Diabetes & Metabolism Journal

Original Articles

Metabolic Risk/Epidemiology
Intra-Abdominal Fat and High Density Lipoprotein Cholesterol Are Associated in a Non-Linear Pattern in Japanese-Americans: Sun Ok Song, You-Cheol Hwang, Steven E. Kahn, Donna L. Leonetti, Wilfred Y. Fujimoto, Edward J. Boyko; Diabetes Metab J. 2020;44(2):277-285. Published online March 10, 2020; DOI: https://doi.org/10.4093/dmj.2019.0008

4,656 View
63 Download
3 Web of Science
4 Crossref

Background

We describe the association between high density lipoprotein cholesterol (HDL-C) concentration and computed tomography (CT)-measured fat depots.

Methods

We examined the cross-sectional associations between HDL-C concentration and intra-abdominal (IAF), abdominal subcutaneous (SCF), and thigh fat (TF) areas in 641 Japanese-American men and women. IAF, SCF, and TF were measured by CT at the level of the umbilicus and mid-thigh. The associations between fat area measurements and HDL-C were examined using multivariate linear regression analysis adjusting for age, sex, diabetes family history, homeostasis model assessment of insulin resistance (HOMA-IR), and body mass index (BMI). Non-linearity was assessed using fractional polynomials.

Results

Mean±standard deviation of HDL-C concentration and IAF in men and women were 1.30±0.34 mg/dL, 105±55.3 cm², and 1.67±0.43 mg/dL, 74.4±46.6 cm² and differed significantly by gender for both comparisons (P<0.001). In univariate analysis, HDL-C concentration was significantly associated with CT-measured fat depots. In multivariate analysis, IAF was significantly and non-linearly associated with HDL-C concentration adjusted for age, sex, BMI, HOMA-IR, SCF, and TF (IAF: β=−0.1012, P<0.001; IAF²: β=0.0008, P<0.001). SCF was also negatively and linearly associated with HDL-C (β=−0.4919, P=0.001).

Conclusion

HDL-C does not linearly decline with increasing IAF in Japanese-Americans. A more complex pattern better fits this association.

Citations

Citations to this article as recorded by

Associations of Serum Uric Acid to High-Density Lipoprotein Cholesterol Ratio with Trunk Fat Mass and Visceral Fat Accumulation
Yansu Wang, Yiting Xu, Tingting Hu, Yunfeng Xiao, Yufei Wang, Xiaojing Ma, Haoyong Yu, Yuqian Bao
Diabetes, Metabolic Syndrome and Obesity.2024; Volume 17: 121. CrossRef
Obesity-related parameters in carriers of some BDNF genetic variants may depend on daily dietary macronutrients intake
Urszula Miksza, Edyta Adamska-Patruno, Witold Bauer, Joanna Fiedorczuk, Przemyslaw Czajkowski, Monika Moroz, Krzysztof Drygalski, Andrzej Ustymowicz, Elwira Tomkiewicz, Maria Gorska, Adam Kretowski
Scientific Reports.2023;[Epub] CrossRef
Computed tomography-based investigation of the correlation of abdominal fat areas with metabolic syndrome
Kai-Yuan Cheng, Tsung-Hsien Yen, Jay Wu, Pei-Hsuan Li, Tian-Yu Shih
Journal of Radiological Science.2023; 48(1): 15. CrossRef
Lower High-Density Lipoprotein Cholesterol Concentration Is Independently Associated with Greater Future Accumulation of Intra-Abdominal Fat
Sun Ok Song, You-Cheol Hwang, Han Uk Ryu, Steven E. Kahn, Donna L. Leonetti, Wilfred Y. Fujimoto, Edward J. Boyko
Endocrinology and Metabolism.2021; 36(4): 835. CrossRef

Obesity and Metabolic Syndrome
Higher High Density Lipoprotein 2 (HDL2) to Total HDL Cholesterol Ratio Is Associated with a Lower Risk for Incident Hypertension: You-Cheol Hwang, Wilfred Y. Fujimoto, Steven E. Kahn, Donna L. Leonetti, Edward J. Boyko; Diabetes Metab J. 2019;43(1):114-122. Published online September 28, 2018; DOI: https://doi.org/10.4093/dmj.2018.0053

4,221 View
46 Download
6 Web of Science
10 Crossref

Abstract PDF PubReader

Background

Recent studies have suggested that high density lipoprotein (HDL) cholesterol is inversely associated with the development of hypertension. We aimed to determine the association between different HDL cholesterol subclasses and risk of future hypertension.

