Impact of Type 2 Diabetes on Nonalcoholic Steatohepatitis and Advanced Fibrosis in Patients with Nonalcoholic Fatty Liver Disease

Objective: Type 2 diabetes mellitus (T2DM) is a risk factor for nonalcoholic fatty liver disease (NAFLD). The aim of this study was to investigate the effect of T2DM on nonalcoholic steatohepatitis (NASH) and advanced fibrosis.Methods: A total of 221 NAFLD patients who had undergone a liver biopsy were included in this study. Subjects were divided into a non-T2DM group and a T2DM group based on glycemic control. NASH was diagnosed by the joint presence of steatosis, ballooning, and lobular inflammation. The steatosis, activity, and fibrosis (SAF) score and NAFLD activity score (NAS) were used to evaluate the severity of NAFLD. The severity of liver fibrosis was evaluated based on the fibrosis stage.Results: The total percentages of NASH and advanced fibrosis in this study were 95.0% and 50.2%, respectively. The percentages of NASH and advanced fibrosis in NAFLD patients with T2DM were 96.1% and 56.5%, respectively, which were higher than those in the non-T2DM group. SAF score (especially activity and fibrosis stage) and NAS (especially ballooning) were higher in NAFLD patients with T2DM than in NAFLD patients without T2DM. Glycemic control and insulin resistance were positively associated with SAF, NAS, and fibrosis stage. Additionally, T2DM elevated the risk of a high NAS and advanced fibrosis.Conclusion: T2DM increases the risk of serious NASH and advanced fibrosis in patients with NAFLD. Liver biopsy can be performed in NAFLD patients with T2DM to confirm the stage of NAFLD. Screening of NASH and advanced fibrosis in NAFLD patients with T2DM is needed.Abbreviations: ALT = alanine aminotransferase; APO = apolipoprotein; AST = aspartate aminotransferase; BMI = body mass index; CI = confidence interval; FPG = fasting plasma glucose; GGT = gamma-glutamyl transferase; HbA1c = hemoglobin A1c; HDL-c = high-density-lipoprotein cholesterol; ¹H-MRS = proton magnetic resonance spectroscopy; HOMA-IR = homeostasis model assessment of insulin resistance; 2hPG = postprandial plasma glucose at 2 hours; LDL-c = low-density-lipoprotein cholesterol; LFC = liver fat content; NAFLD = nonalcoholic fatty liver disease; NAS = NAFLD activity score; NASH = nonalcoholic steatohepatitis; OGTT = oral glucose tolerance test; OR = odds ratio; T2DM = type 2 diabetes mellitus; TC = total cholesterol; TG = triglyceride; SAF = steatosis, activity, and fibrosis; US-FLI = ultrasonographic fatty liver indicator     

Clinical Profile of Nonalcoholic Fatty Liver Disease Among Young Patients With Type 1 Diabetes Mellitus Seen at a Diabetes Speciality Center in India

ObjectiveTo estimate the prevalence and clinical profile of nonalcoholic fatty liver disease (NAFLD) among young type 1 diabetes mellitus (T1DM) patients at a tertiary care diabetes center in India.MethodsElectronic medical records of T1DM patients (age at first diagnosis of T1DM ≤ 25 years) registered between January 1992 and May 2013 who had undergone ultrasonography and denied history of any alcohol intake (n = 736) were reviewed. NAFLD was diagnosed if there was any degree of fatty liver. Retinopathy was initially assessed by direct and indirect ophthalmoscopy and later by retinal photography. Nephropathy was diagnosed if urine protein excretion was > 500 mg/day, and neuropathy was diagnosed if a patient’s vibration perception threshold on biothesiometry was ≥ 20 V.ResultsA total of 204/736 (27.7%) T1DM patients had NAFLD. Compared to T1DM subjects without NAFLD those with NAFLD had higher body mass index (BMI) (18.9 ± 4.2 vs. 20.2 ± 4.7 kg/m², P < .001), waist circumference (67.9 ± 13.2 vs. 71.9 ± 13.3 cm, P < .05), systolic blood pressure (110 ± 15 vs. 116 ± 18 mm Hg, P < .001) and diastolic blood pressure (72 ± 9 vs. 74 ± 10 mm Hg, P < .05), while fasting blood glucose (201 ± 101 vs. 183 ± 101 mg/dL, P < .05) and alkaline phosphatase (419 [12.5] vs. 315 [15.8], P < .001) levels were lower in patients with T1DM with NAFLD. Multiple logistic regression analysis showed a significant association between NAFLD and retinopathy (odds ratio [OR]: 2.01, 95% confidence interval [CI]: 1.13-3.43; P = .017, after adjusting for sex, duration of diabetes, overweight/obesity, hypertension, fasting plasma glucose, nephropathy, and nephropathy (OR: 1.89, 95% CI: 1.02-3.50; P = .042), after adjusting for sex and fasting plasma glucose.ConclusionsThis study suggests that NAFLD is also seen among T1DM patients and that it has an independent and significant association with retinopathy and nephropathy. (Endocr Pract. 2014;20:1249-1257)     

Gallstone disease is associated with more severe liver damage in patients with non-alcoholic Fatty liver disease

Background

Nonalcoholic fatty liver disease (NAFLD) and gallstone disease (GD) are both highly prevalent in the general population and associated with obesity and insulin resistance. We aimed to evaluate the prevalence of GD in a cross sectional study of NAFLD patients and to define whether the presence of GD is associated with diabetes and predicts more severe liver disease.

