BACKGROUND AND OBJECTIVE

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as the causative agent of COVID-19 has significantly challenged the public health landscape in late 2019. After almost 3 years of the first ever SARS-CoV-2 case, the World Health Organization (WHO) declared the end of this global health emergency in May 2023. Although, despite the subsequent drop of COVID-19 cases, the SARS-CoV-2 infection still exhibited multiple waves of infection, primarily attributed to the appearance of new variants. Five of these variants have been classified as Variants of Concern (VOC): Alpha, Beta, Gamma, Delta, and the most recent, Omicron. Therefore, the development of methods for the timely and accurate detection of viral variants remains fundamental, ensuring an ongoing and effective response to the disease. This study aims to evaluate the feasibility of the application of an in-house approach in genomic surveillance for the detection of SARS-CoV-2 variants using in silico designed primers.

METHODS

The primers used for the study were particularly designed based on conserved regions of certain genes in the virus, targeting distinct mutations found in known variants of SARS-CoV-2. Viral RNA extracts from nasopharyngeal samples (n=14) were subjected to quantitative and qualitative tests (Nanodrop and AGE). Selected samples were then analyzed by RT-PCR and amplicons were submitted for sequencing. Sequence alignment analysis was carried out to identify the prevailing COVID-19 variant present in the sample population.

RESULTS

The study findings demonstrated that the in-house method was able to successfully amplify conserved sequences (spike, envelope, membrane, ORF1ab) and enabled identification of the circulating SARS-CoV-2 variant among the samples. Majority of the samples were identified as Omicron variant. Three out of four designed primers effectively bound into the conserved sequence of target genes present in the sample, revealing the specific SARSCoV-2 variant. The detected mutations characterized for Omicron found in the identified lineages included K417N, S477N, and P681H which were also identified as mutations of interest. Furthermore, identification of the B.1.448 lineage which was not classified in any known variant also provided the potential of the developed in-house method in detecting unknown variants of COVID-19.

CONCLUSION

Among the five VOCs, Omicron is the most prevalent and dominant variant. The in-house direct PCR product sequencing surveillance (DPPSS) method provided an alternative platform for SAR-CoV-2 variant analysis which is accessible and affordable than the conventional diagnostic surveillance methods and the whole genome sequencing. Further evaluation and improvements on the oligonucleotide primers may offer significant contribution to the development of a specific and direct PCRbased detection of new emerging COVID-19 variants.

Sars-cov-2 ; Polymerase Chain Reaction ; Dna Primers ; Oligonucleotide Primers ; Computer Simulation ; Conserved Sequence ; Coronavirus ; Covid-19 ; Disease ; Emergencies ; Evaluation Studies As Topic ; Genes ; Genome ; Global Health ; Health ; Identification (psychology) ; Infection ; Infections ; Membranes ; Methods ; Mutation ; Oligonucleotides ; Organizations ; Population ; Public Health ; Rna ; Rna, Viral ; Sars Virus ; Sequence Alignment ; Severe Acute Respiratory Syndrome ; Syndrome ; Viruses ; Whole Genome Sequencing ; World Health Organization

BACKGROUND AND OBJECTIVE

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as the causative agent of COVID-19 has significantly challenged the public health landscape in late 2019. After almost 3 years of the first ever SARS-CoV-2 case, the World Health Organization (WHO) declared the end of this global health emergency in May 2023. Although, despite the subsequent drop of COVID-19 cases, the SARS-CoV-2 infection still exhibited multiple waves of infection, primarily attributed to the appearance of new variants. Five of these variants have been classified as Variants of Concern (VOC): Alpha, Beta, Gamma, Delta, and the most recent, Omicron. Therefore, the development of methods for the timely and accurate detection of viral variants remains fundamental, ensuring an ongoing and effective response to the disease. This study aims to evaluate the feasibility of the application of an in-house approach in genomic surveillance for the detection of SARS-CoV-2 variants using in silico designed primers.

METHODS

The primers used for the study were particularly designed based on conserved regions of certain genes in the virus, targeting distinct mutations found in known variants of SARS-CoV-2. Viral RNA extracts from nasopharyngeal samples (n=14) were subjected to quantitative and qualitative tests (Nanodrop and AGE). Selected samples were then analyzed by RT-PCR and amplicons were submitted for sequencing. Sequence alignment analysis was carried out to identify the prevailing COVID-19 variant present in the sample population.

RESULTS

The study findings demonstrated that the in-house method was able to successfully amplify conserved sequences (spike, envelope, membrane, ORF1ab) and enabled identification of the circulating SARS-CoV-2 variant among the samples. Majority of the samples were identified as Omicron variant. Three out of four designed primers effectively bound into the conserved sequence of target genes present in the sample, revealing the specific SARSCoV-2 variant. The detected mutations characterized for Omicron found in the identified lineages included K417N, S477N, and P681H which were also identified as mutations of interest. Furthermore, identification of the B.1.448 lineage which was not classified in any known variant also provided the potential of the developed in-house method in detecting unknown variants of COVID-19.

