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Diabetes Metab J : Diabetes & Metabolism Journal



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Clinical Characteristics of Type 2 Diabetes Patients according to Family History of Diabetes
Seung Uk Jeong, Dong Gu Kang, Dae Ho Lee, Kang Woo Lee, Dong-Mee Lim, Byung Joon Kim, Keun-Yong Park, Hyoun-Jung Chin, Gwanpyo Koh
Korean Diabetes J. 2010;34(4):222-228.   Published online August 31, 2010
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  • 26 Download
  • 14 Crossref
AbstractAbstract PDFPubReader   

Type 2 diabetes mellitus (T2DM) has a strong genetic component, and its prevalence is notably increased in the family members of T2DM patients. However, there are few studies about the family history of T2DM. We carried out this study to assess the influences of family history on clinical characteristics in T2DM patients.


This is a cross-sectional study involving 651 T2DM patients. Patient history and physical examination were performed and fasting blood was taken. If any first degree relative was diabetic, a family history of diabetes was considered to exist.


Among the total 621 patients, 38.4% had a family history of diabetes. Patients with a family history had a younger age, higher weight, younger age at diagnosis and higher triglyceride level than did those without a family history. Dyslipidemia medication and metabolic syndrome were more prevalent in familial diabetes. Sex, blood pressure, previous treatment for diabetes, HbA1c, C-peptide, total cholesterol, high density lipoprotein cholesterol, and low density lipoprotein cholesterol were not different between familial and non-familial diabetes. Upon multiple linear regression analysis, the family history of diabetes remained significantly associated with serum triglyceride level.


In T2DM patients with a family history of diabetes, the disease tended to develop earlier. Metabolic syndrome and cardiovascular risk factors are more prevalent in familial T2DM than they were in non-familial T2DM. These results support the necessity of earlier screening for diabetes in family members of T2DM patients and more active prevention against cardiovascular disease in T2DM patients with a family history.


