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Nnamudi AC, Orhue NJ, Ijeh II, Nwabueze AN. Finnish diabetes risk score outperformed triglyceride-glucose index in diabetes risk prediction. J Diabetes Metab Disord 2023; 22:1337-1345. [PMID: 37975096 PMCID: PMC10638212 DOI: 10.1007/s40200-023-01252-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 06/13/2023] [Indexed: 11/19/2023]
Abstract
Purpose Triglyceride-Glucose (TyG) index is a surrogate marker of insulin resistance. This study compared the performance of TyG index and the Finnish diabetes risk score (FINDRISC) in diabetes risk prediction. Methods This cross-sectional study involved 122 young adults (aged 15-35 years) in Asaba, Delta State, Nigeria. Anthropometric measurements and biochemical analysis were done following standard protocols. Diabetes risk scoring was done using the FINDRISC questionnaire. TyG index was calculated logarithmically. Discrimination between TyG index and FINDRISC was done by plotting receiver operating characteristic (ROC) curves. Results High risk participants had significantly (p < 0.001) higher mean values of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) relative to the lower risk categories. Participants in TyG index Quartile 4 had significantly higher mean values of triglyceride (p < 0.001) and fasting plasma glucose (p < 0.05). BMI and triglyceride had the most significant (p < 0.001) positive correlation with FINDRISC and TyG index, respectively. A moderately elevated to high risk (FINDRISC ≥ 12) of developing diabetes was found in 14.8% of the participants; with a female preponderance (20.6%) relative to males (7.4%). More than half of the participants (52.5%) had slightly elevated risk and differences in diabetes risk susceptibility were significant (p < 0.001) across gender. FINDRISC had an AUC value of 0.826 while TyG index had an AUC value of 0.628 for diabetes risk prediction. Conclusion FINDRISC had a better performance than TyG index in the prediction of diabetes risk in this population. The use of other TyG-related parameters rather than TyG index is recommended in future studies. Supplementary Information The online version contains supplementary material available at 10.1007/s40200-023-01252-y.
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Affiliation(s)
- Anthony Chibuzor Nnamudi
- Department of Biochemistry, Faculty of Basic Medical Sciences, PAMO University of Medical Sciences, Port Harcourt, Nigeria
| | - Noghayin Jerry Orhue
- Department of Biochemistry, Faculty of Life Sciences, University of Benin, Benin City, Nigeria
| | - Ifeoma Irene Ijeh
- Department of Biochemistry, College of Natural and Applied Sciences, Michael Okpara University of Agriculture, Umudike, Nigeria
| | - Amarachi Nene Nwabueze
- African Centre of Excellence in Public Health and Toxicological Research (ACE-PUTOR), University of Port Harcourt, Port Harcourt, Nigeria
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Xing Y, Liu J, Gao Y, Zhu Y, Zhang Y, Ma H. Stronger Associations of TyG Index with Diabetes Than TyG-Obesity-Related Parameters: More Pronounced in Young, Middle-Aged, and Women. Diabetes Metab Syndr Obes 2023; 16:3795-3805. [PMID: 38028992 PMCID: PMC10676865 DOI: 10.2147/dmso.s433493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 11/07/2023] [Indexed: 12/01/2023] Open
Abstract
Purpose The triglyceride glucose (TyG) index and TyG-related indicators have been proposed as a marker of insulin resistance. It is unclear which is the best indicator to predict diabetes mellitus (DM) in Chinese. This study aimed to investigate the predictive value of different biomarkers for the incidence of DM. Patients and methods Between January 2017 and December 2020, 5575 subjects who underwent health examinations in Hebei General Hospital were retrospectively included. The primary endpoint was new onset DM. Results During a median follow-up of 3.03 years, 133(2.39%) individuals developed DM. Multivariable cox proportional hazards models revealed that TyG index and TyG-related parameters were positively associated with DM risk. As the interaction analyses showed, there were significant interactions with sex and age levels in relation to DM risk (both P for interaction <0.05). Risk prediction for DM was significantly improved by adding TyG index to the baseline model using conventional diabetic risk factors in predicting DM at follow-up. Conclusion This population-based cohort study suggested a causal relationship between TyG index and DM after adjusting for other confounding factors. This independent and significant association was more apparent in females and subjects younger than 65 years. Compared with the TyG-BMI, TyG-WC, TyG-WHtR, the TyG index was a more effective predictor of DM.
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Affiliation(s)
- Yuling Xing
- Department of Endocrinology, Hebei General Hospital, Shijiazhuang, People’s Republic of China
| | - Jing Liu
- Department of Endocrinology, Hebei General Hospital, Shijiazhuang, People’s Republic of China
| | - Yu Gao
- Department of Endocrinology, Affiliated Hospital of Chengde Medical University, Chengde, People’s Republic of China
| | - Yajun Zhu
- Department of Endocrinology, Hebei General Hospital, Shijiazhuang, People’s Republic of China
| | - Yunjia Zhang
- Department of Endocrinology, Hebei General Hospital, Shijiazhuang, People’s Republic of China
| | - Huijuan Ma
- Department of Endocrinology, The First Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China
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Fu X, Liu H, Liu J, Li N, Li L, Ke D, Liu M, Lu Y, Duan L, Ma L, Huo Y, Lei Q, Yan S. Association Between Triglyceride-Glucose Index and the Risk of Type 2 Diabetes Mellitus in an Older Chinese Population Aged Over 75 Years. Front Public Health 2022; 9:796663. [PMID: 35399348 PMCID: PMC8989963 DOI: 10.3389/fpubh.2021.796663] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 12/14/2021] [Indexed: 01/19/2023] Open
Abstract
Background The association between the triglyceride–glucose (TyG) index and type 2 diabetes mellitus (T2DM) in older adults has not been fully understood. This research aims to explore the association between the TyG index and the incidence of T2DM in an older Chinese population aged over 75 years. Methods This longitudinal analysis study was performed based on a database from a health check screening program in China. The participants were stratified based on the quintile ranges of the TyG index (Q1 to Q5 groups). T2DM was defined as fasting plasma glucose (FPG) ≥ 7.00 mmol/L and/or self-reported T2DM. The cumulative incidences of T2DM in various quintile groups were estimated by the Kaplan–Meier method. The Cox proportional hazard model was used to examine the independent impact of the TyG index on the risk of T2DM during the follow-up period. Subgroup analysis was performed by gender and BMI to further validate the credibility of the results. Results During the follow-up period, a total of 231 new-onset T2DM cases were recorded among the 2,571 individuals aged over 75 years. After adjusting confounding factors, elevated TyG index independently indicated a higher risk of T2DM (HR = 1.89; 95% CI, 1.47–2.44; p < 0.01). Higher TyG index quintile groups (Q3 to Q5) also presented with a higher risk of T2DM (hazard ratio (HR) = 1.36, 1.44, and 2.12, respectively) as compared with the lowest quintile group (Q1). Subgroup analysis showed that increased TyG index led to a higher risk of T2DM with HR = 2.35 (95% CI, 1.73–3.19), 1.90 (95% CI, 1.27–2.83), 2.95 (95% CI, 1.94–4.50), and 1.72 (95% CI, 1.25–2.35) in male subgroup, female subgroup, BMI < 24 kg/m2 subgroup, and BMI ≥ 24 kg/m2 subgroup, respectively. Conclusions Triglyceride–glucose index independently correlated with the risk of incident T2DM in Chinese adults aged over 75 years. The TyG index might be useful in monitoring T2DM in the older populations.