Methodology/Principal Findings

We merged databases of four Liver Units, comprising 524 consecutive biopsy-proven NAFLD (373 males) observed between January 2003 and June 2010. GD was diagnosed in 108 (20%), and 313 cases (60%) were classified by liver biopsy as nonalcoholic steatohepatitis (NASH). The GD subgroup was characterized by a significantly higher prevalence of females, prediabetes/diabetes, abdominal obesity and metabolic syndrome, older age, higher BMI, fasting glucose, HOMA-IR and lower ALT. The prevalence of GD progressively increased with advancing fibrosis and with the severity of necroinflammatory activity (p for trend  = 0.0001 and  = 0.01, respectively), without differences in the severity of steatosis. At multivariate analysis GD was associated with female gender (OR 1.37, 95% CI 1.04–1.8), age (OR 1.027, 95% CI1.003–1.05), fasting glucose (OR 1.21, 95% CI 1.10–1.33) and NASH (OR 1.40,95% CI 1.06–1.89), whereas ALT levels were associated with a lower GD risk (OR 0.98, 95% CI 0.97–0.99). When subjects with cirrhosis were excluded from analysis, the association between GD and fasting glucose, female gender, and NASH was maintained.

Conclusion

Patients with NAFLD have a high prevalence of GD, which characterizes subjects with altered glucose regulation and more advanced liver disease.     

Total Body Adiposity,Triglycerides, and Leg Fat are Independent Risk Factors for Diabetic Peripheral Neuropathy in Chinese Patients with type 2 Diabetes Mellitus

Objective: To evaluate the risk factors associated with diabetic peripheral neuropathy (DPN) in Chinese patients with type 2 diabetes mellitus (T2DM).Methods: Between January 2014 and December 2017, 107 participants who had obesity with T2DM and 349 participants who had normal weight with T2DM, matched for age, sex, and duration of diabetes, were recruited. The clinical and biochemical parameters were measured in each patient. DPN was diagnosed based on neuropathy symptom score and neuropathy deficit score. Motor and sensory nerve conduction velocities were measured by electromyography. Body fat mass was estimated by dual-energy X-ray absorptiometry, while hepatic steatosis was evaluated by ultrasonography.Results: The group with obesity had a significant higher prevalence of DPN (66.62%) than that (46.99%) of the group with normal weight. Compared to the patients with normal weight, the sural sensory nerve in the right lower limbs of the patients with obesity was more susceptible to damage. Hypertriglyceridemia in the patients with obesity was a significant independent risk factor for DPN (odds ratio &lsqb;OR], 3.90 &lsqb;95% confidence interval (CI), 1.01 to 15.02]; P = .04), while the duration of diabetes (OR, 1.33 &lsqb;95% CI, 1.07 to 1.65]; P<.01) and leg subcutaneous fat mass (OR, 0.72 &lsqb;95% CI, 0.57 to 0.90]; P<.01) in the patients with normal weight were independent risk factors for DPN. The presence of obesity alone in patients with T2DM could predict high DPN risk (OR, 3.09 &lsqb;95% CI, 1.11 to 8.65]; P = .04).Conclusion: Reducing total body adiposity and triglyceride levels, as well as avoiding leg subcutaneous fat atrophy, could be new prevention strategies for DPN in Chinese patients with T2DM.Abbreviations: ALB = albumin; ALT = alanine transaminase; AST = aspartate transaminase; AUC = area under the curve; AUCc-p/AUCglu = AUC of C-peptide/AUC of glucose; BMI = body mass index; BP = blood pressure; CI = confidence interval; Cr = creatinine; DBP = diastolic blood pressure; DPN = diabetic peripheral neuropathy; FC-P = fasting C-peptide; FPG = fasting plasma glucose; FFA = free fatty acid; γ-GGT = γ-glutamyl transferase; HbA1c = glycated hemoglobin A1c; HDL-C = high-density-lipoprotein cholesterol; ISI = insulin sensitivity index; ISSI-2 = insulin secretion-sensitivity index-2; LDL-C = low-density-lipoprotein cholesterol; MNCS = motor nerve conduction velocity; OGTT = oral glucose tolerance test; PG = plasma glucose; SAT = subcutaneous adipose tissue; SBP = systolic blood pressure; SNCS = sensory nerve conduction velocity; T2DM = type 2 diabetes mellitus; TC = total cholesterol; TG = triglyceride; UA = uric acid; VAT = visceral adipose tissue; WC = waist circumference     

Relative Contributions of Ectopic Liver and Abdominal Fat Accumulation to Arterial Stiffness

Objective: To compare the arterial stiffness between the abdominal obese population without nonalcoholic fatty liver disease (NAFLD) (referred to as abdominal fat accumulation), the normal-weight population with NAFLD (ectopic liver fat accumulation), and the population with both abdominal obesity and NAFLD (accumulation of both abdominal and ectopic liver fat).Methods: A total of 111,552 Chinese adults who underwent the health checkups from January 2012 to December 2012 were screened. Clinical and biochemical parameters were measured in each subject. NAFLD was diagnosed by ultrasonography. Arterial stiffness was evaluated by cardio-ankle vascular index (CAVI).Results: Normal-weight subjects with NAFLD had significantly higher CAVI than subjects with abdominal obesity with or without NAFLD (8.12 ± 1.16 vs. 7.93 ± 1.38, 7.96 ± 1.20; P<.01). When the presence of abdominal obesity, NAFLD, and both diseases (abdominal obesity and NAFLD) were included in regression analyses individually, CAVI was independently associated with abdominal obesity or NAFLD or both after adjusting for confounders. When the presence of abdominal obesity and NAFLD and both diseases were included simultaneously in regression analyses, the association between NAFLD and CAVI and the association between both diseases and CAVI remained significant, whereas the association between abdominal obesity and CAVI was no longer significant. The presence of NAFLD conferred a greater odds ratios of having an elevated CAVI than did the presence of abdominal obesity or even the presence of both diseases.Conclusion: Ectopic liver fat accumulation is associated with greater risk of arterial stiffness compared with abdominal fat accumulation or accumulation of both abdominal and ectopic liver fat.Abbreviations: ALT = alanine aminotransferase AST = aspartate aminotransferase BMI = body mass index CAVI = cardioankle vascular index CI = confidence interval Cr = creatinine FFA = free fatty acid FPG = fasting plasma glucose ?-GGT = ?-glutamyl transferase HDL-C = high-density-lipoprotein cholesterol LDL-C = lowdensity-lipoprotein cholesterol NAFLD = nonalcoholic fatty liver disease OR = odds ratio TC = total cholesterol TG = triglyceride UA = uric acid WC = waist circumference     

