A non-synonymous coding change in the CYP19A1 gene Arg264Cys (rs700519) does not affect circulating estradiol, bone structure or fracture

Background The biosynthesis of estrogens from androgens is catalyzed by aromatase P450 enzyme, coded by the CYP19A1 gene on chromosome 15q21.2. Genetic variation within the CYP19A1 gene sequence has been shown to alter the function of the enzyme. The aim of this study is to investigate whether a non-synonymous Arg264Cys (rs700519) single nucleotide polymorphism (SNP) is associated with altered levels of circulating estradiol, areal bone mineral density or fracture. Methods This population- based study of 1,022 elderly Caucasian women (mean age 74.95 ± 2.60 years) was genotyped for the rs700519 SNP were analyzed to detect any association with endocrine and bone phenotypes. Results The genotype frequencies were 997 wildtype (97.6%), 24 heterozygous (2.3%) and 1 homozygous (0.1%). When individuals were grouped by genotype, there was no association between the polymorphism and serum estradiol (wildtype 27.5 ± 16.0; variants 31.2 ± 18.4, P = 0.27). There was also no association seen on hip bone mineral density (wildtype 0.81 ± 0.12; 0.84 ± 0.14 for variants, P = 0.48) or femoral neck bone mineral density (0.69 ± 0.10 for wildtype; 0.70 ± 0.12 for variants, P = 0.54) before or after correction of the data with age, height, weight and calcium therapy. There were also no associations with quantitative ultrasound measures of bone structure (broadband ultrasound attenuation, speed of sound and average stiffness). Conclusions In a cohort of 1,022 elderly Western Australian women, the presence of Arg264Cys (rs700519) polymorphism was not found to be associated with serum estradiol, bone structure or phenotypes

Genome Sequence of Erythromelalgia-Related Poxvirus Identifies it as an Ectromelia Virus Strain

Erythromelagia is a condition characterized by attacks of burning pain and inflammation in the extremeties. An epidemic form of this syndrome occurs in secondary students in rural China and a virus referred to as erythromelalgia-associated poxvirus (ERPV) was reported to have been recovered from throat swabs in 1987. Studies performed at the time suggested that ERPV belongs to the orthopoxvirus genus and has similarities with ectromelia virus, the causative agent of mousepox. We have determined the complete genome sequence of ERPV and demonstrated that it has 99.8% identity to the Naval strain of ectromelia virus and a slighly lower identity to the Moscow strain. Small DNA deletions in the Naval genome that are absent from ERPV may suggest that the sequenced strain of Naval was not the immediate progenitor of ERPV

Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion

The personality traits of neuroticism and extraversion are predictive of a number of social and behavioural outcomes and psychiatric disorders. Twin and family studies have reported moderate heritability estimates for both traits. Few associations have been reported between genetic variants and neuroticism/extraversion, but hardly any have been replicated. Moreover, the ones that have been replicated explain only a small proportion of the heritability (<∼2%). Using genome-wide single-nucleotide polymorphism (SNP) data from ∼12 000 unrelated individuals we estimated the proportion of phenotypic variance explained by variants in linkage disequilibrium with common SNPs as 0.06 (s.e.=0.03) for neuroticism and 0.12 (s.e.=0.03) for extraversion. In an additional series of analyses in a family-based sample, we show that while for both traits ∼45% of the phenotypic variance can be explained by pedigree data (that is, expected genetic similarity) one third of this can be explained by SNP data (that is, realized genetic similarity). A part of the so-called ‘missing heritability' has now been accounted for, but some of the reported heritability is still unexplained. Possible explanations for the remaining missing heritability are that: (i) rare variants that are not captured by common SNPs on current genotype platforms make a major contribution; and/ or (ii) the estimates of narrow sense heritability from twin and family studies are biased upwards, for example, by not properly accounting for nonadditive genetic factors and/or (common) environmental factors

Abiotic ammonium formation in the presence of Ni-Fe metals and alloys and its implications for the Hadean nitrogen cycle

Experiments with dinitrogen-, nitrite-, nitrate-containing solutions were conducted without headspace in Ti reactors (200°C), borosilicate septum bottles (70°C) and HDPE tubes (22°C) in the presence of Fe and Ni metal, awaruite (Ni80Fe20) and tetrataenite (Ni50Fe50). In general, metals used in this investigation were more reactive than alloys toward all investigated nitrogen species. Nitrite and nitrate were converted to ammonium more rapidly than dinitrogen, and the reduction process had a strong temperature dependence. We concluded from our experimental observations that Hadean submarine hydrothermal systems could have supplied significant quantities of ammonium for reactions that are generally associated with prebiotic synthesis, especially in localized environments. Several natural meteorites (octahedrites) were found to contain up to 22 ppm Ntot. While the oxidation state of N in the octahedrites was not determined, XPS analysis of metals and alloys used in the study shows that N is likely present as nitride (N3-). This observation may have implications toward the Hadean environment, since, terrestrial (e.g., oceanic) ammonium production may have been supplemented by reduced nitrogen delivered by metal-rich meteorites. This notion is based on the fact that nitrogen dissolves into metallic melts

