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Volume 44(5); October 2020
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Reviews
Genetics
Update on Monogenic Diabetes in Korea
Ye Seul Yang, Soo Heon Kwak, Kyong Soo Park
Diabetes Metab J. 2020;44(5):627-639.   Published online October 21, 2020
DOI: https://doi.org/10.4093/dmj.2020.0214
  • 6,544 View
  • 241 Download
  • 11 Web of Science
  • 10 Crossref
AbstractAbstract PDFPubReader   ePub   
Monogenic diabetes, including maturity-onset diabetes of the young, neonatal diabetes, and other rare forms of diabetes, results from a single gene mutation. It has been estimated to represent around 1% to 6% of all diabetes. With the advances in genome sequencing technology, it is possible to diagnose more monogenic diabetes cases than ever before. In Korea, 11 studies have identified several monogenic diabetes cases, using Sanger sequencing and whole exome sequencing since 2001. The recent largest study, using targeted exome panel sequencing, found a molecular diagnosis rate of 21.1% for monogenic diabetes in clinically suspected patients. Mutations in glucokinase (GCK), hepatocyte nuclear factor 1α (HNF1A), and HNF4A were most commonly found. Genetic diagnosis of monogenic diabetes is important as it determines the therapeutic approach required for patients and helps to identify affected family members. However, there are still many challenges, which include a lack of simple clinical criterion for selecting patients for genetic testing, difficulties in interpreting the genetic test results, and high costs for genetic testing. In this review, we will discuss the latest updates on monogenic diabetes in Korea, and suggest an algorithm to screen patients for genetic testing. The genetic tests and non-genetic markers for accurate diagnosis of monogenic diabetes will be also reviewed.

Citations

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    Tohru Yorifuji, Yoh Watanabe, Kana Kitayama, Yuki Yamada, Shinji Higuchi, Jun Mori, Masaru Kato, Toru Takahashi, Tokuko Okuda, Takane Aoyama
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    Hong-Yan Sun, Xiao-Yan Lin
    World Journal of Diabetes.2023; 14(12): 1738.     CrossRef
  • Maturity-Onset Diabetes of the Young (MODY)
    Seung Shin Park, Soo Heon Kwak
    The Journal of Korean Diabetes.2022; 23(3): 157.     CrossRef
  • The Genetic Spectrum of Maturity-Onset Diabetes of the Young (MODY) in Qatar, a Population-Based Study
    Asma A. Elashi, Salman M. Toor, Ilhame Diboun, Yasser Al-Sarraj, Shahrad Taheri, Karsten Suhre, Abdul Badi Abou-Samra, Omar M. E. Albagha
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  • Age at Diagnosis and the Risk of Diabetic Nephropathy in Young Patients with Type 1 Diabetes Mellitus (Diabetes Metab J 2021;45:46-54)
    Ye Seul Yang, Tae Seo Sohn
    Diabetes & Metabolism Journal.2021; 45(2): 277.     CrossRef
  • Sequencing Cell-free Fetal DNA in Pregnant Women With GCK-MODY
    Soo Heon Kwak, Camille E Powe, Se Song Jang, Michael J Callahan, Sarah N Bernstein, Seung Mi Lee, Sunyoung Kang, Kyong Soo Park, Hak C Jang, Jose C Florez, Jong-Il Kim, Jong Hee Chae
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    Bo Kyung Koo, Seoil Moon, Min Kyong Moon
    BMC Geriatrics.2021;[Epub]     CrossRef
  • A rare, likely pathogenic GCK variant related to maturity-onset diabetes of the young type 2: A case report
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Metabolic Risk/Epidemiology
Nonalcoholic Fatty Liver Disease: A Drug Revolution Is Coming
Soung Won Jeong
Diabetes Metab J. 2020;44(5):640-657.   Published online October 21, 2020
DOI: https://doi.org/10.4093/dmj.2020.0115
  • 11,847 View
  • 544 Download
  • 16 Web of Science
  • 16 Crossref
AbstractAbstract PDFPubReader   ePub   
The worldwide prevalence of non-alcoholic fatty liver disease is around 25%, and that of nonalcoholic steatohepatitis (NASH) ranges from 1.5% to 6.45%. Patients with NASH, especially those with fibrosis, are at higher risk for adverse outcomes such as cirrhosis and liver-related mortality. Although vitamin E, pioglitazone, and liraglutide improved liver histology in randomized trials, there are currently no Food and Drug Administration-approved drugs for NASH. Five pharmacologic agents—obeticholic acid, elafibranor, cenicriviroc, resmetirom, and aramchol—are being evaluated in large, histology-based phase 3 trials. Within 2 to 4 years, new and effective drugs for the treatment of NASH are expected. Additionally, many phase 2 trials are ongoing for various agents. Based on the results of phase 2 and 3 trials, combination treatments are also being investigated. Future treatment strategies will comprise drug combinations and precision medicine based on the different phenotypes of NASH and treatment response of the individual patient.