Prognostic Value of Non-Invasive Fibrosis and Steatosis Tools,Hepatic Venous Pressure Gradient (HVPG) and Histology in Nonalcoholic Steatohepatitis

Background & Aims

Non-invasive diagnostic methods for liver fibrosis predict clinical outcomes in viral hepatitis and nonalcoholic fatty liver disease (NAFLD). We specifically evaluated prognostic value of non-invasive fibrosis methods in nonalcoholic steatohepatitis (NASH) against hepatic venous pressure gradient (HVPG) and liver histology.

Methods

This was a retrospective cohort study of 148 consecutive patients who met the following criteria: transjugular liver biopsy with HVPG measurement; biopsy-proven NASH; absence of decompensation; AST-to-Platelets Ratio Index (APRI), fibrosis-4 (FIB-4), NAFLD fibrosis score, ultrasound, hepatic steatosis index and Xenon-133 scan available within 6 months from biopsy; a minimum follow-up of 1 year. Outcomes were defined by death, liver transplantation, cirrhosis complications. Kaplan–Meier and Cox regression analyses were employed to estimate incidence and predictors of outcomes, respectively. Prognostic value was expressed as area under the curve (AUC).

Results

During a median follow-up of 5 years (interquartile range 3-8), 16.2% developed outcomes, including 7.4% who died or underwent liver transplantation. After adjustment for age, sex, diabetes, the following fibrosis tools predicted outcomes: HVPG >10mmHg (HR=9.60; 95% confidence interval [CI] 3.07-30.12), histologic fibrosis F3-F4 (HR=3.14; 1.41-6.95), APRI >1.5 (HR=5.02; 1.6-15.7), FIB-4 >3.25 (HR=6.33; 1.98-20.2), NAFLD fibrosis score >0.676 (HR=11.9; 3.79-37.4). Prognostic value was as follows: histologic fibrosis stage, AUC=0.85 (95% CI 0.76-0.93); HVPG, AUC=0.81 (0.70-0.91); APRI, AUC=0.89 (0.82-0.96); FIB-4, AUC=0.89 (0.83-0.95); NAFLD fibrosis score, AUC=0.79 (0.69-0.91). Neither histologic steatosis nor non-invasive steatosis methods predicted outcomes (AUC<0.50).

Conclusions

Non-invasive methods for liver fibrosis predict outcomes of patients with NASH. They could be used for serial monitoring, risk stratification and targeted interventions.     

Association Of Peripheral 5-Hydroxyindole-3-Acetic Acid,A Serotonin Derivative,with Metabolic Syndrome and Low-Grade Inflammation

Objective: The constellation of metabolic abnormalities seen in metabolic syndrome (MetS) has been linked to atherosclerosis and adverse cardiovascular outcomes due to heightened inflammation. Accumulating evidence suggests that peripheral 5-hydroxyindole-3-acetic acid (5-HIAA), the derivative end-product of serotonin (5-HT), might be involved in the pathogenesis of obesity, and abnormal lipid and glucose metabolism. We examined the association between serum 5-HIAA concentrations and MetS and also highly sensitive C-reactive protein (hsCRP).Methods: We assessed 180 healthy adults (110 males and 70 females) in a cross-sectional setting. Anthropometric indices and blood pressure were measured, as were laboratory parameters including fasting 5-HIAA concentrations. The associations between 5-HIAA and individual components of MetS, as well as MetS as a single entity, were investigated with bivariate correlation and logistic regression analyses.Results: Eighty-nine individuals (49.4%) were diagnosed with MetS. Significant correlations were found between 5-HIAA concentrations and age (r = 0.184), waist circumference (r = 0.415), high-density lipoprotein (HDL) cholesterol (r = -0.148), systolic blood pressure (r = 0.374), diastolic blood pressure (r = 0.355), homeostasis model assessment of insulin resistance (r = 0.201), and hsCRP (r = 0.453) were found (P<.05 in all tests). In logistic regression, 5-HIAA was significantly associated with 4 MetS components including central obesity, raised triglycerides, raised blood pressure, and raised fasting plasma glucose (FPG) (P<.05). Moreover, 5-HIAA was a predictor of MetS as a single entity, and the relationship persisted after adjusting for hsCRP (odds ratio [OR] = 4.41, 95% confidence interval [CI]: 2.58-7.67, P<.001).Conclusion: Elevated concentrations of 5-HIAA are seen in individuals with MetS. Increased 5-HIAA is also associated with hsCRP, a marker of chronic lowgrade inflammation underlying MetS.Abbreviations: BMI = body mass index CI = confidence interval FI = fasting insulin FPG = fasting plasma glucose HbA1c = glycated hemoglobin HDL = high-density lipoprotein 5-HIAA = 5-hydroxyindole-3-acetic acid 5-HT = 5-hydroxytryptamine HOMA-IR = homeostatic model assessment of insulin resistance hsCRP = highly sensitive C-reactive protein LDL = low-density lipoprotein MetS = metabolic syndrome OR = odds ratio     

