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"Jin-Su Choi"

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"Jin-Su Choi"

Original Articles
Association between Apolipoprotein E Polymorphism and Chronic Kidney Disease in the Korean General Population: Dong-gu Study
Seong-Woo Choi, Sun-Seog Kweon, Jin-Su Choi, Jung-Ae Rhee, Young-Hoon Lee, Hae-Sung Nam, Seul-Ki Jeong, Kyeong-Soo Park, So-Yeon Ryu, Hee Nam Kim, Hye-Rim Song, Min-Ho Shin
Korean J Fam Med 2014;35(6):276-282.   Published online November 21, 2014
DOI: https://doi.org/10.4082/kjfm.2014.35.6.276
Background

Few studies have investigated the association between Apolipoprotein E (APOE) polymorphisms and chronic kidney disease (CKD) in the general population, and their results are inconsistent.

Methods

The current study population was composed of 9,033 subjects aged ≥ 50 years who participated in the baseline survey of the Dong-gu Study, which was conducted in Korea between 2007 and 2010. APOE polymorphisms were identified by polymerase chain reaction, and the estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease equation.

Results

Individuals with the APOE E2 allele had significantly lower total and low density lipoprotein cholesterol levels, those with the APOE E4 allele had lower high density lipoprotein (HDL) cholesterol levels, and those with the APOE E3 allele had lower log-triglyceride levels. Adjusting for covariates (sex, age, body mass index, smoking, systolic blood pressure, hypertension, diabetes, total cholesterol, HDL cholesterol, log-transformed triglycerides, and log-transformed albumin to creatinine ratio), mean eGFR was not significantly different among APOE alleles (E2, 69.4 mL/min/1.73 m2; E3, 69.5 mL/min/1.73 m2; E4, 69.4 ml/min/1.73 m2; P = 0.873). Additionally, the odds ratios (ORs) indicated that APOE polymorphisms were not independent risk factors for CKD (OR, 1.07; 95% confidence interval [CI], 0.91 to 1.26 for the E2 vs. E3 allele; OR, 1.01; 95% CI, 0.88 to 1.16 for the E4 vs. E3 allele).

Conclusion

APOE polymorphisms were not associated with either eGFR or CKD in the general Korean population.

Citations

Citations to this article as recorded by  
  • An African perspective on the genetic risk of chronic kidney disease: a systematic review
    Cindy George, Yandiswa Y Yako, Ikechi G Okpechi, Tandi E Matsha, Francois J. Kaze Folefack, Andre P Kengne
    BMC Medical Genetics.2018;[Epub]     CrossRef
  • 64,410 View
  • 21 Download
  • 1 Web of Science
  • 1 Crossref
Comparison of the Framingham Risk Score, UKPDS Risk Engine, and SCORE for Predicting Carotid Atherosclerosis and Peripheral Arterial Disease in Korean Type 2 Diabetic Patients
Hye-Ran Ahn, Min-Ho Shin, Woo-Jun Yun, Hye-Yeon Kim, Young-Hoon Lee, Sun-Seog Kweon, Jung-Ae Rhee, Jin-Su Choi, Seong-Woo Choi
Korean J Fam Med 2011;32(3):189-196.   Published online March 31, 2011
DOI: https://doi.org/10.4082/kjfm.2011.32.3.189
Background

To compare the predictability of the Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study (UKPDS) risk engine, and the Systematic Coronary Risk Evaluation (SCORE) for carotid atherosclerosis and peripheral arterial disease in Korean type 2 diabetic patients.

Methods

Among 1,275 registered type 2 diabetes patients in the health center, 621 subjects with type 2 diabetes participated in the study. Well-trained examiners measured the carotid intima-media thickness (IMT), carotid plaque, and ankle brachial index (ABI). The subject's 10-year risk of coronary heart disease was calculated according to the FRS, UKPDS, and SCORE risk scores. These three risk scores were compared to the areas under the curve (AUC).

Results

The odds ratios (ORs) of all risk scores increased as the quartiles increased for plaque, IMT, and ABI. For plaque and IMT, the UKPDS risk score provided the highest OR (95% confidence interval) at 3.82 (2.36, 6.17) and at 6.21 (3.37, 11.45). For ABI, the SCORE risk estimation provided the highest OR at 7.41 (3.20, 17.18). However, no significant difference was detected for plaque, IMT, or ABI (P = 0.839, 0.313, and 0.113, respectively) when the AUCs of the three risk scores were compared. When we graphed the Kernel density distribution of these three risk scores, UKPDS had a higher distribution than FRS and SCORE.

Conclusion

No significant difference was observed when comparing the predictability of the FRS, UKPDS risk engine, and SCORE risk estimation for carotid atherosclerosis and peripheral arterial disease in Korean type 2 diabetic patients.

