BackgroundBody mass index (BMI), waist circumference (WC), visceral adiposity index (VAI), triglyceride glucose index (TyG), TyG-BMI, and TyG-WC have been reported as markers of insulin resistance or type 2 diabetes mellitus (T2DM). However, little is known about the associations between the aforementioned markers and the risk of prediabetes and diabetes in first-degree relatives (FDRs) of T2DM patients.Methods1544 FDRs of T2DM patients (635 men and 909 women) were enrolled in the initial cross-sectional study and all of them finished corresponding examinations. Logistic regression analysis and receiver operating characteristic (ROC) curve were used to compare and identify the associations of the six parameters (BMI, WC, VAI, TyG, TyG-BMI and TyG-WC) with the prevalence of prediabetes and diabetes. Subsequently, 452 of them were followed-up for an average of 5 years. Cox proportional hazard regression model was applied to confirm the predictive value of the optimal marker.ResultsAmong the indices, TyG-WC was more strongly associated with the prevalence of prediabetes and diabetes. Compared with participants in the lowest quartile of TyG-WC, the adjusted odds ratio and 95 % CIs for prediabetes and diabetes was 11.19 (7.62–16.42) for those in the top quartile of TyG-WC. Moreover, the largest AUC was also observed in TyG-WC (0.765, 95 % CIs 0.741–0.789, P < 0.001). The robust predictive value of TyG-WC was further confirmed in the follow-up study (HR: 7.13, 95 % CIs 3.41–14.90, P < 0.001).ConclusionsTyG-WC is a novel and clinically effective marker for early identifying the risks of prediabetes and diabetes in FDRs of T2DM patients.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-016-1020-8) contains supplementary material, which is available to authorized users.

Objective: To evaluate the effects and safety of 300-600 mg a-lipoic acid (ALA) given i.v. for diabetic peripheral neuropathy (DPN). Methods: We searched the databases of Medline, Embase, and Cochrane central register of Controlled Trials and Chinese biological medicine for clinical trials of ALA in the treatment of DPN. Data were extracted to examine methodological quality and describe characteristics of studies. The primary outcomes were efficacy, median motor nerve conduction velocity (MNCV), median sensory nerve conduction velocity (SNCV), peroneal MNCV, and peroneal SNCV. Secondary outcomes were adverse events. Results: Fifteen randomized controlled trials met the inclusion criteria. The treatment group involved the administration of ALA 300-600 mg i.v. per day. And the control group used the same interventions except for ALA. Compared with the control group, nerve conduction velocities increased significantly in the treatment group. The weighted mean differences in nerve conduction velocities were 4.63 (95% confidence interval 3.58-5.67) for median MNCV, 3.17 (1.75-4.59) for median SNCV, 4.25 (2.78-5.72) for peroneal MNCV, and 3.65 (1.50-5.80) for peroneal SNCV in favor of the treatment group. The odds ratio in terms of efficacy was 4.03 (2.73-5.94) for ALA. Furthermore, no serious adverse events were observed during the treatment period. Conclusions:The results of this meta-analysis provide evidence that treatment with ALA (300-600 mg/day i.v. for 2-4 weeks) is safe and that the treatment can significantly improve both nerve conduction velocity and positive neuropathic symptoms. However, the evidence may not be strong because most of the studies included in this meta-analysis have poor methodological quality.

Local genetic correlation quantifies the genetic similarity of complex traits in specific genomic regions. However, accurate estimation of local genetic correlation remains challenging, due to linkage disequilibrium in local genomic regions and sample overlap across studies. We introduce SUPERGNOVA, a statistical framework to estimate local genetic correlations using summary statistics from genome-wide association studies. We demonstrate that SUPERGNOVA outperforms existing methods through simulations and analyses of 30 complex traits. In particular, we show that the positive yet paradoxical genetic correlation between autism spectrum disorder and cognitive performance could be explained by two etiologically distinct genetic signatures with bidirectional local genetic correlations.

ObjectivesTo explore the association between the triglyceride to HDL-C ratio (TG/HDL-C) and insulin resistance in Chinese patients with newly diagnosed type 2 diabetes mellitus.MethodsPatients with newly diagnosed type 2 diabetes mellitus (272 men and 288 women) were enrolled and divided into three groups according to TG/HDL-C tertiles. Insulin resistance was defined by homeostatic model assessment of insulin resistance (HOMA-IR). Demographic information and clinical characteristics were obtained. Spearman’s correlation was used to estimate the association between TG/HDL-C and other variables. Multiple logistic regression analyses were adopted to obtain probabilities of insulin resistance. A receiver operating characteristic analysis was conducted to evaluate the ability of TG/HDL-C to discriminate insulin resistance.ResultsTG/HDL-C was associated with insulin resistance in Chinese patients with newly diagnosed T2DM (Spearman’s correlation coefficient = 0.21, P < 0.01). Patients in the higher tertiles of TG/HDL-C had significantly higher HOMA-IR values than patients in the lower tertiles [T1: 2.68(1.74–3.70); T2: 2.96(2.29–4.56); T3: 3.09(2.30–4.99)]. Multiple logistic regression analysis showed that TG/HDL-C was significantly associated with HOMA-IR, and patients in the higher TG/HDL-C tertile had a higher OR than those in the lower TG/HDL-C tertile, after adjusting for multiple covariates including indices for central obesity [T1: 1; T2: 4.02(1.86–8.71); T3: 4.30(1.99–9.29)]. Following stratification of waist circumference into quartiles, the effect of TG/HDL-C on insulin resistance remained significant irrespective of waist circumference.ConclusionsTG/HDL-C was associated with insulin resistance independent of waist circumference. Whether it could be a surrogate marker for insulin resistance in Chinese patients with newly diagnosed type 2 diabetes mellitus still needs to be confirmed by more researches.

Hyperglycemia was a strong risk factor for diabetic retinopathy. In pre-diabetic subjects, diabetic retinopathy was also associated with hypertension and obesity.