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Aim: Overweight and obesity are important risk factors of gestational diabetes mellitus (GDM). Clustering of metabolic risk factors in early pregnancy may be a potential pathogenesis between the link of overweight/obesity and GDM. Since it remains unexplored, we investigated if overweight and obesity are associated with clustering of metabolic risk factors in early pregnancy and the risk of GDM in this cohort study., Methods: Total 527 women who visited National Taiwan University Hospital for prenatal care in between November 2013 to April 2018 were enrolled. Risk factors of GDM in the first prenatal visit (FPV) were recorded. Overweight/obesity was defined if body mass index ≥24 kg/m2. GDM was diagnosed from the result of a 75g oral glucose tolerance test in 24-28 gestational weeks., Results: Overweight/obesity was associated with clustering of metabolic risk factors of GDM, including high fasting plasma glucose, high HbA1c, insulin resistance, high plasma triglyceride and elevated blood pressure in FPV (p<0.05). There was a positive relationship between the number of metabolic risk factors and the incidence of GDM (p <0.05). The odds ratios of HbA1c and diastolic blood pressure were higher in overweight/obese women, compared with those in normal-weight women., Conclusions: Overweight/obesity is associated with clustering of metabolic risk factors in early pregnancy, which is correlated with higher risk of GDM. Our findings suggest that metabolic risk factors during early pregnancy should be evaluated in overweight/obese women., Competing Interests: The authors have declared that no competing interests exist.

Objective: Using a specific cutoff of fasting plasma glucose (FPG) to screen gestational diabetes mellitus (GDM) can reduce the use of oral glucose tolerance tests (OGTT). Since the prevalence of GDM increases with age, this screening method may not be appropriate in healthcare systems where women become pregnant at older ages. Therefore, we aimed to develop a screening algorithm for GDM that takes maternal age into consideration., Methods: We included 945 pregnant women without history of GDM who received 75g OGTT to diagnose GDM in 2011. Screening algorithms using FPG with or without age were developed. Another 362 pregnant women were recruited in 2013-2015 as the validation cohort., Results: Using FPG criteria alone, more GDM diagnoses were missed in women ≥35 years than in women <35 years (13.2% vs. 5.8%, p <0.001). Among GDM women ≥35 years, 63.6% had FPG <92 mg/dL (5.1 mmol/L). Use of the algorithm with an "age plus FPG" cutoff could reduce the use of OGTT (OGTT%) from 77.6% to 62.9%, while maintaining good sensitivity (from 91.9% to 90.2%) and specificity (from 100% to 100%). Similar reduction in OGTT% was found in the validation cohort (from 86.4% to 76.8%). In the simulation, if the percentage of women ≥35 years were 40% or more, the screening algorithm with an "age plus FPG" cutoff could further reduce OGTT% by 11.0%-18.8%., Conclusions: A screening algorithm for GDM that takes maternal age into consideration can reduce the use of OGTT when women become pregnant at older ages.

The ALDH2 gene encodes the mitochondrial aldehyde dehydrogenase 2 (ALDH2), a critical enzyme involved in ethanol clearance through acetaldehyde metabolism. ALDH2 also catalyzes the metabolism of other bioreactive aldehydes, including propionaldehyde, butyraldehyde, and 4-hydroxykenals (4-HNE). Increased levels of 4-HNE in adipose tissue positively correlate with obesity and insulin resistance. However, it remains unclear whether ALDH2 is involved in regulation of adipocyte differentiation. Here, we found that ALDH2 protein levels were lower in white adipose tissue of high-fat diet-fed mice and ob/ob mice relative to lean mice. Knockdown of ALDH2 expression in 3T3-L1 preadipocytes caused an increase in intracellular 4-HNE, thereby attenuated adipocyte differentiation. By contrast, an ALDH2 activator, Alda-1, significantly accelerated adipogenesis, which was accompanied by an increase in adipogenic gene expression. Consistently, adipogenesis was reduced when protein kinase C ε (PKCε), an ALDH2 phosphorylating activator, was silenced in 3T3-L1 preadipocytes, whereas treatment with a PKCε agonist in 3T3-L1 preadipocytes enhanced adipogenesis. Whole-genome microarray profiling of Alda-1-treated cells demonstrated several upregulated transcripts encoding proteins involved in metabolism and the majority of these transcripts are for proteins involved in PPAR signaling pathways. Furthermore, PKCε-ALDH2 interaction alleviates 4-HNE induced aberrant PPARγ regulation on adipogenesis. Taken together, these results demonstrate that ALDH2 activation enhances adipogenesis and signaling pathways involving PPARγ. Thus, activation of PKCε-ALDH2 regulatory axis may be a therapeutic target for treating obesity and type 2 diabetes., Competing Interests: The authors have declared that no competing interests exist.

