Diabetes & Metabolism Journal

Original Articles

Others
Clinical Trial Protocol for Porcine Islet Xenotransplantation in South Korea: Byung-Joon Kim, Jun-Seop Shin, Byoung-Hoon Min, Jong-Min Kim, Chung-Gyu Park, Hee-Jung Kang, Eung Soo Hwang, Won-Woo Lee, Jung-Sik Kim, Hyun Je Kim, Iov Kwon, Jae Sung Kim, Geun Soo Kim, Joonho Moon, Du Yeon Shin, Bumrae Cho, Heung-Mo Yang, Sung Joo Kim, Kwang-Won Kim; Diabetes Metab J. 2024;48(6):1160-1168. Published online May 21, 2024; DOI: https://doi.org/10.4093/dmj.2023.0260

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Abstract PDF Supplementary Material PubReader ePub: Background
Islet transplantation holds promise for treating selected type 1 diabetes mellitus patients, yet the scarcity of human donor organs impedes widespread adoption. Porcine islets, deemed a viable alternative, recently demonstrated successful longterm survival without zoonotic risks in a clinically relevant pig-to-non-human primate islet transplantation model. This success prompted the development of a clinical trial protocol for porcine islet xenotransplantation in humans.
Methods
A single-center, open-label clinical trial initiated by the sponsor will assess the safety and efficacy of porcine islet transplantation for diabetes patients at Gachon Hospital. The protocol received approval from the Gachon Hospital Institutional Review Board (IRB) and the Korean Ministry of Food and Drug Safety (MFDS) under the Investigational New Drug (IND) process. Two diabetic patients, experiencing inadequate glycemic control despite intensive insulin treatment and frequent hypoglycemic unawareness, will be enrolled. Participants and their family members will engage in deliberation before xenotransplantation during the screening period. Each patient will receive islets isolated from designated pathogen-free pigs. Immunosuppressants and systemic infection prophylaxis will follow the program schedule. The primary endpoint is to confirm the safety of porcine islets in patients, and the secondary endpoint is to assess whether porcine islets can reduce insulin dose and the frequency of hypoglycemic unawareness.
Conclusion
A clinical trial protocol adhering to global consensus guidelines for porcine islet xenotransplantation is presented, facilitating streamlined implementation of comparable human trials worldwide.

Cardiovascular Risk/Epidemiology
Psychotic Disorders and the Risk of Type 2 Diabetes Mellitus, Atherosclerotic Cardiovascular Diseases, and All-Cause Mortality: A Population-Based Matched Cohort Study: You-Bin Lee, Hyewon Kim, Jungkuk Lee, Dongwoo Kang, Gyuri Kim, Sang-Man Jin, Jae Hyeon Kim, Hong Jin Jeon, Kyu Yeon Hur; Diabetes Metab J. 2024;48(1):122-133. Published online January 3, 2024; DOI: https://doi.org/10.4093/dmj.2022.0431

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Abstract PDF Supplementary Material PubReader ePub: Background
The effects of psychotic disorders on cardiometabolic diseases and premature death need to be determined in Asian populations.
Methods
In this population-based matched cohort study, the Korean National Health Insurance Service database (2002 to 2018) was used. The risk of type 2 diabetes mellitus (T2DM), acute myocardial infarction (AMI), ischemic stroke, composite of all cardiometabolic diseases, and all-cause death during follow-up was compared between individuals with psychotic disorders treated with antipsychotics (n=48,162) and 1:1 matched controls without psychiatric disorders among adults without cardiometabolic diseases before or within 3 months after baseline.
Results
In this cohort, 53,683 composite cases of all cardiometabolic diseases (during median 7.38 years), 899 AMI, and 1,216 ischemic stroke cases (during median 14.14 years), 7,686 T2DM cases (during median 13.26 years), and 7,092 deaths (during median 14.23 years) occurred. The risk of all outcomes was higher in subjects with psychotic disorders than matched controls (adjusted hazard ratios [95% confidence intervals]: 1.522 [1.446 to 1.602] for T2DM; 1.455 [1.251 to 1.693] for AMI; 1.568 [1.373 to 1.790] for ischemic stroke; 1.595 [1.565 to 1.626] for composite of all cardiometabolic diseases; and 2.747 [2.599 to 2.904] for all-cause mortality) during follow-up. Similar patterns of associations were maintained in subgroup analyses but more prominent in younger individuals (P for interaction <0.0001) when categorized as those aged 18–39, 40–64, or ≥65 years.
Conclusion
Patients with psychotic disorders treated with antipsychotics were associated with increased risk of premature allcause mortality and cardiometabolic outcomes in an Asian population. This relationship was more pronounced in younger individuals, especially aged 18 to 39 years.

Complications
Association of Muscle Mass Loss with Diabetes Development in Liver Transplantation Recipients: Sejeong Lee, Minyoung Lee, Young-Eun Kim, Hae Kyung Kim, Sook Jung Lee, Jiwon Kim, Yurim Yang, Chul Hoon Kim, Hyangkyu Lee, Dong Jin Joo, Myoung Soo Kim, Eun Seok Kang; Diabetes Metab J. 2024;48(1):146-156. Published online January 3, 2024; DOI: https://doi.org/10.4093/dmj.2022.0100