Methods

A total of 270 Japanese Americans (130 men, 140 women) without hypertension between the ages of 34 to 75 years were enrolled. Blood pressure was measured with a mercury sphygmomanometer, and average blood pressure was calculated. Incident hypertension was determined 5 to 6 and 10 to 11 years after enrollment. HDL2, HDL3, and total HDL cholesterol were measured at baseline.

Results

During 10 years of follow-up, the cumulative incidence of hypertension was 28.1% (76/270). In univariate analysis, age, diabetes, waist circumference, systolic and diastolic blood pressure, fasting glucose, insulin resistance index, total and low density lipoprotein cholesterol, and visceral adipose tissue were significant predictors for incident hypertension. Among the HDL cholesterol subclass, HDL2 cholesterol was inversely associated with hypertension incidence, but both total and HDL3 cholesterol were not. In addition, HDL2/HDL cholesterol was inversely associated with future hypertension risk. In multivariate analysis, age (odds ratio [OR], 1.71; 95% confidence interval [CI], 1.26 to 2.31; P=0.001), systolic blood pressure (OR, 1.83; 95% CI, 1.31 to 2.56; P<0.001), and HDL2/HDL cholesterol (OR, 0.71; 95% CI, 0.52 to 0.98; P=0.035), were associated with future development of hypertension.

Conclusion

A higher proportion of HDL2 cholesterol among total HDL cholesterol predicted a lower risk for incident hypertension. However, concentrations of total HDL, HDL2, and HDL3 cholesterol were not independent predictors of incident hypertension.

Citations

Citations to this article as recorded by

The Association of HDL2b with Metabolic Syndrome Among Normal HDL-C Populations in Southern China
Tong Chen, Shiquan Wu, Ling Feng, SiYu Long, Yu Liu, WenQian Lu, Wenya Chen, Guoai Hong, Li Zhou, Fang Wang, Yuechan Luo, Hequn Zou
Diabetes, Metabolic Syndrome and Obesity.2024; Volume 17: 363. CrossRef
Long-term PM1 exposure and hypertension hospitalization: A causal inference study on a large community-based cohort in South China
Yuqin Zhang, Shirui Chen, Jing Wei, Jie Jiang, Xiao Lin, Ying Wang, Chun Hao, Wenjing Wu, Zhupei Yuan, Jie Sun, Han Wang, Zhicheng Du, Wangjian Zhang, Yuantao Hao
Science Bulletin.2024;[Epub] CrossRef
High-Density Lipoprotein Signaling via Sphingosine-1-Phosphate Receptors Safeguards Spontaneously Hypertensive Rats against Myocardial Ischemia/Reperfusion Injury
Aishah Al-Jarallah, Fawzi A. Babiker
Pharmaceutics.2024; 16(4): 497. CrossRef
Effects of cardiometabolic risk factors on blood pressure in outpatients at Sominé DOLO hospital, Mopti, Mali
Modibo Coulibaly, Adama Kondé, Djibril Traoré, Ousmane Bah, Valentin Sagara, Bakary Maiga
International Journal of Clinical Biochemistry and Research.2023; 10(1): 87. CrossRef
The association of lipid metabolism with bone metabolism and the role of human traits: a Mendelian randomization study
Jian Kang, Shuangli Zhao, Xize Wu, Can Wang, Zongkun Jiang, Shixuan Wang
Frontiers in Endocrinology.2023;[Epub] CrossRef
The role of different lipid measures for incident hypertension during more than 12-year follow-up: Tehran Lipid and Glucose Study
Amirreza Hadaegh, Samaneh Akbarpour, Maryam Tohidi, Niloofar Barzegar, Somayeh Hosseinpour-Niazi, Fereidoun Azizi, Farzad Hadaegh
British Journal of Nutrition.2022; 128(9): 1700. CrossRef
High Density Lipoprotein Reduces Blood Pressure and Protects Spontaneously Hypertensive Rats Against Myocardial Ischemia-Reperfusion Injury in an SR-BI Dependent Manner
Aishah Al-Jarallah, Fawzi Babiker
Frontiers in Cardiovascular Medicine.2022;[Epub] CrossRef
Association between the Uric Acid to High Density Lipoprotein Cholesterol Ratio and Systolic Pressure in Chinese Short Stature Children and Adolescents
广欣李
Advances in Clinical Medicine.2022; 12(09): 8266. CrossRef
Associations Between Peripheral Blood Microbiome and the Risk of Hypertension
Yang Jing, Hui Zhou, Honghong Lu, Xiaofang Chen, Liangyue Zhou, Jingqi Zhang, Jing Wu, Chen Dong
American Journal of Hypertension.2021; 34(10): 1064. CrossRef
How was the Diabetes Metabolism Journal added to MEDLINE?
Hye Jin Yoo
Science Editing.2020; 7(2): 201. CrossRef