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Affiliation(s)
- Xiaomin Fu
- Department of Endocrinology, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Hongzhou Liu
- Department of Endocrinology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.,Department of Endocrinology, First Hospital of Handan City, Handan, China
| | - Jing Liu
- Clinics of Cadre, Department of Outpatient, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Nan Li
- Department of Endocrinology, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Lele Li
- Department of Endocrinology, Genetics, Metabolism and Adolescent Medicine, National Center for Children's Health, Beijing Children's Hospital, The Capital Medical University, Beijing, China
| | - Dianshan Ke
- Department of Orthopedics, Fujian Provincial Hospital, Fuzhou, China
| | - Minyan Liu
- Department of Endocrinology, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Yanhui Lu
- Department of Endocrinology, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Lihua Duan
- Department of Ultrasound Medicine, Handan Central Hospital, Handan, China
| | - Linlin Ma
- General Surgery Department 5, Handan Central Hospital, Handan, China
| | - Yanfei Huo
- Physical Examination Center, Handan Central Hospital, Handan, China
| | - Qinghua Lei
- Physical Examination Center, Handan Central Hospital, Handan, China
| | - Shuangtong Yan
- Department of Endocrinology, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
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Ke P, Wu X, Xu M, Feng J, Xu H, Gan Y, Wang C, Deng Z, Liu X, Fu W, Tian Q, He Y, Zhong L, Jiang H, Lu Z. Comparison of obesity indices and triglyceride glucose-related parameters to predict type 2 diabetes mellitus among normal-weight elderly in China. Eat Weight Disord 2022; 27:1181-1191. [PMID: 34195936 DOI: 10.1007/s40519-021-01238-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 06/01/2021] [Indexed: 12/16/2022] Open
Abstract
PURPOSE Although a significant proportion of type 2 diabetes mellitus (T2DM) cases arose from normal-weight individuals, studies on indicators of T2DM in normal-weight people are limited. Accordingly, this study aims to investigate the predictive value of obesity indices and triglyceride glucose-related parameters (TyG-related parameters) in T2DM among normal-weight Chinese elderly. METHODS A total of 24,215 normal-weight Chinese elderly (age ≥ 60 years) [body mass index-BMI (18.5-23.9 kg/m2)] were included. Obesity indices and triglyceride glucose-related parameters (TyG-related parameters) included waist circumference (WC), waist-to-height ratio (WHtR), visceral adiposity index (VAI), lipid accumulation product (LAP), and TyG-related parameters (TyG, TyG-BMI, TyG-WC, and TyG-WHtR). Multivariate logistic regression analysis was performed to examine the associations between obesity- and TyG-related indices and T2DM. The areas under the curve (AUC) of the receiver-operating characteristic (ROC) curve analyses were used to evaluate and compare the predictive value of the different indices. RESULTS The prevalence of T2DM was 14.2% in normal-weight individuals. Among the indices, TyG was significantly associated with T2DM among men and women, respectively, (adjusted odds ratio-aOR per SD 3.46; 95% CI 3.23-3.71) and (aOR per SD 3.64; 95% CI 3.43-3.86). Compared with other indices, TyG had the highest AUC value for T2DM in men (AUC: 0.818, 95% CI 0.810-0.825) and women (AUC: 0.824, 95% CI 0.814-0.833). CONCLUSIONS TyG is an effective marker and outperforms other indices when predicting T2DM in the normal-weight Chinese elderly population. LEVEL OF EVIDENCE Level V: Opinions of authorities, based on descriptive studies, narrative reviews, clinical experience, or reports of expert committees.
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Affiliation(s)
- Pan Ke
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Xia Wu
- Baoan District Songgang People's Hospital, Shenzhen, Guangdong, China
| | - Minzhi Xu
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Jie Feng
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Hongbin Xu
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Yong Gan
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Chao Wang
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Zhenyu Deng
- Baoan District Songgang People's Hospital, Shenzhen, Guangdong, China
| | - Xiang Liu
- Baoan District Songgang People's Hospital, Shenzhen, Guangdong, China
| | - Wenning Fu
- School of Nursing, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qingfeng Tian
- School of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Yan He
- School of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Lirong Zhong
- School of Public Health, Hubei University of Medicine, Shiyan, Hubei, China
| | - Heng Jiang
- Centre for Alcohol Policy Research, School of Psychology and Public Health, La Trobe University, Melbourne, VIC, 3086, Australia.
- School of Population and Global Health, Centre for Health Equity, University of Melbourne, MelbourneMelbourne, VIC, Australia.
| | - Zuxun Lu
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China.
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Li X, Xue Y, Dang Y, Liu W, Wang Q, Zhao Y, Zhang Y. Association of Non-Insulin-Based Insulin Resistance Indices with Risk of Incident Prediabetes and Diabetes in a Chinese Rural Population: A 12-Year Prospective Study. Diabetes Metab Syndr Obes 2022; 15:3809-3819. [PMID: 36530590 PMCID: PMC9756794 DOI: 10.2147/dmso.s385906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE Three non-insulin-based insulin resistance (IR) indices, ie, triglyceride-glucose (TyG) index, triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio, and metabolic score for IR (METS-IR), were considered powerful and simplified alternatives for IR. However, evidence for the association between the three IR indices and incident type 2 diabetes mellitus (T2DM), especially impaired fasting glucose (IFG), remains limited. Therefore, this study aimed to explore the association among IR indices, incident IFG, and T2DM in a rural population cohort. METHODS We analyzed data from 2209 adults (aged 24-75 years) at baseline and from 1205 normoglycemic participants who were followed up. Cox proportional hazards models were used to evaluate the associations between the three indices and IFG or T2DM. Restricted cubic spline curves based on the Cox regression model were used to examine the association between baseline indices and incident T2DM. RESULTS For the baseline data, logistic analyses demonstrated that the TyG index, TG/HDL-C ratio, and METS-IR had a significantly positive correlation with IFG or T2DM after multivariable adjustment. During a median follow-up of 12.17 years, 157 incident cases of IFG and 97 incident cases of T2DM were noted. The risk of T2DM, but not IFG, was strongly associated with the baseline TyG index in the adjusted model, and participants with the TyG index in the third tertile had a higher risk of developing T2DM (adjusted hazards ratio, 2.84; 95% confidence intervals, 1.26-6.37; p for trend <0.001) than those in the lowest tertile (reference). Moreover, a linear relationship was observed between the TyG index and T2DM incidence. The TG/HDL-C ratio and METS-IR had no significant relationship with the risk of IFG or T2DM. CONCLUSION The TyG index is more useful than the TG/HDL-C ratio and METS-IR in predicting T2DM in the normoglycemic population.
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Affiliation(s)
- Xiaoxia Li
- Department of Epidemiology and Health Statistics, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
- Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
| | - Yixuan Xue
- Department of Epidemiology and Health Statistics, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
| | - Yuanyuan Dang
- Department of Epidemiology and Health Statistics, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
| | - Wanlu Liu
- Department of Epidemiology and Health Statistics, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
| | - Qingan Wang
- Department of Epidemiology and Health Statistics, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
- Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
| | - Yi Zhao
- Department of Epidemiology and Health Statistics, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
- Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
| | - Yuhong Zhang
- Department of Epidemiology and Health Statistics, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
- Key Laboratory of Environmental Factors and Chronic Disease Control, School of Public Health and Management of Ningxia Medical University, Yinchuan, People’s Republic of China
- Correspondence: Yuhong Zhang, Department of Epidemiology and Health Statistics School of Public Health and Management, Ningxia Medical University, 1160 Shengli Street, Xingqing District, Yinchuan, 750004, People’s Republic of China, Tel +86951-6980144, Fax +86951-6980144, Email
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Li X, Sun M, Yang Y, Yao N, Yan S, Wang L, Hu W, Guo R, Wang Y, Li B. Predictive Effect of Triglyceride Glucose-Related Parameters, Obesity Indices, and Lipid Ratios for Diabetes in a Chinese Population: A Prospective Cohort Study. Front Endocrinol (Lausanne) 2022; 13:862919. [PMID: 35432185 PMCID: PMC9007200 DOI: 10.3389/fendo.2022.862919] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 02/25/2022] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE The purpose of this study was to evaluate the association between triglyceride glucose (TyG) index and new-onset diabetes under different glycemic states and to compare the predictive value of TyG-related parameters, obesity indices, and lipid ratios for new-onset diabetes. METHODS Data were collected from the China Health and Retirement Longitudinal Study (CHARLS), consisting of 6,258 participants aged ≥45 years. Participants were grouped according to their glycemic states. Cox proportional hazards models and restricted cubic spline regression were used to explore the association between TyG index and diabetes. Cox proportional hazard models were applied to confirm the predictive value of the optimal marker. Receiver operating characteristic (ROC) curves were used to compare the predictive value. RESULTS TyG index was positively correlated with the risk of diabetes (hazard ratio (HR), 1.75; 95% confidence interval (CI), 1.56-1.97), and the linear association existed (p < 0.001). The highest correlation with diabetes was visceral adiposity index (VAI) (HR, 2.04; 95% CI, 1.44-2.90) in normal fasting glucose (NFG) group and TyG-body mass index (TyG-BMI) (HR, 2.53; 95% CI, 1.97-3.26) in impaired fasting glucose (IFG) group. The largest area under curve (AUC) was observed in TyG-waist-to-height ratio (TyG-WHtR) in the NFG group (AUC, 0.613; 95% CI, 0.527-0.700), and TyG-BMI had the highest AUC in the IFG group (AUC, 0.643; 95% CI, 0.601-0.685). CONCLUSION The association between TyG index and new-onset diabetes was positive and linear. TyG-WHtR was a clinically effective marker for identifying the risks of diabetes in the NFG group and TyG-BMI was an effective marker to predict diabetes in the IFG group.
