A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels.

ABSTRACT: Coagulation factor VIII (FVIII) and its carrier protein von Willebrand factor (VWF) are critical to coagulation and platelet aggregation. We leveraged whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program along with TOPMed-based imputation of genotypes in additional samples to identify genetic associations with circulating FVIII and VWF levels in a single-variant meta-analysis, including up to 45 289 participants. Gene-based aggregate tests were implemented in TOPMed. We identified 3 candidate causal genes and tested their functional effect on FVIII release from human liver endothelial cells (HLECs) and VWF release from human umbilical vein endothelial cells. Mendelian randomization was also performed to provide evidence for causal associations of FVIII and VWF with thrombotic outcomes. We identified associations (P < 5 × 10-9) at 7 new loci for FVIII (ST3GAL4, CLEC4M, B3GNT2, ASGR1, F12, KNG1, and TREM1/NCR2) and 1 for VWF (B3GNT2). VWF, ABO, and STAB2 were associated with FVIII and VWF in gene-based analyses. Multiphenotype analysis of FVIII and VWF identified another 3 new loci, including PDIA3. Silencing of B3GNT2 and the previously reported CD36 gene decreased release of FVIII by HLECs, whereas silencing of B3GNT2, CD36, and PDIA3 decreased release of VWF by HVECs. Mendelian randomization supports causal association of higher FVIII and VWF with increased risk of thrombotic outcomes. Seven new loci were identified for FVIII and 1 for VWF, with evidence supporting causal associations of FVIII and VWF with thrombotic outcomes. B3GNT2, CD36, and PDIA3 modulate the release of FVIII and/or VWF in vitro.

Cardiorespiratory Fitness Is Associated with Decreased Platelet Reactivity.

PURPOSE: Platelets are key mediators in cardiovascular disease (CVD). Low cardiorespiratory fitness (CRF) is a risk factor for CVD. The purpose of our study was to assess if CRF associates with platelet function. METHODS: Platelet assays and cardiopulmonary exercise testing were conducted in the Framingham Heart Study (n = 3,014). Linear mixed effects models estimated associations between CRF (assessed by peak oxygen uptake [VO2]), and multiple platelet reactivity assays. Models were adjusted for multiple medications, risk factors, relatedness and prevalent CVD. RESULTS: Nineteen associations passed the significance threshold in the fully adjusted models, all indicating higher CRF associated with decreased platelet reactivity. Significant traits spanned multiple platelet agonists. Strongest associations were observed in Multiplate whole blood testing after TRAP-6 (e.g., velocity, beta = -0.563, 95% CI [-0.735,-0.391], p = 1.38E-10), ADP (e.g., velocity, beta = -0.514, 95% CI [-0.681,-0348], p = 1.41E-09), collagen (e.g., velocity, beta = -0.387, 95% CI [-0.549,-0.224], p = 3.01E-06), ristocetin (e.g., AUC, beta = -0.365, 95% CI [-0.522,-0.208], p = 5.17E-06) and arachidonic acid stimulation of platelets (e.g., velocity, beta = -0.298, 95% CI [-0.435,-0.162], p = 3.39E-04), and light transmission aggregometry (LTA) after ristocetin stimulation (e.g., max aggregation, beta = -0.362, 95% CI [-0.540,-0.184], p = 6.64E-05). One trait passed significance threshold in the aspirin sub-sample (LTA ristocetin primary slope, beta = -0.733, 95% CI [-1.134,-0.333], p = 3.30E-04), and another in a model including von Willebrand Factor levels as a covariate (U46619, a thromboxane receptor mimetic, AUC in the Optimul assay, beta = -0.36, 95%CI [-0.551,-0.168], p = 2.35E-04). No strong interactions were observed between the associations and sex, age or body mass index in formal interaction analyses. CONCLUSIONS: Our findings build on past work that shows CRF to be associated with reduced CVD by suggesting decreased platelet reactivity may play a mechanistic role. We found significant associations with multiple platelet agonists, indicating higher CRF may globally inhibit platelets; however, given multiple strong associations after TRAP-6 and ADP stimulation, PAR-1 and purinergic signaling may be most heavily involved. This is notable since each of these receptor pathways are tied to anti-coagulant (DOACs/thrombin inhibitors) and anti-platelet therapies (P2Y12/PAR1/PAR4 inhibitors) for CVD prevention.

