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Background: Type 2 diabetes (T2D) has been increasing recently in Taiwan which causes 43% of the total population of dialysis. In the present study, our goal was to compare the accuracy of logistic regression (LR) and gradient boosting classification (GBC) of artificial intelligence in predicting diabetes kidney disease (DKD) in a Chinese cohort. Methods: Totally, there were 365 men and 320 women with T2D enrolled and followed for four years. They were further divided into quintiles according to the estimated glomerular filtration rate (eGFR). Both LR and GBC were used to estimate the future DKD. Simple correlation was applied to evaluate the correlation between factors and eGFR at the end of follow-up (eGFR-FU). Sixty percent participants, as training group, were randomly sampled. The others were the validation group. The equations obtained from the training group of both methods are applied to calculate the receiver operation curve (ROC) of the validation group. Results: At the end of the follow-up, the eGFR-FU significantly different in both genders. The baseline eGFR is negatively related to age, duration of T2D, low density lipoprotein, ALT, systolic blood pressure, but positively related to fasting plasma glucose (FPG) and creatinine in men. In women, the relationship of FPG disappears. The ROC for LR is 0.88 and for GBC is 0.97 for men, and 0.82 and 0.94 for women, respectively. Both findings reach statistically significance. Conclusion: In conclusion, GBC could provide a better prediction compared to traditional LR in patients with T2D followed up for 4 years.

The urine albumin–creatinine ratio (uACR) is a warning for the deterioration of renal function in type 2 diabetes (T2D). The early detection of ACR has become an important issue. Multiple linear regression (MLR) has traditionally been used to explore the relationships between risk factors and endpoints. Recently, machine learning (ML) methods have been widely applied in medicine. In the present study, four ML methods were used to predict the uACR in a T2D cohort. We hypothesized that (1) ML outperforms traditional MLR and (2) different ranks of the importance of the risk factors will be obtained. A total of 1147 patients with T2D were followed up for four years. MLR, classification and regression tree, random forest, stochastic gradient boosting, and eXtreme gradient boosting methods were used. Our findings show that the prediction errors of the ML methods are smaller than those of MLR, which indicates that ML is more accurate. The first six most important factors were baseline creatinine level, systolic and diastolic blood pressure, glycated hemoglobin, and fasting plasma glucose. In conclusion, ML might be more accurate in predicting uACR in a T2D cohort than the traditional MLR, and the baseline creatinine level is the most important predictor, which is followed by systolic and diastolic blood pressure, glycated hemoglobin, and fasting plasma glucose in Chinese patients with T2D.

Introduction: Diabetes mellitus (DM) is a known risk factor for tuberculosis (TB), leading to an approximate three-fold higher risk of developing active TB. However, epidemiological studies on the prevalence of latent TB infection (LTBI) in DM patients are lacking. In this study, we investigated the presence of LTBI and determined risk factors for LTBI in DM patients. Methodology: We conducted a cross-sectional study at Taipei Medical University-Shuang Ho Hospital in northern Taiwan. The study population comprised DM patients (aged 20-70 years) attending a metabolism outpatient clinic between February 2011 and February 2013, excluding patients who were suspected or confirmed to have active TB. Venous blood samples were drawn from patients to detect LTBI using the QuantiFERON-TB Gold In-Tube (QFT-GIT) method. Results: We enrolled 1120 patients with DM. The QFT-GIT showed positive results for 241 people (21.5%) and negative results for 879 people (78.5%). The mean age at QFT-GIT positivity was 58.2 years, which was significantly dissimilar to the mean age at QFT-GIT negativity, which was 55.0 years (p < 0.001). Multivariate logistic regression indicated that the trend of QFT-GIT positivity increased after the age of 50 years. Effective glycemic control did not differ significantly between QFT-GIT-positive and -negative patients. Moreover, men were predominant were predominant in both QFT-GIT-positive and -negative patients. Conclusions: More than one-fifth of DM patients have LTBI. Among the DM patients, those older than 50 years may have a higher risk of LTBI. Moreover, effective glycemic control did not differ significantly in patients with LTBI.

