- Pathophysiology
- Glutamic Acid Decarboxylase and Tyrosine Phosphatase-Related Islet Antigen-2 Positivity among Children and Adolescents with Diabetes in Korea
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Ka Young Kim, Min Seung Kim, Yun Jeong Lee, Young Ah Lee, Seong Yong Lee, Choong Ho Shin, Jae Hyun Kim
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Diabetes Metab J. 2022;46(6):948-952. Published online March 8, 2022
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DOI: https://doi.org/10.4093/dmj.2021.0332
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Abstract
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- Autoantibodies against glutamic acid decarboxylase (GADA), tyrosine phosphatase-related islet antigen 2 (IA2A), insulin (INSA), and islet cells (ICA) are critical for determining the type of diabetes and management strategy in new-onset diabetes mellitus (NODM), but there have been few reports of all diabetes-associated autoantibody (DAA) in Korea. We retrospectively analyzed 193 patients with NODM aged 0 to 18 years who were followed at two tertiary centers in Korea (2017 to 2021). Patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) were 93 (48.2%) and 100 (51.8%), respectively. In T1DM patients, the DAA positivity rate was 94.6%; prevalence of GADA, IA2A, INSA, and ICA was 71.0%, 71.0%, 31.2%, and 10.8%, respectively; and IA2A added 10.7% point autoantibody positivity (83.9% for GADA+INSA+ICA and 94.6% for GADA+INSA+ICA+IA2A). Among the patients with T2DM, 12 (12.0%) were positive for DAA, and all were positive for INSA. These findings suggest that DAA at diagnosis, especially GADA and IA2A, is useful for classifying diabetes in Korean children and adolescents.
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Citations
Citations to this article as recorded by
- Immune-Checkpoint Inhibitors-Induced Type 1 Diabetes Mellitus: From Its Molecular Mechanisms to Clinical Practice
Yun Kyung Cho, Chang Hee Jung Diabetes & Metabolism Journal.2023; 47(6): 757. CrossRef - Diagnostic and Therapeutic Strategies of Type 2 Diabetes Mellitus in Youth
Hwa Young Kim, Jae Hyun Kim The Ewha Medical Journal.2022;[Epub] CrossRef
- Metabolic Risk/Epidemiology
- Maternal Hyperglycemia during Pregnancy Increases Adiposity of Offspring
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Hye Rim Chung, Joon Ho Moon, Jung Sub Lim, Young Ah Lee, Choong Ho Shin, Joon-Seok Hong, Soo Heon Kwak, Sung Hee Choi, Hak Chul Jang
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Diabetes Metab J. 2021;45(5):730-738. Published online February 22, 2021
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DOI: https://doi.org/10.4093/dmj.2020.0154
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Abstract
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- Background
The effect of intrauterine hyperglycemia on fat mass and regional fat proportion of the offspring of mothers with gestational diabetes mellitus (OGDM) remains to be determined.
Methods The body composition of OGDM (n=25) and offspring of normoglycemic mothers (n=49) was compared using dualenergy X-ray absorptiometry at age 5 years. The relationship between maternal glucose concentration during a 100 g oral glucose tolerance test (OGTT) and regional fat mass or proportion was analyzed after adjusting for maternal prepregnancy body mass index (BMI).
Results BMI was comparable between OGDM and control (median, 16.0 kg/m2 vs. 16.1 kg/m2 ). Total, truncal, and leg fat mass were higher in OGDM compared with control (3,769 g vs. 2,245 g, P=0.004; 1,289 g vs. 870 g, P=0.017; 1,638 g vs. 961 g, P=0.002, respectively), whereas total lean mass was lower in OGDM (15,688 g vs. 16,941 g, P=0.001). Among OGDM, total and truncal fat mass were correlated with fasting and 3-hour glucose concentrations of maternal 100 g OGTT during pregnancy (total fat mass, r=0.49, P=0.018 [fasting], r=0.473, P=0.023 [3-hour]; truncal fat mass, r=0.571, P=0.004 [fasting], r=0.558, P=0.006 [3-hour]), but there was no correlation between OGDM leg fat mass and maternal OGTT during pregnancy. Regional fat indices were not correlated with concurrent maternal 75 g OGTT values.
Conclusion Intrauterine hyperglycemia is associated with increased fat mass, especially truncal fat, in OGDM aged 5 years.