Glycated Albumin at 4 Weeks Correlates with A1C Levels at 12 Weeks and Reflects Short-Term Glucose Fluctuations

Objective: Evaluate the performance of glycated albumin (GA) monitoring by comparing it to other measures of glycemic control during intensification of antidiabetic therapy.Methods: This 12-week, prospective, multicenter study compared the diagnostic clinical performance of GA to glycated hemoglobin A1C (A1C), fructosamine corrected for albumin (FRA), fasting plasma glucose (FPG), and mean blood glucose (MBG) estimated from self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) in 30 patients with suboptimally controlled type 1 or 2 diabetes.Results: Mean A1C decreased from 9.5% to 8.1%. Mean SMBG correlated closely with CGM (Pearson r = 0.783 for daily estimates and r = 0.746 for weekly estimates, P<.0001). Both GA and FRA levels significantly correlated with changes from baseline in A1C and mean weekly SMBG (P<.001). The lowest observed median GA occurred at 4 weeks, followed by a small increase and then a slight reduction, mirroring changes in overall mean SMBG values. The median A1C fell throughout the treatment period, failing to reflect short-term changes in SMBG. A ≥1% reduction in GA at 4 weeks was significantly associated with a ≥0.5% change in A1C at 12 weeks (odds ratio &lsqb;OR] = 19.0, 95% confidence interval &lsqb;CI]: 1.4, 944, P = .018).Conclusion: In patients receiving glucose-lowering therapy, changes in GA at 4 weeks were concordant with changes in A1C at 12 weeks, and both GA and FRA more accurately reflected short-term blood glucose fluctuations than A1C.Abbreviations: A1C = glycated hemoglobin A1C ARIC = Atherosclerosis Risk in Communities CGM = continuous glucose monitoring FPG = fasting plasma glucose FRA = fructosamine corrected for albumin GA = glycated albumin MBG = mean blood glucose OR = odds ratio SMBG = self-monitoring of blood glucose     

Prevalence and predictors of non-alcoholic fatty liver disease in tertiary care hospital of Taif,Saudi Arabia: A retrospective study

BackgroundThe prevalence of nonalcoholic fatty liver disease (NAFLD) in Saudi Arabia is predicted to exceed 30% by 2030. NAFLD leads to liver fibrosis, thus increasing morbidity and health care burden. Obesity and diabetes have been strongly associated with NAFLD in different cities in Saudi Arabia.ObjectivesTherefore, we aim to determine the prevalence rate of NAFLD and specific risk factors for NAFLD among patients of tertiary care hospital of Taif city.Material and methodsWe retrospectively analyzed the medical records of patients for two years, between Feb 2017 and Feb 2019, (n = 100) referred to the hepatology clinic at King Abdulaziz Specialist Hospital in Taif. The diagnosis of NAFLD was based on the radiology report for patients who were aged >20 years old. Other parameters including fasting blood glucose (FBG), platelets count, alanine transaminase (ALT), aspartate transaminase (AST) and total bilirubin were statistically analyzed.ResultsWe found that 40% (P < 0.05) of all patients had NAFLD. The results revealed that a significantly high number of patients with NAFLD have high FBG levels (75%, P < 0.0001) and total bilirubin (P < 0.05). Meanwhile, platelet count was significantly reduced in patients with NAFLD (P < 0.05).ConclusionNAFLD can be a serious health problem in the Taif region. In addition, high FBG is a significant specific risk factor for NAFLD. Health care providers should pay more attention to limiting the prevalence of NAFLD and its risk factors.     

Relationship of Adipokines and Proinflammatory Cytokines Among Asian Indians With Obesity and Youth Onset Type 2 Diabetes

Objective: It is well known that inflammation is associated with diabetes, but it is unclear whether obesity mediates this association in individuals with youth-onset type 2 diabetes mellitus (T2DM-Y).Methods: We recruited individuals with T2DM-Y (age at onset <25 years) and age-matched normal glucose tolerance (NGT) subjects. Participants were further classified using Asia-Pacific body mass index cut-points for obesity and categorized as: nonobese NGT (n = 100), Obese NGT (n = 50), nonobese T2DM-Y (n = 50), and obese T2DM-Y (n = 50). We compared adipokines (adiponectin and leptin) and proinflammatory cytokines (tumor necrosis factor alpha &lsqb;TNF-α] and monocyte chemotactic protein-1 &lsqb;MCP-1]) across groups.Results: Compared to nonobese NGT, the other 3 groups (obese NGT, nonobese T2DM-Y, and obese T2DM-Y) were found to have lower adiponectin (7.7 vs. 5.7, 4.2, 3.8 μg/mL, P<.01), and higher leptin (3.6 vs. 5.4, 5.7, 7.9 μg/mL, P<.001) and MCP 1 (186 vs. 272, 340, 473 pg/mL, P<.001) respectively. However, TNF-α levels were higher only among nonobese T2DM-Y (112 pg/mL) and obese T2DM-Y (141 pg/mL, P<.01 for each). After adjusting for age, sex, waist, hypertension, homeostatic model assessment of insulin resistance (HOMA-IR), serum cholesterol, triglycerides, and family history of diabetes, adiponectin was associated with 33% and 41% lower odds of being nonobese T2DM and obese T2DM, respectively. However, adjusted for same factors, leptin, TNF-α, and MCP-1 were associated with markedly higher odds (5- to 14-fold) of nonobese and obese T2DM.Conclusion: In young Asian Indians, leptin and proinflammatory cytokines are positively, and adiponectin negatively, associated with both nonobese and obese T2DM-Y compared to nonobese NGT individuals.Abbreviations: BMI = body mass index CI = confidence interval FPG = fasting plasma glucose HOMA-IR = homeostatic model assessment of insulin resistance IGT = impaired glucose tolerance MCP-1 = monocyte chemotactic protein-1 NGT = normal glucose tolerance OGTT = oral glucose tolerance test OR = odds ratio T2DM-Y = youth-onset type 2 diabetes TNF-α = tumor necrosis factor-α     

