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Complications
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Association of Succinate and Adenosine Nucleotide Metabolic Pathways with Diabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus
Inha Jung, Seungyoon Nam, Da Young Lee, So Young Park, Ji Hee Yu, Ji A Seo, Dae Ho Lee, Nan Hee Kim
Received October 23, 2023  Accepted May 6, 2024  Published online July 1, 2024  
DOI: https://doi.org/10.4093/dmj.2023.0377    [Epub ahead of print]
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
Although the prevalence of diabetic kidney disease (DKD) is increasing, reliable biomarkers for its early detection are scarce. This study aimed to evaluate the association of adenosine and succinate levels and their related pathways, including hyaluronic acid (HA) synthesis, with DKD.
Methods
We examined 235 participants and categorized them into three groups: healthy controls; those with diabetes but without DKD; and those with DKD, which was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2. We compared the concentrations of urinary adenosine, succinate, and HA and the serum levels of cluster of differentiation 39 (CD39) and CD73, which are involved in adenosine generation, among the groups with DKD or albuminuria. In addition, we performed multiple logistic regression analysis to evaluate the independent association of DKD or albuminuria with the metabolites after adjusting for risk factors. We also showed the association of these metabolites with eGFR measured several years before enrollment. This study was registered with the Clinical Research Information Service (https://cris.nih.go.kr; Registration number: KCT0003573).
Results
Urinary succinate and serum CD39 levels were higher in the DKD group than in the control and non-DKD groups. Correlation analysis consistently linked urinary succinate and serum CD39 concentrations with eGFR, albuminuria, and ΔeGFR, which was calculated retrospectively. However, among the various metabolites studied, only urinary succinate was identified as an independent indicator of DKD and albuminuria.
Conclusion
Among several potential metabolites, only urinary succinate was independently associated with DKD. These findings hold promise for clinical application in the management of DKD.
Review
Pathophysiology
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Attention to Innate Circadian Rhythm and the Impact of Its Disruption on Diabetes
Da Young Lee, Inha Jung, So Young Park, Ji Hee Yu, Ji A Seo, Kyeong Jin Kim, Nam Hoon Kim, Hye Jin Yoo, Sin Gon Kim, Kyung Mook Choi, Sei Hyun Baik, Nan Hee Kim
Diabetes Metab J. 2024;48(1):37-52.   Published online January 3, 2024
DOI: https://doi.org/10.4093/dmj.2023.0193
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AbstractAbstract PDFPubReader   ePub   
Novel strategies are required to reduce the risk of developing diabetes and/or clinical outcomes and complications of diabetes. In this regard, the role of the circadian system may be a potential candidate for the prevention of diabetes. We reviewed evidence from animal, clinical, and epidemiological studies linking the circadian system to various aspects of the pathophysiology and clinical outcomes of diabetes. The circadian clock governs genetic, metabolic, hormonal, and behavioral signals in anticipation of cyclic 24-hour events through interactions between a “central clock” in the suprachiasmatic nucleus and “peripheral clocks” in the whole body. Currently, circadian rhythmicity in humans can be subjectively or objectively assessed by measuring melatonin and glucocorticoid levels, core body temperature, peripheral blood, oral mucosa, hair follicles, rest-activity cycles, sleep diaries, and circadian chronotypes. In this review, we summarized various circadian misalignments, such as altered light-dark, sleep-wake, rest-activity, fasting-feeding, shift work, evening chronotype, and social jetlag, as well as mutations in clock genes that could contribute to the development of diabetes and poor glycemic status in patients with diabetes. Targeting critical components of the circadian system could deliver potential candidates for the treatment and prevention of type 2 diabetes mellitus in the future.
Letter
Original Articles
Technology/Device
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Clinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus
Da Young Lee, Namho Kim, Inha Jung, So Young Park, Ji Hee Yu, Ji A Seo, Jihee Kim, Kyeong Jin Kim, Nam Hoon Kim, Hye Jin Yoo, Sin Gon Kim, Kyung Mook Choi, Sei Hyun Baik, Sung-Min Park, Nan Hee Kim
Diabetes Metab J. 2023;47(6):826-836.   Published online August 24, 2023
DOI: https://doi.org/10.4093/dmj.2022.0273
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  • 1 Web of Science
  • 1 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
There was limited evidence to evaluate the association between lifestyle habits and continuous glucose monitoring (CGM) metrics. Thus, we aimed to depict the behavioral and metabolic determinants of CGM metrics in insulin-treated patients with type 2 diabetes mellitus (T2DM).
Methods
This is a prospective observational study. We analyzed data from 122 insulin-treated patients with T2DM. Participants wore Dexcom G6 and Fitbit, and diet information was identified for 10 days. Multivariate-adjusted logistic regression analysis was performed for the simultaneous achievement of CGM-based targets, defined by the percentage of time in terms of hyper, hypoglycemia and glycemic variability (GV). Intake of macronutrients and fiber, step counts, sleep, postprandial C-peptide-to-glucose ratio (PCGR), information about glucose lowering medications and metabolic factors were added to the analyses. Additionally, we evaluated the impact of the distribution of energy and macronutrient during a day, and snack consumption on CGM metrics.
Results
Logistic regression analysis revealed that female, participants with high PCGR, low glycosylated hemoglobin (HbA1c) and daytime step count had a higher probability of achieving all targets based on CGM (odds ratios [95% confidence intervals] which were 0.24 [0.09 to 0.65], 1.34 [1.03 to 1.25], 0.95 [0.9 to 0.99], and 1.15 [1.03 to 1.29], respectively). And participants who ate snacks showed a shorter period of hyperglycemia and less GV compared to those without.
Conclusion
We confirmed that residual insulin secretion, daytime step count, HbA1c, and women were the most relevant determinants of adequate glycemic control in insulin-treated patients with T2DM. In addition, individuals with snack consumption were exposed to lower times of hyperglycemia and GV.