Citations

Citations to this article as recorded by  
  • Recent Progresses on Pathophysiology, Diagnosis, Therapeutic Modalities, and Management of Non-alcoholic Fatty Liver Disorder
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  • Increased expression of sodium-glucose cotransporter 2 and O-GlcNAcylation in hepatocytes drives non-alcoholic steatohepatitis
    Hye Jin Chun, Eun Ran Kim, Minyoung Lee, Da Hyun Choi, Soo Hyun Kim, Eugene Shin, Jin-Hong Kim, Jin Won Cho, Dai Hoon Han, Bong-Soo Cha, Yong-ho Lee
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  • Efficacy and safety of evogliptin in patients with type 2 diabetes and non‐alcoholic fatty liver disease: A multicentre, double‐blind, randomized, comparative trial
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  • Triglyceride and glucose index is a simple and easy‐to‐calculate marker associated with nonalcoholic fatty liver disease
    Kyung‐Soo Kim, Sangmo Hong, Hong‐Yup Ahn, Cheol‐Young Park
    Obesity.2022; 30(6): 1279.     CrossRef
  • Thyroid diseases and new approaches for their treatment
    E. A. Fokina, A. O. Shpakov
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  • Gemigliptin Alleviates Succinate-Induced Hepatic Stellate Cell Activation by Ameliorating Mitochondrial Dysfunction
    Giang Nguyen, So Young Park, Dinh Vinh Do, Dae-Hee Choi, Eun-Hee Cho
    Endocrinology and Metabolism.2022; 37(6): 918.     CrossRef
  • Inhibition of 11β-hydroxysteroid dehydrogenase 1 relieves fibrosis through depolarizing of hepatic stellate cell in NASH
    Su-Yeon Lee, Sanghwa Kim, Inhee Choi, Yeonhwa Song, Namjeong Kim, Hyung Chul Ryu, Jee Woong Lim, Hyo Jin Kang, Jason Kim, Haeng Ran Seo
    Cell Death & Disease.2022;[Epub]     CrossRef
  • Lessons on Drug Development: A Literature Review of Challenges Faced in Nonalcoholic Fatty Liver Disease (NAFLD) Clinical Trials
    Joel Yeh Siang Chen, Damien Chua, Carissa Odelia Lim, Wan Xi Ho, Nguan Soon Tan
    International Journal of Molecular Sciences.2022; 24(1): 158.     CrossRef
  • Metabolic Spectrum of Liver Failure in Type 2 Diabetes and Obesity: From NAFLD to NASH to HCC
    Hyunmi Kim, Da Som Lee, Tae Hyeon An, Hyun-Ju Park, Won Kon Kim, Kwang-Hee Bae, Kyoung-Jin Oh
    International Journal of Molecular Sciences.2021; 22(9): 4495.     CrossRef
  • Allopurinol ameliorates high fructose diet induced hepatic steatosis in diabetic rats through modulation of lipid metabolism, inflammation, and ER stress pathway
    In-Jin Cho, Da-Hee Oh, Jin Yoo, You-Cheol Hwang, Kyu Jeung Ahn, Ho-Yeon Chung, Soung Won Jeong, Ju-Young Moon, Sang-Ho Lee, Sung-Jig Lim, In-Kyung Jeong
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  • Effects of intragastric balloon placement in metabolic dysfunction-associated fatty liver disease: A systematic review and meta-analysis
    João Remí de Freitas Júnior, Igor Braga Ribeiro, Diogo Turiani Hourneaux de Moura, Vitor Massaro Takamatsu Sagae, Gabriel Mayo Vieira de Souza, Guilherme Henrique Peixoto de Oliveira, Sergio A Sánchez-Luna, Thiago Ferreira de Souza, Eduardo Turiani Hourne
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  • The New Therapeutic Approaches in the Treatment of Non-Alcoholic Fatty Liver Disease
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Basic Research
Revisiting the Bacterial Phylum Composition in Metabolic Diseases Focused on Host Energy Metabolism
Yeonmi Lee, Hui-Young Lee
Diabetes Metab J. 2020;44(5):658-667.   Published online July 9, 2020
DOI: https://doi.org/10.4093/dmj.2019.0220
  • 8,949 View
  • 131 Download
  • 19 Web of Science
  • 19 Crossref
AbstractAbstract PDFPubReader   ePub   