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Abstract PDF Supplementary Material PubReader ePub: Background
Post-transplant diabetes mellitus (PTDM) is one of the most significant complications after transplantation. Patients with end-stage liver diseases requiring transplantation are prone to sarcopenia, but the association between sarcopenia and PTDM remains to be elucidated. We aimed to investigate the effect of postoperative muscle mass loss on PTDM development.
Methods
A total of 500 patients who underwent liver transplantation at a tertiary care hospital between 2005 and 2020 were included. Skeletal muscle area at the level of the L3–L5 vertebrae was measured using computed tomography scans performed before and 1 year after the transplantation. The associations between the change in the muscle area after the transplantation and the incidence of PTDM was investigated using a Cox proportional hazard model.
Results
During the follow-up period (median, 4.9 years), PTDM occurred in 165 patients (33%). The muscle mass loss was greater in patients who developed PTDM than in those without PTDM. Muscle depletion significantly increased risk of developing PTDM after adjustment for other confounding factors (hazard ratio, 1.50; 95% confidence interval, 1.23 to 1.84; P=0.001). Of the 357 subjects who had muscle mass loss, 124 (34.7%) developed PTDM, whereas of the 143 patients in the muscle mass maintenance group, 41 (28.7%) developed PTDM. The cumulative incidence of PTDM was significantly higher in patients with muscle loss than in patients without muscle loss (P=0.034).
Conclusion
Muscle depletion after liver transplantation is associated with increased risk of PTDM development.

Others
Development of Various Diabetes Prediction Models Using Machine Learning Techniques: Juyoung Shin, Jaewon Kim, Chanjung Lee, Joon Young Yoon, Seyeon Kim, Seungjae Song, Hun-Sung Kim; Diabetes Metab J. 2022;46(4):650-657. Published online March 11, 2022; DOI: https://doi.org/10.4093/dmj.2021.0115

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Background
There are many models for predicting diabetes mellitus (DM), but their clinical implication remains vague. Therefore, we aimed to create various DM prediction models using easily accessible health screening test parameters.
Methods
Two sets of variables were used to develop eight DM prediction models. One set comprised 62 easily accessible examination results of commonly used variables from a tertiary university hospital. The second set comprised 27 of the 62 variables included in the national routine health checkups. Gradient boosting and random forest algorithms were used to develop the models. Internal validation was performed using the stratified 10-fold cross-validation method.
Results
The area under the receiver operating characteristic curve (ROC-AUC) for the 62-variable DM model making 12-month predictions for subjects without diabetes was the largest (0.928) among those of the eight DM prediction models. The ROC-AUC dropped by more than 0.04 when training with the simplified 27-variable set but still showed fairly good performance with ROC-AUCs between 0.842 and 0.880. The accuracy was up to 11.5% higher (from 0.807 to 0.714) when fasting glucose was included.
Conclusion
We created easily applicable diabetes prediction models that deliver good performance using parameters commonly assessed during tertiary university hospital and national routine health checkups. We plan to perform prospective external validation, hoping that the developed DM prediction models will be widely used in clinical practice.

Citations

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Predictive modeling for the development of diabetes mellitus using key factors in various machine learning approaches
Marenao Tanaka, Yukinori Akiyama, Kazuma Mori, Itaru Hosaka, Kenichi Kato, Keisuke Endo, Toshifumi Ogawa, Tatsuya Sato, Toru Suzuki, Toshiyuki Yano, Hirofumi Ohnishi, Nagisa Hanawa, Masato Furuhashi
Diabetes Epidemiology and Management.2024; 13: 100191. CrossRef
Validation of the Framingham Diabetes Risk Model Using Community-Based KoGES Data
Hye Ah Lee, Hyesook Park, Young Sun Hong
Journal of Korean Medical Science.2024;[Epub] CrossRef
Integrated Embedded system for detecting diabetes mellitus using various machine learning techniques
Rishita Konda, Anuraag Ramineni, Jayashree J, Niharika Singavajhala, Sai Akshaj Vanka
EAI Endorsed Transactions on Pervasive Health and Technology.2024;[Epub] CrossRef
Predicting diabetes in adults: identifying important features in unbalanced data over a 5-year cohort study using machine learning algorithm
Maryam Talebi Moghaddam, Yones Jahani, Zahra Arefzadeh, Azizallah Dehghan, Mohsen Khaleghi, Mehdi Sharafi, Ghasem Nikfar
BMC Medical Research Methodology.2024;[Epub] CrossRef
The Present and Future of Artificial Intelligence-Based Medical Image in Diabetes Mellitus: Focus on Analytical Methods and Limitations of Clinical Use
Ji-Won Chun, Hun-Sung Kim
Journal of Korean Medical Science.2023;[Epub] CrossRef
Machine learning for predicting diabetic metabolism in the Indian population using polar metabolomic and lipidomic features
Nikita Jain, Bhaumik Patel, Manjesh Hanawal, Anurag R. Lila, Saba Memon, Tushar Bandgar, Ashutosh Kumar
Metabolomics.2023;[Epub] CrossRef
Retrospective cohort analysis comparing changes in blood glucose level and body composition according to changes in thyroid‐stimulating hormone level
Hyunah Kim, Da Young Jung, Seung‐Hwan Lee, Jae‐Hyoung Cho, Hyeon Woo Yim, Hun‐Sung Kim
Journal of Diabetes.2022; 14(9): 620. CrossRef
Improving Machine Learning Diabetes Prediction Models for the Utmost Clinical Effectiveness
Juyoung Shin, Joonyub Lee, Taehoon Ko, Kanghyuck Lee, Yera Choi, Hun-Sung Kim
Journal of Personalized Medicine.2022; 12(11): 1899. CrossRef

Basic Research
Differentiation of Microencapsulated Neonatal Porcine Pancreatic Cell Clusters in Vitro Improves Transplant Efficacy in Type 1 Diabetes Mellitus Mice: Gyeong-Jin Cheon, Heon-Seok Park, Eun-Young Lee, Min Jung Kim, Young-Hye You, Marie Rhee, Ji-Won Kim, Kun-Ho Yoon; Diabetes Metab J. 2022;46(5):677-688. Published online February 7, 2022; DOI: https://doi.org/10.4093/dmj.2021.0202