By means of a combination of genome-wide and follow-up studies, recent large-scale association studies of populations of European descent have now identified over 46 loci associated with coronary artery disease (CAD). As part of the TAICHI Consortium, we have collected and genotyped 8556 subjects from Taiwan, comprising 5423 controls and 3133 cases with coronary artery disease, for 9087 CAD SNPs using the CardioMetaboChip. We applied penalized logistic regression to ascertain the top SNPs that contribute together to CAD susceptibility in Taiwan. We observed that the 9p21 locus contributes to CAD at the level of genome-wide significance (rs1537372, with the presence of C, the major allele, the effect estimate is -0.216, standard error 0.033, p value 5.8x10-10). In contrast to a previous report, we propose that the 9p21 locus is a single genetic contribution to CAD in Taiwan because: 1) the penalized logistic regression and the follow-up conditional analysis suggested that rs1537372 accounts for all of the CAD association in 9p21, and 2) the high linkage disequilibrium observed for all associated SNPs in 9p21. We also observed evidence for the following loci at a false discovery rate >5%: SH2B3, ADAMTS7, PHACTR1, GGCX, HTRA1, COL4A1, and LARP6-LRRC49. We also took advantage of the fact that penalized methods are an efficient approach to search for gene-by-gene interactions, and observed that two-way interactions between the PHACTR1 and ADAMTS7 loci and between the SH2B3 and COL4A1 loci contribute to CAD risk. Both the similarities and differences between the significance of these loci when compared with significance of loci in studies of populations of European descent underscore the fact that further genetic association of studies in additional populations will provide clues to identify the genetic architecture of CAD across all populations worldwide.

Background: Diabetes is the leading cause of end-stage renal disease (ESRD) worldwide. Vascular adhesion protein-1 (VAP-1) participates in inflammation and catalyzes the deamination of primary amines into aldehydes, hydrogen peroxide, and ammonia, both of which are involved in the pathogenesis of diabetic complications. We have shown that serum VAP-1 is higher in patients with diabetes and in patients with chronic kidney disease (CKD), and can predict cardiovascular mortality in subjects with diabetes. In this study, we investigated if serum VAP-1 can predict ESRD in diabetic subjects., Methods: In this prospective cohort study, a total of 604 type 2 diabetic subjects were enrolled between 1996 to 2003 at National Taiwan University Hospital, Taiwan, and were followed for a median of 12.36 years. The development of ESRD was ascertained by linking our database with the nationally comprehensive Taiwan Society Nephrology registry. Serum VAP-1 concentrations at enrollment were measured by time-resolved immunofluorometric assay., Results: Subjects with serum VAP-1 in the highest tertile had the highest incidence of ESRD (p<0.001). Every 1-SD increase in serum VAP-1 was associated with a hazard ratio of 1.55 (95%CI 1.12-2.14, p<0.01) for the risk of ESRD, adjusted for smoking, history of cardiovascular disease, body mass index, hypertension, HbA1c, duration of diabetes, total cholesterol, use of statins, ankle-brachial index, estimated GFR, and proteinuria. We developed a risk score comprising serum VAP-1, HbA1c, estimated GFR, and proteinuria, which could predict ESRD with good performance (area under the ROC curve = 0.9406, 95%CI 0.8871-0.9941, sensitivity = 77.3%, and specificity = 92.8%). We also developed an algorithm based on the stage of CKD and a risk score including serum VAP-1, which can stratify these subjects into 3 categories with an ESRD risk of 0.101%/year, 0.131%/year, and 2.427%/year, respectively., Conclusions: In conclusion, serum VAP-1 can predict ESRD and is a useful biomarker to improve risk stratification in type 2 diabetic subjects.