Over a hundred billion bacteria are found in human intestines. This has emerged as an environmental factor in metabolic diseases, such as obesity and related diseases. The majority of these bacteria belong to two dominant phyla, Bacteroidetes and Firmicutes. Since the ratio of Firmicutes to Bacteroidetes increases in people with obesity and in various animal models, it has been assumed that phylum composition causes the increase in occurrence of metabolic diseases over the past decade. However, this assumption has been challenged by recent studies that have found even an opposite association of phylum composition within metabolic diseases. Moreover, the gut microbiota affects host energy metabolism in various ways including production of metabolites and interaction with host intestinal cells to regulate signaling pathways that affect energy metabolism. However, the direct effect of gut bacteria on host energy intake, such as energy consumption by the bacteria itself and its effects on intestinal energy absorption, has been underestimated. This review aims to discuss whether increased ratio of Firmicutes to Bacteroidetes is associated with the development of metabolic diseases, and whether energy competition between the bacteria and host is a missing part of the mechanism linking gut microbiota to metabolic diseases.

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Editorial
Early Development of Bidirectional Associations between Sleep Disturbance and Diabetes
Yongin Cho
Diabetes Metab J. 2020;44(5):668-670.   Published online October 21, 2020
DOI: https://doi.org/10.4093/dmj.2020.0198
  • 3,602 View
  • 114 Download
  • 3 Web of Science
  • 5 Crossref
PDFPubReader   ePub   

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Original Articles
Technology/Device
Data Configuration and Publication Trends for the Korean National Health Insurance and Health Insurance Review & Assessment Database
Hae Kyung Kim, Sun Ok Song, Junghyun Noh, In-Kyung Jeong, Byung-Wan Lee
Diabetes Metab J. 2020;44(5):671-678.   Published online October 21, 2020
DOI: https://doi.org/10.4093/dmj.2020.0207
  • 7,127 View
  • 243 Download
  • 49 Web of Science
  • 55 Crossref
AbstractAbstract PDFPubReader   ePub   
Background
Big data reports related to diseases and health care for the Korean population have been published since the National Health Insurance Service (NHIS) and the Health Insurance Review & Assessment (HIRA) Service provided limited open access to their databases. Here, we reviewed the structure, content, and means of using data from the National Health Insurance (NHI) system for the benefit of Korean researchers and presented the latest publication trends in Korean healthcare data procured from the NHI and HIRA databases.
Methods
Since 2013, researchers have been able to obtain nationwide population-based studies using the NHI and HIRA databases of the insured. We searched publications using the NHI and the HIRA databases between 2013 and 2019 retrieved from PubMed.
Results
The NHI and HIRA databases provide nationwide population-based data. The total number of publications from 2014 to 2019 using NHI and HIRA databases is 2,541 and 655, respectively. A total of 5,465 endocrinology-related studies were performed during 2014 to 2019.
Conclusion
The NHIS and HIRA databases have provided tools for guidelines to approach world-leading population-based epidemiology and disease research.