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Pranata R, Huang I, Lim MA, Vania R. The association between triglyceride-glucose index and the incidence of type 2 diabetes mellitus-a systematic review and dose-response meta-analysis of cohort studies. Endocrine 2021; 74:254-262. [PMID: 34086260 DOI: 10.1007/s12020-021-02780-4] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 05/25/2021] [Indexed: 01/29/2023]
Abstract
ABSTARCT AIMS: We aimed to assess the dose-response relationship between triglyceride-glucose (TyG) index and the incidence of type 2 diabetes mellitus (T2DM). METHODS We performed a comprehensive systematic literature search using PubMed, Scopus, and Embase for records published from inception until 9 February 2021. The effect estimates were reported as relative risks (RRs). RESULTS 270,229 subjects from 14 studies were included in this systematic review and meta-analysis. The pooled incidence of T2DM was 9%. Meta-regression analysis indicates that baseline age (coefficient: 0.67, p = 0.026), drinking (coefficient: 0.03, p = 0.035), and HDL (coefficient: -0.89, p = 0.035) affected the incidence of T2DM in future. High TyG index was associated with increased incidence of T2DM in pooled unadjusted (RR 4.68 [3.01, 7.29], p < 0.001; I2: 96.6%) and adjusted model (adjusted RR 3.54 [2.75, 4.54], p < 0.001; I2: 83.7%). Dose-response meta-analysis for the adjusted RR showed that the linear association analysis was not significant per 0.1 increase in TyG index (RR 1.01 [0.99, 1.03], p = 0.223). There is a non-linear trend (p < 0.001) for the association between TyG index and incidence of T2DM. The dose-response curve became increasingly steeper at TyG index above 8.6. CONCLUSIONS TyG index was associated with the incidence of T2DM in a non-linear fashion.
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Affiliation(s)
- Raymond Pranata
- Faculty of Medicine, Universitas Pelita Harapan, Tangerang, Indonesia.
| | - Ian Huang
- Faculty of Medicine, Universitas Pelita Harapan, Tangerang, Indonesia
- Department of Internal Medicine, Faculty of Medicine, Universitas Padjadjaran, Hasan Sadikin General Hospital, Bandung, Indonesia
| | | | - Rachel Vania
- Faculty of Medicine, Universitas Pelita Harapan, Tangerang, Indonesia
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Zhang Z, Lai M, Piro AL, Alexeeff SE, Allalou A, Röst HL, Dai FF, Wheeler MB, Gunderson EP. Intensive lactation among women with recent gestational diabetes significantly alters the early postpartum circulating lipid profile: the SWIFT study. BMC Med 2021; 19:241. [PMID: 34620173 PMCID: PMC8499506 DOI: 10.1186/s12916-021-02095-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 08/12/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Women with a history of gestational diabetes mellitus (GDM) have a 7-fold higher risk of developing type 2 diabetes (T2D). It is estimated that 20-50% of women with GDM history will progress to T2D within 10 years after delivery. Intensive lactation could be negatively associated with this risk, but the mechanisms behind a protective effect remain unknown. METHODS In this study, we utilized a prospective GDM cohort of 1010 women without T2D at 6-9 weeks postpartum (study baseline) and tested for T2D onset up to 8 years post-baseline (n=980). Targeted metabolic profiling was performed on fasting plasma samples collected at both baseline and follow-up (1-2 years post-baseline) during research exams in a subset of 350 women (216 intensive breastfeeding, IBF vs. 134 intensive formula feeding or mixed feeding, IFF/Mixed). The relationship between lactation intensity and circulating metabolites at both baseline and follow-up were evaluated to discover underlying metabolic responses of lactation and to explore the link between these metabolites and T2D risk. RESULTS We observed that lactation intensity was strongly associated with decreased glycerolipids (TAGs/DAGs) and increased phospholipids/sphingolipids at baseline. This lipid profile suggested decreased lipogenesis caused by a shift away from the glycerolipid metabolism pathway towards the phospholipid/sphingolipid metabolism pathway as a component of the mechanism underlying the benefits of lactation. Longitudinal analysis demonstrated that this favorable lipid profile was transient and diminished at 1-2 years postpartum, coinciding with the cessation of lactation. Importantly, when stratifying these 350 women by future T2D status during the follow-up (171 future T2D vs. 179 no T2D), we discovered that lactation induced robust lipid changes only in women who did not develop incident T2D. Subsequently, we identified a cluster of metabolites that strongly associated with future T2D risk from which we developed a predictive metabolic signature with a discriminating power (AUC) of 0.78, superior to common clinical variables (i.e., fasting glucose, AUC 0.56 or 2-h glucose, AUC 0.62). CONCLUSIONS In this study, we show that intensive lactation significantly alters the circulating lipid profile at early postpartum and that women who do not respond metabolically to lactation are more likely to develop T2D. We also discovered a 10-analyte metabolic signature capable of predicting future onset of T2D in IBF women. Our findings provide novel insight into how lactation affects maternal metabolism and its link to future diabetes onset. TRIAL REGISTRATION ClinicalTrials.gov NCT01967030 .
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Affiliation(s)
- Ziyi Zhang
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Endocrinology, Sir Run Run Shaw Hospital, Zhejiang University, Zhejiang, Hangzhou, China
| | - Mi Lai
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Anthony L Piro
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Stacey E Alexeeff
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Amina Allalou
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Hannes L Röst
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada
| | - Feihan F Dai
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
| | - Michael B Wheeler
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
- Metabolism Research Group, Division of Advanced Diagnostics, Toronto General Research Institute, Toronto, Ontario, Canada.
| | - Erica P Gunderson
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA.
- Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, USA.
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Triglyceride glucose (TyG) index as a predictor of incident type 2 diabetes among nonobese adults: a 12-year longitudinal study of the Korean Genome and Epidemiology Study cohort. Transl Res 2021; 228:42-51. [PMID: 32827706 DOI: 10.1016/j.trsl.2020.08.003] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 08/12/2020] [Accepted: 08/17/2020] [Indexed: 01/18/2023]
Abstract
The rate of undiagnosed type 2 diabetes tends to increase in lean Koreans, while the triglyceride glucose (TyG) index has been proposed as a surrogate marker of peripheral insulin resistance. We investigated the longitudinal relationship between TyG and incident type 2 diabetes among apparently healthy Korean adults. We assessed 4285 lean adults without diabetes aged 40-69 years from the Korean Genome and Epidemiology Study. Participants were divided into 4 groups according to quartiles of TyG index, calculated as ln [fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2]. We prospectively assessed the hazard ratios (HRs) with 95% confidence intervals (CIs) for incident type 2 diabetes, based on the American Diabetes Association criteria, using multivariate Cox proportional hazards regression models, over 12 years after the baseline survey. During the follow-up period, 631 (14.7%) participants had newly developed type 2 diabetes. The HRs of incident type 2 diabetes in each TyG index quartile were 1.00, 1.63 (95%CI, 1.18-2.24), 2.30 (95%CI, 1.68-3.14), and 3.67 (95%CI, 2.71-4.98), respectively, after adjusting for age, sex, body mass index, waist circumference, smoking status, alcohol intake, and physical activity. Higher TyG index precedes and significantly predicts type 2 diabetes among community-dwelling middle aged and elderly lean Koreans.
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Association between Triglyceride-Glucose Index and Type 2 Diabetes Mellitus in the Japanese Population: A Secondary Analysis of a Retrospective Cohort Study. BIOMED RESEARCH INTERNATIONAL 2020; 2020:2947067. [PMID: 33490240 PMCID: PMC7787715 DOI: 10.1155/2020/2947067] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 12/01/2020] [Accepted: 12/02/2020] [Indexed: 12/23/2022]
Abstract
Triglyceride-glucose index (TyG index) is associated with type 2 diabetes mellitus (T2DM), but research on this relationship is limited in Japan. The purpose of this study was to evaluate the correlation between TyG index and the risk of T2DM in the Japanese population. Here, 12732 participants were selected from the NAGALA study (NAfld in the Gifu Area, Longitudinal Analysis) conducted between 2004 and 2015 for a retrospective cohort analysis. The association between TyG index and T2DM was assessed using the Cox proportional-hazard model. Subgroup analyses were conducted according to age, sex, smoking status, alcohol consumption, waist circumference, BMI, and follow-up duration. The formula for TyG index was expressed as ln [fasting triglyceride level (mg/dL) × fasting plasma glucose level (mg/dL)/2]. After follow-up, 150 (1.18%) patients developed T2DM. After adjusting for potential confounders, a linear relationship was observed between TyG and the risk of T2DM. After adjusting for age, sex, BMI, waist circumference, HDL-cholesterol, total cholesterol, systolic blood pressure, regular exercise, smoking status, and alcohol consumption, TyG index, as a continuous variable, was associated with an increased risk of T2DM (adjusted hazard ratio (aHR), 1.79; 95% confidence interval (95% CI), 1.25-2.57). Compared with the first quartile of TyG index, subjects in the fourth quartile were 2.33-fold more likely to develop T2DM (aHR 2.33, 95% CI 1.09-4.96; P for trend 0.0224). Subgroup analyses showed that the association between TyG index and incident T2DM stably existed in different subgroups according to the variables tested. Therefore, TyG index was linearly related to the risk of incident T2DM in the Japanese population and may be used as a monitoring tool.