Prostaglandin reductase 2 (PTGR2) is the enzyme that catalyzes 15-keto-PGE2, an endogenous PPARγ ligand, into 13,14-dihydro-15-keto-PGE2. Previously, we have reported a novel oncogenic role of PTGR2 in gastric cancer, where PTGR2 was discovered to modulate ROS-mediated cell death and tumor transformation. In the present study, we demonstrated the oncogenic potency of PTGR2 in pancreatic cancer. First, we observed that the majority of the human pancreatic ductal adenocarcinoma tissues was stained positive for PTGR2 expression but not in the adjacent normal parts. In vitro analyses showed that silencing of PTGR2 expression enhanced ROS production, suppressed pancreatic cell proliferation, and promoted cell death through increasing 15-keto-PGE2. Mechanistically, silencing of PTGR2 or addition of 15-keto-PGE2 suppressed the expressions of solute carrier family 7 member 11 (xCT) and cystathionine gamma-lyase (CTH), two important providers of intracellular cysteine for the generation of glutathione (GSH), which is widely accepted as the first-line antioxidative defense. The oxidative stress-mediated cell death after silencing of PTGR2 or addition of 15-keto-PGE2 was further abolished after restoring intracellular GSH concentrations and cysteine supply by N-acetyl-L-cysteine and 2-Mercaptomethanol. Our data highlight the therapeutic potential of targeting PTGR2/15-keto-PGE2 for pancreatic cancer.

In the diagnosis of diabetes mellitus, hemoglobin A1c (HbA1c) is sometimes measured to determine the need of an oral glucose tolerance test (OGTT). However, HbA1c does not accurately reflect glycemic status in certain conditions. This study was performed to test the possibility that measurement of serum glycated albumin (GA) better assesses the need for OGTT. From 2006 to 2012, 1559 subjects not known to have diabetes or to use anti-diabetic medications were enrolled. Serum GA was measured, and a 75-g OGTT was then performed to diagnose diabetes. Serum GA correlated significantly to age (r = 0.27, p<0.001), serum albumin (r = -0.1179, age-adjusted p = 0.001), body mass index (r = -0.24, age-adjusted p<0.001), waist circumference (r = -0.16, age-adjusted p<0.001), and plasma GA (r = 0.999, p<0.001), but was unaffected by diet (p = 0.8). Using serum GA at 15% for diagnosis of diabetes, the sensitivity, specificity, and area under the receiver-operating characteristic curve were 74%, 85%, and 0.86, respectively. Applying a fasting plasma glucose (FPG) value of < 100 mg/dL to exclude diabetes and of ≥ 126 mg/dL to diagnose diabetes, 14.4% of the study population require an OGTT (OGTT%) with a sensitivity of 78.8% and a specificity of 100%. When serum GA value of 14% and 17% were used to exclude and diagnose diabetes, respectively, the sensitivity improved to 83.3%, with a slightly decrease in specificity (98.2%), but a significant increase in OGTT% (35%). Using combined FPG and serum GA cutoff values (FPG < 100 mg/dL plus serum GA < 15% to exclude diabetes and FPG ≥ 126 mg/dL or serum GA ≥ 17% to diagnose diabetes), the OGTT% was reduced to 22.5% and the sensitivity increased to 85.6% with no change in specificity (98.2%). In the diagnosis of diabetes, serum GA measurements can be used to determine the need of an OGTT.