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Background
Neonatal porcine pancreatic cell clusters (NPCCs) have been proposed as an alternative source of β cells for islet transplantation because of their low cost and growth potential after transplantation. However, the delayed glucose lowering effect due to the immaturity of NPCCs and immunologic rejection remain as a barrier to NPCC’s clinical application. Here, we demonstrate accelerated differentiation and immune-tolerant NPCCs by in vitro chemical treatment and microencapsulation.
Methods
NPCCs isolated from 3-day-old piglets were cultured in F-10 media and then microencapsulated with alginate on day 5. Differentiation of NPCCs is facilitated by media supplemented with activin receptor-like kinase 5 inhibitor II, triiodothyronine and exendin-4 for 2 weeks. Marginal number of microencapsulated NPCCs to cure diabetes with and without differentiation were transplanted into diabetic mice and observed for 8 weeks.
Results
The proportion of insulin-positive cells and insulin mRNA levels of NPCCs were significantly increased in vitro in the differentiated group compared with the undifferentiated group. Blood glucose levels decreased eventually after transplantation of microencapsulated NPCCs in diabetic mice and normalized after 7 weeks in the differentiated group. In addition, the differentiated group showed nearly normal glucose tolerance at 8 weeks after transplantation. In contrast, neither blood glucose levels nor glucose tolerance were improved in the undifferentiated group. Retrieved graft in the differentiated group showed greater insulin response to high glucose compared with the undifferentiated group.
Conclusion
in vitro differentiation of microencapsulated immature NPCCs increased the proportion of insulin-positive cells and improved transplant efficacy in diabetic mice without immune rejection.

Citations

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Dual-targeted nano-encapsulation of neonatal porcine islet-like cell clusters with triiodothyronine-loaded bifunctional polymersomes
Sang Hoon Lee, Minse Kim, Eun-Jin Lee, Sun Mi Ahn, Yu-Rim Ahn, Jaewon Choi, Jung-Taek Kang, Hyun-Ouk Kim
Discover Nano.2024;[Epub] CrossRef
Long‐term efficacy of encapsulated xenogeneic islet transplantation: Impact of encapsulation techniques and donor genetic traits
Heon‐Seok Park, Eun Young Lee, Young‐Hye You, Marie Rhee, Jong‐Min Kim, Seong‐Soo Hwang, Poong‐Yeon Lee
Journal of Diabetes Investigation.2024; 15(6): 693. CrossRef

Short Communication

Basic Research
GPR40 Agonism Modulates Inflammatory Reactions in Vascular Endothelial Cells: Joo Won Kim, Eun Roh, Kyung Mook Choi, Hye Jin Yoo, Hwan-Jin Hwang, Sei Hyun Baik; Diabetes Metab J. 2022;46(3):506-511. Published online January 24, 2022; DOI: https://doi.org/10.4093/dmj.2021.0092

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Endothelial dysfunction is strongly linked with inflammatory responses, which can impact cardiovascular disease. Recently, G protein-coupled receptor 40 (GPR40) has been investigated as a modulator of metabolic stress; however, the function of GPR40 in vascular endothelial cells has not been reported. We analyzed whether treatment of GPR40-specific agonists modulated the inflammatory responses in human umbilical vein endothelial cells (HUVECs). Treatment with LY2922470, a GPR40 agonist, significantly reduced lipopolysaccharide (LPS)-mediated nuclear factor-kappa B (NF-κB) phosphorylation and movement into the nucleus from the cytosol. However, treatment with another GPR40 agonist, TAK875, did not inhibit LPS-induced NF-κB activation. LPS treatment induced expression of adhesion molecules vascular cell adhesion molecule-1 (VCAM-1) and intercellular adhesion molecule-1 (ICAM-1) and attachment of THP-1 cells to HUVECs, which were all decreased by LY2922470 but not TAK875. Our results showed that ligand-dependent agonism of GPR40 is a promising therapeutic target for overcoming inflammatory reactions in the endothelium.

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Synthetic GPR40/FFAR1 agonists: An exhaustive survey on the most recent chemical classes and their structure-activity relationships
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European Journal of Medicinal Chemistry.2024; 264: 115990. CrossRef
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Aloe emodin promotes mucosal healing by modifying the differentiation fate of enteroendocrine cells via regulating cellular free fatty acid sensitivity
Weilian Bao, Jiaren Lyu, Guize Feng, Linfeng Guo, Dian Zhao, Keyuan You, Yang Liu, Haidong Li, Peng Du, Daofeng Chen, Xiaoyan Shen
Acta Pharmaceutica Sinica B.2024; 14(9): 3964. CrossRef
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Xin Zhang, Fei Hu, Jie Li, Lin Chen, Yu-fei Mao, Qiu-bo Li, Chen-yao Nie, Cai Lin, Jian Xiao
European Journal of Pharmaceutical Sciences.2024; 200: 106847. CrossRef
Free Fatty Acids and Free Fatty Acid Receptors: Role in Regulating Arterial Function
Fengzhi Yu, Boyi Zong, Lili Ji, Peng Sun, Dandan Jia, Ru Wang
International Journal of Molecular Sciences.2024; 25(14): 7853. CrossRef
Critical role of G protein-coupled receptor 40 in B cell response and the pathogenesis of rheumatoid arthritis in mice and patients
Anqi Li, Xiaoyi Wang, Jingwen Li, Xiaoyu Li, Jue Wang, Yang Liu, Zhihong Wang, Xiaobing Yang, Jiapeng Gao, Juanjie Wu, Tao Sun, Lixia Huo, Yanfeng Yi, Jiantong Shen, Jiexun Cai, Yunliang Yao
Cell Reports.2024; 43(10): 114858. CrossRef
GPR40 deficiency worsens metabolic syndrome‐associated periodontitis in mice
Yanchun Li, Zhongyang Lu, Cameron L. Kirkwood, Keith L. Kirkwood, Stephen A. Wank, Ai‐Jun Li, Maria F. Lopes‐Virella, Yan Huang
Journal of Periodontal Research.2023; 58(3): 575. CrossRef
Signaling pathways and intervention for therapy of type 2 diabetes mellitus
Rong Cao, Huimin Tian, Yu Zhang, Geng Liu, Haixia Xu, Guocheng Rao, Yan Tian, Xianghui Fu
MedComm.2023;[Epub] CrossRef
G Protein-Coupled Receptor 40 Agonist LY2922470 Alleviates Ischemic-Stroke-Induced Acute Brain Injury and Functional Alterations in Mice
Yingyu Lu, Wanlu Zhou, Qinghua Cui, Chunmei Cui
International Journal of Molecular Sciences.2023; 24(15): 12244. CrossRef
AM1638, a GPR40-Full Agonist, Inhibited Palmitate- Induced ROS Production and Endoplasmic Reticulum Stress, Enhancing HUVEC Viability in an NRF2-Dependent Manner
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Learn from failures and stay hopeful to GPR40, a GPCR target with robust efficacy, for therapy of metabolic disorders
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Brief Report