Complications
Risk Factors for the Development and Progression of Diabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus and Advanced Diabetic Retinopathy: Kyung-Jin Yun, Hye Ji Kim, Mee Kyoung Kim, Hyuk-Sang Kwon, Ki-Hyun Baek, Young Jung Roh, Ki-Ho Song; Diabetes Metab J. 2016;40(6):473-481. Published online September 20, 2016; DOI: https://doi.org/10.4093/dmj.2016.40.6.473

4,403 View
44 Download
25 Web of Science
26 Crossref

Abstract PDF PubReader

Background

Some patients with type 2 diabetes mellitus (T2DM) do not develop diabetic kidney disease (DKD) despite the presence of advanced diabetic retinopathy (DR). We aimed to investigate the presence of DKD and its risk factors in patients with T2DM and advanced DR.

Methods

We conducted a cross-sectional study in 317 patients with T2DM and advanced DR. The phenotypes of DKD were divided into three groups according to the urine albumin/creatinine ratio (uACR, mg/g) and estimated glomerular filtration rate (eGFR, mL/min/1.73 m²): no DKD (uACR <30 and eGFR ≥60), non-severe DKD (uACR ≥30 or eGFR <60), and severe DKD (uACR ≥30 and eGFR <60). Mean systolic and diastolic blood pressure, mean glycosylated hemoglobin (HbA1c) level, and HbA1c variability (standard deviation [SD] of serial HbA1c values or HbA1c-SD) were calculated for the preceding 2 years.

Results

The prevalence of no DKD, non-severe DKD, and severe DKD was 37.2% (n=118), 37.0% (n=117), and 25.8% (n=82), respectively. HbA1c-SD and the triglyceride/high density lipoprotein cholesterol (TG/HDL-C) ratio correlated positively with uACR and negatively with eGFR. Multiple linear regression analyses showed that the HbA1c-SD and TG/HDL-C ratio were significantly related with eGFR. Multiple logistic regression analyses after adjusting for several risk factors showed that HbA1c-SD and the TG/HDL-C ratio were significant risk factors for severe DKD.

Conclusion

The prevalence of DKD was about 60% in patients with T2DM and advanced DR. HbA1c variability and TG/HDL-C ratio may affect the development and progression of DKD in these patients.

