A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association studies (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185 thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7 million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most known CAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidate genes that newly implicate biological processes in vessel walls. We observed intra-locus allelic heterogeneity but little evidence of low frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect siz

The Effect of Epstein-Barr Virus Latent Membrane Protein 2 Expression on the Kinetics of Early B Cell Infection

Infection of human B cells with wild-type Epstein-Barr virus (EBV) in vitro leads to activation and proliferation that result in efficient production of lymphoblastoid cell lines (LCLs). Latent Membrane Protein 2 (LMP2) is expressed early after infection and previous research has suggested a possible role in this process. Therefore, we generated recombinant EBV with knockouts of either or both protein isoforms, LMP2A and LMP2B (Δ2A, Δ2B, Δ2A/Δ2B) to study the effect of LMP2 in early B cell infection. Infection of B cells with Δ2A and Δ2A/Δ2B viruses led to a marked decrease in activation and proliferation relative to wild-type (wt) viruses, and resulted in higher percentages of apoptotic B cells. Δ2B virus infection showed activation levels comparable to wt, but fewer numbers of proliferating B cells. Early B cell infection with wt, Δ2A and Δ2B viruses did not result in changes in latent gene expression, with the exception of elevated LMP2B transcript in Δ2A virus infection. Infection with Δ2A and Δ2B viruses did not affect viral latency, determined by changes in LMP1/Zebra expression following BCR stimulation. However, BCR stimulation of Δ2A/Δ2B cells resulted in decreased LMP1 expression, which suggests loss of stability in viral latency. Long-term outgrowth assays revealed that LMP2A, but not LMP2B, is critical for efficient long-term growth of B cells in vitro. The lowest levels of activation, proliferation, and LCL formation were observed when both isoforms were deleted. These results suggest that LMP2A appears to be critical for efficient activation, proliferation and survival of EBV-infected B cells at early times after infection, which impacts the efficient long-term growth of B cells in culture. In contrast, LMP2B did not appear to play a significant role in these processes, and long-term growth of infected B cells was not affected by the absence of this protein. © 2013 Wasil et al

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

Distinct stem cells subpopulations isolated from human adipose tissue exhibit different chondrogenic and osteogenic differentiation potential

Recently adipose tissue has become a research topic also for the searching for an alternative stem cells source to use in cell based therapies such as tissue engineer. In fact Adipose Stem Cells (ASCs) exhibit an important differentiation potential for several cell lineages such as chondrogenic, osteogenic, myogenic, adipogenic and endothelial cells. ASCs populations isolated using standard methodologies (i.e., based on their adherence ability) are very heterogeneous but very few studies have analysed this aspect. Consequently, several questions are still pending, as for example, on what regard the existence/ or not of distinct ASCs subpopulations. The present study is originally aimed at isolating selected ASCs subpopulations, and to analyse their behaviour towards the heterogeneous population regarding the expression of stem cell markers and also regarding their osteogenic and chondrogenic differentiation potential. Human Adipose derived Stem Cells (hASCs) subpopulations were isolated using immunomagnetic beads coated with several different antibodies (CD29, CD44, CD49d, CD73, CD90, CD 105, Stro-1 and p75) and were characterized by Real Time RT-PCR in order to assess the expression of mesenchymal stem cells markers (CD44, CD73, Stro-1, CD105 and CD90) as well as known markers of the chondrogenic (Sox 9, Collagen II) and osteogenic lineage (Osteopontin, Osteocalcin). The obtained results underline the complexity of the ASCs population demonstrating that it is composed of several subpopulations, which express different levels of ASCs markers and exhibit distinctive differentiation potentials. Furthermore, the results obtained clearly evidence of the advantages of using selected populations in cell-based therapies, such as bone and cartilage regenerative medicine approaches.EU funded Marie Curie Actions Alea Jacta Est for a PhD fellowship. This work was carried out under the scope of the European NoE EXPERTISSUES (NMP3-CT-2004-500283)

Nano-Architecture of nitrogen-doped graphene films synthesized from a solid CN source

New synthesis routes to tailor graphene properties by controlling the concentration and chemical configuration of dopants show great promise. Herein we report the direct reproducible synthesis of 2-3% nitrogen-doped ‘few-layer’ graphene from a solid state nitrogen carbide a-C:N source synthesized by femtosecond pulsed laser ablation. Analytical investigations, including synchrotron facilities, made it possible to identify the configuration and chemistry of the nitrogen-doped graphene films. Auger mapping successfully quantified the 2D distribution of the number of graphene layers over the surface, and hence offers a new original way to probe the architecture of graphene sheets. The films mainly consist in a Bernal ABA stacking three-layer architecture, with a layer number distribution ranging from 2 to 6. Nitrogen doping affects the charge carrier distribution but has no significant effects on the number of lattice defects or disorders, compared to undoped graphene synthetized in similar conditions. Pyridinic, quaternary and pyrrolic nitrogen are the dominant chemical configurations, pyridinic N being preponderant at the scale of the film architecture. This work opens highly promising perspectives for the development of self-organized nitrogen-doped graphene materials, as synthetized from solid carbon nitride, with various functionalities, and for the characterization of 2D materials using a significant new methodology

Shape description and matching using integral invariants on eccentricity transformed images