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Complications
Deterioration of Sleep Quality According to Glycemic Status
Myung Haeng Hur, Mi-Kyoung Lee, Kayeon Seong, Jun Hwa Hong
Diabetes Metab J. 2020;44(5):679-686.   Published online April 17, 2020
DOI: https://doi.org/10.4093/dmj.2019.0125
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Background

Type 2 diabetes mellitus (T2DM) is a progressive disease with multiple complications. The present study aimed to determine the effects of glycemic status on sleep quality in individuals with T2DM, prediabetes, and normal glucose tolerance (NGT).

Methods

A total of 90 participants were categorized into three groups, T2DM (n=30), prediabetes (n=30), and NGT (n=30). Objective sleep quality was measured with the actigraph wrist-worn device over 3 nights and subjective sleep quality was evaluated with a questionnaire.

Results

The duration of diabetes in the T2DM group was 2.23 years and the glycosylated hemoglobin (HbA1c) levels in the T2DM, prediabetes, and NGT groups were 7.83%, 5.80%, and 5.31%, respectively. Sleep efficiency decreased across the T2DM, prediabetes, and NGT groups (86.25%, 87.99%, and 90.22%, respectively; P=0.047). Additionally, HbA1c levels revealed a significant negative correlation with sleep efficiency (r=−0.348, P=0.001). The sleep quality questionnaire results were similar among the three groups.

Conclusion

Although the participants in the present study were not necessarily conscious of their sleep disturbances, deterioration in sleep quality progressed according to glycemic status.

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  • Nutritional Biomarkers and Factors Correlated with Poor Sleep Status among Young Females: A Case-Control Study
    Sara AL-Musharaf, Lama AlAjllan, Ghadeer Aljuraiban, Munirah AlSuhaibani, Noura Alafif, Syed Danish Hussain
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    Christina Antza, Ryan Ottridge, Smitaa Patel, Gemma Slinn, Sarah Tearne, Matthew Nicholls, Brendan Cooper, Asad Ali, Abd A. Tahrani
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  • Early Development of Bidirectional Associations between Sleep Disturbance and Diabetes
    Yongin Cho
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Complications
Association of Snoring with Prediabetes and Type 2 Diabetes Mellitus: The Cardiovascular and Metabolic Diseases Etiology Research Center Cohort
So Mi Jemma Cho, Hokyou Lee, Jee-Seon Shim, Hyeon Chang Kim
Diabetes Metab J. 2020;44(5):687-698.   Published online April 16, 2020
DOI: https://doi.org/10.4093/dmj.2019.0128
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background

Evidence suggests that habitual snoring is an independent risk factor for poor glycemic health. We examined the associations between snoring with prediabetes and diabetes in Korean population.

Methods

Self-reported snoring characteristics were collected from 3,948 middle-aged adults without prior cardiovascular diseases. Multivariable linear regression assessed the association of snoring intensity, frequency, disruptiveness, and disrupted breathing with fasting glucose and glycosylated hemoglobin (HbA1c) level. Then, multinomial regression evaluated how increasing snoring symptoms are associated with the risk for prediabetes and diabetes, adjusting for socioeconomic and behavioral risk factors of diabetes, obesity, hypertension, and other sleep variables.