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Citations
Citations to this article as recorded by
- Advances in free fatty acid profiles in gestational diabetes mellitus
Haoyi Du, Danyang Li, Laura Monjowa Molive, Na Wu Journal of Translational Medicine.2024;[Epub] CrossRef - 2023 Clinical Practice Guidelines for Diabetes Management in Korea: Full Version Recommendation of the Korean Diabetes Association
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 Diabetes & Metabolism Journal.2024; 48(4): 546. CrossRef - Type 1 Diabetes and Pregnancy: Challenges in Glycemic Control and Maternal–Fetal Outcomes
Tejumola Apata, Dennis Samuel, Laticia Valle, Sarah D. Crimmins Seminars in Reproductive Medicine.2024;[Epub] CrossRef - Association between serum free fatty acids and gestational diabetes mellitus
Danyang Li, Haoyi Du, Na Wu Frontiers in Endocrinology.2024;[Epub] CrossRef - High-fat diet during pregnancy lowers fetal weight and has a long-lasting adverse effect on brown adipose tissue in the offspring
Mihoko Yamaguchi, Jun Mori, Nozomi Nishida, Satoshi Miyagaki, Yasuhiro Kawabe, Takeshi Ota, Hidechika Morimoto, Yusuke Tsuma, Shota Fukuhara, Takehiro Ogata, Takuro Okamaura, Naoko Nakanishi, Masahide Hamaguchi, Hisakazu Nakajima, Michiaki Fukui, Tomoko I Journal of Developmental Origins of Health and Disease.2023; 14(2): 261. CrossRef - Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms
Byung Soo Kang, Seon Ui Lee, Subeen Hong, Sae Kyung Choi, Jae Eun Shin, Jeong Ha Wie, Yun Sung Jo, Yeon Hee Kim, Kicheol Kil, Yoo Hyun Chung, Kyunghoon Jung, Hanul Hong, In Yang Park, Hyun Sun Ko Scientific Reports.2023;[Epub] CrossRef - Effects of early standardized management on the growth trajectory of offspring with gestational diabetes mellitus at 0–5 years old: a preliminary longitudinal study
Bingbing Guo, Jingjing Pei, Yin Xu, Yajie Wang, Xinye Jiang Scientific Reports.2023;[Epub] CrossRef - Gestational Diabetes Mellitus: Diagnostic Approaches and Maternal-Offspring Complications
Joon Ho Moon, Hak Chul Jang Diabetes & Metabolism Journal.2022; 46(1): 3. CrossRef - Increased Pro-Inflammatory T Cells, Senescent T Cells, and Immune-Check Point Molecules in the Placentas of Patients With Gestational Diabetes Mellitus
Yea Eun Kang, Hyon-Seung Yi, Min-Kyung Yeo, Jung Tae Kim, Danbit Park, Yewon Jung, Ok Soon Kim, Seong Eun Lee, Ji Min Kim, Kyong Hye Joung, Ju Hee Lee, Bon Jeong Ku, Mina Lee, Hyun Jin Kim Journal of Korean Medical Science.2022;[Epub] CrossRef
- Epidemiology
- Discrepancies between Glycosylated Hemoglobin and Fasting Plasma Glucose for Diagnosing Impaired Fasting Glucose and Diabetes Mellitus in Korean Youth and Young Adults
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Jieun Lee, Young Ah Lee, Jae Hyun Kim, Seong Yong Lee, Choong Ho Shin, Sei Won Yang
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Diabetes Metab J. 2019;43(2):174-182. Published online November 2, 2018
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DOI: https://doi.org/10.4093/dmj.2018.0046
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- Background
Glycosylated hemoglobin (HbA1c) has been recommended as a diagnostic test for prediabetes and diabetes. Here, we evaluated the level of agreement between diagnoses based on fasting plasma glucose (FPG) versus HbA1c levels and determined optimal HbA1c cutoff values for these diseases in youth and young adults. MethodsThe study included 7,332 subjects (n=4,129, aged 10 to 19 years in youth group; and n=3,203 aged 20 to 29 years in young adult group) from the 2011 to 2016 Korea National Health and Nutrition Examination Survey. Prediabetes and diabetes were defined as 100 to 125 mg/dL (impaired fasting glucose [IFG]) and ≥126 mg/dL for FPG (diabetes mellitus [DM] by FPG [DMFPG]), and 5.7% to 6.4% and ≥6.5% for HbA1c, respectively. ResultsIn the youth group, 32.5% with IFG had an HbA1c level of 5.7% to 6.4%, and 72.2% with DMFPG had an HbA1c ≥6.5%. In the young adult group, 27.5% with IFG had an HbA1c level of 5.7% to 6.4%, and 66.6% with DMFPG had an HbA1c ≥6.5%. Kappa coefficients for agreement between the FPG and HbA1c results were 0.12 for the youth group and 0.19 for the young adult group. In receiver operating characteristic curve analysis, the optimal HbA1c cutoff for IFG and DMFPG were 5.6% and 5.9% in youths and 5.5% and 5.8% in young adults, respectively. ConclusionUsefulness of HbA1c for diagnosis of IFG and DMFPG in Koreans aged <30 years remains to be determined due to discrepancies between the results of glucose- and HbA1c-based tests. Additional testing might be warranted at lower HbA1c levels to detect IFG and DMFPG in this age group.
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