A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

HMGB1 is negatively correlated with the development of endometrial carcinoma and prevents cancer cell invasion and metastasis by inhibiting the process of epithelial-to-mesenchymal transition

Xiaorong Luan,1,2 Chunjing Ma,2 Ping Wang,2 Fenglan Lou1 1Nursing College, Shandong University, 2Qilu Hospital of Shandong University, Jinan, People’s Republic of China Abstract: High-mobility group box protein 1 (HMGB1), a nuclear protein that plays a significant role in DNA architecture and transcription, was correlated with the progression of some types of cancer. However, the role of HMGB1 in endometrial cancer cell invasion and metastasis remains unexplored. HMGB1 expression was initially assessed by immunohistochemistry and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in normal endometrial tissue and endometrial carcinoma tissue. High expressions of HMGB1 protein were detected in normal endometrial tissues; however, in endometrial cancer tissues, the expressions of HMGB1 were found to be very weak. Furthermore, HMGB1 expressions were negatively correlated with advanced stage and lymph node metastasis in endometrial cancer. Then by RT-qPCR, Western blot and immunocytochemistry, HMGB1 was also detected in primary cultured endometrial cells and four kinds of endometrial cancer cell lines (Ishikawa, HEC-1A, HEC-1B and KLE). We found that the expression of HMGB1 was much higher in normal endometrial cells than in endometrial cancer cells, and reduced expression levels of HMGB1 were observed especially in the highly metastatic cell lines. Using lentivirus transfection, HMGB1 small hairpin RNA was constructed, and this infected the lowly invasive endometrial cancer cell lines, Ishikawa and HEC-1B. HMGB1 knockdown significantly enhanced the proliferation, invasion and metastasis of endometrial cancer cells and induced the process of epithelial-to-mesenchymal transition. These results can contribute to the development of a new potential therapeutic target for endometrial cancer. Keywords: HMGB1, endometrial cancer, invasion, metastasis, epithelial-to-mesenchymal transitio

One-step electrochemical fabrication of a nickel oxide nanoparticle/polyaniline nanowire/graphene oxide hybrid on a glassy carbon electrode for use as a non-enzymatic glucose biosensor

We propose here a novel non-enzymatic glucose biosensor composed of a nickel oxide nanoparticle/polyaniline nanowire/graphene oxide hybrid composite on a glassy carbon electrode (NiONP/PANiNW/GO/GCE). The composite, prepared by mixing aniline with graphene oxide (GO) together, was transferred onto the surface of a bare glassy carbon electrode (GCE). This was then immersed in deoxygenated 50 mM NiCl2 solution and electrodeposited at -0.8 V for 400 s to obtain the modified electrode, NiONP/PANiNW/GO/GCE. We characterized the morphology and electrochemical performance of the modified electrode using scanning electron microscopy (SEM) and cyclic voltammetry (CV), respectively. We found that the NiONP/PANiNW/GO/GCE exhibits higher electrocatalytic activity for glucose oxidation than a nickel oxide nanosheet/graphene oxide modified glassy carbon electrode (NiONS/GO/GCE) in alkaline solution. The sensitivity of the sensor towards glucose oxidation is 376.22 mu A mM(-1) cm(-2) with a linearity range of 2 mu M to 5.560 mM and a detection limit of 0.5 mM (S/N = 3). The sensor selectively detects glucose in the presence of common interfering species such as ascorbic acid, uric acid and dopamine. Furthermore, we examined the applicability of this modified electrode as a sensing probe for the detection of glucose concentration in fetal bovine serum. We conclude that the highly selective and sensitive NiONP/PANiNW/GO/GCE based nonenzymatic glucose sensor has the potential to be applied to the accurate measurement of glucose levels for various practical purposes such as clinical diagnosis and food analysis, etc