Technology/Device
Do-It-Yourself Open Artificial Pancreas System in Children and Adolescents with Type 1 Diabetes Mellitus: Real-World Data: Min Sun Choi, Seunghyun Lee, Jiwon Kim, Gyuri Kim, Sung Min Park, Jae Hyeon Kim; Diabetes Metab J. 2022;46(1):154-159. Published online November 23, 2021; DOI: https://doi.org/10.4093/dmj.2021.0011

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Few studies have been conducted among Asian children and adolescents with type 1 diabetes mellitus (T1DM) using do-it-yourself artificial pancreas system (DIY-APS). We evaluated real-world data of pediatric T1DM patients using DIY-APS. Data were obtained for 10 patients using a DIY-APS with algorithms. We collected sensor glucose and insulin delivery data from each participant for a period of 4 weeks. Average glycosylated hemoglobin was 6.2%±0.3%. The mean percentage of time that glucose level remained in the target range of 70 to 180 mg/dL was 82.4%±7.8%. Other parameters including time above range, time below range and mean glucose were also within the recommended level, similar to previous commercial and DIY-APS studies. However, despite meeting the target range, unadjusted gaps were still observed between the median basal setting and temporary basal insulin, which should be handled by healthcare providers.

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Real-world efficacy and safety of open-source automated insulin delivery for people with type 1 diabetes mellitus: Experience from mainland China
Yongwen Zhou, Mengyun Lei, Daizhi Yang, Ping Ling, Ying Ni, Hongrong Deng, Wen Xu, Xubin Yang, Benjamin John Wheeler, Jianping Weng, Jinhua Yan
Diabetes Research and Clinical Practice.2024; 218: 111910. CrossRef
Advances in Continuous Glucose Monitoring and Integrated Devices for Management of Diabetes with Insulin-Based Therapy: Improvement in Glycemic Control
Jee Hee Yoo, Jae Hyeon Kim
Diabetes & Metabolism Journal.2023; 47(1): 27. CrossRef
Open-source automated insulin delivery systems (OS-AIDs) in a pediatric population with type 1 diabetes in a real-life setting: the AWeSoMe study group experience
Judith Nir, Marianna Rachmiel, Abigail Fraser, Yael Lebenthal, Avivit Brener, Orit Pinhas-Hamiel, Alon Haim, Eve Stern, Noa Levek, Tal Ben-Ari, Zohar Landau
Endocrine.2023; 81(2): 262. CrossRef
Efficacy and safety of Android artificial pancreas system use at home among adults with type 1 diabetes mellitus in China: protocol of a 26-week, free-living, randomised, open-label, two-arm, two-phase, crossover trial
Mengyun Lei, Beisi Lin, Ping Ling, Zhigu Liu, Daizhi Yang, Hongrong Deng, Xubin Yang, Jing Lv, Wen Xu, Jinhua Yan
BMJ Open.2023; 13(8): e073263. CrossRef
Barriers to Uptake of Open-Source Automated Insulin Delivery Systems: Analysis of Socioeconomic Factors and Perceived Challenges of Caregivers of Children and Adolescents With Type 1 Diabetes From the OPEN Survey
Antonia Huhndt, Yanbing Chen, Shane O’Donnell, Drew Cooper, Hanne Ballhausen, Katarzyna A. Gajewska, Timothée Froment, Mandy Wäldchen, Dana M. Lewis, Klemens Raile, Timothy C. Skinner, Katarina Braune
Frontiers in Clinical Diabetes and Healthcare.2022;[Epub] CrossRef
Toward Personalized Hemoglobin A1c Estimation for Type 2 Diabetes
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Original Articles

Metabolic Risk/Epidemiology
A Comparison of Predictive Performances between Old versus New Criteria in a Risk-Based Screening Strategy for Gestational Diabetes Mellitus: Subeen Hong, Seung Mi Lee, Soo Heon Kwak, Byoung Jae Kim, Ja Nam Koo, Ig Hwan Oh, Sohee Oh, Sun Min Kim, Sue Shin, Won Kim, Sae Kyung Joo, Errol R. Norwitz, Souphaphone Louangsenlath, Chan-Wook Park, Jong Kwan Jun, Joong Shin Park; Diabetes Metab J. 2020;44(5):726-736. Published online April 13, 2020; DOI: https://doi.org/10.4093/dmj.2019.0126

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Background

The definition of the high-risk group for gestational diabetes mellitus (GDM) defined by the American College of Obstetricians and Gynecologists was changed from the criteria composed of five historic/demographic factors (old criteria) to the criteria consisting of 11 factors (new criteria) in 2017. To compare the predictive performances between these two sets of criteria.