Background: The liver plays a key role in fuel metabolism. It is well established that liver disease is associated with an increased risk for diabetes mellitus. Hepatitis C virus infection has been known to increase the risk of diabetes. However, much less is known about the role of hepatitis B virus (HBV) infection in diabetes. We examined the association of diabetes based on the vaccination status for HBV., Methods: In this cross-sectional study, we included adult subjects (≥20 y/o) with HBV serology available from the National Health and Nutrition Examination Survey 2005-2010. Diabetes was defined as established diabetes or fasting plasma glucose concentration ≥7.0 mmol/L, 2-hour plasma glucose concentration ≥11.1 mmol/L, or HbA1c ≥ 47.5 mmol/mol (6.5%). Vaccination was based on the reported history and immunization was determined by HBV serology. The odds ratio (OR) with 95% confidence intervals (95% CI) were calculated with consideration of the following covariates: age, gender, BMI, ethnic/racial group, current smoker, current alcohol consumption, family history of diabetes, poverty index, and education., Results: This study included 15,316 subjects. Among them, 2,320 subjects was immunized based the HBV serology. Among 4,063 subjects who received HBV vaccination, successful vaccination was only noted in 39% of subjects. The HBV vaccination was not associated with diabetes (OR: 1.08, 95%CI: 0.96-1.23). Serology evidence of HBV immunization was associated with a reduced OR of diabetes (0.75, 95%CI: 0.62-0.90). Successful HBV vaccination was also associated with a reduced OR of diabetes (0.67, 95%CI: 0.52-0.84)., Conclusions: Although our study shows the association of HBV vaccination with the reduced odds of diabetes by 33%, a prospective study is warranted to confirm and examine the impact of HBV vaccination in prevention of diabetes.

Objectives: Growth arrest-specific 6 (Gas6), a vitamin K-dependent protein, has been implicated in systemic inflammation, obesity, and insulin resistance (IR). Data from recent studies suggest that polymorphisms in the Gas6 gene are associated with cardiovascular disorders and type 2 diabetes (T2D). However, the association of Gas6 gene variants with obesity, IR, and T2D development has not been explored., Materials and Methods: Four common single nucleotide polymorphisms (SNPs) in the Gas6 gene were genotyped in 984 participants from the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe) family cohort. An insulin suppression test was performed to determine IR based on steady-state plasma glucose (SSPG). Associations between IR indices and obesity, and SNP genotypes, based on previously-reported data for this cohort (Phase I), were analyzed. In the present follow-up study (Phase II), the effects of gene variants of Gas6 on the progression to T2D were explored in individuals who were free of T2D in Phase I. The mean follow-up period for Phase II was 5.7 years., Results: The mean age of the study population in Phase I was 49.5 years and 16.7% of individuals developed T2D during follow-up. After adjusting for covariates, three SNPs (rs8191973, rs8197974, and rs7323932) were found to be associated with SSPG levels (p = 0.007, p = 0.03, and p = 0.011, respectively). This association remained significant after multiple testing and showed a significant interaction with physical activity for SNP rs8191973. However, no other significant correlations were observed between Gas6 polymorphisms and other indices of IR or obesity. A specific haplotype, AACG (from rs8191974, rs7323932, rs7331124, and rs8191973), was positively associated with SSPG levels (p = 0.0098). None of the polymorphisms were associated with an increased risk of T2D development., Conclusions: Our results suggest that Gas6 gene variants are associated with IR, although their effects on subsequent progression to T2D were minimal in this prospective Asian cohort.

Multi-channel magnetocardiography (MCG) is a sensitive technique to map spatial ventricular repolarization with high resolution and reproducibility. Spatial ventricular repolarization heterogeneity measured by MCG has been shown to accurately detect and localize myocardial ischemia. Here, we explored whether these measurements correlated with cardiovascular risk factors in patients with type 2 diabetes. Two hundreds and seventy-seven type 2 diabetic patients without known coronary artery disease (CAD) and arrhythmia were recruited consecutively from the outpatient clinic of National Taiwan University Hospital. The spatially distributed QTc contour maps were constructed with 64-channel MCG using the superconducting quantum interference device (SQUID) system. Indices of myocardial repolarization heterogeneity including the smoothness index of QTc (SI-QTc) and QTc dispersion were derived and analyzed for association with conventional cardiovascular risk factors. SI-QTc correlated strongly with the QTc dispersion (r = 0.70, p <0.0001). SI-QTc was significantly higher in patients with presence of metabolic syndrome in comparison to those without metabolic syndrome (8.56 vs. 7.96 ms, p = 0.02). In univariate correlation analyses, QTc dispersion was associated with smoking status (average 79.90, 83.83, 86.51, and 86.00 ms for never smokers, ex-smokers, current smokers reporting less than 10 cigarettes daily, and current smoker reporting more than 10 cigarettes daily, respectively, p = 0.03), body weight (r = 0.15, p = 0.01), and hemoglobin A1c (r = 0.12, p = 0.04). In stepwise multivariate regression analyses, QTc dispersion was associated with smoking (p = 0.02), body weight (p = 0.04), total cholesterol levels (p = 0.05), and possibly estimated glomerular filtration rate (p = 0.07). In summary, spatial heterogeneity of myocardial repolarization measured by MCG is positively associated cardiovascular risk factors including adiposity, smoking, and total cholesterol levels.

