Antenatal risk factors for peanut allergy in children

<p>Abstract</p> <p>Background</p> <p>Prenatal factors may contribute to the development of peanut allergy. We evaluated the risk of childhood peanut allergy in association with pregnancy exposure to Rh immune globulin, folic acid and ingestion of peanut-containing foods.</p> <p>Methods</p> <p>We conducted a web-based case-control survey using the Anaphylaxis Canada Registry, a pre-existing database of persons with a history of anaphylaxis. A total of 1300 case children with reported peanut allergy were compared to 113 control children with shellfish allergy. All were evaluated for maternal exposure in pregnancy to Rh immune globulin and folic acid tablet supplements, as well as maternal avoidance of dietary peanut intake in pregnancy.</p> <p>Results</p> <p>Receipt of Rh immune globulin in pregnancy was not associated with a higher risk of peanut allergy (odds ratio [OR] 0.86, 95% confidence interval [CI] 0.51 to 1.45), nor was initiation of folic acid tablet supplements before or after conception (OR 0.53, 95% CI 0.19 to 1.48). Complete avoidance of peanut-containing products in pregnancy was associated with a non-significantly lower risk of peanut allergy (OR 0.53, 95% CI 0.27 to 1.03).</p> <p>Conclusion</p> <p>The risk of childhood peanut allergy was not modified by the following common maternal exposures in pregnancy: Rh immune globulin, folic acid or peanut-containing foods.</p> <p>Clinical implications</p> <p>Rh immune globulin, folic acid supplement use and peanut avoidance in pregnancy have yet to be proven to modulate the risk of childhood anaphylaxis to peanuts.</p> <p>Capsule Summary</p> <p>Identification of prenatal factors that contribute to peanut allergy might allow for prevention of this life-threatening condition. This article explores the role of three such factors.</p

Fungal BLAST and Model Organism BLASTP Best Hits: new comparison resources at the Saccharomyces Genome Database (SGD)

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is a scientific database of gene, protein and genomic information for the yeast Saccharomyces cerevisiae. SGD has recently developed two new resources that facilitate nucleotide and protein sequence comparisons between S.cerevisiae and other organisms. The Fungal BLAST tool provides directed searches against all fungal nucleotide and protein sequences available from GenBank, divided into categories according to organism, status of completeness and annotation, and source. The Model Organism BLASTP Best Hits resource displays, for each S.cerevisiae protein, the single most similar protein from several model organisms and presents links to the database pages of those proteins, facilitating access to curated information about potential orthologs of yeast proteins

Expanded protein information at SGD: new pages and proteome browser

The recent explosion in protein data generated from both directed small-scale studies and large-scale proteomics efforts has greatly expanded the quantity of available protein information and has prompted the Saccharomyces Genome Database (SGD; ) to enhance the depth and accessibility of protein annotations. In particular, we have expanded ongoing efforts to improve the integration of experimental information and sequence-based predictions and have redesigned the protein information web pages. A key feature of this redesign is the development of a GBrowse-derived interactive Proteome Browser customized to improve the visualization of sequence-based protein information. This Proteome Browser has enabled SGD to unify the display of hidden Markov model (HMM) domains, protein family HMMs, motifs, transmembrane regions, signal peptides, hydropathy plots and profile hits using several popular prediction algorithms. In addition, a physico-chemical properties page has been introduced to provide easy access to basic protein information. Improvements to the layout of the Protein Information page and integration of the Proteome Browser will facilitate the ongoing expansion of sequence-specific experimental information captured in SGD, including post-translational modifications and other user-defined annotations. Finally, SGD continues to improve upon the availability of genetic and physical interaction data in an ongoing collaboration with BioGRID by providing direct access to more than 82 000 manually-curated interactions

Genome Snapshot: a new resource at the Saccharomyces Genome Database (SGD) presenting an overview of the Saccharomyces cerevisiae genome

