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We investigated the prevalence and clinical metabolic characteristics of lean nonalcoholic fatty liver disease (NAFLD) in an elderly Chinese population and assessed the relevance of lipid markers and genetic variation. All 5,338 community subjects underwent detailed clinical and laboratory examinations and were divided into three groups: lean (Body mass index (BMI) < 23 kg/m2, n = 2,012), overweight (BMI = 23–24.9 kg/m2, n = 1,354), and obese (BMI ≥ 25 kg/m2, n = 1,972). Single nucleotide polymorphisms were selected based on those reported in previous NAFLD or obesity genome-wide association studies. The frequencies of alleles and genotypes were calculated and statistically analyzed with Pearson's χ2 tests. One-way ANCOVA was used to test the association between positive SNPs and metabolic parameters in lean NAFLD individuals. Our results showed that the C allele frequency of rs2279026, the G allele of rs2279028, the C allele of rs780093, and the C allele frequency of rs1260326 were higher in obese NAFLD than in lean NAFLD (P < 0.05). In addition, we observed an association between the CC of rs1421085, TT of rs3751812, AA of rs8050136, and AA of rs9939609 genotypes in the FTO gene and low-density lipoprotein levels (P < 0.05). In conclusion, our findings provide a unique perspective on the prevalence, genetic characteristics, and metabolic profile of NAFLD in older lean individuals in China. This is the first study to examine the association between genetic variants in the FTO, TFAP2B and GCKR genes and NAFLD in a cohort of lean individuals. [ABSTRACT FROM AUTHOR]

Background: Dyslipidaemia is a risk factor for abnormal blood glucose. However, studies on the predictive values of lipid markers in prediabetes and diabetes simultaneously are limited. This study aimed to assess the associations and predictive abilities of lipid indices and abnormal blood glucose. Methods: A sample of 7667 participants without diabetes were enrolled in this cross-sectional study conducted in 2016, and all of them were classified as having normal glucose tolerance (NGT), prediabetes or diabetes. Blood glucose, blood pressure and lipid parameters (triglycerides, TG; total cholesterol, TC; high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; non-high-density lipoprotein cholesterol, non-HDL-C; and triglyceride glucose index, TyG) were evaluated or calculated. Logistic regression models were used to analyse the association between lipids and abnormal blood glucose. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess the discriminatory power of lipid parameters for detecting prediabetes or diabetes. Results: After adjustment for potential confounding factors, the TyG was the strongest marker related to abnormal blood glucose compared to other lipid indices, with odds ratios of 2.111 for prediabetes and 5.423 for diabetes. For prediabetes, the AUCs of the TG, TC, HDL-C, LDL-C, TC/HDL-C, TG/HDL-C, non-HDL-C and TyG indices were 0.605, 0.617, 0.481, 0.615, 0.603, 0.590, 0.626 and 0.660, respectively, and the cut-off points were 1.34, 4.59, 1.42, 2.69, 3.39, 1.00, 3.19 and 8.52, respectively. For diabetes, the AUCs of the TG, TC, HDL-C, LDL-C, TC/HDL-C, TG/HDL-C, non-HDL-C and TyG indices were 0.712, 0.679, 0.440, 0.652, 0.686, 0.692, 0.705, and 0.827, respectively, and the cut-off points were 1.35, 4.68, 1.42, 2.61, 3.44, 0.98, 3.13 and 8.80, respectively. Conclusions: The TyG, TG and non-HDL-C, especially TyG, are accessible biomarkers for screening individuals with undiagnosed diabetes. [ABSTRACT FROM AUTHOR]

Background: Obesity is associated with the development of polycystic ovary syndrome (PCOS) and contributes substantially to metabolic abnormalities in women with PCOS. The study aimed to describe and compare the practices of physicians in the diagnosis, evaluation, and treatment of obesity in patients with PCOS. Methods: Reproductive endocrinologists (Repro-Endo) and obstetrician-gynecologists (non-reproductive medicine specialty, OB-Gyn) in China participated in a survey, and their responses were analyzed using χ2 tests, Fisher exact tests, and multivariable logistic regression analysis. Results: The study analyzed 1318 survey responses (85.8% OB-Gyn; 97.3% women). Body mass index was the most common diagnostic criterion for obesity; only 1.3% of participants measured waist circumference to identify abdominal obesity. More Repro-Endo participants (25% of all participants) enquired about the psychological problems of patients with obesity than OB-Gyn participants, and 42.5% of participants reported ordering both a lipid profile and oral glucose tolerance test (OGTT) for patients with obesity and PCOS. Multivariable analysis, that included physician's specialty, age, hospital grade, and number of patients with PCOS seen annually, revealed that OB-Gyn participants were less likely to order OGTT (OR, 0.3; 95% CI, 0.2–0.4) and lipid profile (OR, 0.2; 95% CI, 0.1–0.3) than Repro-Endo participants. The most common treatments for patients with PCOS were lifestyle modification (> 95%) and metformin (> 80%). More Repro-Endo participants prescribed metformin at a dose of 1.5 g/day compared with OB-Gyn (47.6% vs. 26.3%), and more OB-Gyn participants reported being unclear about the appropriate dosage of metformin for patients with obesity and PCOS (8.9% vs. 1.6%). Conclusion: Our survey identified knowledge gaps in metabolic screening for patients with obesity and PCOS and a disparity in the evaluation and treatment of obesity in PCOS among different specialties. Similarly, it highlights the need to improve obesity management education for physicians caring for women with PCOS. [ABSTRACT FROM AUTHOR]