Results

Higher snoring intensity and frequency were positively associated with fasting glucose and HbA1c levels. Participants presenting the most severe snoring were at 1.84 times higher risk (95% confidence interval [CI], 1.09 to 2.29) for prediabetes and 2.24 times higher risk (95% CI, 1.84 to 2.95) for diabetes, compared to non-snorers. Such graded association was also observed amongst the most frequent snorers with higher risk for prediabetes (odds ratio [OR], 1.78; 95% CI, 1.29 to 2.22) and diabetes (OR, 2.03; 95% CI, 1.45 to 2.85). Disruptive snoring (OR, 1.60; 95% CI, 1.12 to 2.28) and near-daily disruptive breathing (OR, 2.18; 95% CI, 1.02 to 4.19) were associated with higher odds for diabetes. Such findings remained robust after additional adjustment for sleep duration, excessive daytime sleepiness, unwakefulness, and sleep-deprived driving.

Conclusion

Snoring is associated with impaired glucose metabolism even in otherwise metabolically healthy adults. Habitual snorers may require lifestyle modifications and pharmacological treatment to improve glycemic profile.

Citations

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  • Does seasonality affect snoring? A study based on international data from the past decade
    Ping Wang, Cai Chen, Xingwei Wang, Ningling Zhang, Danyang Lv, Wei Li, Fulai Peng, Xiuli Wang
    Sleep and Breathing.2023; 27(4): 1297.     CrossRef
  • Association Between Snoring and Diabetes Among Pre- and Postmenopausal Women
    Yun Yuan, Fan Zhang, Jingfu Qiu, Liling Chen, Meng Xiao, Wenge Tang, Qinwen Luo, Xianbin Ding, Xiaojun Tang
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    Minhan Yi, Quanming Fei, Kun Liu, Wangcheng Zhao, Ziliang Chen, Yuan Zhang
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  • Sleeping Duration, Napping and Snoring in Association with Diabetes Control among Patients with Diabetes in Qatar
    Hiba Bawadi, Asma Al Sada, Noof Al Mansoori, Sharifa Al Mannai, Aya Hamdan, Zumin Shi, Abdelhamid Kerkadi
    International Journal of Environmental Research and Public Health.2021; 18(8): 4017.     CrossRef
  • Changes in creatinine‐to‐cystatin C ratio over 4 years, risk of diabetes, and cardiometabolic control: The China Health and Retirement Longitudinal Study
    Shanhu Qiu, Xue Cai, Yang Yuan, Bo Xie, Zilin Sun, Tongzhi Wu
    Journal of Diabetes.2021; 13(12): 1025.     CrossRef
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    Jinsha Ma, Huifang Zhang, Hui Wang, Qian Gao, Heli Sun, Simin He, Lingxian Meng, Tong Wang
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    Yongin Cho
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Metabolic Risk/Epidemiology
The Association between Pulmonary Functions and Incident Diabetes: Longitudinal Analysis from the Ansung Cohort in Korea
Hoon Sung Choi, Sung Woo Lee, Jin Taek Kim, Hong Kyu Lee
Diabetes Metab J. 2020;44(5):699-710.   Published online April 16, 2020
DOI: https://doi.org/10.4093/dmj.2019.0109
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AbstractAbstract PDFPubReader   ePub   
Background

We sought to explore whether reduced pulmonary function is an independent risk factor for incident diabetes in Koreans.

Methods

We conducted a prospective cohort study of pulmonary function as a risk factor for incident diabetes using 10-year follow-up data from 3,864 middle-aged adults from the Ansung cohort study in Korea. The incidence of diabetes was assessed using both oral glucose tolerance tests and glycosylated hemoglobin levels.

