Metabolic syndrome (MetS) which is caused by obesity and insulin resistance, is well known for its predictive capability for the risk of type 2 diabetes mellitus and cardiovascular disease. The development of MetS is associated with multiple genetic factors, environmental factors and lifestyle. We performed a genome-wide association study to identify single-nucleotide polymorphism (SNP) related to MetS in large Korean population based samples of 1,362 subjects with MetS and 6,061 controls using the Axiom^® Korean Biobank Array 1.0. We replicated the data in another sample including 502 subjects with MetS and 1,751 controls. After adjusting for age and sex, rs662799 located in the APOA5 gene were significantly associated with MetS. 15 SNPs in GCKR, C2orf16, APOA5, ZPR1, and BUD13 were associated with high triglyceride (TG). 14 SNPs in APOA5, ALDH1A2, LIPC, HERPUD1, and CETP, and 2 SNPs in MTNR1B were associated with low high density lipoprotein cholesterol (HDL-C) and high fasting blood glucose respectively. Among these SNPs, 6 TG SNPs: rs1260326, rs1260333, rs1919127, rs964184, rs2075295 and rs1558861 and 11 HDL-C SNPs: rs4775041, rs10468017, rs1800588, rs72786786, rs173539, rs247616, rs247617, rs3764261, rs4783961, rs708272, and rs7499892 were first discovered in Koreans. Additional research is needed to confirm these 17 novel SNPs in Korean population.

The prevalence of metabolic syndrome (MS) in the nonobese population is not low. However, the identification and risk mitigation of MS are not easy in this population. We aimed to develop an MS prediction model using genetic and clinical factors of nonobese Koreans through machine learning methods. A prediction model for MS was designed for a nonobese population using clinical and genetic polymorphism information with five machine learning algorithms, including naïve Bayes classification (NB). The analysis was performed in two stages (training and test sets). Model A was designed with only clinical information (age, sex, body mass index, smoking status, alcohol consumption status, and exercise status), and for model B, genetic information (for 10 polymorphisms) was added to model A. Of the 7,502 nonobese participants, 647 (8.6%) had MS. In the test set analysis, for the maximum sensitivity criterion, NB showed the highest sensitivity: 0.38 for model A and 0.42 for model B. The specificity of NB was 0.79 for model A and 0.80 for model B. In a comparison of the performances of models A and B by NB, model B (area under the receiver operating characteristic curve [AUC] = 0.69, clinical and genetic information input) showed better performance than model A (AUC = 0.65, clinical information only input). We designed a prediction model for MS in a nonobese population using clinical and genetic information. With this model, we might convince nonobese MS individuals to undergo health checks and adopt behaviors associated with a preventive lifestyle.

A deep learning model to predict incident lung cancer from chest radiographs showed added value to the 2021 U.S. Preventive Services Task Force recommendations for low-dose CT lung cancer screening... Background A deep learning (DL) model to identify lung cancer screening candidates based on their chest radiographs requires external validation with a recent real-world non–U.S. sample. Purpose To...

Huiyul Park, Eileen L. Yoon, Goh Eun Chung, Eun Kyung Choe, Jung Ho Bae, Seung Ho Choi, Mimi Kim, Woochang Hwang, Hye-Lin Kim, Sun Young Yang, Dae Won Jun. Gut and Liver 2024;18:316-27. https://doi.org/10.5009/gnl230044

A relationship between lung function and sarcopenia has been suggested. This study aimed to evaluate the association between lung function and abdominal skeletal muscle mass, as measured by computed tomography (CT). The clinical records of 1907 subjects (1406 males, mean age 53.1 ± 9.2 years), who underwent routine health check-ups, including spirometry and abdominal CT, were retrospectively reviewed. The CT-measured skeletal muscle index (SMI_CT, cm²/(kg/m²) was defined as the skeletal muscle area of the third lumbar vertebrae (L3) level that is normalized by the body mass index. The mean values of forced vital capacity (FVC) and forced expiratory volume in one second (FEV1) gradually increased as the SMI_CT quartiles increased (all p for trend < 0.05). The proportions of subjects with less than 80% of the predicted FVC (%) and predicted FEV1 (%) significantly decreased as the SMI_CT quartiles increased (all p for trend < 0.05). The β regression coefficients for FVC and FEV1 significantly increased as the SMI_CT quartiles increased after adjusting for other confounding variables (p for trend < 0.05). This study showed that abdominal muscle mass, which was precisely measured by CT, independently affected lung function proportionally after adjusting for confounding factors in relatively healthy adults.

Epidemiologic evidence indicates that the prevalence and severity of coronary artery disease vary depending on ethnicity. In this study, a genome-wide association study for coronary artery calcification (CAC) was performed in a Korean population-based sample of 400 subjects without prior coronary artery disease and replicated in another of 1,288 subjects. CAC score, as assessed by multi-detector computed tomography, was evaluated in volunteers for screening purposes as part of a routine health examination. CAC score greater than the 90th percentile across the age in each sex group was considered severe CAC. Single nucleotide polymorphisms (SNPs) associated with severe CAC after adjusting for age, sex, hypertension, and diabetes were investigated using the additive model of logistic regression. One SNP (rs10757272 in the intronic region of the CDKN2B-AS1 gene in chromosome 9p21.3) met Bonferroni correction in the discovery set (p = 7.55E-08) and was also significant in the validation set by TaqMan assay (p = 0.036). Subjects with rs10757272 were found to have an increased odds ratio (OR) of having severe CAC in multivariate logistic regression analysis after adjusting for age, sex, hypertension, and diabetes (adjusted OR 3.24 and 95% CI 2.11–4.97). In conclusion, SNP rs10757272 in chromosome 9p21.3 was associated with severe CAC based on age and sex in an asymptomatic community-based Korean population. Therefore, it was associated with promotion of coronary artery calcification in subclinical state.