Citations

Citations to this article as recorded by

Ocular and Systemic Risk Factors for Disease Worsening Among Patients with NPDR
Charles C. Wykoff, Diana V. Do, Roger A. Goldberg, Dilsher S. Dhoot, Jennifer I. Lim, Weiming Du, Fabiana Q. Silva, Rutvi Desai, Hadi Moini, Kimberly Reed, Alyson J. Berliner, Robert Vitti, W. Lloyd Clark
Ophthalmology Retina.2024; 8(4): 399. CrossRef
Interpretable prediction model for assessing diabetes complication risks in Chinese sufferers
Ye Shiren, Ye Jiangnan, Ye Xinhua, Ni Xinye
Diabetes Research and Clinical Practice.2024; 209: 111560. CrossRef
Dose-response association of diabetic kidney disease with routine clinical parameters in patients with type 2 diabetes mellitus: a systematic review and meta-analysis
Jianbo Guo, Chen Liu, Yifan Wang, Baoyi Shao, Tung Leong Fong, Ngai Chung Lau, Hui Zhang, Haidi Li, Jianan Wang, Xinyu Lu, Anqi Wang, Cheuk Lung Leung, Xin Wei Chia, Fei Li, Xiaoming Meng, Qingyong He, Haiyong Chen
eClinicalMedicine.2024; 69: 102482. CrossRef
Sex-Specific Computed Tomography Abdominal Fat and Skeletal Muscle Characteristics in Type 2 Diabetic Retinopathy Patients With/Without Comorbid Diabetic Kidney Disease
Jinlei Fan, Liping Zuo, Mingyuan Hou, Bowen Wang, Yueming An, Baoli Hao, Dexin Yu
Academic Radiology.2023; 30(11): 2686. CrossRef
The concordance and discordance of diabetic kidney disease and retinopathy in patients with type 2 diabetes mellitus: A cross-sectional study of 26,809 patients from 5 primary hospitals in China
Zhaoxiang Liu, Xianglan Li, Yanlei Wang, Yanxia Song, Qiang Liu, Junxia Gong, Wenshuang Fan, Chunmei Lv, Chenxiang Cao, Wenhui Zhao, Jianzhong Xiao
Frontiers in Endocrinology.2023;[Epub] CrossRef
Ferroptosis: new insight into the mechanisms of diabetic nephropathy and retinopathy
Luxin Li, Yucen Dai, Dan Ke, Jieting Liu, Peijian Chen, Dong Wei, Tongtong Wang, Yanjie Teng, Xiaohuan Yuan, Zhen Zhang
Frontiers in Endocrinology.2023;[Epub] CrossRef
Predicting diabetic kidney disease for type 2 diabetes mellitus by machine learning in the real world: a multicenter retrospective study
Xiao zhu Liu, Minjie Duan, Hao dong Huang, Yang Zhang, Tian yu Xiang, Wu ceng Niu, Bei Zhou, Hao lin Wang, Ting ting Zhang
Frontiers in Endocrinology.2023;[Epub] CrossRef
Developing screening tools to estimate the risk of diabetic kidney disease in patients with type 2 diabetes mellitus
Xu Cao, Xiaomei Pei
Technology and Health Care.2023; : 1. CrossRef
Association between serum complements and kidney function in patients with diabetic kidney disease
Meng-chao Liu, Jia-lin Li, Yue-fen Wang, Yuan Meng, Gui-min Zheng, Zhen Cai, Cun Shen, Meng-di Wang, Xiang-gang Zhu, Yang-zi Chen, Yu-lin Wang, Wen-jing Zhao, Wen-quan Niu, Yao-xian Wang
Frontiers in Endocrinology.2023;[Epub] CrossRef
Coagulation Function and Type 2 Diabetic Kidney Disease: A Real-World Observational Study
Meng-chao Liu, Wen-quan Niu, Yue-fen Wang, Yuan Meng, Gui-min Zheng, Zhen Cai, Cun Shen, Xiang-gang Zhu, Meng-di Wang, Jia-lin Li, Wen-jing Zhao, Yao-xian Wang, Eusebio Chiefari
Journal of Diabetes Research.2023; 2023: 1. CrossRef
Punicalagin alleviates renal injury via the gut-kidney axis in high-fat diet-induced diabetic mice
Qinglian Hua, Yaling Han, Haifeng Zhao, Haowen Zhang, Bei Yan, Shengjie Pei, Xin He, Yue Li, Xiangyuan Meng, Lei Chen, Feng Zhong, Duo Li
Food & Function.2022; 13(2): 867. CrossRef
Status and Trends of the Association Between Diabetic Nephropathy and Diabetic Retinopathy From 2000 to 2021: Bibliometric and Visual Analysis
Wenwen Lin, Yayong Luo, Fang Liu, Hangtian Li, Qian Wang, Zheyi Dong, Xiangmei Chen
Frontiers in Pharmacology.2022;[Epub] CrossRef