Sequencing and annotation of the entire Saccharomyces cerevisiae genome has made it possible to gain a genome-wide perspective on yeast genes and gene products. To make this information available on an ongoing basis, the Saccharomyces Genome Database (SGD) () has created the Genome Snapshot (). The Genome Snapshot summarizes the current state of knowledge about the genes and chromosomal features of S.cerevisiae. The information is organized into two categories: (i) number of each type of chromosomal feature annotated in the genome and (ii) number and distribution of genes annotated to Gene Ontology terms. Detailed lists are accessible through SGD's Advanced Search tool (), and all the data presented on this page are available from the SGD ftp site ()

Factor XII mutations, estrogen-dependent inherited angioedema, and related conditions

The clinical, biochemical and genetic features of the conditions known as estrogen-dependent inherited angioedema, estrogen-associated angioedema, hereditary angioedema with normal C-1 inhibitor, type III angioedema, or factor XII angioedema are reviewed. Discussion emphasizes pathogenesis, diagnosis, and management

The Gene Ontology in 2010: extensions and refinements

The Gene Ontology (GO) Consortium (http://www.geneontology.org) (GOC) continues to develop, maintain and use a set of structured, controlled vocabularies for the annotation of genes, gene products and sequences. The GO ontologies are expanding both in content and in structure. Several new relationship types have been introduced and used, along with existing relationships, to create links between and within the GO domains. These improve the representation of biology, facilitate querying, and allow GO developers to systematically check for and correct inconsistencies within the GO. Gene product annotation using GO continues to increase both in the number of total annotations and in species coverage. GO tools, such as OBO-Edit, an ontology-editing tool, and AmiGO, the GOC ontology browser, have seen major improvements in functionality, speed and ease of use.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Oxford University Press. The published article can be found at: http://nar.oxfordjournals.org/

Sex differences in body composition and bone mineral density in phenylketonuria: A cross-sectional study

Background: Low bone mineral density (BMD) and subsequent skeletal fragility have emerged as a long-term complication of phenylketonuria (PKU). Objective: To determine if there are differences in BMD and body composition between male and female participants with PKU. Methods: From our randomized, crossover trial [1] of participants with early-treated PKU who consumed a low-phenylalanine (Phe) diet combined with amino acid medical foods (AA-MF) or glycomacropeptide medical foods (GMP-MF), a subset of 15 participants (6 males, 9 females, aged 15–50 y, 8 classical and 7 variant PKU) completed one dual energy X-ray absorptiometry (DXA) scan and 3-day food records after each dietary treatment. Participants reported lifelong compliance with AA-MF. In a crossover design, 8 participants (4 males, 4 females, aged 16–35y) provided a 24-h urine collection after consuming AA-MF or GMP-MF for 1–3weeks each. Results: Male participants had significantly lower mean total body BMD Z-scores (means±SE, males=−0.9±0.4; females, 0.2±0.3; p=0.01) and tended to have lower mean L1–4 spine and total femur BMD Z-scores compared to female participants. Only 50% percent of male participants had total body BMD Z-scores above −1.0 compared to 100% of females (p=0.06). Total femur Z-scores were negatively correlated with intake of AA-MF (r=−0.58; p=0.048). Males tended to consume more grams of protein equivalents per day from AA-MF (means±SE, males: 67±6g, females: 52±4g; p=0.057). Males and females demonstrated similar urinary excretion of renal net acid, magnesium and sulfate; males showed a trend for higher urinary calcium excretion compared to females (means ± SE, males: 339±75mg/d, females: 228±69mg/d; p=0.13). Females had a greater percentage of total fat mass compared to males (means±SE, males: 24.5±4.8%, females: 36.5±2.5%; p=0.047). Mean appendicular lean mass index was similar between males and females. Male participants had low-normal lean mass based on the appendicular lean mass index. Conclusions: Males with PKU have lower BMD compared with females with PKU that may be related to higher intake of AA-MF and greater calcium excretion. The trial was registered at www.clinicaltrials.gov as NCT01428258. Keywords: Amino acid, Appendicular lean mass index, Glycomacropeptide, Medical food, Osteoporosis, Renal net acid, Trabecular bone score, Urinary calcium excretio