Woo Yong Shin

DNA methylation is a major epigenetic mark with important roles in genetic regulation. Methylated cytosines are found primarily at CpG dinucleotides, but are also found at non-CpG sites (CpA, CpT, and CpC). The general functions of CpG and non-CpG methylation include gene silencing or activation depending on the methylated regions. CpG and non-CpG methylation are found throughout the whole genome, including repetitive sequences, enhancers, promoters, and gene bodies. Interestingly, however, non-CpG methylation is restricted to specific cell types, such as pluripotent stem cells, oocytes, neurons, and glial cells. Thus, accumulation of methylation at non-CpG sites and CpG sites in neurons seems to be involved in development and disease etiology. Here, we provide an overview of CpG and non-CpG methylation and their roles in neurological diseases.

Jung-Ah Kim, M.D., Hae In Bang, M.D., Jeong Won Shin, M.D., Ph.D., Yoonhye Park, M.T., Saerom Kim, M.T., Mi-Young Kim, M.T., Eui Young Jang, M.T., Woo Yong Shin, M.D., Jieun Kim, M.D., Ph.D., Rojin Park, M.D., Ph.D., and Tae Youn Choi, M.D., Ph.D.. Ann Lab Med 2022;42:688-92. https://doi.org/10.3343/alm.2022.42.6.688

BACKGROUND: The germline mutations of DDX41, also known as DEAD box RNA helicase 41, have been found in about 1.5% of myeloid neoplasms (MNs). Development of MDS/AML is relatively common in germline DDX41 mutations. However, a variety of hematological malignancies (HMs) have been reported. CASE PRESENTATION: We report a novel case of bi-alleleic DDX41 mutations in B-cell lymphoblastic leukemia (B-ALL), with unusual location of DDX41 mutations. The gene expression profile (GEP) of Ph + B-ALL with bi-alleleic DDX41 mutations showed heterogeneously transitional GEP and altered gene expression levels of genes involved in the process essential for red blood cells and myeloid cell differentiation were noted. CONCLUSIONS: We report that DDX41 mutations are unusual but can be an underlying event in Ph + B-ALL and screening DDX41 mutations can be also informative for patients awaiting for haploidentical stem cell transplantation and choosing the therapy.

According to increased availability and awareness of automated blood bank analyzer with its speed and efficiency, use of automated analyzer in hospital blood bank has been increasing rapidly. We compared the ABO blood group typing results between automated analyzer IH-500 and manual method in healthy adults and patients with ABO discrepancies to provide useful information on interpretation of blood grouping results by automated analyzer.

Background: Transfusion guidelines are not only essential for the optimal use of blood products, but also help reduce transfusion-related adverse reactions and improve patients' outcomes. In this hospital, a transfusion-indication data-entry program based on the national transfusion guidelines was developed and applied to the electronic medical record system in 2016. All transfusion orders, except for emergencies, have been performed using this program since then. This study analyzed the reasons for the transfusion to monitor the blood product usage and provide feedback to clinicians. Methods: The transfusion-indications were classified by the blood product and a pop-up window listing these indications was produced. The indications were as follows: red blood cells (RBCs) -acute blood loss, chronic anemia, surgery/procedure, transplantation and 'other'; platelets (PLTs) -active bleeding, bleeding prophylaxis, surgery/procedure, massive transfusion, and 'other'; fresh frozen plasma (FFP) -bleeding in coagulopathy, bleeding prophylaxis in coagulopathy, massive transfusion, plasma exchange, and 'other'. The indications entered into the data-entry program from Sep 2016 to Feb 2018 were analyzed. Results: The most common indications for transfusion were chronic anemia for RBCs (7977/16138, 49.4%), bleeding prophylaxis for PLTs (5726/11158, 51.3%), and 'other' for FFP (2180/6024, 36.2%). Many clinicians entered the transfusion indication as 'other', but the free-text supplied by the clinician when 'other' was selected, often corresponded to an indication already categorized in the transfusion-indication data-entry program. Conclusion: Feedback and training on the data of transfusion indications are needed for clinicians to properly use blood products by operating the transfusion-indication data-entry program more efficiently. (