Citations to this article as recorded by  
  • Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes
    Eva Gonzalez-Flo, Elaheh Kheirabadi, Carlos Rodriguez-Caso, Javier Macía
    Frontiers in Physiology.2023;[Epub]     CrossRef
  • Role of Cytokines (IL-17 and IL-33), FGF-18, and WNT-5 in the Pathogenesis of Patients with Established Type II Diabetes
    Przha Mohammed, Kawa Amin
    Journal of Zankoy Sulaimani - Part A.2023; 25(2): 11.     CrossRef
  • Cellular Chitchatting: Exploring the Role of Exosomes as Cardiovascular Risk Factors
    Giulia Germena, Laura Cecilia Zelarayán, Rabea Hinkel
    Frontiers in Cell and Developmental Biology.2022;[Epub]     CrossRef
  • Combined associations of family history and self-management with age at diagnosis and cardiometabolic risk in 86,931 patients with type 2 diabetes: Joint Asia Diabetes Evaluation (JADE) Register from 11 countries
    Johnny T. K. Cheung, Eric Lau, Cyrus C. T. Tsui, Edmond L. N. Siu, Naomi K. W. Tse, Nicole Y. L. Hui, Ronald C. W. Ma, Alice P. S. Kong, Amy Fu, Vanessa Lau, Weiping Jia, Wayne H. H. Sheu, Leorino Sobrepena, K. H. Yoon, Alexander T. B. Tan, Yook-Chin Chia
    BMC Medicine.2022;[Epub]     CrossRef
  • Capsaicin, its clinical significance in patients with painful diabetic neuropathy
    Phiwayinkosi V. Dludla, Bongani B. Nkambule, Ilenia Cirilli, Fabio Marcheggiani, Sihle E. Mabhida, Khanyisani Ziqubu, Yonela Ntamo, Babalwa Jack, Tawanda M. Nyambuya, Sidney Hanser, Sithandiwe E. Mazibuko-Mbeje
    Biomedicine & Pharmacotherapy.2022; 153: 113439.     CrossRef
  • Safety profile of sodium glucose co-transporter 2 (SGLT2) inhibitors: A brief summary
    Annamaria Mascolo, Raffaella Di Napoli, Nunzia Balzano, Donato Cappetta, Konrad Urbanek, Antonella De Angelis, Lucia Scisciola, Irene Di Meo, Maria Giuseppa Sullo, Concetta Rafaniello, Liberata Sportiello
    Frontiers in Cardiovascular Medicine.2022;[Epub]     CrossRef
  • Impact of triglycerides and waist circumference on insulin resistance and β-cell function in non-diabetic first-degree relatives of type 2 diabetes
    Fahd Ahmed, Molham AL-Habori, Ebtesam Al-Zabedi, Riyadh Saif-Ali
    BMC Endocrine Disorders.2021;[Epub]     CrossRef
  • Orientin Improves Substrate Utilization and the Expression of Major Genes Involved in Insulin Signaling and Energy Regulation in Cultured Insulin-Resistant Liver Cells
    Sithandiwe E. Mazibuko-Mbeje, Sinenhlanhla X. H. Mthembu, Andani Tshiitamune, Ndivhuwo Muvhulawa, Fikile T. Mthiyane, Khanyisani Ziqubu, Christo J. F. Muller, Phiwayinkosi V. Dludla
    Molecules.2021; 26(20): 6154.     CrossRef
  • Identification of Pre-Diabetic Biomarkers in the Progression of Diabetes Mellitus
    Jae-Ho Lee, Do-Young Kim, Rubee Pantha, Eun-Ho Lee, Jae-Hoon Bae, Eugene Han, Dae-Kyu Song, Taeg Kyu Kwon, Seung-Soon Im
    Biomedicines.2021; 10(1): 72.     CrossRef
  • Shared (epi)genomic background connecting neurodegenerative diseases and type 2 diabetes
    Valerio Caputo, Andrea Termine, Claudia Strafella, Emiliano Giardina, Raffaella Cascella
    World Journal of Diabetes.2020; 11(5): 155.     CrossRef
  • Family history of diabetes in both parents is strongly associated with impaired residual β‐cell function in Japanese type 2 diabetes patients
    Minoru Iwata, Yutaka Kamura, Hisae Honoki, Kaori Kobayashi, Manabu Ishiki, Kunimasa Yagi, Yasuo Fukushima, Atsuko Takano, Hiromi Kato, Shihou Murakami, Kiyohiro Higuchi, Chikaaki Kobashi, Kazuhito Fukuda, Yukiko Koshimizu, Kazuyuki Tobe
    Journal of Diabetes Investigation.2020; 11(3): 564.     CrossRef
  • The relationship between age of onset and risk factors including family history and life style in Korean population with type 2 diabetes mellitus
    Jin-Won Noh, Jin Hee Jung, Jeong Eun Park, Jung Hwa Lee, Kang Hee Sim, Jumin Park, Min Hee Kim, Ki-Bong Yoo
    Journal of Physical Therapy Science.2018; 30(2): 201.     CrossRef
  • Clinical Characteristics of Subjects with Sulfonylurea-Dependent Type 2 Diabetes
    Se Hee Min, Soo Heon Kwak, Young Min Cho, Kyong Soo Park, Hye Seung Jung
    Endocrinology and Metabolism.2015; 30(4): 509.     CrossRef
  • Nutritional Assessment of Type II Diabetic Patients
    El-Sayed H. Bakr
    Pakistan Journal of Nutrition.2015; 14(6): 308.     CrossRef
Cystatin C is a Valuable Marker for Predicting Future Cardiovascular Diseases in Type 2 Diabetic Patients.
Seung Hwan Lee, Kang Woo Lee, Eun Sook Kim, Ye Ree Park, Hun Sung Kim, Shin Ae Park, Mi Ja Kang, Yu Bai Ahn, Kun Ho Yoon, Bong Yun Cha, Ho Young Son, Hyuk Sang Kwon
Korean Diabetes J. 2008;32(6):488-497.   Published online December 1, 2008
  • 2,356 View
  • 22 Download
  • 2 Crossref
AbstractAbstract PDF
Recent studies suggest that serum Cystatin C is both a sensitive marker for renal dysfunction and a predictive marker for cardiovascular diseases. We aimed to evaluate the association between Cystatin C and various biomarkers and to find out its utility in estimating risk for cardiovascular diseases in type 2 diabetic patients. METHODS: From June 2006 to March 2008, anthropometric measurements and biochemical studies including biomarkers for risk factors of cardiovascular diseases were done in 520 type 2 diabetic patients. A 10-year risk for coronary heart diseases and stroke was estimated using Framingham risk score and UKPDS risk engine. RESULTS: The independent variables showing statistically significant associations with Cystatin C were age (beta = 0.009, P < 0.0001), hemoglobin (beta = -0.038, P = 0.0006), serum creatinine (beta = 0.719, beta < 0.0001), uric acid (beta = 0.048, P = 0.0004), log hsCRP (beta = 0.035, P = 0.0021) and homocysteine (beta = 0.005, P = 0.0228). The levels of microalbuminuria, carotid intima-media thickness, fibrinogen and lipoprotein (a) also correlated with Cystatin C, although the significance was lost after multivariate adjustment. Calculated risk for coronary heart diseases increased in proportion to Cystatin C quartiles: 3.3 +/- 0.4, 6.2 +/- 0.6, 7.6 +/- 0.7, 8.4 +/- 0.7% from Framingham risk score (P < 0.0001); 13.1 +/- 0.9, 21.2 +/- 1.6, 26.1 +/- 1.7, 35.4 +/- 2.0% from UKPDS risk engine (P < 0.0001) (means +/- SE). CONCLUSIONS: Cystatin C is significantly correlated with various emerging biomarkers for cardiovascular diseases. It was also in accordance with the calculated risk for cardiovascular diseases. These findings verify Cystatin C as a valuable and useful marker for predicting future cardiovascular diseases in type 2 diabetic patients.