Objective: Whether retroperitoneal fat should be included in the measurement of visceral fat remains controversial. We compared the relationships of fat areas in peritoneal, retroperitoneal, and subcutaneous compartments to metabolic syndrome, adipokines, and incident hypertension and diabetes., Methods: We enrolled 432 adult participants (153 men and 279 women) in a community-based cohort study. Computed tomography at the umbilicus level was used to measure the fat areas., Results: Retroperitoneal fat correlated significantly with metabolic syndrome (adjusted odds ratio (OR), 5.651, p<0.05) and the number of metabolic abnormalities (p<0.05). Retroperitoneal fat area was significantly associated with blood pressure, plasma glycemic indices, lipid profile, C-reactive protein, adiponectin (r =  -0.244, P<0.05), and leptin (r = 0.323, p<0.05), but not plasma renin or aldosterone concentrations. During the 2.94 ± 0.84 years of follow-up, 32 participants developed incident hypertension. Retroperitoneal fat area (hazard ration (HR) 1.62, p = 0.003) and peritoneal fat area (HR 1.62, p = 0.009), but not subcutaneous fat area (p = 0.14) were associated with incident hypertension. Neither retroperitoneal fat area, peritoneal fat area, nor subcutaneous fat areas was associated with incident diabetes after adjustment., Conclusions: Retroperitoneal fat is similar to peritoneal fat, but differs from subcutaneous fat, in terms of its relationship with metabolic syndrome and incident hypertension. Retroperitoneal fat area should be included in the measurement of visceral fat for cardio-metabolic studies in human.

In this paper we try to define insulin resistance (IR) precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI) or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ), a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT). We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with "main effects" is not satisfactory, but prediction that includes interactions may be.

Background: Several genome-wide association studies (GWAS) involving European populations have successfully identified risk genetic variants associated with type 2 diabetes mellitus (T2DM). However, the effects conferred by these variants in Han Chinese population have not yet been fully elucidated., Methods: We analyzed the effects of 24 risk genetic variants with reported associations from European GWAS in 3,040 Han Chinese subjects in Taiwan (including 1,520 T2DM cases and 1,520 controls). The discriminative power of the prediction models with and without genotype scores was compared. We further meta-analyzed the association of these variants with T2DM by pooling all candidate-gene association studies conducted in Han Chinese., Results: Five risk variants in IGF2BP2 (rs4402960, rs1470579), CDKAL1 (rs10946398), SLC30A8 (rs13266634), and HHEX (rs1111875) genes were nominally associated with T2DM in our samples. The odds ratio was 2.22 (95% confidence interval, 1.81-2.73, P<0.0001) for subjects with the highest genetic score quartile (score>34) as compared with subjects with the lowest quartile (score<29). The incoporation of genotype score into the predictive model increased the C-statistics from 0.627 to 0.657 (P<0.0001). These estimates are very close to those observed in European populations. Gene-environment interaction analysis showed a significant interaction between rs13266634 in SLC30A8 gene and age on T2DM risk (P<0.0001). Further meta-analysis pooling 20 studies in Han Chinese confirmed the association of 10 genetic variants in IGF2BP2, CDKAL1, JAZF1, SCL30A8, HHEX, TCF7L2, EXT2, and FTO genes with T2DM. The effect sizes conferred by these risk variants in Han Chinese were similar to those observed in Europeans but the allele frequencies differ substantially between two populations., Conclusion: We confirmed the association of 10 variants identified by European GWAS with T2DM in Han Chinese population. The incorporation of genotype scores into the prediction model led to a small but significant improvement in T2DM prediction.