Obstructive Sleep Apnea, Platelet Aggregation, and Cardiovascular Risk.

BACKGROUND: Although related, the precise mechanisms linking obstructive sleep apnea (OSA) and cardiovascular disease (CVD) are unclear. Platelets are mediators of CVD risk and thrombosis and prior studies suggested associations of OSA and platelet activity. The aim of this study is to assess the link between OSA, platelet activity, and CVD-related risk factors. METHODS AND RESULTS: We studied the association of OSA-measures and platelet aggregation in participants dually enrolled in the SHHS (Sleep Heart and Health Study) and FHS (Framingham Heart Study). We applied linear regression models with adjustment for demographic and clinical covariates and explored interactions with OSA and CVD-related factors, including age, sex, body mass index, hypertension, OSA diagnosis (apnea-hypopnea index 4%≥5), and aspirin use. Our final sample was of 482 participants (60 years [14.00], 50.4% female). No associations were observed between apnea-hypopnea index 4% and platelet aggregation in the main sample. Stratified analysis revealed an association in aspirin users (n=65) for our primary exposure (apnea-hypopnea index 4%, ß=0.523; P<0.001; n=65), and secondary exposures: hypoxic burden (ß=0.358; P<0.001), minimum saturation (ß=-0.519; P=0.026), and oxygen desaturation index 3% (ß=74.672; P=0.002). No associations were detected in nonaspirin users (n=417). CONCLUSIONS: No associations were detected between OSA and platelet aggregation in a community sample. Our finding that OSA associates with increased platelet aggregation in the aspirin group, most of whom use it for primary prevention of CVD, suggests that platelet aggregation may mediate the adverse impact of OSA on vascular health in individuals with existing CVD risk, supporting further investigation.

Factors that modulate platelet reactivity as measured by 5 assay platforms in 3429 individuals.

Background: Assessment of platelet function is key in diagnosing bleeding disorders and evaluating antiplatelet drug efficacy. However, there is a prevailing "one-size-fits-all" approach in the interpretation of measures of platelet reactivity, with arbitrary cutoffs often derived from healthy volunteer responses. Objectives: Our aim was to compare well-used platelet reactivity assays. Methods: Blood and platelet-rich plasma obtained from the Framingham Heart Study (N = 3429) were assayed using a range of agonists in 5 platelet assays: light transmission aggregometry, Optimul aggregometry, Multiplate impedance aggregometry (Roche Diagnostics), Total Thrombus-Formation Analysis System, and flow cytometry. Using linear mixed-effect models, we determined the contribution of preanalytical and technical factors that modulated platelet reactivity traits. Results: A strong intra-assay correlation of platelet traits was seen in all assays, particularly Multiplate velocity (r = 0.740; ristocetin vs arachidonic acid). In contrast, only moderate interassay correlations were observed (r = 0.375; adenosine diphosphate Optimul Emax vs light transmission aggregometry large area under the curve). As expected, antiplatelet drugs strongly reduced platelet responses, with aspirin use primarily targeting arachidonic acid-induced aggregation, and explained substantial variance (ß = -1.735; P = 4.59 × 10-780; variance proportion = 46.2%) and P2Y12 antagonists blocking adenosine diphosphate responses (ß = -1.612; P = 6.75 × 10-27; variance proportion = 2.1%). Notably, female sex and older age were associated with enhanced platelet reactivity. Fasting status and deviations from standard venipuncture practices did not alter platelet reactivity significantly. Finally, the agonist batch, phlebotomist, and assay technician (more so for assays that require additional sample manipulation) had a moderate to large effect on measured platelet reactivity. Conclusion: Caution must be exercised when extrapolating findings between assays, and the use of standard ranges must be medication-specific and sex-specific at a minimum. Researchers should also consider preanalytical and technical variables when designing experiments and interpreting platelet reactivity measures.