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Genome-Wide Association of New-Onset Hypertension According to Renin Concentration: The Korean Genome and Epidemiology Cohort Study

2026-07-16T07:56:06Z

Title: Genome-Wide Association of New-Onset Hypertension According to Renin Concentration: The Korean Genome and Epidemiology Cohort Study Authors: Lee, Sung Bum; Park, Byoung Jin; Hong, Kyung-Won; Jung, Dong Hyuk Abstract: The renin-angiotensin system (RAS) is a crucial regulator of vascular resistance and blood volume in the body. This study aimed to examine the genetic predisposition of the plasma renin concentration influencing future hypertension incidence. Based on the Korean Genome and Epidemiology Cohort dataset, 5211 normotensive individuals at enrollment were observed over 12 years, categorized into the low-renin and high-renin groups. We conducted genome-wide association studies for the total, low-renin, and high-renin groups. Among the significant SNPs, the lead SNPs of each locus were focused on for further interpretation. The effect of genotypes was determined by logistic regression analysis between controls and new-onset hypertension, after adjusting for potential confounding variables. During a mean follow-up period of 7.6 years, 1704 participants (32.7%) developed hypertension. The low-renin group showed more incidence rates of new-onset hypertension (35.3%) than the high-renin group (26.5%). Among 153 SNPs in renin-related gene regions, two SNPs (rs11726091 and rs8137145) showed an association in the high-renin group, four SNPs (rs17038966, rs145286444, rs2118663, and rs12336898) in the low-renin group, and three SNPs (rs1938859, rs7968218, and rs117246401) in the total population. Most significantly, the low-renin SNP rs12336898 in the SPTAN1 gene, closely related to vascular wall remodeling, was associated with the development of hypertension (p-value = 1.3 x 10(-6)). We found the candidate genetic polymorphisms according to blood renin concentration. Our results might be a valuable indicator for hypertension risk prediction and preventive measure, considering renin concentration with genetic susceptibility.

Diagnostic performance of endoscopic ultrasound-artificial intelligence using deep learning analysis of gallbladder polypoid lesions

2026-07-16T06:50:19Z

Title: Diagnostic performance of endoscopic ultrasound-artificial intelligence using deep learning analysis of gallbladder polypoid lesions Authors: Jang, Sung Ill; Kim, Young Jae; Kim, Eui Joo; Kang, Huapyong; shon, seung jin; Seol, Yu Jin; Lee, Dong Ki; Kim, Kwang Gi; Cho, Jae Hee Abstract: Background and Aim Endoscopic ultrasound (EUS) is the most accurate diagnostic modality for polypoid lesions of the gallbladder (GB), but is limited by subjective interpretation. Deep learning-based artificial intelligence (AI) algorithms are under development. We evaluated the diagnostic performance of AI in differentiating polypoid lesions using EUS images. Methods The diagnostic performance of the EUS-AI system with ResNet50 architecture was evaluated via three processes: training, internal validation, and testing using an AI development cohort of 1039 EUS images (836 GB polyps and 203 gallstones). The diagnostic performance was verified using an external validation cohort of 83 patients and compared with the performance of EUS endoscopists. Results In the AI development cohort, we developed an EUS-AI algorithm and evaluated the diagnostic performance of the EUS-AI including sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. For the differential diagnosis of neoplastic and non-neoplastic GB polyps, these values for EUS-AI were 57.9%, 96.5%, 77.8%, 91.6%, and 89.8%, respectively. In the external validation cohort, we compared diagnostic performances between EUS-AI and endoscopists. For the differential diagnosis of neoplastic and non-neoplastic GB polyps, the sensitivity and specificity were 33.3% and 96.1% for EUS-AI; they were 74.2% and 44.9%, respectively, for the endoscopists. Besides, the accuracy of the EUS-AI was between the accuracies of mid-level (66.7%) and expert EUS endoscopists (77.5%). Conclusions This newly developed EUS-AI system showed favorable performance for the diagnosis of neoplastic GB polyps, with a performance comparable to that of EUS endoscopists.

