STRAD Pseudokinases Regulate Axogenesis and LKB1 Stability

BACKGROUND: Neuronal polarization is an essential step of morphogenesis and connectivity in the developing brain. The serine/threonine kinase LKB1 is a key regulator of cell polarity, metabolism, tumorigenesis, and is required for axon formation. It is allosterically regulated by two related and evolutionarily conserved pseudokinases, STe20-Related ADapters (STRADs) α and β. The roles of STRADα and STRADβ in the developing nervous system are not fully defined, nor is it known whether they serve distinct functions. RESULTS: We find that STRADα is highly spliced and appears to be the primal STRAD paralog. We report that each STRAD is sufficient for axogenesis and promoting cell survival in the developing cortex. We also reveal a reciprocal protein-stabilizing relationship in vivo between LKB1 and STRADα, whereby STRADα specifically maintains LKB1 protein levels via cytoplasmic compartmentalization. CONCLUSIONS: We demonstrate a novel role for STRADβ in axogenesis and also show for the first time in vivo that STRADα, but not STRADβ, is responsible for LKB1 protein stability

Associations of risk factors of e-cigarette and cigarette use and susceptibility to use among baseline PATH study youth participants (2013–2014)

Introduction: Improved understanding of the distribution of traditional risk factors of cigarette smoking among youth who have ever used or are susceptible to e-cigarettes and cigarettes will inform future longitudinal studies examining transitions in use. Methods: Multiple logistic regression analysis was conducted using data from youth (ages 12–17 years) who had ever heard of e-cigarettes at baseline of the PATH Study (n = 12,460) to compare the distribution of risk factors for cigarette smoking among seven mutually exclusive groups based on ever cigarette/e-cigarette use and sus- ceptibility status. Results: Compared to committed never users, youth susceptible to e-cigarettes, cigarettes, or both had increasing odds of risk factors for cigarette smoking, with those susceptible to both products at highest risk, followed by cigarettes and e-cigarettes. Compared to e-cigarette only users, dual users had higher odds of nearly all risk factors (aOR range = 1.6–6.8) and cigarette only smokers had higher odds of other (non-e-cigarette) tobacco use (aOR range=1.5–2.3), marijuana use (aOR=1.9, 95%CI=1.4–2.5), a high GAIN substance use score (aOR = 1.9, 95%CI = 1.1–3.4), low academic achievement (aOR range = 1.6–3.4), and exposure to smoking (aOR range = 1.8–2.1). No differences were observed for externalizing factors (depression, anxiety, etc.), sen- sation seeking, or household use of non-cigarette tobacco. Conclusions: Among ever cigarette and e-cigarette users, dual users had higher odds of reporting traditional risk factors for smoking, followed by single product cigarette smokers and e-cigarette users. Understanding how e- cigarette and cigarette users differ may inform youth tobacco use prevention efforts and advise future studies assessing probability of progression of cigarette and e-cigarette use

The Etiology of Multiple Sclerosis: Genetic Evidence for the Involvement of the Human Endogenous Retrovirus HERV-Fc1

We have investigated the role of human endogenous retroviruses in multiple sclerosis by analyzing the DNA of patients and controls in 4 cohorts for associations between multiple sclerosis and polymorphisms near viral restriction genes or near endogenous retroviral loci with one or more intact or almost-intact genes. We found that SNPs in the gene TRIM5 were inversely correlated with disease. Conversely, SNPs around one retroviral locus, HERV-Fc1, showed a highly significant association with disease. The latter association was limited to a narrow region that contains no other known genes. We conclude that HERV-Fc1 and TRIM5 play a role in the etiology of multiple sclerosis. If these results are confirmed, they point to new modes of treatment for multiple sclerosis

Expression of a malarial Hsp70 improves defects in chaperone-dependent activities in ssa1 mutant yeast

