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Hamostaseologie 2019; 39(04): 383-391
DOI: 10.1055/s-0038-1675574
Original Article
Georg Thieme Verlag KG Stuttgart · New York

Functional Classification of Paediatric Patients with Non-syndromic Delta-Storage Pool Deficiency

Georgi Manukjan
1   Institute of Experimental Biomedicine, University Hospital Würzburg, Würzburg, Germany
,
Julia Eilenberger
1   Institute of Experimental Biomedicine, University Hospital Würzburg, Würzburg, Germany
2   Practice for Pediatric Hematology and Hemostaseology, Munich, Germany
,
Oliver Andres
3   University Children's Hospital Würzburg, Würzburg, Germany
,
Christian Schambeck
4   Haemostasikum, Munich, Germany
,
Stefan Eber
2   Practice for Pediatric Hematology and Hemostaseology, Munich, Germany
,
Harald Schulze
1   Institute of Experimental Biomedicine, University Hospital Würzburg, Würzburg, Germany
› Author Affiliations
Further Information

Publication History

22 March 2018

28 June 2018

Publication Date:
21 November 2018 (online)

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Abstract

Storage pool disease (SPD) covers a group of platelet defects in which α- and/or delta-granules are reduced or cannot be secreted adequately in response to agonists. The detection of delta-granule release defects is hampered by a lack of fast and feasible tests. We aimed to implement a flow cytometry–based kinetic mepacrine assay to better identify and subgroup childhood patients with a mild to moderate bleeding diathesis and compare our method to established laboratory tests. We analysed 50 children with suspected SPD whose initial parameters were re-assessed in a second site visit. Mepacrine uptake and release patterns were correlated with CD63 exposure, platelet ADP/ATP release and content, and the bleeding score ascertained by the ISTH-BAT. Mepacrine release was overall significantly reduced in investigated patients compared with controls. Summarizing, our time-resolved approach proved to be a quick and inexpensive tool that was additionally able to distinguish between mepacrine uptake, mepacrine release, and combined defects. Classification of patients using such a kinetic assay makes it feasible to sensitively detect frequently missed SPD and to group these patients for further analyses and clinical correlations.

Zusammenfassung

Storage pool disease (SPD) umfasst eine Gruppe von Thrombozytendefekten, bei denen die α und/oder dichten Granula vermindert vorliegen bzw. nach Stimulation mit Agonisten nicht ausreichend ausgeschüttet werden können. Die Detektion von Freisetzungsdefekten der dichten Granula ist erschwert durch das Fehlen schneller und verlässlicher Tests. In dieser Arbeit haben wir einen durchflusszytometrischen kinetischen Mepacrin-Assay etabliert, um kindliche Patienten mit milder bis moderater Blutungsneigung besser identifizieren und gruppieren zu können und unseren Test mit anderen gängigen Methoden zu vergleichen. Wir haben dazu 50 Kinder mit Verdacht auf SPD analysiert, welche auch bei wiederholter Einbestellung ähnliche Blutungsparameter zeigten. Die Mepacrinaufnahme und –freisetzungsmuster wurden mit der Oberflächenexpression von CD63 auf Thrombozyten, der ADP/ATP-Freisetzung und dem ADP-Gehalt sowie dem Blutungsscore, nach den Kriterien der ISTH-BAT, korreliert. Die Mepacrinfreisetzung war insgesamt in der untersuchten Patientenkohorte signifikant reduziert verglichen zu Gesundspenderkontrollen. Zusammenfassend stellt sich unser zeitaufgelöster Ansatz als schnelles und kostengünstiges Hilfsmittel heraus, welches es möglich macht, zwischen Aufnahme-, Freisetzungs- und kombinierten Defekten zu unterscheiden. Die Klassifizierung von Patienten nach Anwendung dieser kinetischen Methode erlaubt es, häufig unerkannte SPD sensitiv zu detektieren und Patienten für weiterführende Untersuchungen und klinische Korrelationen zu gruppieren.

Keywords

platelet granules - bleeding management - flow cytometry

Schlüsselwörter

Thrombozytengranula - Blutungsmanagement - Durchflusszytometrie

Authors' Contributions

H.S. and O.A. planned the study and obtained approval of the local institutional review board; S.E., J.E., and O.A. enrolled and treated patients; C.S. performed whole blood aggregometry and luminometry; J.E. and G.M. analysed blood samples by flow cytometry; G.M. and H.S. wrote the manuscript.