Citations

Citations to this article as recorded by  
  • Explanatory variables of objectively measured 24-h movement behaviors in people with prediabetes and type 2 diabetes: A systematic review
    Lotte Bogaert, Iris Willems, Patrick Calders, Eveline Dirinck, Manon Kinaupenne, Marga Decraene, Bruno Lapauw, Boyd Strumane, Margot Van Daele, Vera Verbestel, Marieke De Craemer
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2024; 18(4): 102995.     CrossRef
Others
Fasting Glucose Variability and the Risk of Dementia in Individuals with Diabetes: A Nationwide Cohort Study
Da Young Lee, Jaeyoung Kim, Sanghyun Park, So Young Park, Ji Hee Yu, Ji A Seo, Nam Hoon Kim, Hye Jin Yoo, Sin Gon Kim, Kyung Mook Choi, Sei Hyun Baik, Kyungdo Han, Nan Hee Kim
Diabetes Metab J. 2022;46(6):923-935.   Published online May 24, 2022
DOI: https://doi.org/10.4093/dmj.2021.0346
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  • 11 Web of Science
  • 10 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
We investigated whether fasting glucose (FG) variability could predict the risk of dementia.
Methods
This cohort study analyzed data from Koreans with diabetes after at least three health examinations by the Korean National Health Insurance Corporation between 2005 and 2010, which included at least one examination between 2009 and 2010. A total of 769,554 individuals were included, excluding those aged <40 years and those with dementia. FG variability was measured using the variability independent of the mean (FG-VIM). The incidence of dementia was defined by the International Classification of Diseases 10th Revision codes and prescription of anti-dementia medication and was subdivided into Alzheimer’s disease (AD) and vascular dementia (VD).
Results
During the 6.9-year follow-up, 54,837, 41,032, and 6,892 cases of all-cause dementia, AD, and VD, respectively, were identified. Cox proportional regression analyses showed that as the FG-VIM quartile increased, the risk of dementia serially increased after adjustment for metabolic factors, income status, and diabetes-related characteristics, including the mean FG. Participants in FG-VIM quartile 4 showed a 18%, 19%, and 17% higher risk for all-cause dementia, AD, and VD, respectively, than those in quartile 1; this particularly included non-obese patients with a longer duration of diabetes, high FG levels, dyslipidemia, and those taking glucose-lowering medications. Conversely, the baseline FG status and dementia showed a U-shaped association.
Conclusion
Increased FG variability over 5 years can predict the risk of dementia in individuals with diabetes in Korea. This finding was more pronounced in patients with less favorable metabolic profiles.