Results

During 37,118 person-years of follow-up, 583 participants developed diabetes (incidence rate: 15.7 per 1,000 person-years). The mean follow-up period was 8.0±3.7 years. Forced vital capacity (FVC; % predicted) and forced expiratory volume in 1 second (FEV1; % predicted) were significantly correlated with incident diabetes in a graded manner after adjustment for sex, age, smoking, exercise, and metabolic parameters. The adjusted hazard ratio (HR) and confidence interval (CI) for diabetes were 1.408 (1.106 to 1.792) and 1.469 (1.137 to 1.897) in the first quartiles of FVC and FEV1, respectively, when compared with the highest quartile. Furthermore, the FVC of the lowest first and second quartiles showed a significantly higher 10-year panel homeostasis model assessment of insulin resistance index, with differences of 0.095 (95% CI, 0.010 to 0.018; P=0.028) and 0.127 (95% CI, 0.044 to 0.210; P=0.003), respectively, when compared to the highest quartiles.

Conclusion

FVC and FEV1 are independent risk factors for developing diabetes in Koreans. Pulmonary factors are possible risk factors for insulin resistance and diabetes.

Citations

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  • 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
  • Independent and combined associations of multiple-heavy-metal exposure with lung function: a population-based study in US children
    Yiting Chen, Anda Zhao, Rong Li, Wenhui Kang, Jinhong Wu, Yong Yin, Shilu Tong, Shenghui Li, Jianyu Chen
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    Guochen Li, Yanqiang Lu, Yanan Qiao, Die Hu, Chaofu Ke
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    Yunping Zhou, Fei Meng, Min Wang, Linlin Li, Pengli Yu, Yunxia Jiang
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  • 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 & Metabolism Journal.2022; 46(4): 650.     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
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    Hoon Sung Choi, Sung Woo Lee, Jin Taek Kim, Hong Kyu Lee
    Diabetes & Metabolism Journal.2020; 44(6): 944.     CrossRef
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    Jin Hwa Kim
    Diabetes & Metabolism Journal.2020; 44(6): 940.     CrossRef
Metabolic Risk/Epidemiology
Sex-, Age-, and Metabolic Disorder-Dependent Distributions of Selected Inflammatory Biomarkers among Community-Dwelling Adults
So Mi Jemma Cho, Hokyou Lee, Jee-Seon Shim, Hyeon Chang Kim
Diabetes Metab J. 2020;44(5):711-725.   Published online April 16, 2020
DOI: https://doi.org/10.4093/dmj.2019.0119
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background

Inflammatory cytokines are increasingly utilized to detect high-risk individuals for cardiometabolic diseases. However, with large population and assay methodological heterogeneity, no clear reference currently exists.

Methods

Among participants of the Cardiovascular and Metabolic Diseases Etiology Research Center cohort, of community-dwelling adults aged 30 to 64 without overt cardiovascular diseases, we presented distributions of tumor necrosis factor (TNF)-α and -β, interleukin (IL)-1α, -1β, and 6, monocyte chemoattractant protein (MCP)-1 and -3 and high sensitivity C-reactive protein (hsCRP) with and without non-detectable (ND) measurements using multiplex enzyme-linked immunosorbent assay. Then, we compared each markers by sex, age, and prevalence of type 2 diabetes mellitus, hypertension, and dyslipidemia, using the Wilcoxon Rank-Sum Test.

Results

In general, there were inconsistencies in direction and magnitude of differences in distributions by sex, age, and prevalence of cardiometabolic disorders. Overall, the median and the 99th percentiles were higher in men than in women. Older participants had higher TNF-α, high sensitivity IL-6 (hsIL-6), MCP-1, hsCRP, TNF-β, and MCP-3 median, after excluding the NDs. Participants with type 2 diabetes mellitus had higher median for all assayed biomarkers, except for TNF-β, IL-1α, and MCP-3, in which the medians for both groups were 0.00 due to predominant NDs. Compared to normotensive group, participants with hypertension had higher TNF-α, hsIL-6, MCP-1, and hsCRP median. When stratifying by dyslipidemia prevalence, the comparison varied significantly depending on the treatment of NDs.

