Bariana Tadbir K, Ouwehand Willem H, Guerrero Jose A, Gomez Keith
Katharine Dormandy Haemophilia Centre and Thrombosis Unit, Royal Free London NHS Foundation Trust, London, UK.
Department of Haematology, University College London Cancer Institute, London, UK.
Br J Haematol. 2017 Mar;176(5):705-720. doi: 10.1111/bjh.14471. Epub 2016 Dec 16.
Inherited disorders of platelet granules are clinically heterogeneous and their prevalence is underestimated because most patients do not undergo a complete diagnostic work-up. The lack of a genetic diagnosis limits the ability to tailor management, screen family members, aid with family planning, predict clinical progression and detect serious consequences, such as myelofibrosis, lung fibrosis and malignancy, in a timely manner. This is set to change with the introduction of high throughput sequencing (HTS) as a routine clinical diagnostic test. HTS diagnostic tests are now available, affordable and allow parallel screening of DNA samples for variants in all of the 80 known bleeding, thrombotic and platelet genes. Increased genetic diagnosis and curation of variants is, in turn, improving our understanding of the pathobiology and clinical course of inherited platelet disorders. Our understanding of the genetic causes of platelet granule disorders and the regulation of granule biogenesis is a work in progress and has been significantly enhanced by recent genomic discoveries from high-powered genome-wide association studies and genome sequencing projects. In the era of whole genome and epigenome sequencing, new strategies are required to integrate multiple sources of big data in the search for elusive, novel genes underlying granule disorders.
血小板颗粒遗传性疾病在临床上具有异质性，其患病率被低估，因为大多数患者未接受全面的诊断检查。缺乏基因诊断限制了针对性管理、筛查家庭成员、辅助计划生育、预测临床进展以及及时发现严重后果（如骨髓纤维化、肺纤维化和恶性肿瘤）的能力。随着高通量测序（HTS）作为常规临床诊断测试的引入，这种情况将得到改变。目前已有HTS诊断测试，且价格可承受，能够对DNA样本进行并行筛查，以检测80个已知的出血、血栓形成和血小板基因中的变异。基因诊断的增加以及对变异的整理反过来又增进了我们对遗传性血小板疾病病理生物学和临床病程的理解。我们对血小板颗粒疾病的遗传原因以及颗粒生物发生调节的理解仍在不断发展，最近来自高功率全基因组关联研究和基因组测序项目的基因组发现显著增强了这方面的认识。在全基因组和表观基因组测序时代，需要新的策略来整合多种大数据来源，以寻找导致颗粒疾病的难以捉摸的新基因。
