patient, including erythrocytes with atypical shapes, "activated" PLTs in fibrin fibers network (at magnification x 5000) [
9,
56].
10. Conclusions
Sobol and Watala (2000) investigated the role of platelets (PLTs) in Diabetes mellitus - related to the micro- and macro-vascular DM2 complications. The analysis of results might be helpful in the new pharmacological strategies - to reduce the level of PLTs activation/hyper-activation, in DM-2 [
66,
67].
"Activated" and "hyper-activated" PLTs in DM2 undergo shape changes and morphological features as membrane blebbing, protrusions/pseudopodia, microvesicules, etc. [
68]. The dynamic events in PLTs continue from an "activated" state during transformation in an "procoagulant phase", when PLTs of diabetic patients are involved in micro- and macrovascular complications of disease.
Scientific contributions, clinical trials and efforts create possibilities to improve anti-platelet drugs and to create new medicines, on the basis of successfull applications of combined hematological indices and hemorheological measurements/parameters: PLTs (count), MPV, PDW, PCR, PLT/Ly ratio, PLT-derived miRNAs, as biomarkers in DM2, etc.). Our view on following up the hematological, hemorheological and hemostatical indices, could create a new way in treatment and management of thrombotic micro- and macrovascular complcations of DM 2.
Diabetes mellitus (DM2) is a hypercoagulable state with enhanced PLTs' activation and increased clotting factors' production: prothrombin, thrombin, fibrinogen, factors VII, VIII, Xi, XII, von Willebrand factor, etc. [
67,
68,
69]. Simultaneously , the fibrinolytic cell system is inhibited due to formaion of clots with high resistance to fibrinolysis. Anti-platelet agents (including natural - plant products), could been effective in prevention and secondary treatment of micro- and macrovascular complications in DM2 [
4,
24,
68,
70,
71,
72,
73,
74].