Background: F-18-fluorodeoxyglucose positron emission tomography (FDG-PET)/computed tomography (CT) can be used to measure bone mineral density (BMD), cross-sectional muscle area (CSMA), Hounsfield units (HU) of liver and muscle, subcutaneous adipose tissue (SAT), abdominal visceral adipose tissue (VAT), and glucose metabolism. The present study aimed to identify age-related changes in body composition and glucose metabolism in Korean using opportunistic FDG-PET/CT imaging. Methods: We analyzed FDG-PET/CT, clinical history, and laboratory data abstracted from the medical records of patients who underwent health screening at a single institute between 2017 and 2022. Results: In total, 278 patients were included in the analysis (male:female=140:138). Age and body mass index were positively correlated in female, but negatively correlated in male. BMD decreased with age more in female, and CSMA decreased with age more in male. Muscle HU decreased with age for both sexes. In female, SAT and VAT increased with age; and in male, SAT decreased slightly while VAT remained stable. Muscle glucose metabolism showed no association with age in male but increased with age in female. CSMA correlated positively with BMD overall; and positively correlated with VAT and SAT in male only. In female only, both SAT and VAT showed negative correlations with glucose metabolism and correlated positively with muscle glucose metabolism. Liver HU values were inversely correlated with VAT, especially in female; and positively correlated with muscle glucose metabolism in female only. Conclusion FDG-PET/CT demonstrated distinct patterns of age-related changes in body composition and glucose metabolism, with significant differences between sexes.

Background: Studies on predictive markers of insulin resistance (IR) and elevated liver transaminases in children and adolescents are limited. We evaluated the predictive capabilities of the single-point insulin sensitivity estimator (SPISE) index, metabolic score for insulin resistance (METS-IR), homeostasis model assessment of insulin resistance (HOMA-IR), the triglyceride (TG)/ high-density lipoprotein cholesterol (HDL-C) ratio, and the triglyceride-glucose index (TyG) for IR and alanine aminotransferase (ALT) elevation in this population. Methods: Data from 1,593 participants aged 10 to 18 years were analyzed using a nationwide survey. Logistic regression analysis was performed with IR and ALT elevation as dependent variables. Receiver operating characteristic (ROC) curves were generated to assess predictive capability. Proportions of IR and ALT elevation were compared after dividing participants based on parameter cutoff points. Results: All parameters were significantly associated with IR and ALT elevation, even after adjusting for age and sex, and predicted IR and ALT elevation in ROC curves (all P<0.001). The areas under the ROC curve of SPISE and METS-IR were higher than those of TyG and TG/HDL-C for predicting IR and were higher than those of HOMA-IR, TyG, and TG/HDL-C for predicting ALT elevation. The proportions of individuals with IR and ALT elevation were higher among those with METS-IR, TyG, and TG/ HDL-C values higher than the cutoff points, whereas they were lower among those with SPISE higher than the cutoff point. Conclusion SPISE and METS-IR are superior to TG/HDL-C and TyG in predicting IR and ALT elevation. Thus, this study identified valuable predictive markers for young individuals.

Extracellular vesicles (EVs) are lipid bilayer-enclosed particles carrying bioactive cargo, including nucleic acids, proteins, and lipids, facilitating intercellular and interorgan communication. In addition to traditional mediators such as hormones, metabolites, and cytokines, increasing evidence suggests that EVs are key modulators in various physiological and pathological processes, particularly influencing metabolic homeostasis and contributing to the progression of cardiometabolic diseases. This review provides an overview of the most recent insights into EV-mediated mechanisms involved in the pathogenesis of obesity, insulin resistance, diabetes mellitus, steatotic liver disease, atherosclerosis, and cardiovascular disease. EVs play a critical role in modulating insulin sensitivity, glucose homeostasis, systemic inflammation, and vascular health by transferring functional molecules to target cells. Understanding the EV-mediated network offers potential for identifying novel biomarkers and therapeutic targets, providing opportunities for EV-based interventions in cardiometabolic disease management. Although many challenges remain, this evolving field highlights the need for further research into EV biology and its translational applications in cardiovascular and metabolic health.