Matching occluded and noisy shapes is a problem frequently encountered in medical image analysis and more generally in computer vision. To keep track of changes inside the breast, for example, it is important for a computer aided detection system to establish correspondences between regions of interest. Shape transformations, computed both with integral invariants (II) and with geodesic distance, yield signatures that are invariant to isometric deformations, such as bending and articulations. Integral invariants describe the boundaries of planar shapes. However, they provide no information about where a particular feature lies on the boundary with regard to the overall shape structure. Conversely, eccentricity transforms (Ecc) can match shapes by signatures of geodesic distance histograms based on information from inside the shape; but they ignore the boundary information. We describe a method that combines the boundary signature of a shape obtained from II and structural information from the Ecc to yield results that improve on them separately

Effect of synthetic hormones on reproduction in Mastomys natalensis

Rodent pest management traditionally relies on some form of lethal control. Developing effective fertility control for pest rodent species could be a major breakthrough particularly in the context of managing rodent population outbreaks. This laboratory-based study is the first to report on the effects of using fertility compounds on an outbreaking rodent pest species found throughout sub-Saharan Africa. Mastomys natalensis were fed bait containing the synthetic steroid hormones quinestrol and levonorgestrel, both singly and in combination, at three concentrations (10, 50, 100 ppm) for seven days. Consumption of the bait and animal body mass was mostly the same between treatments when analysed by sex, day and treatment. However, a repeated measures ANOVA indicated that quinestrol and quinestrol+levonorgestrel treatments reduced consumption by up to 45%, particularly at the higher concentrations of 50 and 100 ppm. Although there was no clear concentration effect on animal body mass, quinestrol and quinestrol+levonorgestrel lowered body mass by up to 20% compared to the untreated and levonorgestrel treatments. Quinestrol and quinestrol+levonorgestrel reduced the weight of male rat testes, epididymis and seminal vesicles by 60-80%, and sperm concentration and motility were reduced by more than 95%. No weight changes were observed to uterine and ovarian tissue; however, high uterine oedema was observed among all female rats consuming treated bait at 8 days and 40 days from trial start. Trials with mate pairing showed there were significant differences in the pregnancy rate with all treatments when compared to the untreated control group of rodents

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Telomerase promoter mutations in cancer: an emerging molecular biomarker?

João Vinagre, Vasco Pinto and Ricardo Celestino contributed equally to the manuscript.Cell immortalization has been considered for a long time as a classic hallmark of cancer cells. Besides telomerase reactivation, such immortalization could be due to telomere maintenance through the “alternative mechanism of telomere lengthening” (ALT) but the mechanisms underlying both forms of reactivation remained elusive. Mutations in the coding region of telomerase gene are very rare in the cancer setting, despite being associated with some degenerative diseases. Recently, mutations in telomerase (TERT) gene promoter were found in sporadic and familial melanoma and subsequently in several cancer models, notably in gliomas, thyroid cancer and bladder cancer. The importance of these findings has been reinforced by the association of TERT mutations in some cancer types with tumour aggressiveness and patient survival. In the first part of this review, we summarize the data on the biology of telomeres and telomerase, available methodological approaches and non-neoplastic diseases associated with telomere dysfunction. In the second part, we review the information on telomerase expression and genetic alterations in the most relevant types of cancer (skin, thyroid, bladder and central nervous system) on record, and discuss the value of telomerase as a new biomarker with impact on the prognosis and survival of the patients and as a putative therapeutic target

Comparison of generalized estimating equations and quadratic inference functions using data from the National Longitudinal Survey of Children and Youth (NLSCY) database

<p>Abstract</p> <p>Background</p> <p>The generalized estimating equations (GEE) technique is often used in longitudinal data modeling, where investigators are interested in population-averaged effects of covariates on responses of interest. GEE involves specifying a model relating covariates to outcomes and a plausible correlation structure between responses at different time periods. While GEE parameter estimates are consistent irrespective of the true underlying correlation structure, the method has some limitations that include challenges with model selection due to lack of absolute goodness-of-fit tests to aid comparisons among several plausible models. The quadratic inference functions (QIF) method extends the capabilities of GEE, while also addressing some GEE limitations.</p> <p>Methods</p> <p>We conducted a comparative study between GEE and QIF via an illustrative example, using data from the "National Longitudinal Survey of Children and Youth (NLSCY)" database. The NLSCY dataset consists of long-term, population based survey data collected since 1994, and is designed to evaluate the determinants of developmental outcomes in Canadian children. We modeled the relationship between hyperactivity-inattention and gender, age, family functioning, maternal depression symptoms, household income adequacy, maternal immigration status and maternal educational level using GEE and QIF. Basis for comparison include: (1) ease of model selection; (2) sensitivity of results to different working correlation matrices; and (3) efficiency of parameter estimates.</p> <p>Results</p> <p>The sample included 795, 858 respondents (50.3% male; 12% immigrant; 6% from dysfunctional families). QIF analysis reveals that gender (male) (odds ratio [OR] = 1.73; 95% confidence interval [CI] = 1.10 to 2.71), family dysfunctional (OR = 2.84, 95% CI of 1.58 to 5.11), and maternal depression (OR = 2.49, 95% CI of 1.60 to 2.60) are significantly associated with higher odds of hyperactivity-inattention. The results remained robust under GEE modeling. Model selection was facilitated in QIF using a goodness-of-fit statistic. Overall, estimates from QIF were more efficient than those from GEE using AR (1) and Exchangeable working correlation matrices (Relative efficiency = 1.1117; 1.3082 respectively).</p> <p>Conclusion</p> <p>QIF is useful for model selection and provides more efficient parameter estimates than GEE. QIF can help investigators obtain more reliable results when used in conjunction with GEE.</p