CONCLUSION

Among the five VOCs, Omicron is the most prevalent and dominant variant. The in-house direct PCR product sequencing surveillance (DPPSS) method provided an alternative platform for SAR-CoV-2 variant analysis which is accessible and affordable than the conventional diagnostic surveillance methods and the whole genome sequencing. Further evaluation and improvements on the oligonucleotide primers may offer significant contribution to the development of a specific and direct PCRbased detection of new emerging COVID-19 variants.

Sars-cov-2 ; Polymerase Chain Reaction ; Dna Primers ; Oligonucleotide Primers

Background: and Purpose The National Brain Biobank of Korea (NBBK) is a brain bank consortium supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, and was launched in 2015 to support research into neurodegenerative disease dementia (NDD). This study aimed to introduce the NBBK and describes clinicopathological correlations based on analyses of data collected from the NBBK. Methods: Four hospital-based brain banks have been established in South Korea: Samsung Medical Center Brain Bank (SMCBB), Seoul National University Hospital Brain Bank (SNUHBB), Pusan National University Hospital Brain Bank (PNUHBB), and Myongji Hospital Brain Bank (MJHBB). Clinical and pathological data were collected from these brain banks using standardized protocols. The prevalence rates of clinical and pathological diagnoses were analyzed in order to characterize the clinicopathological correlations. Results: Between August 2016 and December 2023, 185 brain specimens were collected and pathologically evaluated (SNUHBB: 117; PNUHBB: 27; SMCBB: 34; MJHBB: 7). The age at consent was 70.8±12.6 years, and the age at autopsy was 71.7±12.4 years. The four-most-common clinical diagnoses were Alzheimer’s disease (AD) dementia (20.0%), idiopathic Parkinson’s disease (15.1%), unspecified dementia (11.9%), and cognitively unimpaired (CU) (11.4%).Most cases of unspecified dementia had a pathological diagnosis of central nervous system (CNS) vasculopathy (31.8%) or AD (31.8%). Remarkably, only 14.2% of CU cases had normal pathological findings. The three-most-common pathological diagnoses were AD (26.5%), CNS vasculopathy (14.1%), and Lewy body disease (13.5%). Conclusions These clinical and neuropathological findings provide a deeper understanding of the mechanisms underlying NDD in South Korea.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Plasma biomarkers, including phosphorylated tau (ptau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), are promising tools for detecting Alzheimer’s disease (AD) pathology. However, cross-laboratory reproducibility remains a challenge, even when using identical analytical platforms such as single-molecule array (Simoa). This study aimed to compare plasma biomarker measurements (ptau217, GFAP, and NfL) between 2 laboratories, the University of Gothenburg (UGOT) and DNAlink, and evaluate their associations with amyloid positron emission tomography (PET) imaging. Methods: Plasma biomarkers were measured using Simoa platforms at both laboratories:the UGOT and DNAlink Incorporation. Diagnostic performance for predicting amyloid PET positivity, cross-laboratory agreement, and the impact of normalization techniques were assessed. Bland-Altman plots and correlation analyses were employed to evaluate agreement and variability. Results: Plasma ptau217 concentrations exhibited strong correlations with amyloid PET global centiloid values, with comparable diagnostic performance between laboratories (area under the curve=0.94 for UGOT and 0.95 for DNAlink). Cross-laboratory agreement for ptau217 was excellent (r=0.96), improving further after natural log transformation. GFAP and NfL also demonstrated moderate to strong correlations (r=0.86 for GFAP and r=0.99 for NfL), with normalization reducing variability. Conclusions Plasma biomarker measurements were consistent across laboratories using identical Simoa platforms, with strong diagnostic performance and improved agreement after normalization. These findings support the scalability of plasma biomarkers for multicenter studies and underscore their potential for standardized applications in AD research and clinical practice.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Plasma biomarkers, including phosphorylated tau (ptau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), are promising tools for detecting Alzheimer’s disease (AD) pathology. However, cross-laboratory reproducibility remains a challenge, even when using identical analytical platforms such as single-molecule array (Simoa). This study aimed to compare plasma biomarker measurements (ptau217, GFAP, and NfL) between 2 laboratories, the University of Gothenburg (UGOT) and DNAlink, and evaluate their associations with amyloid positron emission tomography (PET) imaging. Methods: Plasma biomarkers were measured using Simoa platforms at both laboratories:the UGOT and DNAlink Incorporation. Diagnostic performance for predicting amyloid PET positivity, cross-laboratory agreement, and the impact of normalization techniques were assessed. Bland-Altman plots and correlation analyses were employed to evaluate agreement and variability. Results: Plasma ptau217 concentrations exhibited strong correlations with amyloid PET global centiloid values, with comparable diagnostic performance between laboratories (area under the curve=0.94 for UGOT and 0.95 for DNAlink). Cross-laboratory agreement for ptau217 was excellent (r=0.96), improving further after natural log transformation. GFAP and NfL also demonstrated moderate to strong correlations (r=0.86 for GFAP and r=0.99 for NfL), with normalization reducing variability. Conclusions Plasma biomarker measurements were consistent across laboratories using identical Simoa platforms, with strong diagnostic performance and improved agreement after normalization. These findings support the scalability of plasma biomarkers for multicenter studies and underscore their potential for standardized applications in AD research and clinical practice.