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da Silva A, Caldas APS, Rocha DMUP, Bressan J. Triglyceride-glucose index predicts independently type 2 diabetes mellitus risk: A systematic review and meta-analysis of cohort studies. Prim Care Diabetes 2020; 14:584-593. [PMID: 32928692 DOI: 10.1016/j.pcd.2020.09.001] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 08/26/2020] [Accepted: 09/02/2020] [Indexed: 01/21/2023]
Abstract
OBJECTIVE Our objective was to perform a systematic review and meta-analysis of cohort studies evaluating the triglyceride-glucose (TyG) index as a tool for type 2 diabetes (T2D) prediction in adults and older adults. METHODS Studies were identified in PubMed, Cochrane, Scopus, and Lilacs. Studies with cohort design, which evaluated the T2D incidence through the hazard ratio (HR) or relative risk (RR) or odds ratio values were included. Were included both studies that evaluated the incidence of T2D from tertiles, quartiles, quintiles, or single TyG index values. First, a meta-analysis only for studies that reported data in HR values was performed. Additionally, given the different association measurements used, the number of T2D cases, non-T2D cases, and the total number of participants were extracted from exposed and non-exposed groups when available. Then the risk ratio was calculated. A meta-analysis using the inverse variance method and the random-effects model was performed. Heterogeneity was assessed by I2 statistics and by inspecting funnel plots. RESULTS Thirteen cohort studies with a total of 70,380 subjects, both sexes, adults, and older adults were included in the meta-analysis. Ten studies showed a significant association of the TyG index with T2D risk through HR estimative (overall HR: 2.44, 95% CI: 2.17-2.76). After estimating RR for nine studies, we also observed a significant association of the TyG index with T2D risk (RR: 3.12, 95 CI: 2.31-4.21). For all analyses, high heterogeneity was verified by I2 and visual inspection of funnel plots. CONCLUSIONS TyG index has a positive and significant association with T2D risk, suggesting that the TyG index may become an applicable tool to identify subjects with T2D risk. However, due to the high heterogeneity observed in overall HR and RR analysis, more studies could be necessary to confirm these results.
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Affiliation(s)
- Alessandra da Silva
- Departamento de Nutrição e Saúde, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
| | - Ana Paula Silva Caldas
- Departamento de Nutrição e Saúde, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
| | | | - Josefina Bressan
- Departamento de Nutrição e Saúde, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
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Amino acid and lipid metabolism in post-gestational diabetes and progression to type 2 diabetes: A metabolic profiling study. PLoS Med 2020; 17:e1003112. [PMID: 32433647 PMCID: PMC7239388 DOI: 10.1371/journal.pmed.1003112] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 04/20/2020] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Women with a history of gestational diabetes mellitus (GDM) have a 7-fold higher risk of developing type 2 diabetes (T2D) during midlife and an elevated risk of developing hypertension and cardiovascular disease. Glucose tolerance reclassification after delivery is recommended, but fewer than 40% of women with GDM are tested. Thus, improved risk stratification methods are needed, as is a deeper understanding of the pathology underlying the transition from GDM to T2D. We hypothesize that metabolites during the early postpartum period accurately distinguish risk of progression from GDM to T2D and that metabolite changes signify underlying pathophysiology for future disease development. METHODS AND FINDINGS The study utilized fasting plasma samples collected from a well-characterized prospective research study of 1,035 women diagnosed with GDM. The cohort included racially/ethnically diverse pregnant women (aged 20-45 years-33% primiparous, 37% biparous, 30% multiparous) who delivered at Kaiser Permanente Northern California hospitals from 2008 to 2011. Participants attended in-person research visits including 2-hour 75-g oral glucose tolerance tests (OGTTs) at study baseline (6-9 weeks postpartum) and annually thereafter for 2 years, and we retrieved diabetes diagnoses from electronic medical records for 8 years. In a nested case-control study design, we collected fasting plasma samples among women without diabetes at baseline (n = 1,010) to measure metabolites among those who later progressed to incident T2D or did not develop T2D (non-T2D). We studied 173 incident T2D cases and 485 controls (pair-matched on BMI, age, and race/ethnicity) to discover metabolites associated with new onset of T2D. Up to 2 years post-baseline, we analyzed samples from 98 T2D cases with 239 controls to reveal T2D-associated metabolic changes. The longitudinal analysis tracked metabolic changes within individuals from baseline to 2 years of follow-up as the trajectory of T2D progression. By building prediction models, we discovered a distinct metabolic signature in the early postpartum period that predicted future T2D with a median discriminating power area under the receiver operating characteristic curve of 0.883 (95% CI 0.820-0.945, p < 0.001). At baseline, the most striking finding was an overall increase in amino acids (AAs) as well as diacyl-glycerophospholipids and a decrease in sphingolipids and acyl-alkyl-glycerophospholipids among women with incident T2D. Pathway analysis revealed up-regulated AA metabolism, arginine/proline metabolism, and branched-chain AA (BCAA) metabolism at baseline. At follow-up after the onset of T2D, up-regulation of AAs and down-regulation of sphingolipids and acyl-alkyl-glycerophospholipids were sustained or strengthened. Notably, longitudinal analyses revealed only 10 metabolites associated with progression to T2D, implicating AA and phospholipid metabolism. A study limitation is that all of the analyses were performed with the same cohort. It would be ideal to validate our findings in an independent longitudinal cohort of women with GDM who had glucose tolerance tested during the early postpartum period. CONCLUSIONS In this study, we discovered a metabolic signature predicting the transition from GDM to T2D in the early postpartum period that was superior to clinical parameters (fasting plasma glucose, 2-hour plasma glucose). The findings suggest that metabolic dysregulation, particularly AA dysmetabolism, is present years prior to diabetes onset, and is revealed during the early postpartum period, preceding progression to T2D, among women with GDM. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01967030.
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Chamroonkiadtikun P, Ananchaisarp T, Wanichanon W. The triglyceride-glucose index, a predictor of type 2 diabetes development: A retrospective cohort study. Prim Care Diabetes 2020; 14:161-167. [PMID: 31466834 DOI: 10.1016/j.pcd.2019.08.004] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 08/08/2019] [Indexed: 01/28/2023]
Abstract
AIMS The triglycerides-glucose (TyG) index, the product of fasting plasma glucose (FPG) and triglycerides (TG) is a novel index. Many previous studies have reported that the TyG index might be a strong predictor of incident type 2 diabetes. We determined whether the TyG index could be a useful predictor for diabetes diagnosis and compared it to the FPG and TG as predictors of type 2 diabetes. METHODS A total of 617 subjects without baseline diabetes were examined and followed up for a median period of 9.2 years. We performed a mixed effect cox regression analysis to evaluate the risk of developing diabetes across the quartiles of the TyG index, calculated as ln[triglyceride (mg/dl)×FPG (mg/dl)/2], and plotted a receiver operating characteristic (ROC) curve to assess discrimination among TyG, FPG and TG. RESULTS During 4,871.56 person-years of follow-up, there were 163 incident cases of diabetes. The risk of diabetes increased across the quartiles of the TyG index. Those in the highest quartile of TyG had a higher risk of developing diabetes (adjusted HR 3.38 95% CI 2.38-4.8, ptrend<0.001) than those in the lowest quartile. The area under the curve (AUC) of the ROC plots were 0.79 (95% CI 0.74-0.83) for FPG, 0.64 (95% CI 0.60-0.69) for TyG and 0.59 (95% CI 0.54-0.64) for TG. CONCLUSION The TyG index was significantly associated with risk of incident diabetes and could be a valuable biomarker of developing diabetes. However, FPG appeared to be a more robust predictor of diabetes.