Citations to this article as recorded by  
  • Lack of Association between Serum Cystatin C Levels and Coronary Artery Disease in Diabetic Patients
    Eun Hee Kim, Ji Hee Yu, Sang Ah Lee, Eui Young Kim, Won Gu Kim, Seung Hun Lee, Eun Hee Cho, Eun Hee Koh, Woo Je Lee, Min-Seon Kim, Joong-Yeol Park, Ki-Up Lee
    Korean Diabetes Journal.2010; 34(2): 95.     CrossRef
  • Insulin resistance and inflammation may have an additional role in the link between cystatin C and cardiovascular disease in type 2 diabetes mellitus patients
    Seung-Hwan Lee, Shin-Ae Park, Seung-Hyun Ko, Hyeon-Woo Yim, Yu-Bae Ahn, Kun-Ho Yoon, Bong-Yun Cha, Ho-Young Son, Hyuk-Sang Kwon
    Metabolism.2010; 59(2): 241.     CrossRef
The Effects of Exendin-4 on IRS-2 Expression and Phosphorylation in INS-1 Cells.
Ji Hyun Kim, Ji Won Kim, Sung Yoon Jeon, Heon Seok Park, Dong Sik Ham, Young Hye You, Seung Hwan Lee, Jae Hyoung Cho, Mi Ja Kang, Kang Woo Lee, Hyuk Sang Kwon, Kun Ho Yoon, Bong Yun Cha, Kwang Woo Lee, Sung Koo Kang, Ho Young Son
Korean Diabetes J. 2008;32(2):102-111.   Published online April 1, 2008
  • 2,570 View
  • 31 Download
AbstractAbstract PDF
Insulin receptor substrate 2 (IRS-2) is a key regulator of beta cell proliferation and apoptosis. This study was aimed to investigate effect of the glucolipotoxicity on apoptosis in INS-1 cell, and the effect of Exendin-4, a GLP-1 receptor agonist, on IRS-2 expression in the glucolipotoxicity induced INS-1 cell. The goal was to discover the new action mechanism and function of Exendin-4 in beta cell apoptosis. METHOD: INS-1 cells were cultured in glucolipotoxic condition for 2, 4 or 6 days and were categorized as G groups. Another group in which 50 nM Exendin-4 was added to INS-1 cells, cultured in glucolipotoxic condition, were named as Ex-4 groups. We investigated the expression of IRS-2 by RT-PCR, phosphorylated IRS-2 and phosphorylated Akt protein levels by western blot. We measured the apoptosis ratio of INS-1 cell in glucolipotoxic condition by TUNEL staining in both groups. RESULT: IRS-2 expression of INS-1 cells decreased with correlation to the time of exposure to glucolipotoxic condition. pIRS-2 and pAkt protein levels decreased in the similar pattern in glucolipotoxicity group. However, this effect of glucolipotoxicity on INS-1 cell was inhibited by the Exendin-4 treatment. In the Ex-4 groups, IRS-2 expression, pIRS-2 and pAkt protein levels remained at the similar level to low glucose condition state. Also, apoptosis induced by glucolipotoxicity was suppressed by Exendin-4 treatment significantly. CONCLUSION: We showed that the long-term treatment of Exendin-4 inhibited the apoptosis of beta cells significantly in glucolipotoxic condition and that this effect of Exendin-4 was related with IRS-2 and Akt among the beta cell's intracellular signal transduction pathway.

Diabetes Metab J : Diabetes & Metabolism Journal