Common variants near MC4R are associated with fat mass, weight and risk of obesity

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.     

Genetic variation in DPP6 is associated with susceptibility to amyotrophic lateral sclerosis

We identified a SNP in the DPP6 gene that is consistently strongly associated with susceptibility to amyotrophic lateral sclerosis (ALS) in different populations of European ancestry, with an overall P value of 5.04 x 10(-8) in 1,767 cases and 1,916 healthy controls and with an odds ratio of 1.30 (95% confidence interval (CI) of 1.18-1.43). Our finding is the first report of a genome-wide significant association with sporadic ALS and may be a target for future functional studies.     

中国苏北预先导孔CCSD-PP2片麻岩中锆石的矿物包裹体及其超高压变质作用的证据

采用激光Raman及阴极发光技术,确认中国大陆科学钻探工程预选预先导孔CCSD－PP2几乎所有类型片麻岩中的锆石均保存典型的柯石英包体以及绿辉石、硬玉、石榴石、多硅白云母等矿物包体,表明片麻岩类岩石曾普遍经历了超高压变质作用,该成果对于重新探讨苏鲁超高压变质带的俯冲－折返机制和对中国大陆科学钻探工程的选址有重要的科学意义。     

Evolution of neoplastic cell lineages in Barrett oesophagus.

It has been hypothesized that neoplastic progression develops as a consequence of an acquired genetic instability and the subsequent evolution of clonal populations with accumulated genetic errors. Accordingly, human cancers and some premalignant lesions contain multiple genetic abnormalities not present in the normal tissues from which the neoplasms arose. Barrett oesophagus (BE) is a premalignant condition which predisposes to oesophageal adenocarcinoma (EA) that can be biopsied prospectively over time because endoscopic surveillance is recommended for early detection of cancer. In addition, oesophagectomy specimens frequently contain the premalignant epithelium from which the cancer arose. Neoplastic progression in BE is associated with alterations in TP53 (also known as p53) and CDKN2A (also known as p16) and non-random losses of heterozygosity (LOH). Aneuploid or increased 4N populations occur in more than 90-95% of EAs, arise in premalignant epithelium and predict progression. We have previously shown in small numbers of patients that disruption of TP53 and CDKN2A typically occurs before aneuploidy and cancer. Here, we determine the evolutionary relationships of non-random LOH, TP53 and CDKN2A mutations, CDKN2A CpG-island methylation and ploidy during neoplastic progression. Diploid cell progenitors with somatic genetic or epigenetic abnormalities in TP53 and CDKN2A were capable of clonal expansion, spreading to large regions of oesophageal mucosa. The subsequent evolution of neoplastic progeny frequently involved bifurcations and LOH at 5q, 13q and 18q that occurred in no obligate order relative to each other, DNA-content aneuploidy or cancer. Our results indicate that clonal evolution is more complex than predicted by linear models.     

An Analysis of an SIRS Epidemic Model with General Direct Immunization in Networks北大核心CSCD

We consider an SIRS epidemic model with a general direct immunization rate on networks. By constructing suitable Lyapunov functions, we find that the dynamical behvaior of the model is completely determined by the epidemic threshold λc. When λ≤λc, the disease-free equilibrium is globally asymptotically stable; when λ>λc, the endemic equilibrium is globally asymptotically stable. In addition, we propose a uniform direct immunization and a targeted direct immunization. The results show that under the same average immunization rate s there exists a critical immunization-lost rate δc so that the epidemic threshold of the targeted direct immunization is smaller (larger) than that of the uniform direct immunization if δ<δc(δ>δc). © 2017, The Journal of Agency of Complex Systems and Complexity Science. All right reserved.     

Germline-specific dgcr8 knockout in zebrafish using a BACK approach

Zebrafish is an important model to study developmental biology and human diseases. However, an effective approach to achieve spatial and temporal gene knockout in zebrafish has not been well established. In this study, we have developed a new approach, namely bacterial artificial chromosome-rescue-based knockout (BACK), to achieve conditional gene knockout in zebrafish using the Cre/loxP system. We have successfully deleted the DiGeorge syndrome critical region gene 8 (dgcr8) in zebrafish germ line and demonstrated that the maternal-zygotic dgcr8 (MZdgcr8) embryos exhibit MZdicer-like phenotypes with morphological defects which could be rescued by miR-430, indicating that canonical microRNAs play critical role in early development. Our findings establish that Cre/loxP-mediated tissue-specific gene knockout could be achieved using this BACK strategy and that canonical microRNAs play important roles in early embryonic development in zebrafish.     

Forecasting with Micro Panels: The Case of Health Care Costs

Micro panels characterized by large numbers of individuals observed over a short time period provide a rich source of information, but as yet there is only limited experience in using such data for forecasting. Existing simulation evidence supports the use of a fixed‐effects approach when forecasting but it is not based on a truly micro panel set‐up. In this study, we exploit the linkage of a representative survey of more than 250,000 Australians aged 45 and over to 4 years of hospital, medical and pharmaceutical records. The availability of panel health cost data allows the use of predictors based on fixed‐effects estimates designed to guard against possible omitted variable biases associated with unobservable individual specific effects. We demonstrate the preference towards fixed‐effects‐based predictors is unlikely to hold in many practical situations, including our models of health care costs. Simulation evidence with a micro panel set‐up adds support and additional insights to the results obtained in the application. These results are supportive of the use of the ordinary least squares predictor in a wide range of circumstances. Copyright © 2016 John Wiley & Sons, Ltd.     

Mechanisms and consequences of intestinal dysbiosis

The composition of the gut microbiota is in constant flow under the influence of factors such as the diet, ingested drugs, the intestinal mucosa, the immune system, and the microbiota itself. Natural variations in the gut microbiota can deteriorate to a state of dysbiosis when stress conditions rapidly decrease microbial diversity and promote the expansion of specific bacterial taxa. The mechanisms underlying intestinal dysbiosis often remain unclear given that combinations of natural variations and stress factors mediate cascades of destabilizing events. Oxidative stress, bacteriophages induction and the secretion of bacterial toxins can trigger rapid shifts among intestinal microbial groups thereby yielding dysbiosis. A multitude of diseases including inflammatory bowel diseases but also metabolic disorders such as obesity and diabetes type II are associated with intestinal dysbiosis. The characterization of the changes leading to intestinal dysbiosis and the identification of the microbial taxa contributing to pathological effects are essential prerequisites to better understand the impact of the microbiota on health and disease.