Early Chronic Kidney Disease (G1-G3a) in Combination with Steatosis as a Predictor of Incident Ischemic Heart Disease: A Longitudinal Study in Non-Diabetic Koreans

2026-07-16T06:57:31Z

Title: Early Chronic Kidney Disease (G1-G3a) in Combination with Steatosis as a Predictor of Incident Ischemic Heart Disease: A Longitudinal Study in Non-Diabetic Koreans Authors: Lee, Sung Bum; Park, Byoung Jin; Lee, Yong Jae; Jung, Dong Hyuk Abstract: Hepatic steatosis and chronic kidney disease (CKD) in the advanced stages are closely related to cardiovascular diseases. Despite the potential connection between early CKD (G1-G3a) and hepatic steatosis on cardiometabolic risks, few studies have revealed their causal link to ischemic heart disease (IHD). We prospectively investigated the combined effect of CKD in earlier stages and hepatic steatosis on incident IHD risk in large-scale, non-diabetic Koreans. Data were assessed from 16,531 participants without diabetes from the Health Risk Assessment Study (HERAS) and Korea Health Insurance Review and Assessment (HIRA) data. We divided the study population into four groups according to the existence of early CKD and hepatic steatosis: controls, early CKD only, hepatic steatosis only, and both early CKD and hepatic steatosis. We prospectively assessed hazard ratios (HRs) with 95% confidence intervals (CIs) for IHD using multivariate Cox proportional-hazard regression models over a 50-month period. During the follow-up period, 326 (2.0%) patients developed IHD. HRs of IHD in the four groups were 1.00 (controls), 1.26 (95% CI 0.72-2.19), 1.19 (95% CI 0.90-1.57) and 1.76 (95% CI 1.04-2.97), respectively, after adjusting for potential confounding variables. Even less than stage 3A, CKD could precede and predict IHD in patients with hepatic steatosis.

(−)-Gallocatechin gallate from green tea rescues cognitive impairment through restoring hippocampal silent synapses in post-menopausal depression

2026-07-16T06:46:39Z

Title: (−)-Gallocatechin gallate from green tea rescues cognitive impairment through restoring hippocampal silent synapses in post-menopausal depression Authors: Sukjin Ko; Won Seuk Jang; Ji-Hyun Jeong; Ji Woong Ahn; Young-Hwan Kim; Sohyun Kim; Hyeon Kyeong Chae; Seungsoo Chung. Abstract: Post-menopausal depression (PMD) is a common psychological disorder accompanied by a cognitive deficit, which is caused by a series of uncontrolled emotional disruptions by strong environmental stressors during menopause. To overcome PMD-induced cognitive deficit, Green tea has been suggested as a dietary supplement because of its ameliorating effect on cognitive dysfunction induced by normal aging or neurodegenerative syndromes; however, its clinical use to improve PMD-accompanied cognitive deficit is still limited due to the controversy for the active ingredients and ambiguous mechanism of its action. Here, we developed modified high-temperature-processed green tea extract (HTP-GTE), which showed lower neuronal toxicity than the conventional green tea extract (GTE). We also demonstrated that HTP-GTE administration prevented the development of learned helplessness (LH) in a rat post-menopausal model. Additionally, HTP-GTE improved LH-induced cognitive impairments simultaneously with rescued the long-term synaptic plasticity. This occurred via the restoration of silent synapse formation by increasing the hippocampal BDNF-tyrosine receptor kinase B pathway in the helpless ovariectomized (OVX) rats. Likewise, we also identified that (−)-gallocatechin gallate was the main contributor of the HTP-GTE effect. Our findings suggested that HTP-GTE has a potential as a preventive nutritional supplement to ameliorate cognitive dysfunctions associated with PMD. © 2021, The Author(s).