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Background: This study aimed to determine independent risk loci of Graves' disease (GD) in the thyroglobulin (TG) region.Methods: In this two-staged association study, a total of 9,757 patients with GD and 10,626 sex-matched controls were recruited from Chinese Han population. Illumina Human660-Quad BeadChips in the discovery stage and TaqMan SNP Genotyping Assays in the replication stage were used for genotyping.Trend test and logistic regression analysis were performed in this association study.Results: In the discovery stage, rs2294025 and rs7005834 were the most highly associated susceptibility loci with GD in TG. In the replication phase, 7 SNPs, including rs2294025 and rs7005834, were selected for fine-mapping. Finally, we confirmed that rs2294025 and rs7005834 were the independent risk loci of GD in the combined populations. At the same time, there was no significant difference between the risk allele frequencies of rs2294025 and rs7005834 in different clinical phenotypes of GD. Conclusions:The fine mapping study of thyroglobulin identified two independent SNPs (rs2294025 and rs7005834) for GD susceptibility. However, no significant differences for rs2294025 and rs7005834 were observed, between the different clinical phenotypes of GD, including gender, Graves' ophthalmopathy (GO), and serum levels of thyrotropin receptor antibody, thyroid peroxidase antibody, and thyroglobulin antibody.These results provide a deeper understanding of the association mechanism of thyroglobulin and GD risk.

Background: The nucleobindin 2 (NUCB2) gene encodes the NUCB2 protein, which plays a critical role in glucose metabolism and diabetes. This study explored the correlation between NUCB2 genetic variants and type 2 diabetes mellitus (T2DM). The study further examined the different NUCB2 variants that confer risk to T2DM in Chinese Han populations. Methods: This study evaluated the anthropometric and glycemic profiles of 578 T2DM patients and 1,609 healthy controls. Subsequently, we genotyped five single nucleotide polymorphisms (SNPs) (rs10832756, rs1330, rs10766383, rs10832757, and rs11024251) in all the study participants using a Sequenom Mass ARRAY SNP genotyping platform. Results: The distribution of polymorphisms was significantly different between the T2DM patients and healthy controls. Our logistic regression analysis results showed that the five NUCB2 SNPs are significantly correlated with the risk for T2DM, especially rs11024251(P=2.97×10 −6). Interestingly, analysis of male and female sub-populations separately showed that only two of the SNPs (rs10832757 and rs11024251) have significant correlation to T2DM in males [P=0.0244, odds ratio (OR) 1.28 and P=0.0062, OR 1.35, respectively). In females however, we identified four significant SNPs (rs1330, rs10766383, rs10832757, and rs11024251; P<0.05, OR 1.31-1.42). Furthermore, we found that rs1330 is associated with body mass index of female subpopulation only (P=0.0174, β =0.0060). Conclusions: NUCB2 polymorphisms could have a pivotal role in the presence of T2DM. Sex-specific SNPs of NUCB2 could account for the differences in clinical features of T2DM between male and female subpopulations. Nevertheless, our results should be replicated using larger sample sizes, and experimental investigations are needed to elucidate the molecular mechanisms of the associations observed in this study.

We compared the prognostic value of nutritional or volumetric parameters measured by body composition in hospitalized patients on maintenance hemodialysis. We conducted a cohort study to assess the association of different parameters of body composition with all-cause mortality in inpatients admitted to our nephrology department from January 2014 to December 2016. Of the 704 study patients, 160 (22.7%) died during a median follow-up of 33 months. In multivariate adjusted Cox models, higher ratio of extracellular water to body cell mass (ECW/BCM) (adjusted HR per 1-SD, 1.49; 95% CI, 1.19 to 1.85), lower lean tissue index (LTI) (adjusted HR per 1-SD, 0.70; 95% CI, 0.57 to 0.86) and lower body cell mass index (BCMI) (adjusted HR per 1-SD, 0.70; 95% CI, 0.58 to 0.85) were associated with a significantly greater risk of death. When these parameters were added to the fully adjusted model, BCMI performed best in improving the predictability for all-cause mortality (integrated discrimination improvement = 0.02, P = 0.04; net reclassification index = 0.11, P = 0.04). Among body composition indexes, ECW/BCM was the most relevant fluid volume indices to mortality and BCMI and LTI were the most relevant nutritional status indices to mortality in maintenance hemodialysis patients. End-stage renal disease (ESRD) has become one of the major health problems in the world. In 2010, it was estimated that 284 individuals per million population were undergoing maintenance dialysis throughout the world 1 , and the number of dialysis patients is growing at an alarming rate 2-5. Dialysis is the major treatment for ESRD and brings a heavy economic burden to all countries 6. Despite this, dialysis patients still have poor prognosis 5,7. The main risk factors for the mortality includes vascular access, cardiovascular complications, cerebrovascular complications, infection, anemia, mineral metabolic disorders, renal osteopathy, fluid overload (FO) and malnutrition 7,8. Bioelectrical impedance analysis-based body composition analysis is widely used and accepted as an ideal tool for assessing fluid volume and nutritional status in maintenance dialysis patients 9. It is easy-to-use, safe, noninvasive, repeatable and comprehensive. It has both anthropometric parameters in assessing fluid volume [such as overhydration (OH) 10 , OH/extracellular water (OH/ECW) 8,11-14 , the ratio of extracellular water to intracellular water (ECW/ICW) 15 , the ratio of extracellular water/body cell mass (ECW/BCM) 16,17 ] and nutrition status [such as lean tissue index (LTI) 11,18-23 , fat tissue index (FTI) 11,18 , body cell mass index (BCMI) 24,25 , BCM/weight 26 ]. However, it is still unclear which nutritional or volumetric parameters of body composition, measured by bioelectrical impedance, have the greatest prognostic value in maintenance hemodialysis patients. We designed this cohort study to assess and compare the association of different parameters in body composition with all-cause medium-term mortality in hemodialysis patients.

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