The Risk Threshold for Hemoglobin A1c Associated With Albuminuria: A Population-Based Study in China
Hong Lian, Hongshi Wu, Jie Ning, Diaozhu Lin, Chulin Huang, Feng Li, Ying Liang, Yiqin Qi, Meng Ren, Li Yan, Lili You, Mingtong Xu
Frontiers in Endocrinology.2021;[Epub] CrossRef
Weight change and microvascular outcomes in patients with new-onset diabetes: a nationwide cohort study
Eun Sil Koh, Kyung Do Han, Mee Kyoung Kim, Eun Sook Kim, Min-Kyung Lee, Ga Eun Nam, Hyuk-Sang Kwon
The Korean Journal of Internal Medicine.2021; 36(4): 932. CrossRef
Albuminuria Is Associated with Steatosis Burden in Patients with Type 2 Diabetes Mellitus and Nonalcoholic Fatty Liver Disease
Eugene Han, Mi Kyung Kim, Byoung Kuk Jang, Hye Soon Kim
Diabetes & Metabolism Journal.2021; 45(5): 698. CrossRef
Effect of Calcium Dobesilate in Preventing Contrast-Induced Nephropathy in Patients with Diabetes and Chronic Kidney Disease
Hao Zhang, Shao-Hua Guo, Zheng-Kai Xue, Ya-Ru Zhang, Jia-Rui Wang, Jing-Jin Che, Tong Liu, Hua-Yue Tao, Guang-Ping Li, Seung-Woon Rha, Swapnil-Zaman Ashraful-Haque, Kang-Yin Chen
Clinics.2021; 76: e2942. CrossRef
Elevated TG/HDL-C and non-HDL-C/HDL-C ratios predict mortality in peritoneal dialysis patients
Wenkai Xia, Xiajuan Yao, Yan Chen, Jie Lin, Volker Vielhauer, Hong Hu
BMC Nephrology.2020;[Epub] CrossRef
Thermal Perception Abnormalities Can Predict Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients
Wei-Ching Fang, Kuei-Mei Chou, Chiao-Yin Sun, Chin-Chan Lee, I-Wen Wu, Yung-Chang Chen, Heng-Chih Pan
Kidney and Blood Pressure Research.2020; 45(6): 926. CrossRef
Association between nonalbumin proteinuria and renal tubular damage of N-acetyl-β-d-glucosaminidase and its clinical relevance in patients with type 2 diabetes without albuminuria
Eugene Han, Mi-Kyung Kim, Yong-ho Lee, Hye Soon Kim, Byung-Wan Lee
Journal of Diabetes and its Complications.2019; 33(3): 255. CrossRef
Detection of Lower Albuminuria Levels and Early Development of Diabetic Kidney Disease Using an Artificial Intelligence-Based Rule Extraction Approach
Yoichi Hayashi
Diagnostics.2019; 9(4): 133. CrossRef
Therapeutic effect of liraglutide on expression of CTGF and BMP‐7 in induced diabetic nephropathy
Maggie M. Ramzy, Ahlam M. Abdalla, Nagwa M. Zenhom, Ahmed M. Okasha, Aya E. Abdelkafy, Rabeh K. Saleh
Journal of Cellular Biochemistry.2019; 120(10): 17512. CrossRef
Are blood lipids associated with microvascular complications among type 2 diabetes mellitus patients? A cross-sectional study in Shanghai, China
Hua Yang, Doris Young, Jian Gao, Yuanzhi Yuan, Minqian Shen, Yuan Zhang, Xueyan Duan, Shanzhu Zhu, Xiaoming Sun
Lipids in Health and Disease.2019;[Epub] CrossRef
Discordance in risk factors for the progression of diabetic retinopathy and diabetic nephropathy in patients with type 2 diabetes mellitus
Ki‐Ho Song, Jee‐Sun Jeong, Mee Kyoung Kim, Hyuk‐Sang Kwon, Ki‐Hyun Baek, Seung‐Hyun Ko, Yu‐Bae Ahn
Journal of Diabetes Investigation.2019; 10(3): 745. CrossRef
Risk factors for the development of micro-vascular complications of type 2 diabetes in a single-centre cohort of patients
Marsida Teliti, Giulia Cogni, Lucia Sacchi, Arianna Dagliati, Simone Marini, Valentina Tibollo, Pasquale De Cata, Riccardo Bellazzi, Luca Chiovato
Diabetes and Vascular Disease Research.2018; 15(5): 424. CrossRef
Higher Prevalence and Progression Rate of Chronic Kidney Disease in Elderly Patients with Type 2 Diabetes Mellitus
Kyung-Soo Kim, Seok Won Park, Yong-Wook Cho, Soo-Kyung Kim
Diabetes & Metabolism Journal.2018; 42(3): 224. CrossRef
Determinants of the Risk of Diabetic Kidney Disease and Diabetic Retinopathy Independent of Glucose Exposure
Bo Kyung Koo
Diabetes & Metabolism Journal.2016; 40(6): 444. CrossRef