Background: Red cell distribution width (RDW) is a predicter of infections, cancer and diabetes. However, the relationship between RDW and β-cell function and insulin resistance remains unclear in patients with type 2 diabetes mellitus (T2DM). The aim of the study was to explore the relationship between RDW and β-cell function in patients with T2DM. Methods: A total of 559 T2DM patients were enrolled in this cross-sectional study. Patients were divided into three groups according to RDW tertiles. Clinical and biochemical characteristics such as age, duration of diabetes, blood pressure, RDW, glycosylated hemoglobin A1c (HbA1c), C-peptide and lipid profiles were collected. Homeostasis model assessment of insulin resistance (HOMA2IR) and homeostasis model assessment of β-cell function (HOMA2%B) were assessed using homeostasis model assessment (HOMA) based on fasting blood glucose (FBG) and fasting C-peptide index (FCPI). Correlations and multiple linear regressions were performed to explore the association between RDW and islet function indexes in total population and in different gender subgroups. Results: The HOMA2%B gradually increased according to RDW tertiles (lowest, second, highest RDW tertiles; 47.1(32.9–75.4), 54.05(34.1–81), and 57.9(38.65–95.4), respectively; P = 0.036). Correlation analysis indicated that there were significant correlations between RDW and age, diabetes duration, diastolic blood pressure (DBP), triglycerides (TG), aspartate transaminase (AST), FBG, HbA1c and HOMA2%B in all subjects. In male subjects, RDW correlated positively with age, high-density lipoprotein cholesterol (HDL) and AST, and it correlated negatively with body mass index (BMI), DBP and TG. In female subjects, RDW correlated positively with age, duration, serum creatinine (Cr), FCPI and HOMA2%B, and it correlated negatively with alanine transaminase (ALT), FBG and HbA1c. Multiple linear regressions indicated that RDW was significantly correlated with HOMA2%B and HbA1c in the total population in both unadjusted and adjusted analysis. This finding could be reproduced in the subgroup of men for HOMA2%B only and in women for HbA1c only. Conclusions: RDW is associated with β-cell function assessed by HOMA2%B after adjusting for covariates in male T2DM patients. [ABSTRACT FROM AUTHOR]

Background: The concept is now emerging that higher thyroid-stimulating hormone (TSH) and lower thyroid hormone levels within the euthyroid range may adversely affect atherosclerosis. The aim of this study was to investigate the potential association between thyroid parameters and lipids profile in a cohort of euthyroid diabetic subjects. Methods: Four hundred and sixty-two euthyroid type 2 diabetes subjects (302 males and 160 females) were consecutively recruited. Clinical and anthropometric data was collected from all participants. Whole blood samples were drawn in the morning after an overnight fasting for the measurement of serum TSH, free thyroxine (FT4), free triiothyronine (FT3), anti-thyroid peroxidase antibody (TPO-Ab) levels, as well as lipid concentrations and glucose. Results: TSH was higher in females than males. Stratified by TSH, high-density lipoprotein cholesterol (HDL-c) level increased in subjects with TSH ≥2.5uIU/mL (P = 0.004). And TSH was associated with HDL-c in a Pearson correlation test, however, the association failed to attain significance in partial correlation analyses, adjusted for age, sex, duration of diabetes, fasting glucose and BMI. In females, total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-c) level was significant lower in subjects with TSH <2.5uIU/mL. TSH was significantly associated with TC and LDL-c, even in a partial correlation analysis (P = 0.006 and 0.011, respectively). In a multiple linear regression analysis (stepwise), TSH was positive associated with TC (β = 0.202, P = 0.005) and LDL-c (β = 0.144, P = 0.010). In one hundred and six patients having TPO antibody assays, 6 (5.66%) were positive. The blood pressure and lipid levels were lower in TPO-Ab positive patients, however, the differences were not significantly. Conclusions: In conclusion, we identified TSH was positively associated with serum TC and LDL-c in euthyroid diabetic women. Our analysis in the subgroup having TPO antibody assays demonstrating non-significantly lower TC levels among seropositive subjects was consistent with the above stated consideration for women as a whole. Further investigations are needed to understand the intimate mechanisms of lipid metabolism in type 2 diabetes with respect to thyroid function. [ABSTRACT FROM AUTHOR]