Background: High platelet count was noted in people with metabolic syndrome. A significant association between platelet count and various metabolic parameters had also been reported. However, all the studies hypothesized that these associations are linear relationships. This work investigated the potential non-linear relationships between platelet count and various metabolic parameters.Methods: A cross-sectional analysis of data from 11198 non-diabetic, non-obese elderly in a Health Screening Center was undertaken to explore the relationship between platelet count and metabolic parameters, including metabolic syndrome, body mass index, waist circumference, body fat, systolic and diastolic blood pressure, fasting plasma glucose, cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, C-reactive protein, insulin resistance, glucose effectiveness, and first-phase and second-phase insulin secretion. The linear relationship between platelet count and metabolic parameters was examined by linear and logistic regression. The non-linear relationship was investigated by the restricted cubic spline model.Results: Multivariable regression analyses showed that a greater PC level was significantly associated with a greater risk of metabolic syndrome (odds ratio 1.025, 95% CI 1.017 to 1.032), a higher body fat, waist circumference, cholesterol, low-density lipoprotein, triglyceride, C-reactive protein, and insulin resistance, and lower high-density lipoprotein cholesterol and glucose effectiveness. The restricted cubic spline analysis adjusted for age and gender demonstrated a strong non-linearity on the relationship between platelet count and all the metabolic parameters, except systolic blood pressure, diastolic blood pressures, fasting plasma glucose, first-phase insulin secretion, and metabolic syndrome. The overall findings suggested a significant linear relationship between platelet count with the risk of metabolic syndrome, and a significant non-linear relationship between platelet count with many metabolic variables.Conclusions: Platelet count is significantly associated with metabolic syndrome, metabolic parameters, and CRP in a linear or non-linear manner. The overall findings hint potential link between high platelet count, metabolic abnormalities, and chronic inflammatory status.

Background: Both hepatitis B (HB) and nonalcoholic fatty liver disease (NAFLD) are related to metabolic syndrome (MetS); however, this relationship remains controversial. In this study, we determined the effects of NAFLD and HB infection on the risk of MetS among elderly individuals. Methods: In total, 24,500 individuals aged >65 years were enrolled; they were classified into four groups: normal individuals (N), patients with only HB infection without abnormal echogenicity (HB-alone), patients with only abnormal echogenicity or fatty liver alone (FL-alone), and patients with both HB infection and abnormal echogenicity (HB-FL). Results: After adjustment for age, compared with group N, men and women with NAFLD (FL-alone and HB-FL) had a significantly higher risk of MetS, whereas no significant difference was observed in the incidence of MetS between groups HB-alone and N. However, group HB-FL had a lower risk of MetS than did group FL-alone. HB infection (HB-alone and HB-FL) was associated with a lower risk of high triglycerides (TGs) and fasting plasma glucose (FPG) than HB infection absence (groups N and FL-alone) in men and women. Lower risk of TG derangement was observed in group HB-alone than in group N. In addition, both men and women in group HB-FL had a lower risk of TG and FPG abnormalities than in group FL-alone, whereas a decrease in incidence of high waist circumference and blood pressure was observed only in men. Conclusion: HB infection protects against MetS development, only in patients with HB infection and NAFLD, but not in normal individuals. Additional studies are warranted to clarify the pathogenesis.

In recent decades, the obesity epidemic has resulted in morbidity and mortality rates increasing globally. In this study, using obese mouse models, we investigated the relationship among urokinase plasminogen activator (uPA), metabolic disorders, glomerular filtration rate, and adipose tissues. Two groups, each comprised of C57BL/6J and BALB/c male mice, were fed a chow diet (CD) and a high fat diet (HFD), respectively. Within the two HFD groups, half of each group were euthanized at 8 weeks (W8) or 16 weeks (W16). Blood, urine and adipose tissues were collected and harvested for evaluation of the effects of obesity. In both mouse models, triglyceride with insulin resistance and body weight increased with duration when fed a HFD in comparison to those in the groups on a CD. In both C57BL/6J and BALB/c HFD mice, levels of serum uPA initially increased significantly in the W8 group, and then the increment decreased in the W16 group. The glomerular filtration rate declined in both HFD groups. The expression of uPA significantly decreased in brown adipose tissue (BAT), but not in white adipose tissue, when compared with that in the CD group. The results suggest a decline in the expression of uPA in BAT in obese m models as the serum uPA increases. There is possibly an association with BAT fibrosis and dysfunction, which may need further study.