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Affiliation(s)
- Panya Chamroonkiadtikun
- Department of Family and Preventive Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand.
| | - Thareerat Ananchaisarp
- Department of Family and Preventive Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand.
| | - Worawit Wanichanon
- Department of Family and Preventive Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand.
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Khan SR, Mohan H, Liu Y, Batchuluun B, Gohil H, Al Rijjal D, Manialawy Y, Cox BJ, Gunderson EP, Wheeler MB. The discovery of novel predictive biomarkers and early-stage pathophysiology for the transition from gestational diabetes to type 2 diabetes. Diabetologia 2019; 62:687-703. [PMID: 30645667 PMCID: PMC7237273 DOI: 10.1007/s00125-018-4800-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 11/13/2018] [Indexed: 12/12/2022]
Abstract
AIMS/HYPOTHESIS Gestational diabetes mellitus (GDM) affects up to 20% of pregnancies, and almost half of the women affected progress to type 2 diabetes later in life, making GDM the most significant risk factor for the development of future type 2 diabetes. An accurate prediction of future type 2 diabetes risk in the early postpartum period after GDM would allow for timely interventions to prevent or delay type 2 diabetes. In addition, new targets for interventions may be revealed by understanding the underlying pathophysiology of the transition from GDM to type 2 diabetes. The aim of this study is to identify both a predictive signature and early-stage pathophysiology of the transition from GDM to type 2 diabetes. METHODS We used a well-characterised prospective cohort of women with a history of GDM pregnancy, all of whom were enrolled at 6-9 weeks postpartum (baseline), were confirmed not to have diabetes via 2 h 75 g OGTT and tested anually for type 2 diabetes on an ongoing basis (2 years of follow-up). A large-scale targeted lipidomic study was implemented to analyse ~1100 lipid metabolites in baseline plasma samples using a nested pair-matched case-control design, with 55 incident cases matched to 85 non-case control participants. The relationships between the concentrations of baseline plasma lipids and respective follow-up status (either type 2 diabetes or no type 2 diabetes) were employed to discover both a predictive signature and the underlying pathophysiology of the transition from GDM to type 2 diabetes. In addition, the underlying pathophysiology was examined in vivo and in vitro. RESULTS Machine learning optimisation in a decision tree format revealed a seven-lipid metabolite type 2 diabetes predictive signature with a discriminating power (AUC) of 0.92 (87% sensitivity, 93% specificity and 91% accuracy). The signature was highly robust as it includes 45-fold cross-validation under a high confidence threshold (1.0) and binary output, which together minimise the chance of data overfitting and bias selection. Concurrent analysis of differentially expressed lipid metabolite pathways uncovered the upregulation of α-linolenic/linoleic acid metabolism (false discovery rate [FDR] 0.002) and fatty acid biosynthesis (FDR 0.005) and the downregulation of sphingolipid metabolism (FDR 0.009) as being strongly associated with the risk of developing future type 2 diabetes. Focusing specifically on sphingolipids, the downregulation of sphingolipid metabolism using the pharmacological inhibitors fumonisin B1 (FB1) and myriocin in mouse islets and Min6 K8 cells (a pancreatic beta-cell like cell line) significantly impaired glucose-stimulated insulin secretion but had no significant impact on whole-body glucose homeostasis or insulin sensitivity. CONCLUSIONS/INTERPRETATION We reveal a novel predictive signature and associate reduced sphingolipids with the pathophysiology of transition from GDM to type 2 diabetes. Attenuating sphingolipid metabolism in islets impairs glucose-stimulated insulin secretion.
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Affiliation(s)
- Saifur R Khan
- Endocrine and Diabetes Platform, Department of Physiology, University of Toronto, Medical Sciences Building, Room 3352, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada
- Advanced Diagnostics, Metabolism, Toronto General Hospital Research Institute, Toronto, ON, Canada
| | - Haneesha Mohan
- Endocrine and Diabetes Platform, Department of Physiology, University of Toronto, Medical Sciences Building, Room 3352, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada
- Advanced Diagnostics, Metabolism, Toronto General Hospital Research Institute, Toronto, ON, Canada
| | - Ying Liu
- Endocrine and Diabetes Platform, Department of Physiology, University of Toronto, Medical Sciences Building, Room 3352, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada
- Advanced Diagnostics, Metabolism, Toronto General Hospital Research Institute, Toronto, ON, Canada
| | - Battsetseg Batchuluun
- Endocrine and Diabetes Platform, Department of Physiology, University of Toronto, Medical Sciences Building, Room 3352, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada
- Advanced Diagnostics, Metabolism, Toronto General Hospital Research Institute, Toronto, ON, Canada
| | - Himaben Gohil
- Endocrine and Diabetes Platform, Department of Physiology, University of Toronto, Medical Sciences Building, Room 3352, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada
- Advanced Diagnostics, Metabolism, Toronto General Hospital Research Institute, Toronto, ON, Canada
| | - Dana Al Rijjal
- Endocrine and Diabetes Platform, Department of Physiology, University of Toronto, Medical Sciences Building, Room 3352, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada
- Advanced Diagnostics, Metabolism, Toronto General Hospital Research Institute, Toronto, ON, Canada
| | - Yousef Manialawy
- Endocrine and Diabetes Platform, Department of Physiology, University of Toronto, Medical Sciences Building, Room 3352, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada
- Advanced Diagnostics, Metabolism, Toronto General Hospital Research Institute, Toronto, ON, Canada
| | - Brian J Cox
- Reproduction and Development Platform, Department of Physiology, University of Toronto, Medical Sciences Building, Room 3360, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada.
- Department of Obstetrics and Gynecology, University of Toronto, Toronto, ON, Canada.
| | - Erica P Gunderson
- Kaiser Permanente Northern California, Division of Research, 2000 Broadway, Oakland, CA, 94612, USA.
| | - Michael B Wheeler
- Endocrine and Diabetes Platform, Department of Physiology, University of Toronto, Medical Sciences Building, Room 3352, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada.
- Advanced Diagnostics, Metabolism, Toronto General Hospital Research Institute, Toronto, ON, Canada.
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15
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Cantero I, Elorz M, Abete I, Marin BA, Herrero JI, Monreal JI, Benito A, Quiroga J, Martínez A, Huarte MP, Uriz-Otano JI, Tur JA, Kearney J, Martinez JA, Zulet MA. Ultrasound/Elastography techniques, lipidomic and blood markers compared to Magnetic Resonance Imaging in non-alcoholic fatty liver disease adults. Int J Med Sci 2019; 16:75-83. [PMID: 30662331 PMCID: PMC6332481 DOI: 10.7150/ijms.28044] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 10/18/2018] [Indexed: 12/24/2022] Open
Abstract
INTRODUCTION Non-alcoholic fatty liver disease (NAFLD) may progress to steatohepatitis, cirrhosis and complicated hepatocellular carcinoma with defined differential symptoms and manifestations. OBJECTIVE To evaluate the fatty liver status by several validated approaches and to compare imaging techniques, lipidomic and routine blood markers with magnetic resonance imaging in adults subjects with non-alcoholic fatty liver disease. MATERIALS AND METHODS A total of 127 overweight/obese with NAFLD, were parallelly assessed by Magnetic Resonance Imaging (MRI), ultrasonography, transient elastography and a validated metabolomic designed test to diagnose NAFLD in this cross-sectional study. Body composition (DXA), hepatic related biochemical measurements as well as the Fatty Liver Index (FLI) were evaluated. This study was registered as FLiO: Fatty Liver in Obesity study; NCT03183193. RESULTS The subjects with more severe liver disease were found to have worse metabolic parameters. Positive associations between MRI with inflammatory and insulin biomarkers were found. A linear regression model including ALT, RBP4 and HOMA-IR was able to explain 40.9% of the variability in fat content by MRI. In ROC analyses a combination panel formed of ALT, HOMA-IR and RBP4 followed by ultrasonography, ALT and metabolomic test showed the major predictive ability (77.3%, 74.6%, 74.3% and 71.1%, respectively) for liver fat content. CONCLUSIONS A panel combination including routine blood markers linked to insulin resistance showed highest associations with MRI considered as a gold standard for determining liver fat content. This combination of tests can facilitate the diagnosis of early stages of non-alcoholic liver disease thereby avoiding other invasive and expensive methods.