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: The associations between thyroid cancer and skeletal outcomes have not been thoroughly investigated. We aimed to investigate the risk of osteoporotic fractures in patients with thyroid cancer compared to that in a matched control group. Methods: This retrospective cohort study included 2,514 patients with thyroid cancer and 75,420 matched controls from the Korean National Health Insurance Service-National Sample Cohort (NHIS-NSC, 2006–2019). The rates of osteoporotic fractures were analyzed, and associations with the levothyroxine dose were evaluated. Results: Patients with thyroid cancer had a significantly lower risk of fracture than did the control group (hazard ratio [HR], 0.81; 95% confidence interval [CI], 0.69 to 0.94; P=0.006). Patients diagnosed with thyroid cancer after the age of 50 years (older cancer group) had a significantly lower risk of fracture than did those in the control group (HR, 0.72; 95% CI, 0.6 to 0.85; P<0.001), especially those diagnosed with spinal fractures (HR, 0.66; 95% CI, 0.51 to 0.85; P=0.001). Patients in the older cancer group started osteoporosis treatment earlier than did those in the control group (65.5±7.5 years vs. 67.3±7.6 years, P<0.001). Additionally, a lower dose of levothyroxine was associated with a reduced risk of fractures. Conclusion In the clinical setting, the risk of fracture in women diagnosed with thyroid cancer after the age of 50 years was lower than that in the control group, which was caused by more proactive osteoporosis treatment in postmenopausal women with thyroid cancer.

Background: Sclerostin, initially recognized for its pivotal role in bone metabolism, has gained attention for its multifaceted impact on overall human health. However, its influence on frailty—a condition that best reflects biological age—has not been thoroughly investigated. Methods: We collected blood samples from 244 older adults who underwent comprehensive geriatric assessments. Sclerostin levels were quantified using an enzyme-linked immunosorbent assay. Frailty was assessed using two validated approaches: the phenotypic model by Fried and the deficit accumulation frailty index (FI) by Rockwood. Results: After controlling for sex, age, and body mass index, we found that serum sclerostin levels were significantly elevated in frail individuals compared to their robust counterparts (P<0.001). There was a positive correlation between serum sclerostin concentrations and the FI (P<0.001). Each standard deviation increase in serum sclerostin was associated with an odds ratio of 1.87 for frailty (P=0.003). Moreover, participants in the highest quartile of sclerostin levels had a significantly higher FI and a 9.91-fold increased odds of frailty compared to those in the lowest quartile (P=0.003 and P=0.039, respectively). Conclusion These findings, which for the first time explore the association between circulating sclerostin levels and frailty, have significant clinical implications, positioning sclerostin as one of potential blood-based biomarkers for frailty that captures the comprehensive physical, mental, and social aspects of the elderly, extending beyond its traditional role in bone metabolism.

Background: Sarcopenia, a multifactorial disorder involving metabolic disturbance, suggests potential for metabolite biomarkers. Carnitine (CN), essential for skeletal muscle energy metabolism, may be a candidate biomarker. We investigated whether CN metabolites are biomarkers for sarcopenia. Methods: Associations between the CN metabolites identified from an animal model of sarcopenia and muscle cells and sarcopenia status were evaluated in men from an age-matched discovery (72 cases, 72 controls) and a validation (21 cases, 47 controls) cohort. Results: An association between CN metabolites and sarcopenia showed in mouse and cell studies. In the discovery cohort, plasma C5-CN levels were lower in sarcopenic men (P=0.005). C5-CN levels in men tended to be associated with handgrip strength (HGS) (P=0.098) and were significantly associated with skeletal muscle mass (P=0.003). Each standard deviation increase in C5-CN levels reduced the odds of low muscle mass (odd ratio, 0.61; 95% confidence interval [CI], 0.42 to 0.89). The area under the receiver operating characteristic curve (AUROC) of CN score using a regression equation of C5-CN levels, for sarcopenia was 0.635 (95% CI, 0.544 to 0.726). In the discovery cohort, addition of CN score to HGS significantly improved AUROC from 0.646 (95% CI, 0.575 to 0.717; HGS only) to 0.727 (95% CI, 0.643 to 0.810; P=0.006; HGS+CN score). The improvement was confirmed in the validation cohort (AUROC=0.563; 95% CI, 0.470 to 0.656 for HGS; and AUROC=0.712; 95% CI, 0.569 to 0.855 for HGS+CN score; P=0.027). Conclusion C5-CN, indicative of low muscle mass, is a potential circulating biomarker for sarcopenia in men. Further studies are required to confirm these results and explore sarcopenia-related metabolomic changes.

