Inherited Thrombocytopenias: Combining High-Throughput Sequencing With Other Relevant Data

We read with interest the article by Wang et al recently published in Clinical and Applied Thrombosis/Hemostasis. Here, the authors have evaluated the role of high-throughput sequencing in 43 apparently familial cases of thrombocytopenia using Drachman review algorithm. Combining clinical and phenotype and next-generation sequencing (NGS) data, only 15 of 43 cases of inherited platelet disorder, that is about 35% of the cases, could be given clear-cut molecular diagnosis. The authors have taken lot of pains to design and execute their study and tried to standardize the technique taking care of all possible sources of error. Considering the fact that only 8.7% of the patients with possible inherited symptomatic disorders of platelet function eventually gets molecular diagnosis, the results should be considered a quantum jump in the field. The results obtained by the present authors are similar or even better than those described from various European consortiums on platelet disorders. When we closely look at the clinical data of the article under discussion, only 2 of 43 patients had syndromic form of the disease in the form of hearing loss and renal disease, respectively. It is generally believed that when one deals with severe bleeding with congenital platelet defects, clear-cut diagnosis even on molecular pathology is expected in most of the cases. In milder cases of bleeding with inherited disorders of platelet function or even when no bleeding or family history is available, getting a molecular diagnosis becomes difficult. Molecular diagnosis of inherited platelet disorder have progressed from polymerase chain reactionsingle strand conformation polymorphism (PCR-SSCP) polymerase chain reaction conformation sensitive gel electrophoresis (PCR-CSGE) followed by Sanger sequencing and then in the present era beginning with DNA, complementary DNA, and different types of microarray to whole-genome sequencing, to whole-exome sequencing using various NGS platforms. However, NGS-based data throws lots of challenges in sequence interpretation. Our present software and statistics associated with the NGS data are lagging far behind the amount of information generated through NGS. Moreover, NGS technology is poor in detecting complex structural rearrangements, inversions and large deletion of genes as also repeated mutations and copy number variations. As many of the platelet proteins are adhesion molecules with many repeat nucleotide sequences, chances of such kind of pathologies in platelet genome are high. Hence, alternative technologies such as multiple ligationdependent probe amplification or similar such techniques in addition to Sanger sequencing needs to complement NGS techniques. Depth of reading of genes by NGS techniques widely vary and for some genes it can be as low as 70% or lower making the data set incomplete with respect to some of the genes. Although the American College of Medical Genetics is developing various algorithms to filter out population noise from real genetic changes causing the disease phenotype, we are still far away from the ideal situation. In the present study, 32 (74%) of 43 cases had no family history and many of them had thrombocytopenia or minor bleeding. We don’t have the data on mean platelet volume (MPV) and associated changes in complete blood counts and morphological changes in platelets and other formed elements of blood associated with studied platelet defects in many of the patients discussed here. These data are useful as they algebraically summate the results of different genetic changes into meaningful phenotypic variables.