Results of contact tracing for SARS-CoV-2 Omicron sub-lineages (BA.4, BA.5, BA.2.75) and the household secondary attack risk

Objectives@#This study aimed to assess the contact tracing outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron sub-lineages BA.4, BA.5, and BA.2.75 within Republic of Korea, and to generate foundational data for responding to future novel variants. @*Methods@#We conducted investigations and contact tracing for 79 confirmed BA.4 cases, 396 confirmed BA.5 cases, and 152 confirmed BA.2.75 cases. These cases were identified through random sampling of both domestically confirmed and imported cases, with the goal of evaluating the pattern of occurrence and transmissibility. @*Results@#We detected 79 instances of Omicron sub-lineage BA.4 across a span of 46 days, 396 instances of Omicron sub-lineage BA.5 in 46 days, and 152 instances of Omicron sub-lineage BA.2.75 over 62 days. One patient with severe illness was confirmed among the BA.5 cases; however, there were no reports of severe illness in the confirmed BA.4 and BA.2.75 cases. The secondary attack risk among household contacts were 19.6% for BA.4, 27.8% for BA.5, and 24.3% for BA.2.75. No statistically significant difference was found between the Omicron sub-lineages. @*Conclusion@#BA.2.75 did not demonstrate a higher tendency for transmissibility, disease severity, or secondary attack risk within households when compared to BA.4 and BA.5. We will continue to monitor major SARS-CoV-2 variants, and we plan to enhance the disease control and response systems.

Increased viral load in patients infected with severe acute respiratory syndrome coronavirus 2 Omicron variant in the Republic of Korea

Objectives@#Coronavirus disease 2019 (COVID-19) has been declared a global pandemic owingto the rapid spread of the causative agent, severe acute respiratory syndrome coronavirus 2.Its Delta and Omicron variants are more transmissible and pathogenic than other variants.Some debates have emerged on the mechanism of variants of concern. In the COVID-19 wave that began in December 2021, the Omicron variant, first reported in South Africa, became identifiable in most cases globally. The aim of this study was to provide data to inform effective responses to the transmission of the Omicron variant. @*Methods@#The Delta variant and the spike protein D614G mutant were compared with the Omicron variant. Viral loads from 5 days after symptom onset were compared usingepidemiological data collected at the time of diagnosis. @*Results@#The Omicron variant exhibited a higher viral load than other variants, resulting in greater transmissibility within 5 days of symptom onset. @*Conclusion@#Future research should focus on vaccine efficacy against the Omicron variant and compare trends in disease severity associated with its high viral load.

The Impact of Entry Restrictions on the Spread of Severe Acute Respiratory Syndrome Coronavirus Variants Between 2021 and 2022

To contain the surge of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the South Korean government has implemented non-pharmacological interventions as well as border restrictions. The efficacy of entry restrictions should be evaluated to facilitate their preparation for new variants of SARS-CoV-2. This study explored the impact of border policy changes on overseas entrants and local cases of SARS-CoV-2 variants. Data from the Korea Disease Control and Prevention Agency randomly collected between April 11, 2021 and August 20, 2022 were evaluated using the Granger causality model. The results showed that the outbreak gap of delta variants between international and domestic cases was 10 weeks, while that of omicron variants was approximately 2 weeks, meaning that the quarantine policy helped contain delta variants rather than more transmissible variants. It is recommended that countries implement quarantine policies based on particular purposes accounting for the specific features of different variants to avoid potential negative impacts on the economy.

Genomic Surveillance of SARS-CoV-2: Distribution of Clades in the Republic of Korea in 2020

Since a novel beta-coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in December 2019, there has been a rapid global spread of the virus. Genomic surveillance was conducted on samples isolated from infected individuals to monitor the spread of genetic variants of SARS-CoV-2 in Korea. The Korea Disease Control and Prevention Agency performed whole genome sequencing of SARS-CoV-2 in Korea for 1 year (January 2020 to January 2021). A total of 2,488 SARSCoV-2 cases were sequenced (including 648 cases from abroad). Initially, the prevalent clades of SARSCoV-2 were the S and V clades, however, by March 2020, GH clade was the most dominant. Only international travelers were identified as having G or GR clades, and since the first variant 501Y.V1 was identified (from a traveler from the United Kingdom on December 22 nd , 2020), a total of 27 variants of 501Y.V1, 501Y.V2, and 484K.V2 have been classified (as of January 25 th , 2021). The results in this study indicated that quarantining of travelers entering Korea successfully prevented dissemination of the SARS-CoV-2 variants in Korea.