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Affiliation(s)
- Irene Cantero
- Department of Nutrition, Food Science and Physiology. Centre for Nutrition Research. School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
| | - Mariana Elorz
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Itziar Abete
- Department of Nutrition, Food Science and Physiology. Centre for Nutrition Research. School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain.,CIBERobn, Physiopathology of Obesity and Nutrition. Instituto de Salud Carlos III. Madrid, Spain
| | - Bertha Araceli Marin
- Department of Nutrition, Food Science and Physiology. Centre for Nutrition Research. School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
| | - Jose Ignacio Herrero
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.,Liver Unit, Clinica Universidad de Navarra, Pamplona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Madrid, Spain
| | - Jose Ignacio Monreal
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.,Clinical Chemistry Department, Clínica Universidad de Navarra, Pamplona, Spain
| | - Alberto Benito
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Jorge Quiroga
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.,Department of Internal Medicine, Clínica Universidad de Navarra, Pamplona, Navarra, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Madrid, Spain
| | - Ana Martínez
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.,Department of Gastroenterology, Complejo Hospitalario de Navarra, Pamplona, Spain
| | - Mª Pilar Huarte
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.,Department of Gastroenterology, Complejo Hospitalario de Navarra, Pamplona, Spain
| | - Juan Isidro Uriz-Otano
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.,Department of Gastroenterology, Complejo Hospitalario de Navarra, Pamplona, Spain
| | - Josep Antoni Tur
- CIBERobn, Physiopathology of Obesity and Nutrition. Instituto de Salud Carlos III. Madrid, Spain.,Research Group on Community Nutrition and Oxidative Stress. University of Balearic Islands. Palma de Mallorca. Spain
| | - John Kearney
- School of Biological Sciences, Dublin Institute of Technology, Dublin, Republic of Ireland
| | - J Alfredo Martinez
- Department of Nutrition, Food Science and Physiology. Centre for Nutrition Research. School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain.,CIBERobn, Physiopathology of Obesity and Nutrition. Instituto de Salud Carlos III. Madrid, Spain.,Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.,IMDEA FOOD. Madrid
| | - M Angeles Zulet
- Department of Nutrition, Food Science and Physiology. Centre for Nutrition Research. School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain.,CIBERobn, Physiopathology of Obesity and Nutrition. Instituto de Salud Carlos III. Madrid, Spain.,Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
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Tohidi M, Baghbani-Oskouei A, Ahanchi NS, Azizi F, Hadaegh F. Fasting plasma glucose is a stronger predictor of diabetes than triglyceride-glucose index, triglycerides/high-density lipoprotein cholesterol, and homeostasis model assessment of insulin resistance: Tehran Lipid and Glucose Study. Acta Diabetol 2018; 55:1067-1074. [PMID: 30066042 DOI: 10.1007/s00592-018-1195-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2018] [Accepted: 07/17/2018] [Indexed: 12/20/2022]
Abstract
AIMS To compare the impact of triglyceride-glucose index (TyG-index), the product of fasting plasma glucose (FPG) and triglycerides (TG) with FPG, 2 h post-challenge plasma glucose (2 h-PCPG), TG/high-density lipoprotein cholesterol (TG/HDL-C), and homeostasis model assessment of insulin resistance (HOMA-IR) indices for prediction of type 2 diabetes (T2D) in Iranian adults during a median follow-up of 12 years. METHODS Study population included 4419 (1858 men) subjects with mean age of 40.6 ± 13.2 years. Multivariable Cox proportional hazard models were used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) for each 1-standard deviation increase in each predictor. Areas under the receiver operating characteristics curves (AUC) and 95% CIs were calculated. RESULTS During follow-up, 215 men and 288 women developed T2D. The multivariable HRs for FPG, 2 h-PCPG, TyG-index, HOMA-IR, HOMA2-IR, and TG/HDL-C were 2.20, 1.97, 1.71, 1.33, 1.30, and 1.35 in men and 2.13, 2.11, 1.44, 1.37, 1.32, and 1.36 in women (all P < 0.001). Among the total population, the AUC for FPG [0.752 (0.727-0.776)] was similar to 2 h-PCPG but higher than TyG-index [0.697 (0.673-0.720)], TG/HDL-C [0.644 (0.620-0.669)], HOMA-IR [0.684 (0.659-0.710)], and HOMA2-IR [0.656 (0.630-0.682)]. In men, AUC of TyG-index was higher than TG/HDL-C but did not differ with HOMA-IR indices. In women, the AUC of TyG-index was higher than HOMA2-IR and TG/HDL-C, but was similar to that of HOMA-IR. CONCLUSIONS FPG is a stronger predictor of T2D than the TyG-index, TG/HDL-C, and HOMA-IR indices. Although TyG-index was better than TG/HDL-C in both genders, it did not rank above HOMA-IR.
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Affiliation(s)
- Maryam Tohidi
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box: 19395-4763, No. 24, Aarabi St. Velenjak area, Tehran, Iran
| | - Aidin Baghbani-Oskouei
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box: 19395-4763, No. 24, Aarabi St. Velenjak area, Tehran, Iran
| | - Noushin Sadat Ahanchi
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box: 19395-4763, No. 24, Aarabi St. Velenjak area, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, No. 24, Aarabi St. Velenjak area, Tehran, Iran
| | - Farzad Hadaegh
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box: 19395-4763, No. 24, Aarabi St. Velenjak area, Tehran, Iran.
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17
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Wang B, Zhang M, Liu Y, Sun X, Zhang L, Wang C, Li L, Ren Y, Han C, Zhao Y, Zhou J, Pang C, Yin L, Feng T, Zhao J, Hu D. Utility of three novel insulin resistance-related lipid indices for predicting type 2 diabetes mellitus among people with normal fasting glucose in rural China. J Diabetes 2018; 10:641-652. [PMID: 29322661 DOI: 10.1111/1753-0407.12642] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Revised: 12/17/2017] [Accepted: 01/07/2018] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Inexpensive and easily measured indices are needed for the early prediction of type 2 diabetes mellitus (T2DM) in rural areas of China. The aim of this study was to compare triglyceride glucose (TyG), visceral adiposity (VAI), and lipid accumulation product (LAP) with traditional individual measures and their ratios for predicting T2DM. METHODS Data for 11 113 people with baseline normal fasting glucose in a rural Chinese cohort were followed for a median of 6.0 years. Cox proportional hazards regression was used to calculate covariate-adjusted hazard ratios (aHRs) and 95% confidence intervals (95% CIs) and receiver operating characteristic analysis was used to compare the ability of traditional measures and TyG, VAI, and LAP at baseline to predict T2DM at follow-up. RESULTS Among individual measures, fasting plasma glucose (FPG) and waist circumference (WC) were strongly associated with T2DM. Of all lipid ratios, an elevated triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C) ratio was associated the most with T2DM. Compared with the first quartiles of TyG, VAI, and LAP, their fourth quartiles were associated with T2DM for men (aHR 3.54 [95% CI 2.08-6.03], 2.89 [1.72-4.87], and 5.02 [2.85-8.85], respectively) and women (6.15 [3.48-10.85], 4.40 [2.61-7.42], and 6.49 [3.48-12.12], respectively). For predicting T2DM risk, TyG, VAI, and LAP were mostly superior to the TG: HDL-C ratio, but did not differ from FPG and WC. CONCLUSIONS Prediction of T2DM was not improved by TyG, VAI, and LAP versus FPG or WC alone. Therefore, TyG, VAI, and LAP may not be inexpensive tools for predicting T2DM in rural Chinese people.