 

  • References

  • 1 Blair P, Flaumenhaft R. Platelet alpha-granules: basic biology and clinical correlates. Blood Rev 2009; 23 (04) 177-189
    CrossrefPubMedGoogle Scholar
  • 2 Cai H, Mullier F, Frotscher B. , et al. Usefulness of flow cytometric mepacrine uptake/release combined with CD63 assay in diagnosis of patients with suspected platelet dense granule disorder. Semin Thromb Hemost 2016; 42 (03) 282-291
    Article in Thieme ConnectPubMedGoogle Scholar
  • 3 Israels SJ, McMillan EM, Robertson C, Singhory S, McNicol A. The lysosomal granule membrane protein, LAMP-2, is also present in platelet dense granule membranes. Thromb Haemost 1996; 75 (04) 623-629
    Article in Thieme ConnectPubMedGoogle Scholar
  • 4 Simon D, Kunicki T, Nugent D. Platelet function defects. Haemophilia 2008; 14 (06) 1240-1249
    CrossrefPubMedGoogle Scholar
  • 5 Nurden P, Nurden AT. Congenital disorders associated with platelet dysfunctions. Thromb Haemost 2008; 99 (02) 253-263
    Article in Thieme ConnectPubMedGoogle Scholar
  • 6 Masliah-Planchon J, Darnige L, Bellucci S. Molecular determinants of platelet delta storage pool deficiencies: an update. Br J Haematol 2013; 160 (01) 5-11
    CrossrefPubMedGoogle Scholar
  • 7 Woods GM, Kudron EL, Davis K, Stanek J, Kerlin BA, O'Brien SH. Light transmission aggregometry does not correlate with the severity of δ-granule platelet storage pool deficiency. J Pediatr Hematol Oncol 2016; 38 (07) 525-528
    CrossrefPubMedGoogle Scholar
  • 8 Sandrock K, Zieger B. Current strategies in diagnosis of inherited storage pool defects. Transfus Med Hemother 2010; 37 (05) 248-258
    PubMedGoogle Scholar
  • 9 Ambrosio AL, Di Pietro SM. Storage pool diseases illuminate platelet dense granule biogenesis. Platelets 2017; 28 (02) 138-146
    CrossrefPubMedGoogle Scholar
  • 10 McGlasson DL, Fritsma GA. Whole blood platelet aggregometry and platelet function testing. Semin Thromb Hemost 2009; 35 (02) 168-180
    Article in Thieme ConnectPubMedGoogle Scholar
  • 11 Gunay-Aygun M, Huizing M, Gahl WA. Molecular defects that affect platelet dense granules. Semin Thromb Hemost 2004; 30 (05) 537-547
    Article in Thieme ConnectPubMedGoogle Scholar
  • 12 Harrison P, Mackie I, Mumford A. , et al; British Committee for Standards in Haematology. Guidelines for the laboratory investigation of heritable disorders of platelet function. Br J Haematol 2011; 155 (01) 30-44
    CrossrefPubMedGoogle Scholar
  • 13 Bugert P. The gears keep turning: current progress in platelet function testing. Transfus Med Hemother 2013; 40 (02) 71
    CrossrefPubMedGoogle Scholar
  • 14 Nieuwenhuis HK, Akkerman JW, Sixma JJ. Patients with a prolonged bleeding time and normal aggregation tests may have storage pool deficiency: studies on one hundred six patients. Blood 1987; 70 (03) 620-623
    CrossrefPubMedGoogle Scholar
  • 15 Knöfler R, Eberl W, Schulze H. , et al. [Diagnosis of inherited diseases of platelet function. Interdisciplinary S2K guideline of the Permanent Paediatric Committee of the Society of Thrombosis and Haemostasis Research (GTH e. V.)]. Hamostaseologie 2014; 34 (03) 201-212
    Article in Thieme ConnectPubMedGoogle Scholar
  • 16 Michelson AD, Barnard MR, Krueger LA, Frelinger III AL, Furman MI. Evaluation of platelet function by flow cytometry. Methods 2000; 21 (03) 259-270
    CrossrefPubMedGoogle Scholar
  • 17 Gordon N, Thom J, Cole C, Baker R. Rapid detection of hereditary and acquired platelet storage pool deficiency by flow cytometry. Br J Haematol 1995; 89 (01) 117-123
    CrossrefPubMedGoogle Scholar
  • 18 Billio A, Moeseneder C, Donazzan G, Triani A, Pescosta N, Coser P. Hermansky-Pudlak syndrome: clinical presentation and confirmation of the value of the mepacrine-based cytofluorimetry test in the diagnosis of delta granule deficiency. Haematologica 2001; 86 (02) 220