Aberrant Promoter Hypomethylation of Sortilin 1: A Moyamoya Disease Biomarker / 대한뇌졸중학회지

BACKGROUND AND PURPOSE: The pathogenesis of moyamoya disease (MMD) remains poorly understood, and no reliable molecular biomarkers for MMD have been identified to date. The present study aimed to identify epigenetic biomarkers for use in the diagnosis of MMD. METHODS: We performed integrated analyses of gene expression profiles and DNA methylation profiles in endothelial colony forming cells (ECFCs) from three patients with MMD and two healthy individuals. Candidate gene mRNA expression and DNA methylation status were further validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and pyrosequencing analysis of an expanded ECFC sample set from nine patients with MMD and ten controls. We evaluated the diagnostic accuracy of the potential biomarkers identified here using receiver operating characteristic curve analyses and further measured major angiogenic factor expression levels using a tube formation assay and RT-qPCR. RESULTS: Five candidate genes were selected via integrated analysis; all five were upregulated by hypomethylation of specific promoter CpG sites. After further validation in an expanded sample set, we identified a candidate biomarker gene, sortilin 1 (SORT1). DNA methylation status at a specific SORT1 promoter CpG site in ECFCs readily distinguished patients with MMD from the normal controls with high accuracy (area under the curve 0.98, sensitivity 83.33%, specificity 100%). Furthermore, SORT1 overexpression suppressed endothelial cell tube formation and modulated major angiogenic factor and matrix metalloproteinase-9 expression, implying SORT1 involvement in MMD pathogenesis. CONCLUSIONS: Our findings suggest that DNA methylation status at the SORT1 promoter CpG site may be a potential biomarker for MMD.

Aberrant Hypomethylation of Solute Carrier Family 6 Member 12 Promoter Induces Metastasis of Ovarian Cancer

PURPOSE: Ovarian cancer (OC) is the most fatal of gynecological malignancies with a high rate of recurrence. We aimed to evaluate the expression of solute carrier family 6, member 12 (SLC6A12) and methylation of its promoter CpG sites in a xenograft mouse model of metastatic OC, and to investigate the regulatory mechanisms that promote aggressive properties during OC progression. MATERIALS AND METHODS: Expression of SLC6A12 mRNA was determined by reverse-transcription quantitative polymerase chain reaction (RT-qPCR), and DNA methylation status of its promoter CpGs was detected by quantitative methylation-specific PCR. The metastatic potential of SLC6A12 was evaluated by in vitro migration/invasion transwell assays. Gene expression and DNA methylation of SLC6A12 and clinical outcomes were further investigated from publicly available databases from curatedOvarianData and The Cancer Genome Atlas. RESULTS: SLC6A12 expression was 8.1–14.0-fold upregulated and its DNA methylation of promoter CpG sites was 41–62% decreased in tumor metastases. After treatment with DNA methyltransferase inhibitor and/or histone deacetylase inhibitor, the expression of SLC6A12 was profoundly enhanced (~8.0-fold), strongly supporting DNA methylation-dependent epigenetic regulation of SLC6A12. Overexpression of SLC6A12 led to increased migration and invasion of ovarian carcinoma cells in vitro, approximately 2.0-fold and 3.3-fold, respectively. The meta-analysis showed that high expression of SLC6A12 was significantly associated with poor overall survival [hazard ratio (HR)=1.07, p value=0.016] and that low DNA methylation levels of SLC6A12 at specific promoter CpG site negatively affected patient survival. CONCLUSION: Our findings provide novel evidence for the biological and clinical significance of SLC6A12 as a metastasis-promoting gene.