Conclusion

Our findings provide sex-, age-, and disease-specific reference values to improve risk prediction and diagnostic performance for inflammatory diseases in both population- and clinic-based settings.

Citations

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  • Characterizing CD8+ TEMRA Cells in CP/CPPS Patients: Insights from Targeted Single-Cell Transcriptomic and Functional Investigations
    Fei Zhang, Qintao Ge, Jialin Meng, Jia Chen, Chaozhao Liang, Meng Zhang
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  • Association between physical activity and inflammatory markers in community-dwelling, middle-aged adults
    So Mi Jemma Cho, Hokyou Lee, Jee-Seon Shim, Justin Y. Jeon, Hyeon Chang Kim
    Applied Physiology, Nutrition, and Metabolism.2021; 46(7): 828.     CrossRef
  • The monocyte-to-lymphocyte ratio: Sex-specific differences in the tuberculosis disease spectrum, diagnostic indices and defining normal ranges
    Thomas S. Buttle, Claire Y. Hummerstone, Thippeswamy Billahalli, Richard J. B. Ward, Korina E. Barnes, Natalie J. Marshall, Viktoria C. Spong, Graham H. Bothamley, Selvakumar Subbian
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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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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
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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  • 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
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    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
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    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
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    Seung Mi Lee, Won Kim
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  • 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
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    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
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COVID-19
Independent Impact of Diabetes on the Severity of Coronavirus Disease 2019 in 5,307 Patients in South Korea: A Nationwide Cohort Study
Sun Joon Moon, Eun-Jung Rhee, Jin-Hyung Jung, Kyung-Do Han, Sung-Rae Kim, Won-Young Lee, Kun-Ho Yoon
Diabetes Metab J. 2020;44(5):737-746.   Published online October 21, 2020
DOI: https://doi.org/10.4093/dmj.2020.0141
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
Inconsistent results have been observed regarding the independent effect of diabetes on the severity of coronavirus disease 2019 (COVID-19). We conducted a nationwide population-based cohort study to evaluate the relationship between diabetes and COVID-19 severity in South Korea.
Methods
Patients with laboratory-confirmed COVID-19 aged ≥30 years were enrolled and medical claims data were obtained from the Korean Health Insurance Review and Assessment Service. Hospitalization, oxygen treatment, ventilator application, and mortality were assessed as severity outcomes. Multivariate logistic regression analyses were performed after adjusting for age, sex, and comorbidities.
Results
Of 5,307 COVID-19 patients, the mean age was 56.0±14.4 years, 2,043 (38.5%) were male, and 770 (14.5%) had diabetes. The number of patients who were hospitalized, who received oxygen, who required ventilator support, and who died was 4,986 (94.0%), 884 (16.7%), 121 (2.3%), and 211 (4.0%), respectively. The proportion of patients with diabetes in the abovementioned outcome groups was 14.7%, 28.1%, 41.3%, 44.6%, showing an increasing trend according to outcome severity. In multivariate analyses, diabetes was associated with worse outcomes, with an adjusted odds ratio (aOR) of 1.349 (95% confidence interval [CI], 1.099 to 1.656; P=0.004) for oxygen treatment, an aOR of 1.930 (95% CI, 1.276 to 2.915; P<0.001) for ventilator use, and an aOR of 2.659 (95% CI, 1.896 to 3.729; P<0.001) for mortality.
Conclusion
Diabetes was associated with worse clinical outcomes in Korean patients with COVID-19, independent of other comorbidities. Therefore, patients with diabetes and COVID-19 should be treated with caution.

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Basic Research
Effects of Microbiota on the Treatment of Obesity with the Natural Product Celastrol in Rats
Weiyue Hu, Lingling Wang, Guizhen Du, Quanquan Guan, Tianyu Dong, Ling Song, Yankai Xia, Xinru Wang
Diabetes Metab J. 2020;44(5):747-763.   Published online May 11, 2020
DOI: https://doi.org/10.4093/dmj.2019.0124
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background

Obesity has become one of the most serious issues threatening the health of humankind, and we conducted this study to examine whether and how celastrol protects against obesity.