Insulin Production and Signaling in Renal Tubules of Drosophila Is under Control of Tachykinin-Related Peptide and Regulates Stress Resistance

The insulin-signaling pathway is evolutionarily conserved in animals and regulates growth, reproduction, metabolic homeostasis, stress resistance and life span. In Drosophila seven insulin-like peptides (DILP1-7) are known, some of which are produced in the brain, others in fat body or intestine. Here we show that DILP5 is expressed in principal cells of the renal tubules of Drosophila and affects survival at stress. Renal (Malpighian) tubules regulate water and ion homeostasis, but also play roles in immune responses and oxidative stress. We investigated the control of DILP5 signaling in the renal tubules by Drosophila tachykinin peptide (DTK) and its receptor DTKR during desiccative, nutritional and oxidative stress. The DILP5 levels in principal cells of the tubules are affected by stress and manipulations of DTKR expression in the same cells. Targeted knockdown of DTKR, DILP5 and the insulin receptor dInR in principal cells or mutation of Dilp5 resulted in increased survival at either stress, whereas over-expression of these components produced the opposite phenotype. Thus, stress seems to induce hormonal release of DTK that acts on the renal tubules to regulate DILP5 signaling. Manipulations of S6 kinase and superoxide dismutase (SOD2) in principal cells also affect survival at stress, suggesting that DILP5 acts locally on tubules, possibly in oxidative stress regulation. Our findings are the first to demonstrate DILP signaling originating in the renal tubules and that this signaling is under control of stress-induced release of peptide hormone

Insulin Signaling, Lifespan and Stress Resistance Are Modulated by Metabotropic GABA Receptors on Insulin Producing Cells in the Brain of Drosophila

Insulin-like peptides (ILPs) regulate growth, reproduction, metabolic homeostasis, life span and stress resistance in worms, flies and mammals. A set of insulin producing cells (IPCs) in the Drosophila brain that express three ILPs (DILP2, 3 and 5) have been the main focus of interest in hormonal DILP signaling. Little is, however, known about factors that regulate DILP production and release by these IPCs. Here we show that the IPCs express the metabotropic GABAB receptor (GBR), but not the ionotropic GABAA receptor subunit RDL. Diminishing the GBR expression on these cells by targeted RNA interference abbreviates life span, decreases metabolic stress resistance and alters carbohydrate and lipid metabolism at stress, but not growth in Drosophila. A direct effect of diminishing GBR on IPCs is an increase in DILP immunofluorescence in these cells, an effect that is accentuated at starvation. Knockdown of irk3, possibly part of a G protein-activated inwardly rectifying K+ channel that may link to GBRs, phenocopies GBR knockdown in starvation experiments. Our experiments suggest that the GBR is involved in inhibitory control of DILP production and release in adult flies at metabolic stress and that this receptor mediates a GABA signal from brain interneurons that may convey nutritional signals. This is the first demonstration of a neurotransmitter that inhibits insulin signaling in its regulation of metabolism, stress and life span in an invertebrate brain

Investigation on Mycobacterium tuberculosis Diversity in China and the Origin of the Beijing Clade

Contains fulltext : 124314.pdf (publisher's version ) (Open Access

Multiple Data Analyses and Statistical Approaches for Analyzing Data from Metagenomic Studies and Clinical Trials

Metagenomics, also known as environmental genomics, is the study of the genomic content of a sample of organisms (microbes) obtained from a common habitat. Metagenomics and other “omics” disciplines have captured the attention of researchers for several decades. The effect of microbes in our body is a relevant concern for health studies. There are plenty of studies using metagenomics which examine microorganisms that inhabit niches in the human body, sometimes causing disease, and are often correlated with multiple treatment conditions. No matter from which environment it comes, the analyses are often aimed at determining either the presence or absence of specific species of interest in a given metagenome or comparing the biological diversity and the functional activity of a wider range of microorganisms within their communities. The importance increases for comparison within different environments such as multiple patients with different conditions, multiple drugs, and multiple time points of same treatment or same patient. Thus, no matter how many hypotheses we have, we need a good understanding of genomics, bioinformatics, and statistics to work together to analyze and interpret these datasets in a meaningful way. This chapter provides an overview of different data analyses and statistical approaches (with example scenarios) to analyze metagenomics samples from different medical projects or clinical trials