The Association Between First-Degree Family History of Diabetes and Metabolic Syndrome

Objective: Because they share genetic and environmental factors with patients with diabetes, the first-degree relatives (FDRs) of patients with diabetes exhibit early signs of metabolic abnormalities. The present study aimed to investigate the correlation between family history of diabetes in FDRs and metabolic syndrome (MS), as well as changes in related risk factors.Methods: The present study population was a part of the baseline survey from the REACTION study. FDRs were defined as individuals having one or more FDRs with diabetes. MS and its components were defined according to the 2007 Joint Committee for Developing Chinese Guidelines.Results: A total of 2,692 individuals with an average age of 57.24 ± 8.35 years were enrolled in the present study. The prevalence of MS in FDRs (36.44%) was significantly higher than that in non-FDRs (25.28%; P<.001). FDRs accounted for 13.37%, 14.32%, 16.67%, 22.47%, 23.53%, and 25.58% of subjects with 0 to 5 MS components, showing an increasing trend (P for trend <.001). After adjusting for gender and age, partial correlation analyses showed significant associations of first-degree family history of diabetes with MS-related indexes (all P<.05). After adjusting for gender, age, lifestyle habits, and total metabolic traits, the first-degree family history of diabetes remained an independent factor that was positively associated with MS (odds ratio, 1.765; P<.001).Conclusion: A first-degree family history of diabetes predisposes individuals to developing MS and stands out as an independent risk factor for MS even without considering the subsequent effects of hyperglycemia.Abbreviations: BMI = body mass index; DBP = diastolic blood pressure; FDR = first-degree relative; FPG = fasting plasma glucose; HbA1c = glycated hemoglobin A1c; HDL-c = high-density-lipoprotein cholesterol; LDL-c = low-density-lipoprotein cholesterol; MAP = mean arterial pressure; MS = metabolic syndrome; OR = odds ratio; SBP = systolic blood pressure; TC = total cholesterol; TG = triglyceride; WC = waist circumference; WHR = waist-to-hip ratio; 2hPG = 2-hour plasma glucose     

Altered Circulating Levels of Retinol Binding Protein 4 and Transthyretin in Relation to Insulin Resistance,Obesity, and Glucose Intolerance in Asian Indians

Objective: Retinol binding protein 4 (RBP4) has been implicated in metabolic disorders including type 2 diabetes mellitus (T2DM), but few studies have looked at transthyretin (TTR) with which RBP4 is normally bound to in the circulation. We report on the systemic levels of RBP4 and TTR and their associations with insulin resistance, obesity, prediabetes, and T2DM in Asian Indians.Methods: Age-matched individuals with normal glucose tolerance (NGT, n = 90), impaired glucose tolerance (IGT, n = 70) and T2DM (n = 90) were recruited from the Chennai Urban Rural Epidemiology Study (CURES). Insulin resistance was estimated using the homeostasis model assessment of insulin resistance (HOMA-IR). RBP4 and TTR levels were measured by enzyme-linked immunosorbent assay (ELISA).Results: Circulatory RBP4 and TTR levels (in μg/mL) were highest in T2DM (RBP4: 13 ± 3.9, TTR: 832 ± 310) followed by IGT (RBP4: 10.5 ± 3.2; TTR: 720 ± 214) compared to NGT (RBP4: 8.7 ± 2.5; TTR: 551 ± 185; P<.001). Compared to nonobese NGT individuals, obese NGT, nonobese T2DM, and obese T2DM had higher RBP4 (8.1 vs. 10.6, 12.1, and 13.2 μg/mL, P<.01) and TTR levels (478 vs. 737, 777, and 900 μg/mL, P<.01). RBP4 but not TTR was significantly (P<.001) correlated with insulin resistance even among NGT subjects. In regression analysis, RBP4 and TTR showed significant associations with T2DM after adjusting for confounders (RBP4 odds ratio [OR]: 1.107, 95% confidence interval [CI]: 1.008–1.216; TTR OR: 1.342, 95% CI: 1.165–1.547).Conclusion: Circulatory levels of RBP4 and TTR showed a significant associations with glucose intolerance, obesity, T2DM and RBP4 additionally, with insulin resistance.Abbreviations: BMI = body mass index CI = confidence interval HDL = high-density lipoprotein IGT = impaired glucose tolerance LDL = low-density lipoprotein NGT = normal glucose tolerance OGTT = oral glucose tolerance test OR = odds ratio RBP4 = retinol binding protein 4 T2DM = type 2 diabetes mellitus TTR = transthyretin WC = waist circumference     

Gestational Weight Gain as an Independent Risk Factor for Macrosomia in Women with Intermediate State Gestational Blood Glucose