Plasmodium falciparum causes the most virulent form of malaria and encodes a large number of molecular chaperones. Because the parasite encounters radically different environments during its lifecycle, many members of this chaperone ensemble may be essential for P. falciparum survival. Therefore, Plasmodium chaperones represent novel therapeutic targets, but to establish the mechanism of action of any developed therapeutics, it is critical to ascertain the functions of these chaperones. To this end, we report the development of a yeast expression system for PfHsp70-1, a P. falciparum cytoplasmic chaperone. We found that PfHsp70-1 repairs mutant growth phenotypes in yeast strains lacking the two primary cytosolic Hsp70s, SSA1 and SSA2, and in strains harboring a temperature sensitive SSA1 allele. PfHsp70-1 also supported chaperone-dependent processes such as protein translocation and ER associated degradation, and ameliorated the toxic effects of oxidative stress. By introducing engineered forms of PfHsp70-1 into the mutant strains, we discovered that rescue requires PfHsp70-1 ATPase activity. Together, we conclude that yeast can be co-opted to rapidly uncover specific cellular activities mediated by malarial chaperones. © 2011 Bell et al

BIOFRAG: A new database for analysing BIOdiversity responses to forest FRAGmentation

Habitat fragmentation studies are producing inconsistent and complex results across which it is nearly impossible to synthesise. Consistent analytical techniques can be applied to primary datasets, if stored in a flexible database that allows simple data retrieval for subsequent analyses. Method: We developed a relational database linking data collected in the field to taxonomic nomenclature, spatial and temporal plot attributes and further environmental variables (e.g. information on biogeographic region. Typical field assessments include measures of biological variables (e.g. presence, abundance, ground cover) of one species or a set of species linked to a set of plots in fragments of a forested landscape. Conclusion: The database currently holds records of 5792 unique species sampled in 52 landscapes in six of eight biogeographic regions: mammals 173, birds 1101, herpetofauna 284, insects 2317, other arthropods: 48, plants 1804, snails 65. Most species are found in one or two landscapes, but some are found in four. Using the huge amount of primary data on biodiversity response to fragmentation becomes increasingly important as anthropogenic pressures from high population growth and land demands are increasing. This database can be queried to extract data for subsequent analyses of the biological response to forest fragmentation with new metrics that can integrate across the components of fragmented landscapes. Meta-analyses of findings based on consistent methods and metrics will be able to generalise over studies allowing inter-comparisons for unified answers. The database can thus help researchers in providing findings for analyses of trade-offs between land use benefits and impacts on biodiversity and to track performance of management for biodiversity conservation in human-modified landscapes.Fil: Pfeifer, Marion. Imperial College London; Reino UnidoFil: Lefebvre, Veronique. Imperial College London; Reino UnidoFil: Gardner, Toby A.. Stockholm Environment Institute; SueciaFil: Arroyo Rodríguez, Víctor. Universidad Nacional Autónoma de México; MéxicoFil: Baeten, Lander. University of Ghent; BélgicaFil: Banks Leite, Cristina. Imperial College London; Reino UnidoFil: Barlow, Jos. Lancaster University; Reino UnidoFil: Betts, Matthew G.. State University of Oregon; Estados UnidosFil: Brunet, Joerg. Swedish University of Agricultural Sciences; SueciaFil: Cerezo Blandón, Alexis Mauricio. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; ArgentinaFil: Cisneros, Laura M.. University of Connecticut; Estados UnidosFil: Collard, Stuart. Nature Conservation Society of South Australia; AustraliaFil: D´Cruze, Neil. The World Society for the Protection of Animals; Reino UnidoFil: Da Silva Motta, Catarina. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Duguay, Stephanie. Carleton University; CanadáFil: Eggermont, Hilde. University of Ghent; BélgicaFil: Eigenbrod, Félix. University of Southampton; Reino UnidoFil: Hadley, Adam S.. State University of Oregon; Estados UnidosFil: Hanson, Thor R.. No especifíca;Fil: Hawes, Joseph E.. University of East Anglia; Reino UnidoFil: Heartsill Scalley, Tamara. United State Department of Agriculture. Forestry Service; Puerto RicoFil: Klingbeil, Brian T.. University of Connecticut; Estados UnidosFil: Kolb, Annette. Universitat Bremen; AlemaniaFil: Kormann, Urs. Universität Göttingen; AlemaniaFil: Kumar, Sunil. State University of Colorado - Fort Collins; Estados UnidosFil: Lachat, Thibault. Swiss Federal Institute for Forest; SuizaFil: Lakeman Fraser, Poppy. Imperial College London; Reino UnidoFil: Lantschner, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche; ArgentinaFil: Laurance, William F.. James Cook University; AustraliaFil: Leal, Inara R.. Universidade Federal de Pernambuco; BrasilFil: Lens, Luc. University of Ghent; BélgicaFil: Marsh, Charles J.. University of Leeds; Reino UnidoFil: Medina Rangel, Guido F.. Universidad Nacional de Colombia; ColombiaFil: Melles, Stephanie. University of Toronto; CanadáFil: Mezger, Dirk. Field Museum of Natural History; Estados UnidosFil: Oldekop, Johan A.. University of Sheffield; Reino UnidoFil: Overal , Williams L.. Museu Paraense Emílio Goeldi. Departamento de Entomologia; BrasilFil: Owen, Charlotte. Imperial College London; Reino UnidoFil: Peres, Carlos A.. University of East Anglia; Reino UnidoFil: Phalan, Ben. University of Southampton; Reino UnidoFil: Pidgeon, Anna Michle. University of Wisconsin; Estados UnidosFil: Pilia, Oriana. Imperial College London; Reino UnidoFil: Possingham, Hugh P.. Imperial College London; Reino Unido. The University Of Queensland; AustraliaFil: Possingham, Max L.. No especifíca;Fil: Raheem, Dinarzarde C.. Royal Belgian Institute of Natural Sciences; Bélgica. Natural History Museum; Reino UnidoFil: Ribeiro, Danilo B.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Ribeiro Neto, Jose D.. Universidade Federal de Pernambuco; BrasilFil: Robinson, Douglas W.. State University of Oregon; Estados UnidosFil: Robinson, Richard. Manjimup Research Centre; AustraliaFil: Rytwinski, Trina. Carleton University; CanadáFil: Scherber, Christoph. Universität Göttingen; AlemaniaFil: Slade, Eleanor M.. University of Oxford; Reino UnidoFil: Somarriba, Eduardo. Centro Agronómico Tropical de Investigación y Enseñanza; Costa RicaFil: Stouffer, Philip C.. State University of Louisiana; Estados UnidosFil: Struebig, Matthew J.. University of Kent; Reino UnidoFil: Tylianakis, Jason M.. University College London; Estados Unidos. Imperial College London; Reino UnidoFil: Teja, Tscharntke. Universität Göttingen; AlemaniaFil: Tyre, Andrew J.. Universidad de Nebraska - Lincoln; Estados UnidosFil: Urbina Cardona, Jose N.. Pontificia Universidad Javeriana; ColombiaFil: Vasconcelos, Heraldo L.. Universidade Federal de Uberlandia; BrasilFil: Wearn, Oliver. Imperial College London; Reino Unido. The Zoological Society of London; Reino UnidoFil: Wells, Konstans. University of Adelaide; AustraliaFil: Willig, Michael R.. University of Connecticut; Estados UnidosFil: Wood, Eric. University of Wisconsin; Estados UnidosFil: Young, Richard P.. Durrell Wildlife Conservation Trust; Reino UnidoFil: Bradley, Andrew V.. Imperial College London; Reino UnidoFil: Ewers, Robert M.. Imperial College London; Reino Unid

Genome-wide analysis identifies genetic effects on reproductive success and ongoing natural selection at the FADS locus

: Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and identify alleles under present-day selection. Using data in 785,604 individuals of European ancestry, we identified 43 genomic loci associated with either number of children ever born (NEB) or childlessness. These loci span diverse aspects of reproductive biology, including puberty timing, age at first birth, sex hormone regulation, endometriosis and age at menopause. Missense variants in ARHGAP27 were associated with higher NEB but shorter reproductive lifespan, suggesting a trade-off at this locus between reproductive ageing and intensity. Other genes implicated by coding variants include PIK3IP1, ZFP82 and LRP4, and our results suggest a new role for the melanocortin 1 receptor (MC1R) in reproductive biology. As NEB is one component of evolutionary fitness, our identified associations indicate loci under present-day natural selection. Integration with data from historical selection scans highlighted an allele in the FADS1/2 gene locus that has been under selection for thousands of years and remains so today. Collectively, our findings demonstrate that a broad range of biological mechanisms contribute to reproductive success

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

Oral abstracts 3: RA Treatment and outcomesO13. Validation of jadas in all subtypes of juvenile idiopathic arthritis in a clinical setting

Background: Juvenile Arthritis Disease Activity Score (JADAS) is a 4 variable composite disease activity (DA) score for JIA (including active 10, 27 or 71 joint count (AJC), physician global (PGA), parent/child global (PGE) and ESR). The validity of JADAS for all ILAR subtypes in the routine clinical setting is unknown. We investigated the construct validity of JADAS in the clinical setting in all subtypes of JIA through application to a prospective inception cohort of UK children presenting with new onset inflammatory arthritis. Methods: JADAS 10, 27 and 71 were determined for all children in the Childhood Arthritis Prospective Study (CAPS) with complete data available at baseline. Correlation of JADAS 10, 27 and 71 with single DA markers was determined for all subtypes. All correlations were calculated using Spearman's rank statistic. Results: 262/1238 visits had sufficient data for calculation of JADAS (1028 (83%) AJC, 744 (60%) PGA, 843 (68%) PGE and 459 (37%) ESR). Median age at disease onset was 6.0 years (IQR 2.6-10.4) and 64% were female. Correlation between JADAS 10, 27 and 71 approached 1 for all subtypes. Median JADAS 71 was 5.3 (IQR 2.2-10.1) with a significant difference between median JADAS scores between subtypes (p < 0.01). Correlation of JADAS 71 with each single marker of DA was moderate to high in the total cohort (see Table 1). Overall, correlation with AJC, PGA and PGE was moderate to high and correlation with ESR, limited JC, parental pain and CHAQ was low to moderate in the individual subtypes. Correlation coefficients in the extended oligoarticular, rheumatoid factor negative and enthesitis related subtypes were interpreted with caution in view of low numbers. Conclusions: This study adds to the body of evidence supporting the construct validity of JADAS. JADAS correlates with other measures of DA in all ILAR subtypes in the routine clinical setting. Given the high frequency of missing ESR data, it would be useful to assess the validity of JADAS without inclusion of the ESR. Disclosure statement: All authors have declared no conflicts of interest. Table 1Spearman's correlation between JADAS 71 and single markers DA by ILAR subtype ILAR Subtype Systemic onset JIA Persistent oligo JIA Extended oligo JIA Rheumatoid factor neg JIA Rheumatoid factor pos JIA Enthesitis related JIA Psoriatic JIA Undifferentiated JIA Unknown subtype Total cohort Number of children 23 111 12 57 7 9 19 7 17 262 AJC 0.54 0.67 0.53 0.75 0.53 0.34 0.59 0.81 0.37 0.59 PGA 0.63 0.69 0.25 0.73 0.14 0.05 0.50 0.83 0.56 0.64 PGE 0.51 0.68 0.83 0.61 0.41 0.69 0.71 0.9 0.48 0.61 ESR 0.28 0.31 0.35 0.4 0.6 0.85 0.43 0.7 0.5 0.53 Limited 71 JC 0.29 0.51 0.23 0.37 0.14 -0.12 0.4 0.81 0.45 0.41 Parental pain 0.23 0.62 0.03 0.57 0.41 0.69 0.7 0.79 0.42 0.53 Childhood health assessment questionnaire 0.25 0.57 -0.07 0.36 -0.47 0.84 0.37 0.8 0.66 0.4