Background Type 2 diabetes (T2D) is known to be one of the most prevalent diseases, and its prevalence is significantly associated with age and metabolic syndrome (MetS). Few studies have been conducted on liver function, MetS and insulin secretion among young adults. Objectives In the present study, we explored the relationship between the liver function enzyme - alanine aminotransferase (ALT) - and first-phase insulin secretion (FPIS) among young adults. Material and methods There were 22,971 men and 28,740 women, aged 18-27 years, assigned to subgroups according to the presence of MetS and quartiles of ALT values. Simple correlation was applied to evaluate their relationship. The difference between the slopes of these relationships and FPIS were statistically analyzed with Chris's calculator. Results Most values for metabolic parameters, including ALT and FPIS, were determined to be relatively high in individuals with MetS. By contrast, individuals with MetS had lower high-density-lipoprotein cholesterol (HDL-C) counts and FPIS. Similar results were observed in the quartiles of ALT. Significant positive results were also found in the linear model. Depending on the ALT level, the slope change of FPIS still demonstrated a positive correlation between ALT and FPIS. This correlation was stronger for men than for women. Conclusions A positive correlation between ALT and FPIS exists among young adults. Moreover, this correlation was stronger for men than for women. Both the cause and the effect require further investigation.

The current standard therapy for metastatic pancreatic cancer is ineffective, necessitating a new treatment approach for prognosis improvement. The urokinase-plasmin activator (uPA) is a critical factor in epithelial-mesenchymal transition (EMT) and cancer metastasis, but its underlying mechanisms in pancreatic cancer remains elusive.We investigated uPA expression in our pancreatic cancer cohort. A bioinformatics approach was used to further determine the role of uPA in pancreatic cancer. We employed MiaPaCa-2 and PANC-1 cell lines to investigate how uPA regulates EMT and metastasis in pancreatic cancer and present a novel approach aimed at inhibiting uPA in pancreatic cancer.We observed that higher uPA mRNA expression was significantly associated with overall-poor survival and progression-free survival in pancreatic cancer. uPA was highly expressed in tumor tissue. Gene set enrichment analysis revealed a positive association between uPA mRNA expression and EMT and transforming growth factor β (TGF-β) signaling pathways. Moreover, shRNA-mediated uPA gene knockdown reduced plasmin, MMP14, and TGF-β activation, leading to the inhibition of PANC-1 cells' EMT marker expression, migration, invasion, and cell viability. Notably, 4-acetyl-antroquinonol B (4-AAQB) treatment suppressed MiaPaCa-2 and PANC-1 cell migratory and invasive abilities by inhibiting the uPA/MMP14/TGF-β axis through upregulation of miR-181d-5p. In the xenograft mouse model of orthotropic pancreatic cancer, 4-AAQB treatment has reduced tumor growth and metastasis rate by deactivating uPA and improving the survival of the mice model.Accordingly, to extent of our knowledge and previous studies, we demonstrated that 4-AAQB is an anti Pan-Cancer drug, and may inhibit pancreatic cancer EMT and metastasis and serve as a new therapeutic approach for patients with late-stage pancreatic cancer.

The Increasing prevalence of type 2 diabetes mellitus (T2DM) has been observed in younger adults. Insulin resistance [IR], decreased first-, second-phase insulin secretion, and glucose effectiveness (GE) (IR, first phase insulin secretion [FPIS], second phase insulin secretion [SPIS], and GE), denoted as diabetes factors (DF), are core for developing T2DM. A body of evidence has shown that inflammation contributes to the development of diabetes. In the present study, our goals were first, evaluate the relationships between white blood cell (WBC) count and, second, examine the relative tightness between the 4 DFs to WBC count. Thus, the pathophysiology of T2DM in Chinese young men could be more understood. 21112 non-obese males between 18 to 27 years old were recruited (mean age: 24.3 ± 0.017), including 1745 subjects with metabolic syndrome. DFs were calculated by the published equations by our groups as follows: IR = log (1.439 + 0.018 × sex - 0.003 × age + 0.029 × body mass index [BMI]- 0.001 × systolic blood pressure [SBP] + 0.006 × diastolic blood pressure + 0.049 × triglycerides [TG] - 0.046 × high-density lipoprotein cholesterol [HDLC] - 0.0116 × fasting plasma glucose [FPG]) × 10 3.3331 FPIS = 10 [1.477 - 0.119 × FPG + 0.079 × BMI - 0.523 × HDLC] 2 SPIS = 10 [-2.4 - 0.088 × FPG + 0.072 × BMI] GE = (29.196 - 0.103 × age - 2.722 × TG - 0.592 × FPG) ×10 −33 The association between DFs and WBC count was analyzed using a simple correlation. The r-values of the simple correlation are regarded as the tightness of the relationships. Higher WBC, FPIS, SPIS, IR, age, BMI, blood pressure, FPG, TG, Cholesterol, low-density lipoprotein cholesterol and lower HDL-C and GE were observed in subjects with metabolic syndrome. A similar trend was seen across the quartiles of WBC levels. Among the 4 DFs, GE has the highest r-value (r = -0.093, P