Methods

This is a secondary analysis of a large prospective cohort study of non-diabetic Korean women with singleton pregnancies designed to examine the risk of GDM in women with nonalcoholic fatty liver disease. Maternal fasting blood was taken at 10 to 14 weeks of gestation and measured for glucose and lipid parameters. GDM was diagnosed by the two-step approach.

Results

Among 820 women, 42 (5.1%) were diagnosed with GDM. Using the old criteria, 29.8% (n=244) of women would have been identified as high risk versus 16.0% (n=131) using the new criteria. Of the 42 women who developed GDM, 45.2% (n=19) would have been mislabeled as not high risk by the old criteria versus 50.0% (n=21) using the new criteria (1-sensitivity, 45.2% vs. 50.0%, P>0.05). Among the 778 patients who did not develop GDM, 28.4% (n=221) would have been identified as high risk using the old criteria versus 14.1% (n=110) using the new criteria (1-specificity, 28.4% vs. 14.1%, P<0.001).

Conclusion

Compared with the old criteria, use of the new criteria would have decreased the number of patients identified as high risk and thus requiring early GDM screening by half (from 244 [29.8%] to 131 [16.0%]).

Citations

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Multi-omics reveals the beneficial effect of Scytosiphon lomentaria fucoidan on glucose and lipid metabolism disorders via regulation of the gut-liver axis in pregnant mice
Shuangru Tang, Weiyun Zheng, Xiaomeng Ren, Shuang Song, Chunqing Ai
Food Bioscience.2024; 62: 105436. CrossRef
Predicting the Risk of Insulin-Requiring Gestational Diabetes before Pregnancy: A Model Generated from a Nationwide Population-Based Cohort Study in Korea
Seung-Hwan Lee, Jin Yu, Kyungdo Han, Seung Woo Lee, Sang Youn You, Hun-Sung Kim, Jae-Hyoung Cho, Kun-Ho Yoon, Mee Kyoung Kim
Endocrinology and Metabolism.2023; 38(1): 129. CrossRef
Metabolic Dysfunction-Associated Fatty Liver Disease and Subsequent Development of Adverse Pregnancy Outcomes
Seung Mi Lee, Young Mi Jung, Eun Saem Choi, Soo Heon Kwak, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Bo Kyung Koo, Sue Shin, Errol R. Norwitz, Chan-Wook Park, Jong Kwan Jun, Won Kim, Joong Shin Park
Clinical Gastroenterology and Hepatology.2022; 20(11): 2542. CrossRef
Nonalcoholic fatty liver disease and early prediction of gestational diabetes mellitus using machine learning methods
Seung Mi Lee, Suhyun Hwangbo, Errol R. Norwitz, Ja Nam Koo, Ig Hwan Oh, Eun Saem Choi, Young Mi Jung, Sun Min Kim, Byoung Jae Kim, Sang Youn Kim, Gyoung Min Kim, Won Kim, Sae Kyung Joo, Sue Shin, Chan-Wook Park, Taesung Park, Joong Shin Park
Clinical and Molecular Hepatology.2022; 28(1): 105. CrossRef
Nonalcoholic fatty liver disease-based risk prediction of adverse pregnancy outcomes: Ready for prime time?
Seung Mi Lee, Won Kim
Clinical and Molecular Hepatology.2022; 28(1): 47. CrossRef
Postprandial Free Fatty Acids at Mid-Pregnancy Increase the Risk of Large-for-Gestational-Age Newborns in Women with Gestational Diabetes Mellitus
So-Yeon Kim, Young Shin Song, Soo-Kyung Kim, Yong-Wook Cho, Kyung-Soo Kim
Diabetes & Metabolism Journal.2022; 46(1): 140. CrossRef
Effect of Different Types of Diagnostic Criteria for Gestational Diabetes Mellitus on Adverse Neonatal Outcomes: A Systematic Review, Meta-Analysis, and Meta-Regression
Fahimeh Ramezani Tehrani, Marzieh Saei Ghare Naz, Razieh Bidhendi-Yarandi, Samira Behboudi-Gandevani
Diabetes & Metabolism Journal.2022; 46(4): 605. CrossRef
Development of early prediction model for pregnancy-associated hypertension with graph-based semi-supervised learning
Seung Mi Lee, Yonghyun Nam, Eun Saem Choi, Young Mi Jung, Vivek Sriram, Jacob S. Leiby, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Sue Shin, Errol R. Norwitz, Chan-Wook Park, Jong Kwan Jun, Won Kim,
Scientific Reports.2022;[Epub] CrossRef
The Clinical Characteristics of Gestational Diabetes Mellitus in Korea: A National Health Information Database Study
Kyung-Soo Kim, Sangmo Hong, Kyungdo Han, Cheol-Young Park
Endocrinology and Metabolism.2021; 36(3): 628. CrossRef
The risk of pregnancy‐associated hypertension in women with nonalcoholic fatty liver disease
Young Mi Jung, Seung Mi Lee, Subeen Hong, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Sue Shin, Errol R. Norwitz, Chan‐Wook Park, Jong Kwan Jun, Won Kim, Joong Shin Park
Liver International.2020; 40(10): 2417. CrossRef

Basic Research
Notch1 Has an Important Role in β-Cell Mass Determination and Development of Diabetes: Young Sil Eom, A-Ryeong Gwon, Kyung Min Kwak, Jin-Young Youn, Heekyoung Park, Kwang-Won Kim, Byung-Joon Kim; Diabetes Metab J. 2021;45(1):86-96. Published online February 26, 2020; DOI: https://doi.org/10.4093/dmj.2019.0160

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Background

Notch signaling pathway plays an important role in regulating pancreatic endocrine and exocrine cell fate during pancreas development. Notch signaling is also expressed in adult pancreas. There are few studies on the effect of Notch on adult pancreas. Here, we investigated the role of Notch in islet mass and glucose homeostasis in adult pancreas using Notch1 antisense transgenic (NAS).