Impact of Serum Triglyceride and High Density Lipoprotein Cholesterol Levels on Early-Phase Insulin Secretion in Normoglycemic and Prediabetic Subjects: Masanori Shimodaira, Tomohiro Niwa, Koji Nakajima, Mutsuhiro Kobayashi, Norinao Hanyu, Tomohiro Nakayama; Diabetes Metab J. 2014;38(4):294-301. Published online August 20, 2014; DOI: https://doi.org/10.4093/dmj.2014.38.4.294

3,205 View
28 Download
15 Web of Science
14 Crossref

Abstract PDF PubReader

Background

Increased triglycerides (TGs) and decreased high density lipoprotein cholesterol (HDL-C) levels are established as diabetic risks for nondiabetic subjects. The aim of this study was to investigate the relationship among TG, HDL-C, TG/HDL-C ratio, and early-phase insulin secretion in normoglycemic and prediabetic subjects.

Methods

We evaluated 663 Japanese subjects who underwent the 75-g oral glucose tolerance test. On the basis of these results, the subjects were divided into four groups: those with normal glucose tolerance (NGT; n=341), isolated impaired fasting glucose (i-IFG; n=211), isolated impaired glucose tolerance (i-IGT; n=71), and combined IFG and IGT (IFG+IGT; n=40). Insulin secretion was estimated by the insulinogenic index (IGI) (Δinsulin/Δglucose [30 to 0 minutes]) and disposition index (DI) (IGI/homeostasis model assessment of insulin resistance).

Results

In prediabetic subjects (i-IFG, i-IGT, and IFG+IGT), linear regression analyses revealed that IGI and DI were positively correlated with HDL-C levels. Moreover, in subjects with i-IGT and (IFG+IGT), but not with i-IFG, the indices of insulin secretion were negatively correlated with the log-transformed TG and TG/HDL-C ratio. In both the subjects with i-IGT, multivariate linear regression analyses revealed that DI was positively correlated with HDL-C and negatively with log-transformed TG and TG/HDL-C ratio. On the other hand, in subjects with NGT, there was no association between insulin secretion and lipid profiles.

Conclusion

These results revealed that serum TG and HDL-C levels have different impacts on early-phase insulin secretion on the basis of their glucose tolerance status.