Methods

We fed male Sprague-Dawley rats a high-fat diet and administered celastrol to obese rats for 3 weeks. By recording body weight (BW) and other measures, we identified the effective dose of celastrol for obesity treatment. Feces were collected to perform 16S rRNA sequencing, and hypothalami were extracted for transcriptome sequencing. We then treated leptin knockout rats with celastrol and explored the changes in energy metabolism. Male Institute of Cancer Research (ICR) mice were used to test the acute toxicity of celastrol.

Results

We observed that celastrol reduced BW and promoted energy expenditure at a dose of 500 µg/kg BW but that food intake was not changed after administration. The diversity of the gut microbiota was improved, with an increased ratio of Bacteroidetes to Firmicutes, and the gut microbiota played an important role in the anti-obesity effects of celastrol. Hypothalamic transcriptome analysis showed a significant enrichment of the leptin signaling pathway, and we found that celastrol significantly enhanced energy expenditure, which was mediated by the leptin signaling pathway. Acute lethal toxicity of celastrol was not observed at doses ranging from 0 to 62.5 mg/kg BW.

Conclusion

Our study revealed that celastrol decreased the BW of obese rats by enhancing energy expenditure but not by suppressing food intake and that this effect was mediated by the improvement of the gut microbiota and the activation of the hypothalamic leptin signaling pathway.

Citations

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Others
Can Habitual Exercise Help Reduce Serum Concentrations of Lipophilic Chemical Mixtures? Association between Physical Activity and Persistent Organic Pollutants
Yu-Mi Lee, Ji-Yeon Shin, Se-A Kim, David R. Jacobs, Duk-Hee Lee
Diabetes Metab J. 2020;44(5):764-774.   Published online May 11, 2020
DOI: https://doi.org/10.4093/dmj.2019.0158
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  • 5 Web of Science
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background

Low-dose persistent organic pollutants (POPs), especially organochlorine pesticides (OCPs), have emerged as a new risk factor of many chronic diseases. As serum concentrations of POPs in humans are mainly determined by both their release from adipose tissue to circulation and their elimination from circulation, management of these internal pathways may be important in controlling the serum concentrations of POPs. As habitual physical activity can increase the elimination of POPs from circulation, we evaluated whether chronic physical activity is related to low serum POP concentrations.

Methods

A cross-sectional study of 1,850 healthy adults (age ≥20 years) without cardio-metabolic diseases who participated in the U.S. National Health and Nutrition Examination Survey 1999 to 2004 was conducted. Information on moderate or vigorous leisure-time physical activity was obtained based on questionnaires. Serum concentrations of OCPs and polychlorinated biphenyls were investigated as typical POPs.

Results

Serum concentrations of OCPs among physically active subjects were significantly lower than those among physically inactive subjects (312.8 ng/g lipid vs. 538.0 ng/g lipid, P<0.001). This difference was maintained after adjustment for potential confounders. When analyses were restricted to physically active subjects, there were small decreases in the serum concentrations of OCPs with increasing duration of physical activity, showing a curvilinear relationship over the whole range of physical activity (Pquadratic <0.001). In analyses stratified by age, sex, body mass index, and smoking status, a strong inverse association was similarly observed among all subgroups.

Conclusion

Physical activity may assist in decreasing serum concentrations of lipophilic chemical mixtures such as OCPs.

Citations

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  • Is Physical Activity an Efficient Strategy to Control the Adverse Effects of Persistent Organic Pollutants in the Context of Obesity? A Narrative Review
    Quentin A. Serrano, Sébastien Le Garf, Vincent Martin, Serge S. Colson, Nicolas Chevalier
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Letters

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