Background: The heterogeneity of chronic kidney disease (CKD) and fragmented analysis methods hinder the precise identification of novel biomarkers. We addressed this challenge using two independent cohorts to integrate genomics and metabolomics, aiming to identify cause-specific biomarkers for CKD in the Korean population. Methods: A longitudinal genome-wide association study using the Cox proportional hazards model was conducted using the Ansan and Ansung cohort. To validate these genomic biomarkers and integrate them with plasma metabolomics biomarkers, we utilized a hospital-based biopsy cohort to identify cause-specific CKD biomarkers. Within the biopsy cohort, we analyzed four disease subsets, including type 2 diabetic kidney disease (DKD), hypertensive nephropathy (HN), immunoglobulin A nephropathy (IgAN), and membranous nephropathy (MN), and compared them with healthy individuals. Significant single nucleotide polymorphisms(SNPs) and metabolites for each CKD subset were identified through logistic regression and correlation-based network analyses. Subsequently, we analyzed the risk of disease progression associated with the identified pairs. Results: A total of 448 variants associated with CKD occurrence were identified, with significant differences in several genetic variants and metabolites observed among patients with DKD, HN, IgAN, and MN compared to healthy individuals. Among 36 SNP-metabolite pairs, those involing FOXB1 and ZFP42 were associated with DKD, whereas pairs involving MMRN1 and SYNJ2 were linked to MN. Notably, the rs1025170 variant in FOXB1 and tyrosine pair was correlated with DKD progression. Conclusion Integrating genomics and metabolomics across independent cohorts enables the discovery of cause-specific biomarkers for the occurrence and progression of CKD in the Korean population.

Objectives: This study aimed to develop a NOVA-based scoring approach for evaluating ultra- processed food (UPF) intake among Korean adults and to examine its performance. Previous studies have reported that young adults have the highest levels of UPF consumption. Accordingly, this study focused on adults aged 19–40 years and developed scoring components reflecting dietary patterns specific to Korean eating habits. Methods: Using 24-hour dietary recall data from adults aged 19–40 years in the Korea National Health and Nutrition Examination Survey (2021–2023), foods were classified according to the Korean-adapted NOVA system. The top 10 food groups accounting for ≥ 80% of cumulative UPF-derived energy were selected to construct the scoring components. The tool was operationalized using food frequency questionnaire (FFQ) data from the Gangwon cohort study (2022–2024). Intake frequencies were converted into scores ranging from 0 (“rarely or never”) to 5 (“≥ 1 time/day”), and summed to generate the NOVA–UPF score (range: 0–50). Results: Among 237 young adults (aged 20–49 years), the mean NOVA–UPF score was 22.9 ± 8.3. A positive association was observed between the NOVA–UPF score and FFQbased UPF energy intake (Spearman’s ρ = 0.629, P < 0.001). Cross-classification showed that 51.9% were classified into the same tertile and 94.9% into the same or adjacent tertiles, with a weighted kappa coefficient of 0.279. Conclusion This NOVA-based scoring approach may serve as a preliminary tool for assessing UPF intake in Korean young adults. Further refinement and rigorous validation using quantitative dietary assessment methods and more diverse populations are required before broader application.

In patients with differentiated thyroid cancer (DTC), initial recurrence risk stratification based on clinical, histopathological, and perioperative data remains the key determinant for guiding management strategies during the first 1-2 years post-treatment. However, the adoption of ongoing risk stratification (ORS), which dynamically reassesses risk by integrating longitudinal clinical data and treatment response, enables more precise long-term prognostic assessment and facilitates highly individualized management. Building upon recent guidelines, the 2026 KTA guideline has been further refined by incorporating robust evidence from large-scale national cohorts and comprehensive systematic reviews. These updated recommendations outline contemporary concepts of ORS, risk-adapted TSH suppression targets, optimized surveillance modalities for recurrence detection, and disease-specific long-term follow-up strategies. Reflecting the paradigm shift toward de-escalated treatment, this revision integrates evolved perspectives on TSH suppression intensity, the clinical interpretation of thyroglobulin levels, and tailored follow-up intervals. These evidence-based recommendations aim to minimize unnecessary treatment and excessive surveillance in the large proportion of patients with excellent prognosis after initial therapy, while ensuring that each patient receives appropriately tailored and effective long-term management.

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: 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: 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.