Cytokines and growth factors participate in immune responses, and the pathogenesis of autoimmune diseases. Herein, we simultaneously examined differential levels of 29 circulating factors to determine their associations in female patients with overt autoimmune thyroid disease (AITD). We enrolled 40 patients with Graves' disease (GD), 20 patients with Hashimoto's thyroiditis (HT), and 14 healthy controls. Twenty-nine circulating factors were simultaneously measured. GD patients with low thyroid-stimulating hormone at the time of sample collection were defined as having active GD. B-cell activating factor (BAFF) levels were associated with GD and HT (

It has been established that prediabetes can causes significant comorbidities, particularly in the elderly. The deterioration of glucose metabolism are generally considered to be results of the impairment of the 4 factors: first, second insulin secretion (FPIS, SPIS, respectively), glucose effectiveness (GE), and insulin resistance. In this study, we enrolled older women to investigate their relationships with prediabetes. Five thousand four hundred eighty-two nonobese, nondiabetic women were included. They were divided into normal glucose tolerance and prediabetes groups. Receiver operating characteristic curve was performed to investigate the effects on whether to have prediabetes for each factors. Two models were built: Model 1: FPIS + SPIS, and Model 2: model 1 + GE. The area under the receiver operating characteristic (aROC) curve was used to determine the predictive power of these models. The aROC curve of GE was significantly higher than the diagonal line followed by SPIS and FPIS accordingly. The aROC curve of Model 1 (0.611) was not different from GE. However, Model 2 improved significantly up to 0.663. Based on this model, an equation was built (−0.003 × GE − 212.6 × SPIS − 17.9 × insulin resistance + 4.8). If the calculated value is equal or higher than 0 (≥0), then the subject has higher chance to have prediabetes (sensitivity = 0.607, specificity = 0.635). Among the 4 factors, GE is the most important contributor for prediabetes in older women. By building a model composed of FPIS, SPIS, and GE, the aROC curve increased significantly. The equation built from this model could predict prediabetes precisely.

Type 2 diabetes mellitus (T2DM) increases coronary artery disease (CAD) risk. In this study, we used T2DM clinical variables to predict abnormality in thallium-201 myocardial perfusion scans (Th-201 scans). These clinical variables were summed stress score (SSS), summed rest score, and summed difference score (SDS), with data obtained from 368 male and 428 female participants with T2DM. Multiple linear regression results were as follows. In male participants, body mass index (BMI) and creatinine (Cr) were associated with SSS (β = 0.224, p

Background Angiogenesis and cytoskeletal transformation are common denominators of many pathological developments. The relationship between angiogenesis, urokinase plasminogen activator receptor (uPAR) signaling pathway, and cytoskeletal transformation is still unknown. In this study, a pGL3-uPAR promoter reporter system combined with Bio-Plex mRNA analysis was established for discovering uPAR modulators to analyze this interconnection. Methods After screening a set of clinically used drugs, atorvastatin (Ator) was found to significantly affect uPAR expression and its ideal dose, 1 μM, was determined for cell study. Mouse endothelial cell (mEC) models, including tube formation for angiogenesis and wound healing assay for migration, were employed to test the effects on angiogenesis and cytoskeletal transformation with (Group Ator) and without (Group C) the treatment of Ator. Results The mEC tube formation and migration was significantly decreased in Group Ator. Regarding cytoskeleton changes, the ratio of F/G actin by Western blotting and the assembly of F-actin (lamellipodia) by immunofluorescence were attenuated. Furthermore, uPAR and all uPAR-related factors, including integrin α5β3, phosphorylated-focal adhesion kinase, and Rac, revealed a significant reduction when compared with Group C. Conclusion We conclude that close regulatory machinery spans angiogenesis, uPAR signaling, and cytoskeletal transformation, and that uPAR modulator Ator can decrease the reorganization of actin cytoskeleton, which may lead to a new approach in angiogenesis.