Citations

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  • Fasting glucose variability and risk of dementia in Parkinson’s disease: a 9-year longitudinal follow-up study of a nationwide cohort
    Sung Hoon Kang, Yunjin Choi, Su Jin Chung, Seok-Joo Moon, Chi Kyung Kim, Ji Hyun Kim, Kyungmi Oh, Joon Shik Yoon, Sang Won Seo, Geum Joon Cho, Seong-Beom Koh
    Frontiers in Aging Neuroscience.2024;[Epub]     CrossRef
  • Effects of a Diabetic Microenvironment on Neurodegeneration: Special Focus on Neurological Cells
    Vishal Chavda, Dhananjay Yadav, Snehal Patel, Minseok Song
    Brain Sciences.2024; 14(3): 284.     CrossRef
  • The relationship between diabetes and the dementia risk: a meta-analysis
    Fang Cao, Fushuang Yang, Jian Li, Wei Guo, Chongheng Zhang, Fa Gao, Xinxin Sun, Yi Zhou, Wenfeng Zhang
    Diabetology & Metabolic Syndrome.2024;[Epub]     CrossRef
  • Effect of glucose variability on the mortality of adults aged 75 years and over during the first year of the COVID-19 pandemic
    Miguel A. Salinero-Fort, F. Javier San Andrés-Rebollo, Juan Cárdenas-Valladolid, José Mostaza, Carlos Lahoz, Fernando Rodriguez-Artalejo, Paloma Gómez-Campelo, Pilar Vich-Pérez, Rodrigo Jiménez-García, José M. de-Miguel-Yanes, Javier Maroto-Rodriguez, Bel
    BMC Geriatrics.2024;[Epub]     CrossRef
  • Association of remnant cholesterol with risk of dementia: a nationwide population-based cohort study in South Korea
    Ji Hye Heo, Han Na Jung, Eun Roh, Kyung-do Han, Jun Goo Kang, Seong Jin Lee, Sung-Hee Ihm
    The Lancet Healthy Longevity.2024; 5(8): e524.     CrossRef
  • Glycated Hemoglobin A1c Time in Range and Dementia in Older Adults With Diabetes
    Patricia C. Underwood, Libin Zhang, David C. Mohr, Julia C. Prentice, Richard E. Nelson, Andrew E. Budson, Paul R. Conlin
    JAMA Network Open.2024; 7(8): e2425354.     CrossRef
  • The Association of Glucose Variability and Dementia Incidence in Latinx Adults with Type 2 Diabetes: A Retrospective Study
    Heather Cuevas, Elizabeth Muñoz, Divya Nagireddy, Jeeyeon Kim, Grace Ganucheau, Fathia Alomoush
    Clinical Nursing Research.2023; 32(2): 249.     CrossRef
  • The effects of long-term cumulative HbA1c exposure on the development and onset time of dementia in the patients with type 2 diabetes mellitus: Hospital based retrospective study (2005–2021)
    Sunyoung Cho, Choon Ok Kim, Bong-soo Cha, Eosu Kim, Chung Mo Nam, Min-Gul Kim, Min Soo Park
    Diabetes Research and Clinical Practice.2023; 201: 110721.     CrossRef
  • Physiological Mechanisms Inherent to Diabetes Involved in the Development of Dementia: Alzheimer’s Disease
    Himan Mohamed-Mohamed, Victoria García-Morales, Encarnación María Sánchez Lara, Anabel González-Acedo, Teresa Pardo-Moreno, María Isabel Tovar-Gálvez, Lucía Melguizo-Rodríguez, Juan José Ramos-Rodríguez
    Neurology International.2023; 15(4): 1253.     CrossRef
  • Cumulative effect of impaired fasting glucose on the risk of dementia in middle-aged and elderly people: a nationwide cohort study
    Jin Yu, Kyu-Na Lee, Hun-Sung Kim, Kyungdo Han, Seung-Hwan Lee
    Scientific Reports.2023;[Epub]     CrossRef
Short Communication
Technology/Device
Comparison of Laser and Conventional Lancing Devices for Blood Glucose Measurement Conformance and Patient Satisfaction in Diabetes Mellitus
Jung A Kim, Min Jeong Park, Eyun Song, Eun Roh, So Young Park, Da Young Lee, Jaeyoung Kim, Ji Hee Yu, Ji A Seo, Kyung Mook Choi, Sei Hyun Baik, Hye Jin Yoo, Nan Hee Kim
Diabetes Metab J. 2022;46(6):936-940.   Published online March 30, 2022
DOI: https://doi.org/10.4093/dmj.2021.0293
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  • 3 Web of Science
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AbstractAbstract PDFPubReader   ePub   
Self-monitoring of capillary blood glucose is important for controlling diabetes. Recently, a laser lancing device (LMT-1000) that can collect capillary blood without skin puncture was developed. We enrolled 150 patients with type 1 or 2 diabetes mellitus. Blood sampling was performed on the same finger on each hand using the LMT-1000 or a conventional lancet. The primary outcome was correlation between glucose values using the LMT-1000 and that using a lancet. And we compared the pain and satisfaction of the procedures. The capillary blood sampling success rates with the LMT-1000 and lancet were 99.3% and 100%, respectively. There was a positive correlation (r=0.974, P<0.001) between mean blood glucose levels in the LMT-1000 (175.8±63.0 mg/dL) and conventional lancet samples (172.5±63.6 mg/dL). LMT-1000 reduced puncture pain by 75.0% and increased satisfaction by 80.0% compared to a lancet. We demonstrated considerable consistency in blood glucose measurements between samples from the LMT-1000 and a lancet, but improved satisfaction and clinically significant pain reduction were observed with the LMT-1000 compared to those with a lancet.