Overexpression of Mucin 13 due to Promoter Methylation Promotes Aggressive Behavior in Ovarian Cancer Cells

PURPOSE: Recent discoveries suggest that aberrant DNA methylation provides cancer cells with advanced metastatic properties. However, the precise regulatory mechanisms controlling metastasis genes and their role in metastatic transformation are largely unknown. To address epigenetically-regulated gene products involved in ovarian cancer metastasis, we examined the mechanisms regulating mucin 13 (MUC13) expression and its influence on aggressive behaviors of ovarian malignancies. MATERIALS AND METHODS: We injected SK-OV-3 ovarian cancer cells peritoneally into nude mice to mimic human ovarian tumor metastasis. Overexpression of MUC13 mRNA was detected in metastatic implants from the xenografts by expression microarray analysis and quantitative reverse-transcription polymerase chain reaction (qRT-PCR). The DNA methylation status within the MUC13 promoter region was determined using bisulfite sequencing PCR and quantitative methylation-specific PCR. We evaluated the effects of exogenous MUC13 on cell invasion and migration using in vitro transwell assays. RESULTS: MUC13 mRNA expression was up-regulated, and methylation of specific CpG sites within the promoter was reduced in the metastatic implants relative to those in wild-type SK-OV-3 cells. Addition of a DNA methyltransferase inhibitor to SK-OV-3 cells induced MUC13 expression, thereby implying epigenetic regulation of MUC13 by promoter methylation. MUC13 overexpression increased migration and invasiveness, compared to control cells, suggesting aberrant up-regulation of MUC13 is strongly associated with progression of aggressive behaviors in ovarian cancer. CONCLUSION: We provide novel evidence for epigenetic regulation of MUC13 in ovarian cancer. We suggest that the DNA methylation status within the MUC13 promoter region may be a potential biomarker of aggressive behavior in ovarian cancer.

Genome-wide Response of Normal WI-38 Human Fibroblast Cells to 1,763 MHz Radiofrequency Radiation

Increased exposure of human to RF fields has raised concerns for its potential adverse effects on our health. To address the biological effects of RF radiation, we used genome wide gene expression as the indicator. We exposed normal WI-38 human fibroblast cells to 1763 MHz mobile phone RF radiation at a specific absorption rate (SAR) of 60 W/kg with an operating cooling system for 24 h. There were no alterations in cell numbers or morphology after RF exposure. Through microarray analysis, we identified no differentially expressed genes (DEGs) at the 0.05 significance level after controlling for multiple testing errors with the Benjaminiochberg false discovery rate (BH FDR) method. Meanwhile, 82 genes were differentially expressed between RF-exposed cells and controls when the significance level was set at 0.01 without correction for multiple comparisons. We found that 24 genes (0.08% of the total genes examined) were changed by more than 1.5-fold on RF exposure. However, significant enrichment of any gene set or pathway was not observed from the functional annotation analysis. From these results, we did not find any evidence that non-thermal RF radiation at a 60-W/kg SAR significantly affects cell proliferation or gene expression in WI-38 cells.

Classification of Biological Effect of 1,763 MHz Radiofrequency Radiation Based on Gene Expression Profiles

Radiofrequency (RF) radiation might induce the transcription of a certain set of genes as other physical stresses like ionizing radiation and UV. To observe transcriptional changes upon RF radiation, we exposed WI-38, human lung fibroblast cell to 1763 MHz of mobile phone RF radiation at 60 W/kg of specific absorption rate (SAR) for 24h with or without heat control. There were no significant changes in cell numbers and morphology after exposure to RF radiation. Using quantitative RT-PCR, we checked the expression of three heat shock protein (HSP) (HSPA1A, HSPA6 and HSP105) and seven stress-related genes (TNFRSF11B, FGF2, TGFB2, ITGA2, BRIP1, EXO1, and MCM10) in RF only and RF/HS groups of RF-exposed cells. The expressions of three heat shock proteins and seven stress-related genes were selectively changed only in RF/HS groups. Based on the expression of ten genes, we could classify thermal and non-thermal effect of RF-exposure, which genes can be used as biomarkers for RF radiation exposure.

A Review of Power and Sample Size Estimation in Genomewide Association Studies / 예방의학회지

Power and sample size estimation is one of the crucially important steps in planning a genetic association study to achieve the ultimate goal, identifying candidate genes for disease susceptibility, by designing the study in such a way as to maximize the success possibility and minimize the cost. Here we review the optimal two-stage genotyping designs for genomewide association studies recently investigated by Wang et al(2006). We review two mathematical frameworks most commonly used to compute power in genetic association studies prior to the main study: Monte-Carlo and non-central chi-square estimates. Statistical powers are computed by these two approaches for case-control genotypic tests under one-stage direct association study design. Then we discuss how the linkagedisequilibrium strength affects power and sample size, and how to use empirically-derived distributions of important parameters for power calculations. We provide useful information on publicly available softwares developed to compute power and sample size for various study designs.