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Tae Yong Kim  (Kim TY) 2 Articles
Association between Type 2 Diabetes and Genetic Variations in Uncoupling Protein 2, beta3-Adrenergic Receptor, and Peroxisome Proliferator-Activated Receptor gamma in Korean.
Min Kyong Moon, Young Min Cho, Hye Seung Jung, Tae Yong Kim, Yun Yong Lee, Joong Yeol Park, Ki Up Lee, Chan Soo Shin, Kyong Soo Park, Seong Yeon Kim, Hong Kyu Lee, Hyoung Doo Shin
Korean Diabetes J. 2002;26(6):469-480.   Published online December 1, 2002
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AbstractAbstract PDF
BACKGROUND
Type 2 diabetes mellitus is a multifactorial disease influenced by numerous genetic and environmental factors. The uncoupling proteins, 2 (UCP2), beta3-adrenergic receptor ADRB3, and peroxisome proliferator-activated receptor gamma PPAR gamma, are genes involved in energy expenditure and fatty acid metabolisms, ans are therefore regarded as candidate genes for type 2 diabetes. In this study, we examined whether the known polymorphisms of UCP2, ADRB3 and PPAR gamma are associated with type 2 diabetes in the Korean population. METHODS: We studied 516 type 2 diabetic patients and 147 control subjects. The enrollment criteria for the control subjects were as follows; age > 60 years, no family history of diabetes in their first-degree relatives, a fasting plasma glucose (FPG) < 6.1 mmol/L, and a HbA1C < 5.8%. Height, weight, waist and hip circumference, FPG, 2 hour-plasma glucose after 75g-glucose load (2h-PG), blood pressure, lipid profile, and fasting insulin level were measured. The Ala55Val polymorphism of the UCP2, Trp64Arg polymorphism of the ADRB3, and Pro12Ala polymorphism of the PPAR gamma were determined by single base extension method. RESULTS: The allele frequency of the Ala55Val variant of the UCP2 tended to be higher in the control subjects than in the type 2 diabetic patients (0.497 vs. 0.456, p=0.064). The allele frequencies of the Trp64Arg polymorphism of the ADRB3, and the Pro12Ala polymorphism of the PPAR gamma, were comparable between the diabetic patients and the control subjects (0.141 vs. 0.152 and 0.033 vs. 0.041, respectively). In the control subjects, the Ala55Val polymorphism of the UCP2 was associated with a significantly lower 2h-PG compared to the wild type (6.0 +/- 0.8 mmol/L vs. 6.6 +/- 0.7 mmol/L, p=0.002). The female control subjects, with the ADRB3 Trp64Arg variant, had a significantly lower triglyceride level than those without the variant (1.36 +/- 0.53 mmol/L vs. 1.74 +/- 0.82 mmol/L, p=0.020). The type 2 diabetic patients, with the ADRB3 Trp64Arg variant showed a significantly lower body mass index (23.6 +/- 2.6 kg/m2vs. 24.6 +/- 3.0 kg/m2, p=0.001). The PPAR gamma Pro12Ala variant, was not associated with any of the features of insulin resistance. The combined genotype of the Val allele of UCP2, Trp allele of ADRB3 and Ala allele of PPAR gamma was less frequent among the type 2 diabetes patients than the control subjects (0.020 vs. 0.056, p=0.039). CONCLUSION: The Ala55Val variant of the UCP2, the Trp64Arg variant of the ADRB3 and the Pro12Ala variant of the PPAR gamma, were not associated with type 2 diabetes in the Korean population. However, the Ala55Val variant of the UCP2 was associated with a lower 2h-PG in the control subjects and the Trp64Arg variant of the ADRB3 was associated with a lower triglyceride level in the female control subjects. Further study may be required to elucidate if the combined genotype of Val allele of UCP2, Trp allele of ADRB3 and Ala allele of PPAR gamma would be protective against type 2 diabetes.
Correlation between Basal Insulin Requirements and Daily Administered Insulin Dosage in Diabetes.
Min Kyong Moon, Jong Ho Ahn, Tae Yong Kim, Won Shik Shinn, Soo Lim, Young Min Cho, Kyong Soo Park, Seong Yeon Kim, Hong Kyu Lee
Korean Diabetes J. 2000;24(5):552-559.   Published online January 1, 2001
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AbstractAbstract
BACKGROUND
In patients who need insulin therapy, it is difficult to assess insulin requirements because of individual variability in insulin sensitivity and secretion. The aim of this study is to know that it is possible to achieve rapidly and efficiently normoglycemia based on insulin infusion algorithm and whether there is correlation between basal insulin requirements and daily administered total insulin dose. METHODS: Total 34 patients were enrolled. Insulin infusion was begun at 2:00 p.m., and bedside blood glucose concentration was measured at hourly intervals. The rate of insulin infusion was adjusted according to blood glucose levels. We compared insulin requirements to maintain normoglycemia (basal insulin requirements) with daily administered total insulin dose. RESULTS: At start, the mean blood glucose concentration was 14.9+/-4.7 mmol/L; by the first hour, it was 10.7+/-3.6 mmol/L; by the second hour, it was 7.4+/-3.1 mmol/L; when the infusion was discontinued, it was 5.7+/-1.0 mmol/L. This algorithm successfully inducted normoglycemia in all patients within 3.5+/-1.8 h. There was significant correlation between basal insulin requirements and daily administered total insulin dosage. And, daily administered insulin dose had significant correlation with first hour glucose concentration, first hour insulin infusion rate, second hour glucose concentration, second hour insulin infusion rate, and glucose concentration at the end. CONCLUSIONS: We concluded that normoglycemia can be achieved rapidly and efficiently based on insulin infusion algorithm. The present study suggested that we could predict daily insulin requirements through basal insulin requirements that we measured.

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