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J.P. Van Geffen et al.
and M6, suggesting that these expression levels deter- mine, at least partially, thrombus formation on these microspots. The PCA with platelet activation markers did not reveal clear links with thrombus parameters, except for the weakest surface M6. Together with the relatively high intra-subject variance of this surface, this finding sug- gests that M6 parameters detect small changes in the acti- vation tendency of platelets, possibly related to the quality of the blood sample.
A PLS prediction model was developed to assess the extent to which the platelet traits can explain the meas- ured inter-subject variation in thrombus formation. Results revealed a limited predictability for platelet adhe- sion (P1) at various microspots (M4-5). Overall, 1-2% of the variance could be predicted in this way, likely because of the multivariate and multidirectional nature of these platelet traits. As a more targeted and powerful approach, regression models were built to predict the M-P matrices from subject-dependent values of GPVI-induced integrin activation and secretion. As expected, the CRP-XL- induced integrin activation and secretion measures were positively associated with GPVI-dependent microspot (M1-2) parameters of platelet adhesion and activation (P1, P7). A negatively weighted prediction was seen for param- eters of M4-5 (VWF-BP + GFOGER-(GPO)n; VWF-BP + rhodocytin), possibly because of the relatively large roles of α2b1 and CLEC-2, respectively, on these surfaces. Regarding GPVI-induced integrin activation, a positively weighted prediction was seen for thrombi on the αIIbb3- dependent microspot M6, suggesting that the variation on this surface had different causes.
Regression analysis also indicated associations for single nucleotide variants that are linked to alterations in platelet size or GPVI-induced platelet activation.20,27 For two single nucleotide variants linked to GPVI expression, rs1613662 (GP6) and rs3557 (super-enhancer for FCER1G), allelic associations were identified with the GPVI-dependent microspots (M1-2, M4) for platelet adhesion (P1) and
platelet activation (P8, integrin activation) parameters. In addition, single nucleotide variant associations were observed for thrombus formation on the CLEC-2-depen- dent microspot M5, for unclear reasons. Other authors have used microfluidics assays to show that subject- dependent differences in platelet calcium fluxes contribute to a variation in collagen-dependent thrombus forma- tion.28 This work supports our findings of the presence of a subject-dependent factor in GPVI-induced platelet acti- vation and thrombus formation on collagen surfaces.
In contrast, no associations were seen for the single nucleotide variant of the VWF-CD9 locus. Plasma levels of VWF are known to determine the thrombus outcome in flow assays.29 However, the variant rs2363877 only modi- fies platelet-accumulated VWF, rather than plasma VWF.20
A limitation of our study is that, despite the measure- ment of over 70 different blood and platelet traits, the number of healthy subjects was restricted to 94, thus lim- iting the statistical power and the precise assignment of the meaning of all individual parameters. Further work in larger cohorts of healthy subjects, and in patients with known platelet and plasma disorders, will add to the char- acterization of many of these parameters.
Acknowledgments
Support was obtained from the Cardiovascular Center (HVC), Maastricht University Medical Center, the Center for Translational Molecular Medicine (Incoag/Mikrobat), Interreg Euregio Meuse-Rhin (Polyvalve), the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre and the National Health Service Blood and Transplant (NHSBT). We gratefully acknowledge the participation of all NIHR BioResource volunteers, and thank the NIHR BioResource center and staff for their contribution. We also thank the National Institute for Health Research and NHS Blood and Transplant for funding support. KD is supported as a HSST trainee by Health Education England. Funders had no role in the study design, data collection and analy- sis, decision to publish, or preparation of the manuscript.
References
1. Stegner D, Nieswandt B. Platelet receptor signaling in thrombus formation. J Mol Med (Berl). 2011;89(2):109-121.
2. Versteeg HH, Heemskerk JW, Levi M, Reitsma PH. New fundamentals in hemosta- sis. Physiol Rev. 2013;93(1):327-358.
3. Swieringa F, Kuijpers MJ, Heemskerk JW, van der Meijden PE. Targeting platelet recep- tor function in thrombus formation: the risk of bleeding. Blood Rev. 2014;28(1):9-21.
4. VonHundelshausenP,AgtenSM,EckardtV, et al. Chemokine interactome mapping enables tailored intervention in acute and chronic inflammation. Sci Transl Med. 2017;9(384).
5. Ruggeri ZM. Platelet adhesion under flow. Microcirculation. 2009;16:58-83.
6. Heemskerk JWM, Sakariassen KS, Zwaginga JJ, et al. Collagen surfaces to measure thrombus formation under flow: possibilities for standardization. J Thromb Haemost. 2011;9(4):856-858.
7. De Witt SM, Swieringa F, Cavill R, et al.
Identification of platelet function defects by multi-parameter assessment of thrombus formation. Nat Commun. 2014;5:4257.
8. Mattheij NJ, Braun A, van Kruchten R, et al. Survival protein anoctamin-6 controls multi- ple platelet responses including phospho- lipid scrambling, swelling, and protein cleav- age. FASEB J. 2016;30(2):727-737.
9. Nagy M, Mastenbroek TG, Mattheij NJ, et al. Variable impairment of platelet functions in patients with severe, genetically linked immune deficiencies. Haematologica. 2018;103(3):540-549.
10. Harrison P, Mackie I, Mumford A, et al. Guidelines for the laboratory investigation of heritable disorders of platelet function. Br J Haematol. 2011;155(1):30-44.
11. Dawood BB, Lowe GC, Lordkipanidze M, et al. Evaluation of participants with sus- pected heritable platelet function disorders including recommendation and validation of a streamlined agonist panel. Blood. 2012;120(25):5041-5049.
12. Goodall AH, Appleby J. Flow-cytometric analysis of platelet-membrane glycoprotein expression and platelet activation. Methods
Mol Biol. 2004;272:225-253.
13. Hayward CP, Harrison P, Cattaneo M, Ortel
TL, Rao AK. Platelet function analyzer (PFA)-100 closure time in the evaluation of platelet disorders and platelet function. J Thromb Haemost. 2006;4(2):312-319.
14. Lordkipanidze M, Lowe GC, Kirkby NS, et al. Characterization of multiple platelet acti- vation pathways in patients with bleeding as a high-throughput screening option: use of 96-well Optimul assay. Blood. 2014;123(8):e11-22.
15. Dovlatova N, Lordkipanidzé M, Lowe GC, et al. Evaluation of a whole blood remote platelet function test for the diagnosis of mild bleeding disorders. J Thromb Haemost. 2014;12(5):660-665.
16. Gieger C, Radhakrishnan A, Cvejic A, et al. New gene functions in megakaryopoiesis and platelet formation. Nature. 2011;480 (7376):201-207.
17. Astle WJ, Elding H, Jiang T, et al. The allelic landscape of human blood cell trait variation and links to common complex disease. Cell. 2016;167(5):1415-1429.
18. Joutsi-Korhonen L, Smethurst PA, Rankin A,
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