Background: The relationship between urokinase-type plasminogen activator (uPA) and the development of type 2 diabetes mellitus (T2DM) was investigated in the study by using mice and cell models, as well as patients with T2DM. Methods: In mice models, wild-type and uPA knockout (uPA-/-) BALB/c mice were used for induction of T2DM. In cell models, insulin secretion rate and &beta, cell proliferation were assessed in normal and high glucose after treating uPA siRNA, uPA, or anti-uPA antibody. In our clinical study, patients with T2DM received an oral glucose-tolerance test, and the relationship between uPA and insulin secretion was assessed. Results: Insulin particles and insulin secretion were mildly restored one month after induction in wild-type mice, but not in uPA-/- mice. In cell models, insulin secretion rate and cell proliferation declined in high glucose after uPA silencing either by siRNA or by anti-uPA antibody. After treatment with uPA, &beta, cell proliferation increased in normal glucose. In clinical study, patients with T2DM and higher uPA levels had better ability of insulin secretion than those with lower uPA levels. Conclusion: uPA may play a substantial role in insulin secretion, &beta, cell regeneration, and progressive development of T2DM. Supplementation of uPA might be a novel approach for prevention and treatment of T2DM in the future.

Background: This study evaluated the relative influence of insulin resistance (IR), first-phase insulin secretion (FPIS), second-phase insulin secretion (SPIS), and glucose effectiveness (...

Although it is known that high uric acid (UA) level is associated with type 2 diabetes (T2DM) and metabolic syndrome (MetS), most of the previous studies were focused on adults. Since aging becomes a major problem for many societies, in this longitudinal study, we investigated the role of UA in future T2DM and MetS in a large cohort of people who were older than 65 years. A cross-sectional and longitudinal study. 18,907 elderly (9,732 men, 9,175 women) aged above 65 years, enrolled from health check-up centers, were classified into three subgroups by 10-year intervals (young old 65-74 years, YO; old old 75-84 years, OO; and oldest old 85-94 years, ODO), with the average follow-up period of 4.3 years. The optimal cut-off values (CoVs) of baseline UA to predict future MetS and T2DM were determined by receiving operating characteristic (ROC) curve analysis. Using these CoVs of UA, the participants were divided into normal- and high-level groups of UA. Cox proportional hazard analysis was used to calculate hazard ratios (HRs) for the subjects with a high level of UA for the risk of future MetS and T2DM. In addition, Kaplan-Meier plots and log rank test were used to evaluate the time effect on the incidence of developing MetS and T2DM between the two groups. In ROC curve analysis, the optimal CoVs of baseline UA were 6.0, 6.3 and 6.7 mg/dl in YO, OO, and ODO men, respectively; 5.5 and 4.9 mg/dl in YO and OO women, respectively (all p < 0.05). However, the CoVs of UA in ODO women (6.1 mg/dl) failed to show its discriminant power (p = 0.13). The Cox regression analysis showed the YO subjects with a higher baseline level of UA had a higher risk of developing MetS (HRs 1.56 and 1.58 for men and women, respectively, both p < 0.001); as for T2DM the HRs were 1.39 and 1.57. In OO men, the HRs was 1.89 for developing future MetS. However, no significant findings could be noted in the ODO group. Kaplan-Meier plots and log rank test also showed the same findings. Our study showed that old subjects with high levels of UA will have a higher chance to have MetS and T2DM, particularly in the YO group (6.0 mg/dl for men and 5.5 mg/dl for women, respectively). Using UA as one of the metabolic biomarkers may help clinicians to early detect and prevent MetS and diabetes.