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Affiliation(s)
- Bingyuan Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Ming Zhang
- Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, China
| | - Yu Liu
- The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, China
| | - Xizhuo Sun
- The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, China
| | - Lu Zhang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Chongjian Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Linlin Li
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yongcheng Ren
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, China
- The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, China
| | - Chengyi Han
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, China
- The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, China
| | - Yang Zhao
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, China
- The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, China
| | - Junmei Zhou
- Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, China
- The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, China
| | - Chao Pang
- Department of Prevention and Health Care, Military Hospital of Henan Province, Zhengzhou, China
| | - Lei Yin
- Department of Prevention and Health Care, Military Hospital of Henan Province, Zhengzhou, China
| | - Tianping Feng
- Department of Prevention and Health Care, Military Hospital of Henan Province, Zhengzhou, China
| | - Jingzhi Zhao
- Department of Prevention and Health Care, Military Hospital of Henan Province, Zhengzhou, China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
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Lee JW, Lim NK, Park HY. The product of fasting plasma glucose and triglycerides improves risk prediction of type 2 diabetes in middle-aged Koreans. BMC Endocr Disord 2018; 18:33. [PMID: 29843706 PMCID: PMC5975474 DOI: 10.1186/s12902-018-0259-x] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Accepted: 05/16/2018] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Screening for risk of type 2 diabetes mellitus (T2DM) is an important public health issue. Previous studies report that fasting plasma glucose (FPG) and triglyceride (TG)-related indices, such as lipid accumulation product (LAP) and the product of fasting glucose and triglyceride (TyG index), are associated with incident T2DM. We aimed to evaluate whether FPG or TG-related indices can improve the predictive ability of a diabetes risk model for middle-aged Koreans. METHODS 7708 Koreans aged 40-69 years without diabetes at baseline were eligible from the Korean Genome and Epidemiology Study. The overall cumulative incidence of T2DM was 21.1% (766 cases) in men and 19.6% (797 cases) in women. Therefore, the overall cumulative incidence of T2DM was 20.3% (1563 cases). Multiple logistic regression analysis was conducted to compare the odds ratios (ORs) for incident T2DM for each index. The area under the receiver operating characteristic curve (AROC), continuous net reclassification improvement (cNRI), and integrated discrimination improvement (IDI) were calculated when each measure was added to the basic risk model for diabetes. RESULTS All the TG-related indices and FPG were more strongly associated with incident T2DM than WC in our study population. The adjusted ORs for the highest quartiles of WC, TG, FPG, LAP, and TyG index compared to the lowest, were 1.64 (95% CI, 1.13-2.38), 2.03 (1.59-2.61), 3.85 (2.99-4.97), 2.47 (1.82-3.34), and 2.79 (2.16-3.60) in men, and 1.17 (0.83-1.65), 2.42 (1.90-3.08), 2.15 (1.71-2.71), 2.44 (1.82-3.26), and 2.85 (2.22-3.66) in women, respectively. The addition of TG-related parameters or FPG, but not WC, to the basic risk model for T2DM (including age, body mass index, family history of diabetes, hypertension, current smoking, current drinking, and regular exercise) significantly increased cNRI, IDI, and AROC in both sexes. CONCLUSIONS Adding either TyG index or FPG into the basic risk model for T2DM increases its prediction and reclassification ability. Compared to FPG, TyG index was a more robust T2DM predictor in the stratified sex and fasting glucose level. Therefore, TyG index should be considered as a screening tool for identification of people at high risk for T2DM in practice.
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Affiliation(s)
- Joung-Won Lee
- Division of Cardiovascular Diseases, Center for Biomedical Sciences, Korea National Institute of Health, 187 Osongsaengmyeng 2-ro, Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do 361-951 South Korea
- Department of Public Health Sciences, Graduate School, Korea University, Seoul, South Korea
| | - Nam-Kyoo Lim
- Division of Cardiovascular Diseases, Center for Biomedical Sciences, Korea National Institute of Health, 187 Osongsaengmyeng 2-ro, Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do 361-951 South Korea
| | - Hyun-Young Park
- Division of Cardiovascular Diseases, Center for Biomedical Sciences, Korea National Institute of Health, 187 Osongsaengmyeng 2-ro, Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do 361-951 South Korea
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Gesteiro E, Bastida S, Barrios L, Sánchez-Muniz FJ. The triglyceride-glucose index, an insulin resistance marker in newborns? Eur J Pediatr 2018; 177:513-520. [PMID: 29350334 DOI: 10.1007/s00431-018-3088-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 12/18/2017] [Accepted: 01/09/2018] [Indexed: 01/19/2023]
Abstract
UNLABELLED The study aims to assess the utility of the triglyceride-glucose index (TyG) as a marker of insulin resistance (IR) in neonates. TyG and the homeostatic model assessment (HOMA-IR) values were compared in 196 singleton, term normoweight and without distress newborns. A Decision Tree procedure (CHAID) was used to classify cases into groups or predict values of a dependent (Ln HOMA-IR) variable. Three nodes were drawn for TyG: ≤ 6.7, > 6.7-7.8 and > 7.8 (p < 0.0001; F = 20.52). The predictability of those TyG values vs HOMA-IR was statistically significant (p < 0.0001). It was neither affected by gender (p = 0.084), glucose challenge test (p = 0.138) classifications nor by the TyG node* glucose challenge test and TyG node*gender interactions (p = 0.456 and p = 0.209, respectively). Glucose, HOMA-IR, and the triglyceride/HDL cholesterol ratio increased progressively from node 1 to 3 for TyG while QUICKI decreased. CONCLUSION In conclusion, TyG appears to be a suitable tool for identifying IR at birth, justifying the further insulin determination in those neonates. TyG ≥ 7.8 is recommended as cut-off point in neonates. The need for a follow-up study to confirm the TyG as early IR marker is desirable. WHAT IS KNOWN • HOMA-IR and the triglyceride-glucose index (TyG) show a high correlation. • The TyG has been used as an insulin resistance marker in adults. WHAT IS NEW • This is the first study where TyG has been assessed in neonates. • TyG appears to be a suitable and cheap tool for identifying insulin resistance at birth.
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Affiliation(s)
- Eva Gesteiro
- Departamento de Nutrición y Ciencia de los Alimentos (Nutrición). Facultad de Farmacia, Universidad Complutense de Madrid e Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Plaza Ramón y Cajal s/n., 28040, Madrid, Spain.,Departamento de Salud y Rendimiento Humano, Facultad de Ciencias de la Actividad Física y del Deporte-INEF, Universidad Politécnica de Madrid, Calle Martín Fierro 7, 28040, Madrid, Spain
| | - Sara Bastida
- Departamento de Nutrición y Ciencia de los Alimentos (Nutrición). Facultad de Farmacia, Universidad Complutense de Madrid e Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Plaza Ramón y Cajal s/n., 28040, Madrid, Spain
| | - Laura Barrios
- Centro de CálculoCientífico de la SGAI. Investigación Operativa y Estadística Aplicada. CSIC, Calle Pinar 19, 28006, Madrid, Spain
| | - Francisco J Sánchez-Muniz
- Departamento de Nutrición y Ciencia de los Alimentos (Nutrición). Facultad de Farmacia, Universidad Complutense de Madrid e Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Plaza Ramón y Cajal s/n., 28040, Madrid, Spain.
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Kim HJ, Moon JS, Park IR, Kim JH, Yoon JS, Won KC, Lee HW. A Novel Index Using Soluble CD36 Is Associated with the Prevalence of Type 2 Diabetes Mellitus: Comparison Study with Triglyceride-Glucose Index. Endocrinol Metab (Seoul) 2017; 32:375-382. [PMID: 28956368 PMCID: PMC5620035 DOI: 10.3803/enm.2017.32.3.375] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Revised: 07/05/2017] [Accepted: 07/06/2017] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Plasma soluble cluster determinant 36 (sCD36) level is closely related with insulin resistance and atherosclerosis, but little is known whether it could be a surrogate for estimating risk of developing diabetes or not. To address this, we evaluated association between sCD36 index, the product of sCD36 and fasting plasma glucose (FPG), and the prevalence of type 2 diabetes mellitus (T2DM), and then compared with triglyceride-glucose (TyG) index which has been suggested simple index for insulin resistance. METHODS This was cross-sectional study, and participants were classified as normal glucose tolerance (NGT), prediabetes, and T2DM according to glucose tolerance. The formula of TyG index was 'ln [FPG (mg/dL)×triglyceride (mg/dL)/2],' and the sCD36 index was 'ln [sCD36 (pg/mL)×FPG (mg/dL)/2].' RESULTS One hundred and fifty-five subjects (mean age, 55.2 years) were enrolled, and patients with T2DM were 75. Both indexes were significantly increased in prediabetes and T2DM rather than NGT, and sCD36 index was positively correlated with both glycosylated hemoglobin and homeostasis model assessment of insulin resistance (r=0.767 and r=0.453, respectively; P<0.05) and negatively with homeostasis model assessment estimate of β-cell function (r=-0.317). The odds ratio (OR) of sCD36 index for T2DM was 4.39 (95% confidential interval, 1.51 to 12.77) after adjusting age, gender, blood pressure, smoking, alcohol, non-high density lipoprotein cholesterol and high-sensitivity C-reactive protein. However, OR of TyG index did not remained significance after adjustment. CONCLUSION sCD36 index has an independent association with the risk of T2DM, and showed better correlation than TyG index. These results suggest sCD36 index might be useful surrogate marker for the risk of diabetes.
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Affiliation(s)
- Ho Jin Kim
- Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
| | - Jun Sung Moon
- Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
| | - Il Rae Park
- Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
| | - Joong Hee Kim
- Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
| | - Ji Sung Yoon
- Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
| | - Kyu Chang Won
- Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
| | - Hyoung Woo Lee
- Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea.