Methods

Western blot analysis was performed for the liver of 8-week-old male NAS mice. We also conducted an intraperitoneal glucose tolerance test (IPGTT) and intraperitoneal insulin tolerance test in 8-week-old male NAS mice and male C57BL/6 mice (control). Morphologic observation of pancreatic islet and β-cell was conducted in two groups. Insulin secretion capacity in islets was measured by glucose-stimulated insulin secretion (GSIS) and perifusion.

Results

NAS mice showed higher glucose levels and lower insulin secretion in IPGTT than the control mice. There was no significant difference in insulin resistance. Total islet and β-cell masses were decreased in NAS mice. The number of large islets (≥250 µm) decreased while that of small islets (<250 µm) increased. Reduced insulin secretion was observed in GSIS and perifusion. Neurogenin3, neurogenic differentiation, and MAF bZIP transcription factor A levels increased in NAS mice.

Conclusion

Our study provides that Notch1 inhibition decreased insulin secretion and decreased islet and β-cell masses. It is thought that Notch1 inhibition suppresses islet proliferation and induces differentiation of small islets. In conclusion, Notch signaling pathway may play an important role in β-cell mass determination and diabetes.

Citations

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The rs2341471-G/G genotype of activating transcription factor 6 (ATF6) is the risk factor of type 2 diabetes in subjects with obesity or overweight
Elena Klyosova, Iuliia Azarova, Irina Petrukhina, Ramis Khabibulin, Alexey Polonikov
International Journal of Obesity.2024; 48(11): 1638. CrossRef
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N6-methylation of RNA-bound adenosine regulator HNRNPC promotes vascular endothelial dysfunction in type 2 diabetes mellitus by activating the PSEN1-mediated Notch pathway
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Diabetes Research and Clinical Practice.2023; 197: 110261. CrossRef
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Review

Complications
Diabetes and Cancer: Cancer Should Be Screened in Routine Diabetes Assessment: Sunghwan Suh, Kwang-Won Kim; Diabetes Metab J. 2019;43(6):733-743. Published online December 23, 2019; DOI: https://doi.org/10.4093/dmj.2019.0177

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Abstract PDF PubReader

Cancer incidence appears to be increased in both type 1 and type 2 diabetes mellitus (DM). DM represents a risk factor for cancer, particularly hepatocellular, hepatobiliary, pancreas, breast, ovarian, endometrial, and gastrointestinal cancers. In addition, there is evidence showing that DM is associated with increased cancer mortality. Common risk factors such as age, obesity, physical inactivity and smoking may contribute to increased cancer risk in patients with DM. Although the mechanistic process that may link diabetes to cancer is not completely understood yet, biological mechanisms linking DM and cancer are hyperglycemia, hyperinsulinemia, increased bioactivity of insulin-like growth factor 1, oxidative stress, dysregulations of sex hormones, and chronic inflammation. However, cancer screening rate is significantly lower in people with DM than that in people without diabetes. Evidence from previous studies suggests that some medications used to treat DM are associated with either increased or reduced risk of cancer. However, there is no strong evidence supporting the association between the use of anti-hyperglycemic medication and specific cancer. In conclusion, all patients with DM should be undergo recommended age- and sex appropriate cancer screenings to promote primary prevention and early detection. Furthermore, cancer should be screened in routine diabetes assessment.

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Original Articles

Clinical Care/Education
Impact of Socioeconomic Status on Health Behaviors, Metabolic Control, and Chronic Complications in Type 2 Diabetes Mellitus: So Hun Kim, Seung Youn Lee, Chei Won Kim, Young Ju Suh, Seongbin Hong, Seong Hee Ahn, Da Hae Seo, Moon-Suk Nam, Suk Chon, Jeong-Taek Woo, Sei Hyun Baik, Yongsoo Park, Kwan Woo Lee, Young Seol Kim; Diabetes Metab J. 2018;42(5):380-393. Published online June 29, 2018; DOI: https://doi.org/10.4093/dmj.2017.0102

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Abstract PDF Supplementary Material PubReader

Background

The aim of the study was to assess the impact of socioeconomic status (SES) on health behaviors, metabolic control, and chronic complications in people with type 2 diabetes mellitus (T2DM) from South Korea, a country with universal health insurance coverage and that has experienced rapid economic and social transition.

Methods

A total of 3,294 Korean men and women with T2DM aged 30 to 65 years, participating in the Korean National Diabetes Program (KNDP) cohort who reported their SES and had baseline clinical evaluation were included in the current cross-sectional analysis. SES included the level of education and monthly household income.

Results

Lower education level and lower income level were closely related, and both were associated with older age in men and women. Women and men with lower income and education level had higher carbohydrate and lower fat intake. After adjustment for possible confounding factors, higher education in men significantly lowered the odds of having uncontrolled hyperglycemia (glycosylated hemoglobin ≥7.5%) (odds ratio [OR], 0.63; 95% confidence interval [CI], 0.43 to 0.91 for highest education; P_trend=0.048), while higher household income in men significantly lowered the odds of having diabetic retinopathy (OR, 0.59; 95% CI, 0.37 to 0.95 for highest income level; P_trend=0.048). In women, lower income was associated with a higher stress level.