Citations

Citations to this article as recorded by  
  • Comparison between a laser-lancing device and automatic incision lancet for capillary blood sampling from the heel of newborn infants: a randomized feasibility trial
    Chul Kyu Yun, Eui Kyung Choi, Hyung Jin Kim, Jaeyoung Kim, Byung Cheol Park, Kyuhee Park, Byung Min Choi
    Journal of Perinatology.2024; 44(8): 1193.     CrossRef
  • Comparison of laser and traditional lancing devices for capillary blood sampling in patients with diabetes mellitus and high bleeding risk
    Min Jeong Park, Soon Young Hwang, Ahreum Jang, Soo Yeon Jang, Eyun Song, So Young Park, Da Young Lee, Jaeyoung Kim, Byung Cheol Park, Ji Hee Yu, Ji A Seo, Kyung Mook Choi, Sei Hyun Baik, Hye Jin Yoo, Nan Hee Kim
    Lasers in Medical Science.2024;[Epub]     CrossRef
Original Article
Clinical Complications
Incidence and Risk Factors for Dementia in Type 2 Diabetes Mellitus: A Nationwide Population-Based Study in Korea
Ji Hee Yu, Kyungdo Han, Sanghyun Park, Hanna Cho, Da Young Lee, Jin-Wook Kim, Ji A Seo, Sin Gon Kim, Sei Hyun Baik, Yong Gyu Park, Kyung Mook Choi, Seon Mee Kim, Nan Hee Kim
Diabetes Metab J. 2020;44(1):113-124.   Published online November 12, 2019
DOI: https://doi.org/10.4093/dmj.2018.0216
  • 9,118 View
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  • 35 Web of Science
  • 36 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