    PubMedGoogle Scholar
  • 19 Lundin A, Richardsson A, Thore A. Continuous monitoring of ATP-converting reactions by purified firefly luciferase. Anal Biochem 1976; 75 (02) 611-620
    CrossrefPubMedGoogle Scholar
  • 20 Cardinal DC, Flower RJ. The electronic aggregometer: a novel device for assessing platelet behavior in blood. J Pharmacol Methods 1980; 3 (02) 135-158
    CrossrefPubMedGoogle Scholar
  • 21 Halimeh S, Angelis Gd, Sander A. , et al. Multiplate whole blood impedance point of care aggregometry: preliminary reference values in healthy infants, children and adolescents. Klin Padiatr 2010; 222 (03) 158-163
    Article in Thieme ConnectPubMedGoogle Scholar
  • 22 Andres O, Henning K, Strauss G, Pflug A, Manukjan G, Schulze H. Diagnosis of platelet function disorders: a standardized, rational, and modular flow cytometric approach. Platelets 2018; 29 (04) 347-356
    CrossrefPubMedGoogle Scholar
  • 23 Bidlingmaier C, Grote V, Budde U, Olivieri M, Kurnik K. Prospective evaluation of a pediatric bleeding questionnaire and the ISTH bleeding assessment tool in children and parents in routine clinical practice. J Thromb Haemost 2012; 10 (07) 1335-1341
    CrossrefPubMedGoogle Scholar
  • 24 Hayward CP, Harrison P, Cattaneo M, Ortel TL, Rao AK. ; Platelet Physiology Subcommittee of the Scientific and Standardization Committee of the International Society on Thrombosis and Haemostasis. Platelet function analyzer (PFA)-100 closure time in the evaluation of platelet disorders and platelet function. J Thromb Haemost 2006; 4 (02) 312-319
    CrossrefPubMedGoogle Scholar
  • 25 Mumford AD, Frelinger III AL, Gachet C. , et al. A review of platelet secretion assays for the diagnosis of inherited platelet secretion disorders. Thromb Haemost 2015; 114 (01) 14-25
    Article in Thieme ConnectPubMedGoogle Scholar
  • 26 Maurer-Spurej E, Pittendreigh C, Wu JK. Diagnosing platelet delta-storage pool disease in children by flow cytometry. Am J Clin Pathol 2007; 127 (04) 626-632
    CrossrefPubMedGoogle Scholar
  • 27 White JG. Electron-dense chains and clusters in platelets from patients with storage pool-deficiency disorders. J Thromb Haemost 2003; 1 (01) 74-79
    CrossrefPubMedGoogle Scholar
  • 28 Knöfler R, Streif W. Strategies in clinical and laboratory diagnosis of inherited platelet function disorders in children. Transfus Med Hemother 2010; 37 (05) 231-235
    PubMedGoogle Scholar
  • 29 Favaloro EJ. Clinical utility of the PFA-100. Semin Thromb Hemost 2008; 34 (08) 709-733
    Article in Thieme ConnectPubMedGoogle Scholar
  • 30 Sánchez-Guiu I, Torregrosa JM, Velasco F. , et al. Hermansky-Pudlak syndrome. Overview of clinical and molecular features and case report of a new HPS-1 variant. Hamostaseologie 2014; 34 (04) 301-309
    Article in Thieme ConnectPubMedGoogle Scholar
  • 31 Dawood BB, Lowe GC, Lordkipanidzé M. , et al. Evaluation of participants with suspected heritable platelet function disorders including recommendation and validation of a streamlined agonist panel. Blood 2012; 120 (25) 5041-5049
    PubMedGoogle Scholar
  • 32 Selle F, James C, Tuffigo M. , et al. Clinical and laboratory findings in patients with δ-storage pool disease: a case series. Semin Thromb Hemost 2017; 43 (01) 48-58
    PubMedGoogle Scholar
  • 33 Bariana TK, Ouwehand WH, Guerrero JA, Gomez K. ; BRIDGE Bleeding, Thrombotic and Platelet Disorders and ThromboGenomics Consortia. Dawning of the age of genomics for platelet granule disorders: improving insight, diagnosis and management. Br J Haematol 2017; 176 (05) 705-720
    CrossrefPubMedGoogle Scholar
  • 34 Westbury SK, Turro E, Greene D. , et al; BRIDGE-BPD Consortium. Human phenotype ontology annotation and cluster analysis to unravel genetic defects in 707 cases with unexplained bleeding and platelet disorders. Genome Med 2015; 7 (01) 36
    CrossrefPubMedGoogle Scholar