Objective: Macrosomia is closely associated with gestational diabetes mellitus (GDM) but its relationship with maternal intermediate state gestational blood glucose (ISGBG; normal fasting blood glucose and 7.8 mmol/L <1 hour blood glucose &lsqb;BG] <10 mmol/L or 6.7 mmol/L <2 hour BG <8.5 mmol/L) is unclear. Here, we analyzed the clinical characteristics and pregnancy outcomes and explored risk factors for macrosomia in women with ISGBG.Methods: A total of 847 women with normal glucose tolerance gestation, 330 with ISGBG, and 99 with GDM were included. Maternal and fetal clinical data were collected and 3-point BG following oral glucose tolerance test, fasting insulin, glycated hemoglobin, and blood lipids profile were measured.Results: The incidence rate of macrosomia among the neonates of women with ISGBG was as high as 10.9%. In the ISGBG group, prepregnancy body mass index (BMI), gestational weight gain (GWG) and the proportion of women with excessive GWG (eGWG) were significantly higher in women with macrosomia compared with those who delivered a normal weight neonate. In women with ISGBG, neonate weight was positively correlated with maternal prepregnancy weight (r = 0.183, P<.01), prepregnancy BMI (r = 0.135, P<.01), and GWG (r = 0.255, P<.01), and negatively correlated with high-density lipoprotein cholesterol (r = -0.172, P<.01). Nonetheless, only eGWG was an independent risk factor (odds ratio = 3.18, 95% confidence interval = 1.26 to 7.88, P<.05) for macrosomia. The risk of macrosomia in pregnant women with prepregnancy BMI <25 kg/m² or BMI ≥25 kg/m² and eGWG was 3.39 and 3.27 times, respectively.Conclusion: The incidence rate of macrosomia is increased in women with ISGBG and eGWG is the strongest independent risk factor. In order to reduce the risk for macrosomia, timely lifestyle intervention to promote appropriate weight gain during pregnancy deserves evaluation.Abbreviations: AUC = area under the curve; BG = blood glucose; 1 hour BG = 1 hour blood glucose after OGTT; 2 hour BG = 2 hour blood glucose after OGTT; BMI = body mass index; CI = confidence interval; eGWG = excessive gestational weight gain; FBG = fasting blood glucose; FINS = fasting insulin; GDM = gestational diabetes mellitus; HbA1c = glycated hemoglobin; HDL-C = high-density lipoprotein cholesterol; HOMA-IR = homeostasis model assessment of insulin resistance index; ISGBG = intermediate state gestation blood glucose; LDL-C = low-density lipoprotein cholesterol; Ln = natural logarithm; MLBW = mature low birth weight; NGTG = normal glucose tolerance gestation; OGTT = oral glucose tolerance test; OR = odds ratio; SD = standard deviation     

Real-World Improvements in Hypoglycemia in an Insulin-Dependent Cohort With Diabetes Mellitus Pre/Post Tandem Basal-Iq Technology Remote Software Update

Objective: Software updatable insulin pumps, such as the t:slim X2 pump from Tandem Diabetes Care, enable access to new technology as soon as it is commercialized. The remote software update process allows for minimal interruption in therapy compared to purchasing a new pump; however, little quantitative data exist on the software update process or on pre/post therapeutic outcomes. We examined real-world usage and impact of a remote software updatable predictive low-glucose suspend (PLGS) technology designed to reduce hypoglycemic events in people with insulin-dependent diabetes.Methods: Approximately 15,000 U.S. Tandem pump users remotely updated their t:slim X2 software to Basal-IQ PLGS technology since its commercial release. We performed a retrospective analysis of users who uploaded at least 21 days of pre/post PLGS update usage data to the Tandem t:connect web application between August 28, 2018, and October 21, 2019 (N = 6,170). Insulin delivery and sensor-glucose values were analyzed per recent international consensus and American Diabetes Association guidelines. Software update performance was also assessed.Results: Median software update time was 5.36 minutes. Overall glycemic outcomes for pre and post software update showed a decrease in sensor time <70 mg/dL from 2.14 to 1.18% (-1.01; 95% confidence interval &lsqb;CI], -0.97, -1.05; P<.001), with overall sensor time 70 to 180 mg/dL increasing from 57.8 to 58.5% (0.64; 95% CI, 0.04, 1.24; P<.001). These improvements were sustained at 3, 6, and 9 months after the update.Conclusion: Introduction of a software updatable PLGS algorithm for the Tandem t:slim X2 insulin pump resulted in sustained reductions of hypoglycemia.Abbreviations: ADA = American Diabetes Association; CGM = continuous glucose monitoring; CI = confidence interval; PLGS = predictive low-glucose suspend; SG = sensor glucose; T1D = type 1 diabetes; T2D = type 2 diabetes; TIR = time-in-range     

Triglyceride Levels and Not Adipokine Concentrations Are Closely Related to Severity of Nonalcoholic Fatty Liver Disease in an Obesity Surgery Cohort