Diabetes mellitus is associated with an increased risk of dementia. We aimed to comprehensively analyze the incidence and risk factors for dementia and young-onset dementia (YOD) in diabetic patients in Korea using the National Health Insurance Service data.

Methods

Between January 1, 2009 and December 31, 2012, a total of 1,917,702 participants with diabetes were included and followed until the date of dementia diagnosis or until December 31, 2015. We evaluated the incidence and risk factors for all dementia, Alzheimer's disease (AD), and vascular dementia (VaD) by Cox proportional hazards analyses. We also compared the impact of risk factors on the occurrence of YOD and late-onset dementia (LOD).

Results

During an average of 5.1 years of follow-up, the incidence of all types of dementia, AD, or VaD was 9.5, 6.8, and 1.3/1,000 person-years, respectively, in participants with diabetes. YOD comprised 4.8% of all dementia occurrence, and the ratio of AD/VaD was 2.1 for YOD compared with 5.5 for LOD. Current smokers and subjects with lower income, plasma glucose levels, body mass index (BMI), and subjects with hypertension, dyslipidemia, vascular complications, depression, and insulin treatment developed dementia more frequently. Vascular risk factors such as smoking, hypertension, and previous cardiovascular diseases were more strongly associated with the development of VaD than AD. Low BMI and a history of stroke or depression had a stronger influence on the development of YOD than LOD.

Conclusion

The optimal management of modifiable risk factors may be important for preventing dementia in subjects with diabetes mellitus.

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    Diabetes Research and Clinical Practice.2023; 201: 110721.     CrossRef
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    Tae-Jin Song, Jimin Jeon, Jinkwon Kim
    Diabetes & Metabolism.2021; 47(6): 101252.     CrossRef
  • Association Between Diabetic Retinopathy and Cognitive Impairment: A Systematic Review and Meta-Analysis
    Dihe Cheng, Xue Zhao, Shuo Yang, Guixia Wang, Guang Ning
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    Yun Kyung Cho, Jiwoo Lee, Hwi Seung Kim, Joong-Yeol Park, Woo Je Lee, Ye-Jee Kim, Chang Hee Jung
    Aging.2021; 13(13): 16974.     CrossRef
  • Letter: Hypoglycemia and Dementia Risk in Older Patients with Type 2 Diabetes Mellitus: A Propensity-Score Matched Analysis of a Population-Based Cohort Study (Diabetes Metab J 2020;44:125–33)
    Jin Hwa Kim
    Diabetes & Metabolism Journal.2020; 44(2): 356.     CrossRef
  • The Interplay between Diabetes and Alzheimer’s Disease—In the Hunt for Biomarkers
    Adriana Kubis-Kubiak, Aleksandra Dyba, Agnieszka Piwowar
    International Journal of Molecular Sciences.2020; 21(8): 2744.     CrossRef
  • Association between cytomegalovirus end-organ diseases and moderate-to-severe dementia: a population-based cohort study
    Kyoung Hwa Lee, Da Eun Kwon, Kyung Do Han, Yeonju La, Sang Hoon Han
    BMC Neurology.2020;[Epub]     CrossRef
Editorial
Clinical Diabetes & Therapeutics
Changes in the Bone Mineral Density of Femur Neck and Total Hip Over a 52-Week Treatment with Lobeglitazone
Da Young Lee, Ji A Seo
Diabetes Metab J. 2017;41(5):374-376.   Published online October 24, 2017
DOI: https://doi.org/10.4093/dmj.2017.41.5.374
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