Unlabelled: Circadian clock genes are critical regulators of energy homeostasis and metabolism. However, whether variation in the circadian genes is associated with metabolic phenotypes in humans remains to be explored. In this study, we systemically genotyped 20 tag single nucleotide polymorphisms (SNPs) in 8 candidate genes involved in circadian clock, including CLOCK, BMAL1(ARNTL), PER1, PER2, CRY1, CRY2, CSNK1E,, and NOC(CCRN4L) in 1,510 non-diabetic Chinese subjects in Taipei and Yunlin populations in Taiwan. Their associations with metabolic phenotypes were analyzed. We found that genetic variation in the NOC gene, rs9684900 was associated with body mass index (BMI) (P = 0.0016, Bonferroni corrected P = 0.032). Another variant, rs135764 in the CSNK1E gene was associated with fasting glucose (P = 0.0023, Bonferroni corrected P = 0.046). These associations were consistent in both Taipei and Yunlin populations. Significant epistatic and joint effects between SNPs on BMI and related phenotypes were observed. Furthermore, NOC mRNA levels in human abdominal adipose tissue were significantly increased in obese subjects compared to non-obese controls., Conclusion: Genetic variation in the NOC gene is associated with BMI in Chinese subjects.

Genes, environment, and the interaction between them are each known to play an important role in the risk for developing complex diseases such as metabolic syndrome. For environmental factors, most studies focused on the measurements observed at the individual level, and therefore can only consider the gene-environment interaction at the same individual scale. Indeed the group-level (called contextual) environmental variables, such as community factors and the degree of local area development, may modify the genetic effect as well. To examine such cross-level interaction between genes and contextual factors, a flexible statistical model quantifying the variability of the genetic effects across different categories of the contextual variable is in need. With a Bayesian generalized linear mixed-effects model with an unconditional likelihood, we investigate whether the individual genetic effect is modified by the group-level residential environment factor in a matched case-control metabolic syndrome study. Such cross-level interaction is evaluated by examining the heterogeneity in allelic effects under various contextual categories, based on posterior samples from Markov chain Monte Carlo methods. The Bayesian analysis indicates that the effect of rs1801282 on metabolic syndrome development is modified by the contextual environmental factor. That is, even among individuals with the same genetic component of PPARG&#95;Pro12Ala, living in a residential area with low availability of exercise facilities may result in higher risk. The modification of the group-level environment factors on the individual genetic attributes can be essential, and this Bayesian model is able to provide a quantitative assessment for such cross-level interaction. The Bayesian inference based on the full likelihood is flexible with any phenotype, and easy to implement computationally. This model has a wide applicability and may help unravel the complexity in development of complex diseases.

Background: 3T3-L1 cells are widely used to study adipogenesis and insulin response. Their adipogenic potential decreases with time in the culture. Expressing exogenous genes in 3T3-L1 cells can be challenging. This work tries to establish and characterize an alternative model of cultured adipocytes that is easier to work with than the 3T3-L1 cells., Methodology/principal Findings: INDUCED CELLS WERE IDENTIFIED AS ADIPOCYTES BASED ON THE FOLLOWING THREE CHARACTERISTICS: (1) Accumulation of triglyceride droplets as demonstrated by oil red O stain. (2) Transport rate of 2-deoxyglucose increased after insulin stimulation. (3) Expression of fat specific genes such as Fabp4 (aP2), Slc2a4 (Glut4) and Pparg (PPARγ). Among the cell lines induced under different conditions in this study, only NIH/3T3 cells differentiated into adipocytes after prolonged incubation in 3T3-L1 induction medium containing 20% instead of 10% fetal bovine serum. Rosiglitazone added to the induction medium shortened the incubation period from 14 to 7 days. The PI3K/AKT pathway showed similar changes upon insulin stimulation in these two adipocytes. C/EBPα mRNA was barely detectable in NIH/3T3 adipocytes. NIH/3T3 adipocytes induced in the presence of rosiglitazone showed higher 2-deoxyglucose transport rate after insulin stimulation, expressed less Agt (angiotensinogen) and more PPARγ. Knockdown of C/EBPα using shRNA blocked 3T3-L1 but not NIH/3T3 cell differentiation. Mouse adipose tissues from various anatomical locations showed comparable levels of C/EBPα mRNA., Conclusions/significance: NIH/3T3 cells were capable of differentiating into adipocytes without genetic engineering. They were an adipocyte model that did not require the reciprocal activation between C/EBPα and PPARγ to differentiate. Future studies in the C/EBPα independent pathways leading to insulin responsiveness may reveal new targets to diabetes treatment.