Citations

Citations to this article as recorded by

The protective effects of lipoxin A4 on type 2 diabetes mellitus: A Chinese prospective cohort study
Sudan Wang, Xiaoyan Qian, Chao Shen, Qian Sun, Yang Jing, Bingyue Liu, Kexin Zhang, Mengyuan Li, Junrong Wang, Hui Zhou, Chen Dong
Frontiers in Endocrinology.2023;[Epub] CrossRef
Interaction between the GCKR rs1260326 variant and serum HDL cholesterol contributes to HOMA-β and ISIMatusda in the middle-aged T2D individuals
Min Shen, Liying Jiang, Hechun Liu, Hao Dai, Hemin Jiang, Yu Qian, Zhixiao Wang, Shuai Zheng, Heng Chen, Tao Yang, Qi Fu, Kuanfeng Xu
Journal of Human Genetics.2023; 68(12): 835. CrossRef
Elevated triglyceride/high-density lipoprotein-cholesterol ratio as a risk factor for progression to prediabetes: a 5-year retrospective cohort study in Japan
Masanori Shimodaira, Yu Minemura, Tomohiro Nakayama
Journal of Diabetes & Metabolic Disorders.2023;[Epub] CrossRef
Association ofTG/HDLCratio trajectory and risk of type 2 diabetes: A retrospective cohort study inChina
Yanyan Zhang, Pei Qin, Yanmei Lou, Ping Zhao, Xue Li, Ranran Qie, Xiaoyan Wu, Minghui Han, Shengbing Huang, Yang Zhao, Dechen Liu, Yuying Wu, Yang Li, Xingjin Yang, Yang Zhao, Yifei Feng, Changyi Wang, Jianping Ma, Xiaolin Peng, Hongen Chen, Dan Zhao, Sha
Journal of Diabetes.2021; 13(5): 402. CrossRef
Triglycerides/high-density lipoprotein cholesterol is a predictor similar to the triglyceride–glucose index for the diagnosis of metabolic syndrome using International Diabetes Federation criteria of insulin resistance in obese adolescents: a cross-sectio
Nazlı Nur Aslan Çin, Hülya Yardımcı, Nevra Koç, Seyit Ahmet Uçaktürk, Mehtap Akçil Ok
Journal of Pediatric Endocrinology and Metabolism.2020; 33(6): 777. CrossRef
Comparison of Serum PCSK9 Levels in Subjects with Normoglycemia, Impaired Fasting Glucose, and Impaired Glucose Tolerance
Eugene Han, Nan Hee Cho, Seong-Su Moon, Hochan Cho
Endocrinology and Metabolism.2020; 35(2): 480. CrossRef
Triglycerides/glucose index is a useful surrogate marker of insulin resistance among adolescents
B Kang, Y Yang, E Y Lee, H K Yang, H-S Kim, S-Y Lim, J-H Lee, S-S Lee, B-K Suh, K-H Yoon
International Journal of Obesity.2017; 41(5): 789. CrossRef
The TyG index may predict the development of cardiovascular events
Laura Sánchez‐Íñigo, David Navarro‐González, Alejandro Fernández‐Montero, Juan Pastrana‐Delgado, Jose Alfredo Martínez
European Journal of Clinical Investigation.2016; 46(2): 189. CrossRef
TyG Index Change Is More Determinant for Forecasting Type 2 Diabetes Onset Than Weight Gain
David Navarro-González, Laura Sánchez-Íñigo, Alejandro Fernández-Montero, Juan Pastrana-Delgado, Jose Alfredo Martinez
Medicine.2016; 95(19): e3646. CrossRef
Comparative analysis of the efficacy of omega-3 fatty acids for hypertriglyceridaemia management in Korea
H.-S. Kim, H. Kim, Y. J. Jeong, S. J. Yang, S. J. Baik, H. Lee, S.-H. Lee, J. H. Cho, I.-Y. Choi, H. W. Yim, K.-H. Yoon
Journal of Clinical Pharmacy and Therapeutics.2016; 41(5): 508. CrossRef
Relationship between insulin sensitivity and insulin secretion rate: not necessarily hyperbolic
S. H. Kim, A. Silvers, J. Viren, G. M. Reaven
Diabetic Medicine.2016; 33(7): 961. CrossRef
The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio as a predictor of insulin resistance but not of β cell function in a Chinese population with different glucose tolerance status
Meicen Zhou, Lixin Zhu, Xiangli Cui, Linbo Feng, Xuefeng Zhao, Shuli He, Fan Ping, Wei Li, Yuxiu Li
Lipids in Health and Disease.2016;[Epub] CrossRef
Interactive effects of C-reactive protein levels on the association between APOE variants and triglyceride levels in a Taiwanese population
Semon Wu, Lung-An Hsu, Ming-Sheng Teng, Jeng-Feng Lin, Hsin-Hua Chou, Ming-Cheng Lee, Yi-Ming Wu, Cheng-Wen Su, Yu-Lin Ko
Lipids in Health and Disease.2016;[Epub] CrossRef
Lipoproteins and β-Cell Functions: From Basic to Clinical Data
Dae Ho Lee
Diabetes & Metabolism Journal.2014; 38(4): 274. CrossRef

First
Prev
Page of 1
Next
Last

Search