Conclusion

Men with lower SES had higher odds of having diabetic retinopathy and uncontrolled hyperglycemia, showing the need to improve care targeted to this population.

Citations

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Others
Generation of Insulin-Expressing Cells in Mouse Small Intestine by Pdx1, MafA, and BETA2/NeuroD: So-Hyun Lee, Marie Rhee, Ji-Won Kim, Kun-Ho Yoon; Diabetes Metab J. 2017;41(5):405-416. Published online September 5, 2017; DOI: https://doi.org/10.4093/dmj.2017.41.5.405

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Abstract PDF Supplementary Material PubReader

Background

To develop surrogate insulin-producing cells for diabetes therapy, adult stem cells have been identified in various tissues and studied for their conversion into β-cells. Pancreatic progenitor cells are derived from the endodermal epithelium and formed in a manner similar to gut progenitor cells. Here, we generated insulin-producing cells from the intestinal epithelial cells that induced many of the specific pancreatic transcription factors using adenoviral vectors carrying three genes: PMB (pancreatic and duodenal homeobox 1 [Pdx1], V-maf musculoaponeurotic fibrosarcoma oncogene homolog A [MafA], and BETA2/NeuroD).

Methods

By direct injection into the intestine through the cranial mesenteric artery, adenoviruses (Ad) were successfully delivered to the entire intestine. After virus injection, we could confirm that the small intestine of the mouse was appropriately infected with the Ad-Pdx1 and triple Ad-PMB.

Results

Four weeks after the injection, insulin mRNA was expressed in the small intestine, and the insulin gene expression was induced in Ad-Pdx1 and Ad-PMB compared to control Ad-green fluorescent protein. In addition, the conversion of intestinal cells into insulin-expressing cells was detected in parts of the crypts and villi located in the small intestine.

Conclusion

These data indicated that PMB facilitate the differentiation of mouse intestinal cells into insulin-expressing cells. In conclusion, the small intestine is an accessible and abundant source of surrogate insulin-producing cells.

Citations

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Harnessing gut cells for functional insulin production: Strategies and challenges
Kelvin Baafi, John C. March
Biotechnology Notes.2023; 4: 7. CrossRef
Differential Morphological Diagnosis of Various Forms of Congenital Hyperinsulinism in Children
Lubov Borisovna Mitrofanova, Anastasia Arkadyevna Perminova, Daria Viktorovna Ryzhkova, Anna Andreyevna Sukhotskaya, Vladimir Gireyevich Bairov, Irina Leorovna Nikitina
Frontiers in Endocrinology.2021;[Epub] CrossRef
Generation of iPSC-derived insulin-producing cells from patients with type 1 and type 2 diabetes compared with healthy control
Min Jung Kim, Eun Young Lee, Young-Hye You, Hae Kyung Yang, Kun-Ho Yoon, Ji-Won Kim
Stem Cell Research.2020; 48: 101958. CrossRef
ERK Regulates NeuroD1-mediated Neurite Outgrowth via Proteasomal Degradation
Tae-young Lee, In-Su Cho, Narayan Bashyal, Francisco J Naya, Ming-Jer Tsai, Jeong Seon Yoon, Jung-Mi Choi, Chang-Hwan Park, Sung-Soo Kim, Haeyoung Suh-Kim
Experimental Neurobiology.2020; 29(3): 189. CrossRef
Generation of a PDX1–EGFP reporter human induced pluripotent stem cell line, KSCBi005-A-3, using the CRISPR/Cas9 system
Youngsun Lee, Hye Young Choi, Ara Kwon, Hyeyeon Park, Mi-Hyun Park, Ji-Won Kim, Min Jung Kim, Yong-Ou Kim, Sungwook Kwak, Soo Kyung Koo
Stem Cell Research.2019; 41: 101632. CrossRef

Intensive Individualized Reinforcement Education Is Important for the Prevention of Hypoglycemia in Patients with Type 2 Diabetes: Yun-Mi Yong, Kyung-Mi Shin, Kang-Min Lee, Jae-Young Cho, Sun-Hye Ko, Min-Hyang Yoon, Tae-Won Kim, Jong-Hyun Jeong, Yong-Moon Park, Seung-Hyun Ko, Yu-Bae Ahn; Diabetes Metab J. 2015;39(2):154-163. Published online March 10, 2015; DOI: https://doi.org/10.4093/dmj.2015.39.2.154

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Background

We investigated whether an intensive individualized reinforcement education program could influence the prevention of hypoglycemic events in patients with type 2 diabetes.

Methods

From March 2013 to September 2013, patients aged 35 to 75 years with type 2 diabetes who had not previously participated in diabetes education, and treated with insulin or a sulfonylurea-containing regimen were included in the study. After structured group education, the patients assigned to the intensive individualized education group (IT) were requested to visit for reinforcement. All subjects in the IT were encouraged to self-manage dose adjustments. Participants in both groups (control group [CG, group education only; n=22] and IT [n=24]) attended follow-up visits at 2, 8, 12, and 24 weeks. At each visit, all patients were asked whether they had experienced hypoglycemia.

Results

The total study population consisted of 20 men (43.5%; mean age and diabetic duration of 55.9±11.0 and 5.1±7.3 years, respectively). At 24 weeks, there were no significant differences in hemoglobin A1c values between the CG and IT. The total number of hypoglycemic events per patient was 5.26±6.5 in the CG and 2.58±2.3 times in the IT (P=0.004). Adherence to lifestyle modification including frequency of exercise, self-monitoring of blood glucose, or dietary habit was not significantly different between the groups. However, adherence to hypoglycemia management, especially the dose adjustment of medication, was significantly higher in the IT compared with the CG.

