Platelets play an important role in primary hemostasis and are involved in atherosclerosis and atherothrombotic events. Inhibition of platelet aggregation is the key step of any treatment of vascular disease. Metabolic conditions like hyperglycemia influence platelet reactivity and the response to platelet inhibitors through direct effects and by glycation of platelet proteins, especially in type 2 diabetes. Increased platelet reactivity involves intensified adhesion and aggregation in patients with diabetes mellitus or those at high risk for the disease. A subpopulation of large, hyperactive platelets circulates in these patients, at a level similar to that predicted from the results of patients who have experienced myocardial infarction. This suggests that the elevated potential for aggregation of such platelets lowers their threshold for activation, thus contributing to the increased incidence of acute cardiovascular events in diabetes mellitus. As a determinant of platelet activation mean platelet volume (MPV) is an emerging risk factor for atherothrombosis. The increase in MPV may precede acute myocardial ischemia, acute myocardial infarction, coronary atherosclerosis, the presence and the short-term prognosis and the long-term risk of stroke and thus is in association with major cardiovascular events. Case–control studies have documented significant positive associations of MPV with type 2 diabetes mellitus, pre-diabetes, obesity, and other metabolic risk factors, whereas smaller platelets are detected in chronic inflammatory disease, inflammatory bowel disease or rheumatoid arthritis. The platelet count is inversely related to the MPV, patients with low MPV present with higher numbers of platelets and vice versa[7–9].
In a study on Japanese subjects MPV in patients with prediabetes was shown to be higher if compared to normal subjects, and it was positively associated with levels of fasting blood glucose in prediabetic and normal subjects. In a Korean study MPV had a significant positive relationship with FPG after adjusting for diabetes in women as a confounding factor pointing out a gender specifity. The positive relationship between an increased glucose level and increased MPV was shown to be a unique phenomenon of diabetes itself.. MPV values seem to be influenced by antidiabetic therapy, MPV is increased in patients with uncontrolled type 2 diabetes mellitus, and was significantly higher in diabetic patients treated with oral hypoglycemic therapy than in those patients on insulin therapy.
Numerous polymorphic surface glycoprotein receptors are responsible for platelet functionality with membrane glycoprotein (GP) IIb/IIIa playing a major role in platelet function. It enables stimulated platelets to bind to fibrinogen and related adhesive proteins, a process that is considered central in the development of thrombosis. The gene encoding GPIIIa shows a common platelet antigen polymorphism [PLA1A2, (ITGB3 rs5918)] at position 1565 in exon 2 of the coding region for glycoprotein IIIa and results in a leucine-proline exchange. The presence of the PLA2 allele was first reported in 1996 to be associated with an increased risk of coronary heart disease (CHD). The importance of the GPIIb/IIIa receptor has been further supported by clinical trials in which GPIIb/IIIa antagonists have been shown to reduce restenosis rate after angioplasty and to reduce the morbidity and mortality associated with unstable angina, high-risk coronary angioplasty, and acute myocardial infarction. Studies on the PLA1A2-polymorphism and coronary risk suggest an influence of the PLA2 allele on the clinical phenotype and the interaction with other environmental factors. The hyperaggregability associated with the PLA2 allele has been linked to an increased surface expression of GPIIb/IIIa receptors and increased affinity for fibrinogen. The result of this altered expression is discussed controversially; because some studies suggest an association of the PLA2 allele with a greater risk of coronary events others do not support this assumption[18, 19]. In particular, the strongest effect of the PLA2 allele was expressed on the risk of occlusion after revascularization procedures, mainly after stent implantation. Some more recently published analyses do not support this hypothesis. Hyperresponsiveness to agonists has been demonstrated in platelets positive for the PLA2 allele in vitro[16, 17]. In a mechanism possibly unrelated to its effect on platelet reactivity to aggregating stimuli, the presence of the PLA2 allele might influence the antiaggregatory effect of platelet inhibitory drugs such as acetylsalicylic acid (ASA), clopidogrel, and GPIIb/IIIa antagonists. Studies evaluating healthy donors indicate a possible role of the PLA2 allele in ASA resistance based on measures of platelet function, particularly in patients homozygous for PLA2.
Beside the inconsistent reports on the predictability of the PLA polymorphism on cardiovascular events Tschoepe and coworkers found a significant association with the metabolic condition of type 2 diabetes mellitus in an analysis of 112 consecutive patients additionally classified according to the presence of macrovascular disease published earlier. This finding is in contrast to a later publication of Maerz and coworkers from the Ludwigshafen Risk and Cardiovascular Health Study which revealed no association of the GPIIIa PLA1A2 polymorphism with type 2 diabetes, glucose metabolism, angiographically proven CHD or myocardial infarction.
With this regard, the aim of this prospective analysis of the KORA S4-survey is to clarify 1) the predictive role of the PLA1A2 polymorphism in the general population in terms of all-cause mortality, 2) its relation with HbA1c, and 3) its relation with main characteristics of platelet morphology.
Research design and methods
The KORA study region consists of the city of Augsburg and the two surrounding districts with about 600,000 inhabitants in 1999. The Bavarian ethic committee approved the KORA S4 study (conducted between 1999 and 2001) which followed the declaration of Helsinki; informed consent was given by each participant. The initial study sample involved 6,640 subjects randomly drawn from the general population. Altogether 4,261 subjects participated in the baseline study (response 67%). Of those, 4,028 had been characterized according their PLA1A2 polymorphism by a flow cytometry based assay as described elsewhere and could be included in the present analysis. Briefly, the polymorphism was determined from frozen EDTA cell samples by flow cytometry analysis using the stereospecific monoclonal antibody SZ21 directed against the ß3-subunit of the GPIIb/IIIa receptor. Mortality was followed up for a maximum of 10 years and cause of death was coded using common ICD coding. Blood collection and processing was described earlier. Diabetes was defined based on self-reported physician diagnosis, use of antidiabetic agents and/or HbA1c levels at baseline ≥6.5% (48 mmol/mol) (N = 209 participants). HbA1c was determined centrally at baseline. HbA1c-values were determined using a turbidimetric immunologic assay (Tina-quant, Roche Diagnostics). The interassay coefficients of variation were 3.9% at HbA1c 5.7% (39 mmol/mol) and 5.2% at HbA1c 9.7% (83 mmol/mol).
Descriptive analysis results of the population characteristics were reported as mean ± standard deviation (SD). Comparison between the groups was done by Mann–Whitney testing or one-way ANOVA followed by Dunnett’s multiple comparison post-test for continuous data and Fisher’s exact test for categorical data.
A multivariate logistical regression model was used to evaluate the cross-sectional association of genotype with HbA1c, MPV, platelet mass and platelet count. Variables investigated for possible confounding included age, sex, BMI, waist-hip ratio, diastolic and systolic blood pressure, cholesterol levels (total, HDL, and LDL), smoking status (categorized: non-smoker, former smoker, current smoker), high alcohol intake (categorized: ≥20 g/day for women; ≥40 g/day for men), leisure time physical activity (categorized: >1 h per week). Association between platelet count and covariates were investigated by linear regression model.
Cox proportional hazards model was used for a multivariate analysis of the risk of overall death with genotypes, HbA1c level and platelet morphology (MPV, platelet count, and platelet mass), taking the same adjustment as previously described. Statistical analysis was done using R version 2.15.1 (The R Foundation for Statistical Computing). P values <0.05 were regarded statistically significant.