Objective: Frailty is an important geriatric syndrome. Adiponectin is an important adipokine that regulates energy homeostasis. The aim of this study is to investigate the relationship between plasma adiponectin levels and frailty in elders., Methods: The demographic data, body weight, metabolic and inflammatory parameters, including plasma glucose, total cholesterol, triglyceride, tumor necrosis factor alpha (TNF-α), c-reactive protein (CRP) and adiponectin levels, were assessed. The frailty score was assessed using the Fried Frailty Index (FFI)., Results: The mean (SD) age of the 168 participants [83 (49.4%) men and 85 (50.6%) women] was 76.86 (6.10) years. Judged by the FFI score, 42 (25%) elders were robust, 92 (54.7%) were pre-frail, and 34 (20.3%) were frail. The mean body mass index was 25.19 (3.42) kg/m(2). The log-transformed mean (SD) plasma adiponectin (µg/mL) level was 1.00 (0.26). The log-transformed mean plasma adiponectin (µg/mL) levels were 0.93 (0.23) in the robust elders, 1.00 (0.27) in the pre-frail elders, and 1.10 (0.22) in the frail elders, and the differences between these values were statistically significant (p  = 0.012). Further analysis showed that plasma adiponectin levels rose progressively with an increasing number of components of frailty in all participants as a whole (p for trend  = 0.024) and males (p for trend  = 0.037), but not in females (p for trend  = 0.223)., Conclusion: Plasma adiponectin levels correlate positively with an increasing number of components of frailty in male elders. The difference between the sexes suggests that certain sex-specific mechanisms may exist to affect the association between adiponectin levels and frailty.

Background: Preclinical and observational studies raise the concern about the safety of insulin glargine in terms of cancer initiation and promotion. This study is designed to examine cancer incidence associated with use of insulin glargine vs. intermediate/long-acting human insulin (HI)., Methodology: A retrospective cohort study using the Taiwan National Health Insurance claims database was conducted to identify adult patients with type 2 diabetes mellitus and without a history of cancer who initiated insulin glargine (n = 10,190) or intermediate/long-acting HI (n = 49,253) during 2004-2007. Exclusive users were followed from the date of insulin initiation to the earliest of cancer diagnosis, death, disenrollment, or December 31 2007. We estimated adjusted hazard ratios and 95% confidence intervals (CIs) with Cox proportional hazards models adjusting for baseline propensity score., Findings: The incidence rate of all cancer per 1,000 person-years was 13.8 for insulin glargine initiators (179 cases) and 16.0 for intermediate/long-acting HI initiators (1,445 cases) during an average follow-up of 2 years. No significant difference in overall cancer risk between insulin glargine initiators and HI initiators was found. For men, however, the adjusted hazard ratio of insulin glargine use as compared with intermediate/long-acting HI was 2.15 (95% CI 1.01-4.59) for pancreatic cancer, and 2.42 (95% CI 1.50-8.40) for prostate cancer. The increased risk was not observed among women., Conclusions: Insulin glargine use did not increase the risk of overall cancer incidence as compared with HI. The positive associations with pancreatic and prostate cancer need further evaluation and validation.