Recent studies have shown an increased abundance of Sphingomonas paucimobilis, an aerobic, Gram-negative bacterium with a distinctive cell envelope rich in glycosphingolipids, within the gut microbiome of individuals with Alzheimer Disease (AD). However, the fact that S. paucimobilis is a well-known pathogen associated with nosocomial infections presents a significant challenge in investigating whether its presence in the gut microbiome is detrimental or beneficial, particularly in the context of AD. This study examines the impact of S. paucimobilis-derived extracellular vesicles (Spa-EV) on Aβ-induced pathology in cellular and animal models of AD. Microarray analysis reveals that Spa-EV treatment modulates Aβ42-induced alterations in gene expression in both HT22 neuronal cells and BV2 microglia cells. Among the genes significantly affected by SpaEV, notable examples include Bdnf, Nt3/4, and Trkb, which are key players of neurotrophic signaling; Pgc1α, an upstream regulator of mitochondrial biogenesis; Mecp2 and Sirt1, epigenetic factors that regulate numerous gene expressions; and Il1β, Tnfα, and Nfκb-p65, which are associated with neuroinflammation. Remarkably, Spa-EV effectively reverses Aβ42-induced alteration in the expression of these genes through the upregulation of Mecp2. Furthermore, administration of Spa-EV in Tg-APP/PS1 mice restores the reduced expression of neurotrophic factors, Pgc1α, MeCP2, and Sirt1, while suppressing the increased expression of proinflammatory genes in the brain. Our results indicate that Spa-EV has the potential to reverse Aβ-induced dysregulation of gene expression in neuronal and microglial cells. These alterations encompass those essential for neurotrophic signaling and neuronal plasticity, mitochondrial function, and the regulation of inflammatory processes.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background/Aims: Magnifying endoscopy with narrow-band imaging (ME-NBI) enables the visualization of detailed microsurface (MS) and microvascular (MV) structures in the gastrointestinal tract. White globe appearance (WGA) is a small whitish lesion with a globular shape identified during ME-NBI for early gastric cancer (EGC). This study aimed to investigate the associations between WGA, clinicopathological characteristics, and other ME-NBI findings in patients with EGC. Methods: The presence or absence of WGA in 122 patients (126 lesions) with an endoscopic diagnosis of EGC who underwent ME-NBI before endoscopic or surgical resection was prospectively collected and retrospectively analyzed. During ME-NBI, the MS and MV patterns and the presence of WGA and white opaque substances (WOS) were investigated. EGC cases were categorized as differentiated or undifferentiated type, and mucosal, submucosal, or advanced. Results: Of 126 lesions, WGA was observed in 25 (19.8%). WGA was associated with tumor size (≤2 cm [17/63, 27.0%] vs >2 cm [8/63, 12.7%]; p=0.044), histologic type differentiated type [22/89, 24.7%] vs undifferentiated type [3/37. 8.1%]; p=0.033), and tumor location (upper third [1/11, 9.1%] vs middle third [18/58, 31.0%] and lower third [6/57, 10.5%]; p=0.017). Although WGA was observed more frequently in lesions with an oval/tubular MS pattern, a fine-network MV pattern, and the absence of WOS, the difference was not statistically significant (MS pattern, p=0.358; MV pattern, p=0.212; WOS, p=0.121, respectively). Conclusions WGA was associated with small tumor size, differentiated-type histology, and middle-third tumor location, and was more frequently observed in lesions with an oval/tubular MS and fine-network MV patterns and the absence of WOS.