Citations

Citations to this article as recorded by  
  • SCORE and SCORE2 in East Asian Population
    JungMin Choi, Soseul Sung, Sue K. Park, Seyong Park, Hyoyeong Kim, Myeong-Chan Cho, Bryan Williams, Hae-Young Lee
    JACC: Asia.2024; 4(4): 265.     CrossRef
  • Predictability of Cardiovascular Risk Scores for Carotid Atherosclerosis in Community-Dwelling Middle-Aged and Elderly Adults
    Chao-Liang Chou, Chun-Chieh Liu, Tzu-Wei Wu, Chun-Fang Cheng, Shu-Xin Lu, Yih-Jer Wu, Li-Yu Wang
    Journal of Clinical Medicine.2024; 13(9): 2563.     CrossRef
  • Determinação da Idade Vascular em Homens Através do Escore de Cálcio Coronariano e seu Impacto na Reestratificação do Risco Cardiovascular
    Ismael Polli, Neide Maria Bruscato, Protasio Lemos Da Luz, Douglas Dal Más Freitas, Angélica Oliveira de Almeida, Waldemar De Carli, Emilio Hideyuki Moriguchi
    Arquivos Brasileiros de Cardiologia.2023;[Epub]     CrossRef
  • Cardiovascular Biomarkers and Calculated Cardiovascular Risk in Orally Treated Type 2 Diabetes Patients: Is There a Link?
    Aleksandra Markova, Mihail Boyanov, Deniz Bakalov, Atanas Kundurdjiev, Adelina Tsakova
    Hormone and Metabolic Research.2021; 53(01): 41.     CrossRef
  • Artificial intelligence framework for predictive cardiovascular and stroke risk assessment models: A narrative review of integrated approaches using carotid ultrasound
    Ankush D. Jamthikar, Deep Gupta, Luca Saba, Narendra N. Khanna, Klaudija Viskovic, Sophie Mavrogeni, John R. Laird, Naveed Sattar, Amer M. Johri, Gyan Pareek, Martin Miner, Petros P. Sfikakis, Athanasios Protogerou, Vijay Viswanathan, Aditya Sharma, Georg
    Computers in Biology and Medicine.2020; 126: 104043.     CrossRef
  • Performance evaluation of 10-year ultrasound image-based stroke/cardiovascular (CV) risk calculator by comparing against ten conventional CV risk calculators: A diabetic study
    Narendra N. Khanna, Ankush D. Jamthikar, Deep Gupta, Andrew Nicolaides, Tadashi Araki, Luca Saba, Elisa Cuadrado-Godia, Aditya Sharma, Tomaz Omerzu, Harman S. Suri, Ajay Gupta, Sophie Mavrogeni, Monika Turk, John R. Laird, Athanasios Protogerou, Petros P.
    Computers in Biology and Medicine.2019; 105: 125.     CrossRef
  • Diabetic retinopathy as an independent predictor of subclinical cardiovascular disease: baseline results of the PRECISED study
    Rafael Simó, Jordi Bañeras, Cristina Hernández, José Rodríguez-Palomares, Filipa Valente, Laura Gutierrez, Teresa González-Alujas, Ignacio Ferreira, Santiago Aguadé-Bruix, Joan Montaner, Daniel Seron, Joan Genescà, Anna Boixadera, José García-Arumí, Aleja
    BMJ Open Diabetes Research & Care.2019; 7(1): e000845.     CrossRef
  • Cardiovascular risk estimated by UKPDS risk engine algorithm in diabetes
    Nebojsa Kavaric, Aleksandra Klisic, Ana Ninic
    Open Medicine.2018; 13(1): 610.     CrossRef
  • Estimation of cardiovascular risk and detection of subclinical carotid atheromatosis in patients with diabetes without a history of cardiovascular disease
    Walter Masson, Salvador De Francesca, Micaela Molinero, Daniel Siniawski, Andrés Mulassi, Frank Espinoza Morales, Melina Huerin, Martín Lobo, Graciela Molinero
    Archives of Endocrinology and Metabolism.2017; 61(2): 122.     CrossRef
  • Perceived and actual risk of cardiovascular disease in patients with rheumatoid arthritis in Korea
    Sunjoo Boo, Erika S. Froelicher, Ju-Hui Yun, Ye-Won Kim, Ju-Yang Jung, Chang-Hee Suh
    Medicine.2016; 95(40): e5117.     CrossRef
  • Impact of carotid atherosclerosis detection on physician and patient behavior in the management of type 2 diabetes mellitus: a prospective, observational, multicenter study
    In-Kyung Jeong, Sin-Gon Kim, Dong Hyeok Cho, Chong Hwa Kim, Chul Sik Kim, Won-Young Lee, Kyu-Chang Won, Doo-Man Kim
    BMC Cardiovascular Disorders.2016;[Epub]     CrossRef
  • 4,716 View
  • 29 Download
  • 11 Crossref
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