Although nonalcoholic fatty liver disease (NAFLD) is frequent in obesity, the metabolic determinants of advanced liver disease remain unclear. Adipokines reflect inflammation and insulin resistance associated with obesity and may identify advanced NAFLD. At the time of obesity surgery, 142 consecutive patients underwent liver biopsy and had their preoperative demographic and clinical data obtained. Liver histology was scored by the NAFLD activity score, and patients subdivided into four groups. Concentrations of retinol‐binding protein 4 (RBP4), adiponectin, tumor necrosis factor‐α (TNF‐α), and leptin were determined ～1 week prior to surgery and results were related to liver histology. The prevalence of no NAFLD was 30%, simple steatosis 23%, borderline nonalcoholic steatohepatitis (NASH) 28%, and definitive NASH 18%. Type 2 diabetes mellitus (T2DM) and metabolic syndrome (MS) prevalence were 39 and 75%, respectively, and did not differ across the four histological groups (P = NS). Triglyceride (TG) and alanine transaminase (ALT) levels, strongly associated with advanced stages of NAFLD and NASH (P = 0.04). TG levels >150 mg/dl, increased the likelihood of NASH 3.4‐fold, whereas high‐density lipoprotein (HDL) levels predicted no NAFLD (P < 0.01). Concentrations of TNF‐α, leptin, and RBP4 did not differ among histological groups and thus did not identify NASH; however, there was a trend for adiponectin to be lower in NASH vs. no NAFLD (P = 0.061). In summary, both TG and ALT levels assist in identification of NASH in an obesity surgery cohort. These findings underscore the importance of fatty acid delivery mechanisms to NASH development in severely obese individuals.     

Improvements in Metabolic Control in Adults with Type 2 Diabetes Following Referral to a Diabetes Center, 2005–2010

Objective: We aimed to compare metabolic control in adults with diabetes in the general population to those newly referred to a diabetes center and after 1 year of specialty care.Methods: We performed a retrospective comparison of adults with diabetes aged ≥20 years data from the National Health and Nutrition Examination Survey (NHANES, n = 1,674) and a diabetes center (n = 3,128) from 2005–2010. NHANES participants represented the civilian, non-institutionalized U.S. population. Diabetes center referrals lived primarily around eastern Massachusetts. The proportion attaining targets for glycated hemoglobin A1c (A1c), blood pressure (BP), low-density lipoprotein (LDL) cholesterol, or all 3 (ABC control) and the proportion prescribed medications to lower A1c, BP, or cholesterol were evaluated.Results: Compared to the general sample, a smaller proportion of new diabetes center referrals had A1c <7% (<53 mmol/mol, 24% vs. 53%, P<.001), BP <130/80 mm Hg (38% vs. 50%, P<.001), and ABC control (5.6% vs. 17%, P<.001) but not LDL<100 mg/dL (<2.6 mmol/L, 54% vs. 53%, P = .65). After 1 year, more diabetes center referrals attained targets for A1c (40%), BP (38%), LDL (67%), and ABC control (15%) (P<.001 for all versus baseline). ABC control was not different between the general sample and diabetes center referrals at 1 year (P = .16). After 1 year, a greater percentage of diabetes center referrals compared to the general sample were prescribed medications to lower glucose (95% vs. 72%), BP (79% vs. 64%), and cholesterol (77% vs. 54%)(all P<.001).Conclusion: Compared to the general population, glycemic control was significantly worse for adults newly referred to the diabetes center. Within 1 year of specialty care, ABC control increased 270% in the setting of significant therapy escalation.Abbreviations:A1c = glycated hemoglobin A1cABC = composite of A1c, blood pressure, and cholesterolACEi = angiotensin-converting enzyme inhibitorARB = angiotensin receptor blockerBMI = body mass indexBP = blood pressureEHR = electronic health recordLDL = low-density lipoproteinNCHS = National Center for Health StatisticsNHANES = National Health and Nutrition Examination SurveyPCP = primary care provider     

Implementation of an Electronic Dashboard with A Remote Management System to Improve Glycemic Management Among Hospitalized Adults

Objective: Better glycemic control for hospitalized diabetic patients significantly reduces health expenditures and improves disease outcomes. We developed a dynamic dashboard with a remote management system and evaluated its impact on inpatient glycemic control.Methods: This was an observational institution-wide study; study participants were enrolled from a 1,500-bed public medical center from 2016 to 2018. We evaluated the impact of a dynamic dashboard system, which analyzed and monitored all glucose data with virtual glycemic management recommendation by a team of endocrinologists, over 3 × 1-year periods: 2016 (pre-implementation), 2017 (development), and 2018 (implementation).Results: A total of 51,641 discharges with 878,159 blood glucose measurements were obtained during the 3-year period. After implementation of the dashboard system, the proportion of patients with poor glycemic control (hyperglycemia or hypoglycemia) was reduced by 31% (from 10.2 to 7.0 per day per 100 patients with glucose monitoring; P<.001); hyperglycemia decreased by 25% (from 6.1 to 4.6 per day per 100 patients with glucose monitoring; P<.001), and hypoglycemia decreased by 45% (from 4.2 to 2.3 per day per 100 patients with glucose monitoring; P<.001). Furthermore, the trend in the proportion of patients within the treat-to-target range showed significant improvement (P<.001) during the development period, with effectiveness maintained throughout the implementation period.Conclusion: We successfully installed a dynamic, electronic medical records-based dashboard monitoring system to improve inpatient glycemic control. The system, supported by a team of endocrinologists via remote recommendations, could efficiently fill an important need for improved glycemic management among hospitalized adults.Abbreviations: CDE = certified diabetes educator; DM = diabetes mellitus; EMR = electronic medical record; POC = point-of-care; TCVGH = Taichung Veterans General Hospital; UCSF = University of California, San Francisco; U.S. = United States; vGMS = virtual glucose management service     

A Cross-Sectional Study of the Association between the 1-Hour Oral Glucose Tolerance Test and the Metabolic Syndrome in a High-Risk Sample with Impaired Fasting Glucose