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Elevated levels of C-reactive protein (CRP) and alanine aminotransferase (ALT) are tightly associated with metabolic syndrome (MetS). However, it is unclear whether the combination of normal CRP and ALT increases probability of the presence of MetS.We enrolled 433 Chinese in health screening with both CRP and ALT in normal range. They were divided into four groups: both low (BL, both low baseline CRP and ALT), only high CRP (HCRP), only high ALT (HALT), and both high (BH, both high baseline CRP and ALT) in different genders. The receiver operating characteristic curve was used for comparing the sensitivity and assessing the cutoff point.The BH group had more numbers of MetS components than the BL group. Addition of CRP and ALT did not further increase the accuracy of predicting MetS with a sensitivity of 65.1% and a specificity of 59.1% in men, and a sensitivity of 77.8% and a specificity of 60.2% in women. The area under curve for ALT was greater than that for CRP (0.62 vs. 0.524 in men; 0.663 vs. 0.598 in women). After adjusting for age, ALT could significantly predict the incidental MetS in both genders; nevertheless, CRP failed to demonstrate prediction. The formula of probability of occurrence of MetS was established on CRP and ALT.Healthy subjects with high baseline ALT may be at risk of developing MetS, and early recognition and prevention are important for health providers. We concluded that local liver inflammation is significantly associated with the presence of MetS compared with systemic inflammation in health screening subjects.

We investigated the role of urokinase plasminogen activator (uPA) and its soluble receptors (suPAR) and plasminogen activator inhibitor-1 (PAI-1) in metabolic syndrome (MetS) components, insulin secretion, and resistance in schoolchildren. We enrolled 387 children, aged 10.3 ± 1.5 years, in Taipei. Anthropometry, fibrinolytic proteins, MetS components, insulin secretion, and resistance were measured. Subjects were divided into normal, overweight, and obese groups. Finally, the relationship between fibrinolytic proteins and metabolic syndrome in boys and girls was analyzed. In boys, PAI-1 was positively associated with body mass index (BMI) percentile, hypertriglyceride, insulin secretion, and resistance. In girls, PAI-1 was positively associated with obesity, hypertriglyceridemia, and insulin secretion. In girls, uPA was positively associated with insulin secretion. suPAR was positively associated with high-sensitivity C-reactive protein in both boys and girls, and with BMI percentile and body fat in girls. The obese boys had higher suPAR and PAI-1 levels than the normal group. The obese girls had higher uPA, suPAR, and PAI-1 than the normal group. Boys and girls with MetS had higher PAI-1. Fibrinolytic proteins, especially PAI-1, are associated with MetS components and insulin secretion in children. Fibrinolytic proteins changes were more likely to occur in girls than in boys.

Metabolic syndrome (MetS) includes obesity, dyslipidemia, elevated blood pressure, and dysglycemia. Subjects with type 2 diabetes (T2D) exhibit features of MetS. The etiology of MetS is complex, involving both environmental and genetic factors. In this study, we examined the role of specific candidate genetic variants on the severity of MetS in T2D subjects. A total of 240 T2D subjects aged 35-64 years were recruited. Waist circumstance, plasma triglycerides, high-density lipoprotein cholesterol, fasting plasma glucose, and blood pressure were measured to define MetS. Subjects were divided into 4 groups according to MetS components. Target genes involved in fibrotic and inflammatory processes, insulin and diabetes, cell growth and proliferation, and hypertension were genotyped. A total of 13 genes and 103 single-nucleotide polymorphisms (SNPs) were analyzed to evaluate their genetic association with MetS severity in T2D subjects. Univariate ordinal logistic regression using a dominant model (homozygous for the major allele vs carriers of the minor allele) revealed 6 SNP markers within 4 genes with genotypes associated with MetS risk. For the SNP genotypes of rs362551 (SNAP25), rs3818569 (RXRG), rs1479355, rs1570070 (IGF2R), and rs916829 (ABCC8), heterozygotes showed a lower risk of MetS compared with the reference group. In addition, the CC genotype was comparable to the TT genotype for rs3777411. There was no gender-specific effect. In conclusion, our results suggest that among the Han Chinese population, several SNPs increase the risk of severe MetS in T2D subjects. Further study in a large population should be conducted.