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Cumulative increased risk of incident type 2 diabetes mellitus with increasing triglyceride glucose index in normal-weight people: The Rural Chinese Cohort Study. Cardiovasc Diabetol 2017; 16:30. [PMID: 28249577 PMCID: PMC5333419 DOI: 10.1186/s12933-017-0514-x] [Citation(s) in RCA: 146] [Impact Index Per Article: 20.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2016] [Accepted: 02/22/2017] [Indexed: 12/15/2022] Open
Abstract
Background Risk of type 2 diabetes mellitus (T2DM) is increased in metabolically obese but normal-weight people. However, we have limited knowledge of how to prevent T2DM in normal-weight people. We aimed to evaluate the association between triglyceride glucose (TyG) index and incident T2DM among normal-weight people in rural China. Methods We included data from 5706 people with normal body mass index (BMI) (18.5–23.9 kg/m2) without baseline T2DM in a rural Chinese cohort followed for a median of 6.0 years. A Cox proportional-hazard model was used to assess the risk of incident T2DM by quartiles of TyG index and difference in TyG index between follow-up and baseline (TyG-D), estimating hazard ratios (HRs) and 95% confidence intervals (CIs). A generalized additive plot was used to show the nonparametric smoothed exposure–response association between risk of T2DM and TyG index as a continuous variable. TyG was calculated as ln [fasting triglyceride level (mg/dl) × fasting plasma glucose level (mg/dl)/2]. Results Risk of incident T2DM was increased with quartiles 2, 3 and 4 versus quartile 1 of TyG index (adjusted HR [aHR] 2.48 [95% CI 1.20–5.11], 3.77 [1.83–7.79], and 5.30 [2.21–12.71], Ptrend < 0.001 across quartiles of TyG index). Risk of incident T2DM was increased with quartile 4 versus quartile 1 of TyG-D (aHR 3.91 [2.22–6.87]). The results were consistent when analyses were restricted to participants without baseline metabolic syndrome and impaired fasting glucose level. The generalized additive plot showed cumulative increased risk of T2DM with increasing TyG index. Conclusions Risk of incident T2DM is increased with increasing TyG index among rural Chinese people, so the index might be an important indicator for identifying people at high risk of T2DM.
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Manco M, Grugni G, Di Pietro M, Balsamo A, Di Candia S, Morino GS, Franzese A, Di Bonito P, Maffeis C, Valerio G. Triglycerides-to-HDL cholesterol ratio as screening tool for impaired glucose tolerance in obese children and adolescents. Acta Diabetol 2016; 53:493-8. [PMID: 26687197 DOI: 10.1007/s00592-015-0824-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Accepted: 12/02/2015] [Indexed: 11/28/2022]
Abstract
AIMS To identify metabolic phenotypes at increased risk of impaired glucose tolerance (IGT) in Italian overweight/obese children (n = 148, age 5-10 years) and adolescents (n = 531, age 10-17.9 year). METHODS Phenotypes were defined as follows: obesity by the 95th cut-points of the Center for Disease Control body mass index reference standards, impaired fasting glucose (fasting plasma glucose ≥100 mg/dl), high circulating triglycerides (TG), TG/HDL cholesterol ≥2.2, waist-to-height ratio (WTHR) >0.6, and combination of the latter with high TG or TG/HDL cholesterol ≥2.2. RESULTS In the 148 obese children, TG/HDL-C ≥ 2.2 (OR 20.19; 95 % CI 2.50-163.28, p = 0.005) and the combination of TG/HDL-C ≥ 2.2 and WTHR > 0.60 (OR 14.97; 95 % CI 2.18-102.76, p = 0.006) were significantly associated with IGT. In the 531 adolescents, TG/HDL-C ≥ 2.2 (OR 1.991; 95 % CI 1.243-3.191, p = 0.004) and the combination with WTHR > 0.60 (OR 2.24; 95 % CI 1.29-3.87, p = 0.004) were associated with significantly increased risk of IGT. In the whole sample, having high TG levels according to the NIH National Heart, Lung and Blood Institute Expert Panel was not associated with an increased risk of presenting IGT. CONCLUSIONS TG/HDL-C ratio can be useful, particularly in children, to identify obese young patients at risk of IGT. Its accuracy as screening tool in a general population needs to be verified. The combination of TG/HDL-C ratio and WTHR > 0.6 did not improve prediction. Having high TG according to the NIH definition was not associated with increased risk of developing IGT.
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Affiliation(s)
- Melania Manco
- Area di Ricerca Malattie Multifattoriali, Obesità e Diabete, Ospedale Pediatrico Bambino Gesù, Rome, Italy.
| | - Graziano Grugni
- Divisione di Auxologia, Istituto Auxologico Italiano, Piancavallo, Verbania, Italy
| | - Mario Di Pietro
- Dipartimento materno-infantile, Ospedale San Liberatore, Atri, Teramo, Italy
| | - Antonio Balsamo
- Dipartimento di Scienze Mediche e Chirurgiche, Programma di Endocrinologia Pediatrica, Unità Operativa di Pediatria, Università di Bologna, Policlinico S. Orsola-Malpighi, Bologna, Italy
| | - Stefania Di Candia
- Dipartimento di Pediatria, Istituto Scientifico San Raffaele, Milano and Azienda Sanitaria Locale 2, Melegnano, Milan, Italy
| | - Giuseppe Stefano Morino
- Area di Ricerca Malattie Multifattoriali, Obesità e Diabete, Ospedale Pediatrico Bambino Gesù, Rome, Italy
| | - Adriana Franzese
- Dipartimento di Scienze Mediche Traslazionali, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Procolo Di Bonito
- Dipartimento di Medicina Interna, Ospedale Santa Maria delle Grazie, Pozzuoli, Napoli, Italy
| | - Claudio Maffeis
- Pediatria ad Indirizzo Diabetologico e Malattie del Metabolismo, Università di Verona, Verona, Italy
| | - Giuliana Valerio
- Dipartimento di Scienze Motorie e del Benessere, Università degli Studi di Napoli Parthenope, Naples, Italy
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Navarro-González D, Sánchez-Íñigo L, Pastrana-Delgado J, Fernández-Montero A, Martinez JA. Triglyceride-glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: The Vascular-Metabolic CUN cohort. Prev Med 2016; 86:99-105. [PMID: 26854766 DOI: 10.1016/j.ypmed.2016.01.022] [Citation(s) in RCA: 209] [Impact Index Per Article: 26.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Revised: 01/24/2016] [Accepted: 01/26/2016] [Indexed: 11/16/2022]
Abstract
AIMS We evaluated the potential role of the triglyceride-glucose index (TyG index) as a predictor of diabetes in a White European cohort, and compared it to fasting plasma glucose (FPG) and triglycerides. METHODS 4820 patients of the Vascular-Metabolic CUN cohort (VMCUN cohort) were examined and followed up for 8.84years (±4.39). We performed a Cox proportional hazard ratio with repeated-measures analyses to assess the risk of developing type 2 diabetes across quartiles of FPG, triglycerides and the TyG index (ln[fasting triglycerides (mg/dl)×fasting plasma glucose (mg/dl)/2]), and plotted a receiver operating characteristics (ROC) curve for discrimination. RESULTS There were 332 incident cases of type 2 diabetes involving 43,197.32person-years of follow-up. We observed a progressively increased risk of diabetes in subjects with TyG index levels of 8.31 or more. Among those with normal fasting glucose at baseline, <100mg/dl, subjects with the TyG index in the fourth quartile were 6.87 times more likely to develop diabetes (95% CI, 2.76-16.85; P for trend<0.001), as compared with the bottom quartile. The areas under the ROC curves (95% CI) were 0.75 (0.70-0.81) for TyG index, 0.66 (0.60-0.72) for FPG and 0.71 (0.65-0.77) for TG, in subjects with normal fasting glucose (p=0.017). CONCLUSIONS Our data suggest that the TyG index is useful for the early identification of individuals at risk of type 2 diabetes. The TyG index seems to be a better predictor than FPG or triglycerides of the potential development of type 2 diabetes in normoglycemic patients.
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Affiliation(s)
| | | | - Juan Pastrana-Delgado
- Department of Internal Medicine, University of Navarra Clinic, Pamplona, Spain; IdiSNA - Health Research Institute of Navarra, Spain
| | - Alejandro Fernández-Montero
- Department of Occupational Medicine, Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
| | - J Alfredo Martinez
- IdiSNA - Health Research Institute of Navarra, Spain; Food Science and Physiology, University of Navarra, Pamplona, Spain; Centre of Biomedical Research in Pathophysiology of Obesity and Nutrition (CIBERObn), Carlos III Hospital, Madrid, Spain
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