Objective: The aim of this study was to evaluate the association between the 1-hour oral glucose tolerance test (OGTT) (≥155 mg/dL) and metabolic syndrome (MS) in a sample with previous impaired fasting glucose (IFG).Methods: Three hundred and twenty four Peruvian subjects with a history of IFG ≥100 mg/dL were selected for a cross-sectional study. They underwent a 75 g OGTT and were assigned to different groups according to the result. We evaluated the association between 1-hour OGTT and MS.Results: The mean age was 56.5 ± 12.6 years and 191 (61.5%) were female. During the OGTT, we found 28 (8.6%) subjects with diabetes, 74 (22.8%) with IGT, and 222 (68.5%) with a normal glucose tolerance test with a 2-hour glucose <140 mg/dL (NGT). In the NGT group, 124 (38.3%) had 1-hour glucose levels <155 mg/dL, while 98 (30.2%) had 1-hour glucose levels ≥155 mg/dL. Evaluating the association between the 1-hour value in the OGTT and MS, we found that subjects with a 1-hour glucose ≥155 mg/dL were more than twice as likely to have MS as those with a 1-hour glucose <155 mg/dL (odds ratio = 2.64, 95% confidence interval: 1.52 to 4.57). In addition, body mass index, fasting glycemia, triglycerides, and waist circumferences were significantly higher in subjects with 1-hour glucose levels ≥155 mg/dL compared to those with 1-hour glucose levels <155 mg/dL (P<.05).Conclusion: Among subjects with IFG, performing an OGTT was helpful to identify subjects with 1-hour glucose levels ≥155 mg/dL and NGT who were significantly more likely to have MS and a worse cardiometabolic risk profile.Abbreviations: AST = aspartate aminotransferase; BMI = body mass index; CI = confidence interval; IFG = impaired fasting glucose; IGT = impaired glucose tolerance; LDL = low-density lipoprotein; MS = metabolic syndrome; NGT = normal glucose tolerance; OGTT = oral glucose tolerance test; OR = odds ratio; T2DM = type 2 diabetes; TG = triglycerides     

Association of Genetic Variation in Adaptor Protein APPL1/APPL2 Loci with Non-Alcoholic Fatty Liver Disease

The importance of genetics and epigenetic changes in the pathogenesis of non alcoholic fatty liver disease (NAFLD) has been increasingly recognized. Adiponectin has a central role in regulating glucose and lipid metabolism and controlling inflammation in insulin-sensitive tissues and low adiponectin levels have been linked to NAFLD. APPL1 and APPL2 are adaptor proteins that interact with the intracellular region of adiponectin receptors and mediate adiponectin signaling and its effects on metabolism. The aim of our study was the evaluation of a potential association between variants at APPL1 and APPL2 loci and NAFLD occurrence. The impact on liver damage and hepatic steatosis severity has been also evaluated. To this aim allele frequency and genotype distribution of APPL1- rs3806622 and -rs4640525 and APPL2-rs 11112412 variants were evaluated in 223 subjects with clinical diagnosis of NAFLD and compared with 231 healthy subjects. The impact of APPL1 and APPL2 SNPs on liver damage and hepatic steatosis severity has been also evaluated. The minor-allele combination APPL1-C/APPL2-A was associated with an increased risk of NAFLD (OR = 2.50 95% CI 1.45–4.32; p<0.001) even after adjustment for age, sex, body mass index, insulin resistance (HOMA-IR), triglycerides and adiponectin levels. This allele combination carrier had higher plasma alanine aminotransferase levels (Diff = 15.08 [7.60–22.57] p = 0.001) and an increased frequency of severe steatosis compared to the reference allele combination (OR = 3.88; 95% CI 1.582–9.531; p<0.001). In conclusion, C-APPL1/A-APPL2 allele combination is associated with NAFLD occurrence, with a more severe hepatic steatosis grade and with a reduced adiponectin cytoprotective effect on liver.     

Side Effects of PTU and MMI in the Treatment of Hyperthyroidism: A Systematic Review and Meta-Analysis

Objective: The present study aimed to investigate the adverse effects of the antithyroid drugs propylthiouracil (PTU) and methimazole (MMI)/carbimazole (CMZ) in treating hyperthyroidism.Methods: Qualitative analysis was performed for studies identified in a literature search up to April 20, 2019, and 30 studies were selected for meta-analysis. The study designs included case-control, randomized controlled, and retrospective cohort. Patients were in four age groups: childhood, gestating mothers, older adults, and other ages, and all were receiving PTU or MMI/CMZ. Adverse reactions to MMI/CMZ and PTU were evaluated and compared.Results: Odds of liver function injury were higher in the PTU group than in the MMI/CMZ group (odds ratio &lsqb;OR], 2.40; 95% confidence interval &lsqb;CI], 1.16 to 4.96; P = .02). Odds of elevated transaminase were much higher in the PTU group than in the MMI/CMZ group (OR, 3.96; 95% CI, 2.49 to 6.28; P<.00001). No significant between-group differences were found in odds of elevated bilirubin, agranulocytosis, rash, or urticaria; incidence of other adverse events; or in children. Odds of birth defects during the first trimester of pregnancy were higher in the MMI/CMZ group than in the PTU group (OR, 1.29; 95% CI, 1.09 to 1.53; P = .003).Conclusion: The impact of PTU on liver injury and transaminase levels is greater than that of MMI/CMZ, but no significant between-group differences are found in the drugs' effects on bilirubin, agranulocytosis and rash, urticaria, or in children. In treating pregnancy-related hyperthyroidism, PTU should be used in the first trimester and MMI reserved for use in late pregnancy.Abbreviations: ALT = alanine aminotransferase; ATD = antithyroid drug; CI = confidence interval; CMZ = carbimazole; GD = Graves disease; MMI = methimazole; MTU = methylthiouracil; NOS = Newcastle-Ottawa Scale; OR = odds ratio; PTU = propylthiouracil; RAI = radioactive iodine