Conclusion

Compared with the structured group education, additional IT resulted in additional benefits in terms of avoidance of hypoglycemia and treating hypoglycemia in patients with type 2 diabetes.

Citations

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Jun Sung Moon, Shinae Kang, Jong Han Choi, Kyung Ae Lee, Joon Ho Moon, Suk Chon, Dae Jung Kim, Hyun Jin Kim, Ji A Seo, Mee Kyoung Kim, Jeong Hyun Lim, Yoon Ju Song, Ye Seul Yang, Jae Hyeon Kim, You-Bin Lee, Junghyun Noh, Kyu Yeon Hur, Jong Suk Park, Sang
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A Cross-Sectional study on risk factors for severe hypoglycemia among Insulin-Treated elderly type 2 diabetes Mellitus (T2DM) patients in Singapore
Michelle Shi Min Ko, Wai Kit Lee, Li Chang Ang, Su-Yen Goh, Yong Mong Bee, Ming Ming Teh
Diabetes Research and Clinical Practice.2022; 185: 109236. CrossRef
Management Status of Patients with Type 2 Diabetes Mellitus at General Hospitals in Korea: A 5-Year Follow-Up Study
Jin Hee Jung, Jung Hwa Lee, Hyang Mi Jang, Young Na, Hee Sun Choi, Yeon Hee Lee, Yang Gyo Kang, Na Rae Kim, Jeong Rim Lee, Bok Rye Song, Kang Hee Sim
The Journal of Korean Diabetes.2022; 23(1): 64. CrossRef
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Huda Y. Almomani, Carlos Rodriguez Pascual, Sayer I. Al-Azzam, Keivan Ahmadi
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The Korean Journal of Internal Medicine.2021; 36(2): 263. CrossRef
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Stijn Crutzen, Tessa van den Born-Bondt, Petra Denig, Katja Taxis
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The Korean Journal of Internal Medicine.2017; 32(6): 967. CrossRef
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Effectiveness of 3-Day Continuous Glucose Monitoring for Improving Glucose Control in Type 2 Diabetic Patients in Clinical Practice: Soo Kyoung Kim, Hye Jeong Kim, Taehun Kim, Kyu Yeon Hur, Sun Wook Kim, Moon-Kyu Lee, Yong-Ki Min, Kwang-Won Kim, Jae Hoon Chung, Jae Hyeon Kim; Diabetes Metab J. 2014;38(6):449-455. Published online December 15, 2014; DOI: https://doi.org/10.4093/dmj.2014.38.6.449

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Background

The aim of this study was to investigate whether adjusting diabetic treatment regimens according to the information obtained from a continuous glucose monitoring system (CGMS) might lead to improved glycemic control in patients with type 2 diabetes.

Methods

We reviewed the medical charts of 172 patients who used the CGMS for 1 year starting in December 2008 and the records of 1,500 patients who visited their regular outpatient clinics during December 2008. Of these patients, a total of 65 CGMS patients and 301 regular outpatients (control group) were enrolled in the study after propensity score matching. There were no differences in baseline glycated hemoglobin (HbA1c), age, and duration of diabetes between the CGMS and the control groups after propensity score matching. The changes in the HbA1c levels from baseline to 6 months were calculated.

Results

The CGMS group showed a significant improvement in the HbA1c level compared to the control group at 3 months (7.9%±1.6% vs. 7.4%±1.2%, P=0.001) and at 6 months (7.4%±1.2% vs. 7.9%±1.6%, P=0.010). There were significant differences in the treatment modality changes between the CGMS group and the control group.

Conclusion

Using a 3-day CGMS was advantageous for improving glucose control in patients with type 2 diabetes and may help these patients to optimize glycemic control in clinical practice.

Citations

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Pattern of Stress-Induced Hyperglycemia according to Type of Diabetes: A Predator Stress Model: Jin-Sun Chang, Young-Hye You, Shin-Young Park, Ji-Won Kim, Hun-Sung Kim, Kun-Ho Yoon, Jae-Hyoung Cho; Diabetes Metab J. 2013;37(6):475-483. Published online December 12, 2013; DOI: https://doi.org/10.4093/dmj.2013.37.6.475

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Background

We aimed to quantify stress-induced hyperglycemia and differentiate the glucose response between normal animals and those with diabetes. We also examined the pattern in glucose fluctuation induced by stress according to type of diabetes.

Methods

To load psychological stress on animal models, we used a predator stress model by exposing rats to a cat for 60 minutes and measured glucose level from the beginning to the end of the test to monitor glucose fluctuation. We induced type 1 diabetes model (T1D) for ten Sprague-Dawley rats using streptozotocin and used five Otsuka Long-Evans Tokushima Fatty rats as obese type 2 diabetes model (OT2D) and 10 Goto-Kakizaki rats as nonobese type 2 diabetes model (NOT2D). We performed the stress loading test in both the normal and diabetic states and compared patterns of glucose fluctuation among the three models. We classified the pattern of glucose fluctuation into A, B, and C types according to speed of change in glucose level.

Results

Increase in glucose, total amount of hyperglycemic exposure, time of stress-induced hyperglycemia, and speed of glucose increase were significantly increased in all models compared to the normal state. While the early increase in glucose after exposure to stress was higher in T1D and NOT2D, it was slower in OT2D. The rate of speed of the decrease in glucose level was highest in NOT2D and lowest in OT2D.

Conclusion

The diabetic state was more vulnerable to stress compared to the normal state in all models, and the pattern of glucose fluctuation differed among the three types of diabetes. The study provides basic evidence for stress-induced hyperglycemia patterns and characteristics used for the management of diabetes patients.

Citations

Citations to this article as recorded by

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B Sivaprakash
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