Serum gamma-glutamyltransferase (γ-GT) is implicated in the pathogenesis of atherosclerosis and metabolic syndrome (MetS) in adults. The relationships between γ-GT and cardiometabolic dysregulation remains unclear in adolescents. We enrolled 7,072 Taiwanese adolescents and followed them for a median of 6.8 years. The optimal cut-off values (CoVs) of baseline γ-GT to predict future MetS, hypertension (HTN), and type 2 diabetes (T2DM) were determined by receiving operating characteristic (ROC) curve. Using these CoVs, the participants were divided into normal- and high-level groups. Cox proportional hazard analysis was used to calculate hazard ratios (HRs) for the subjects with a high level of γ-GT for the risk of future cardiometabolic dysregulation. Serum γ-GT was significantly higher in the subjects with MetS than in those without MetS at baseline (p

Background Although uric acid (UA) is not in the definition of metabolic syndrome (MetS), several studies had shown the positive correlation between UA and MetS. Due to the progress in the public health, the aging of the general population becomes a major issue. However, the aforementioned relationship between UA and MetS is not fully explored in elderly group. To fill up this deficient piece of knowledge, we enrolled Chinese elderly to shed light on the relationships between UA levels and MetS. Methods We randomly selected subjects aged 65 and older undergoing routine health checkups in Taiwan. After excluding subjects with taking medications known to affect components of MetS or UA, a total of 27,553 Chinese were eligible for analysis. All the participants were further divided into four groups according to the UA level. Results All the MetS components were significantly lower in the UA1 group. In simple correlation, all the MetS components were also correlated with UA. However, age and blood pressure became non-significant in multiple regressions. Compared to UA1, all the other 3 groups had higher odds ratio for MetS. Conclusion Higher UA level have higher rate of having MetS in Chinese elderly. UA could be regard as an ancillary tool for the awareness of MetS.

Decreased insulin sensitivity (IS) and impaired insulin secretion are major pathological features of type 2 diabetes (T2DM). The product of these factors is the disposition index (DI). We aimed to develop an equation for predicting DI. We enrolled 167 participants in our study. We randomly assigned 126 (75%) of the participants to the study group, whose data would be used to build the equation for estimating the DI. The remaining 41 participants comprised the external validation group. A frequently sampled intravenous glucose-tolerance test was performed for all participants, and the IS, the glucose sensitivity, the acute insulin response to the glucose load, and the DI were determined. Three factors were selected from multiple linear regression analysis, and we constructed the equation log (DI) = 2.449 - 0.113 × fasting plasma glucose + 0.046 × body mass index - 0.612 × high-density lipoprotein cholesterol. Using this equation, the calculated log (DI) significantly correlated with the measured log (DI) in the external validation group (r = 0.428, p = 0.007). By using the equation based on the demographic data and measurements of metabolic syndrome components, the DI could be predicted with acceptable accuracy (r = 0.428). Because of the relationships between the MetS and demographic parameters, this method of predicting DI may help further clinicians' understanding of the underlying pathological mechanisms in T2DM.

Aims/Introduction How to measure insulin resistance (IR) accurately and conveniently is a critical issue for both clinical practice and research. In the present study, we tried to modify the β-cell function, insulin sensitivity, and glucose tolerance test (BIGTT) in patients with normal glucose tolerance (NGT) and abnormal glucose tolerance (AGT) by oral glucose tolerance test (OGTT) and metabolic syndrome (MetS) components. Materials and Methods There were 327 participants enrolled and divided into NGT or AGT. Data from 75% of the participants were used to build the models, and the remaining 25% were used for external validation. Steady-state plasma glucose (SSPG) concentration derived from the insulin suppression test was regarded as the standard measurement for IR. Five models were built from multiple regression: model 1 (MetS model with sex, age and MetS components); model 2 (simple OGTT model with sex, age, plasma glucose, and insulin concentrations at 0 and 120 min during OGTT); model 3 (full OGTT model with sex, age, and plasma glucose and insulin concentrations at 0, 30, 60, 90, 120, and 180 min during OGTT); model 4 (simple combined model): model 1 and model 2; and model 5 (full model): model 1 and 3. Results In general, our models had higher r2 compared with surrogates derived from OGTT, such as homeostasis model assessment-insulin resistance and quantitative insulin sensitivity check index. Among them, model 5 had the highest r2 (0.505 in NGT, 0.556 in AGT, respectively). Conclusions Our modified BIGTT models proved to be accurate and easy methods for estimating IR, and can be used in clinical practice and research.