57 research outputs found

    Protective role of DNJ-27/ERdj5 in Caenorhabditis elegans models of human neurodegenerative diseases

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    Aims: Cells have developed quality control systems for protection against proteotoxicity. Misfolded and aggregation-prone proteins, which are behind the initiation and progression of many neurodegenerative diseases (ND), are known to challenge the proteostasis network of the cells. We aimed to explore the role of DNJ-27/ERdj5, an endoplasmic reticulum (ER)-resident thioredoxin protein required as a disulfide reductase for the degradation of misfolded proteins, in well-established Caenorhabditis elegans models of Alzheimer, Parkinson and Huntington diseases. Results: We demonstrate that DNJ-27 is an ER luminal protein and that its expression is induced upon ER stress via IRE-1/XBP-1. When dnj-27 expression is downregulated by RNA interference we find an increase in the aggregation and associated pathological phenotypes (paralysis and motility impairment) caused by human β-amyloid peptide (Aβ), α-synuclein (α-syn) and polyglutamine (polyQ) proteins. In turn, DNJ-27 overexpression ameliorates these deleterious phenotypes. Surprisingly, despite being an ER-resident protein, we show that dnj-27 downregulation alters cytoplasmic protein homeostasis and causes mitochondrial fragmentation. We further demonstrate that DNJ-27 overexpression substantially protects against the mitochondrial fragmentation caused by human Aβ and α-syn peptides in these worm models. Innovation: We identify C. elegans dnj-27 as a novel protective gene for the toxicity associated with the expression of human Aβ, α-syn and polyQ proteins, implying a protective role of ERdj5 in Alzheimer, Parkinson and Huntington diseases. Conclusion: Our data support a scenario where the levels of DNJ-27/ERdj5 in the ER impact cytoplasmic protein homeostasis and the integrity of the mitochondrial network which might underlie its protective effects in models of proteotoxicity associated to human ND

    Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk

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    The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.The work was partially supported by the Fondo de Investigacion Sanitaria, Instituto de Salud Carlos III (G03/174, 00/0745, PI051436, PI061614, PI09-02102, G03/174 and Sara Borrell fellowship to ELM) and Ministry of Science and Innovation (MTM2008-06747-C02-02 and FPU fellowship award to VU), Spain; AGAUR-Generalitat de Catalunya (Grant 2009SGR-581); Fundaciola Maratode TV3; Red Tematica de Investigacion Cooperativa en Cancer (RTICC); Asociacion Espanola Contra el Cancer (AECC); EU-FP7-201663; and RO1-CA089715 and CA34627; the Spanish National Institute for Bioinformatics (www.inab.org); and by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, USA. MD Anderson support for this project included U01 CA 127615 (XW); R01 CA 74880 (XW); P50 CA 91846 (XW, CPD); Betty B. Marcus Chair fund in Cancer Prevention (XW); UT Research Trust fund (XW) and R01 CA 131335 (JG)

    Multi-messenger observations of a binary neutron star merger

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    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

    Modelling optimal location for pre-hospital helicopter emergency medical services

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    <p>Abstract</p> <p>Background</p> <p>Increasing the range and scope of early activation/auto launch helicopter emergency medical services (HEMS) may alleviate unnecessary injury mortality that disproportionately affects rural populations. To date, attempts to develop a quantitative framework for the optimal location of HEMS facilities have been absent.</p> <p>Methods</p> <p>Our analysis used five years of critical care data from tertiary health care facilities, spatial data on origin of transport and accurate road travel time catchments for tertiary centres. A location optimization model was developed to identify where the expansion of HEMS would cover the greatest population among those currently underserved. The protocol was developed using geographic information systems (GIS) to measure populations, distances and accessibility to services.</p> <p>Results</p> <p>Our model determined Royal Inland Hospital (RIH) was the optimal site for an expanded HEMS – based on denominator population, distance to services and historical usage patterns.</p> <p>Conclusion</p> <p>GIS based protocols for location of emergency medical resources can provide supportive evidence for allocation decisions – especially when resources are limited. In this study, we were able to demonstrate conclusively that a logical choice exists for location of additional HEMS. This protocol could be extended to location analysis for other emergency and health services.</p

    Comprehensive Analysis of 5-Aminolevulinic Acid Dehydrogenase (ALAD) Variants and Renal Cell Carcinoma Risk among Individuals Exposed to Lead

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    BACKGROUND: Epidemiologic studies are reporting associations between lead exposure and human cancers. A polymorphism in the 5-aminolevulinic acid dehydratase (ALAD) gene affects lead toxicokinetics and may modify the adverse effects of lead. METHODS: The objective of this study was to evaluate single-nucleotide polymorphisms (SNPs) tagging the ALAD region among renal cancer cases and controls to determine whether genetic variation alters the relationship between lead and renal cancer. Occupational exposure to lead and risk of cancer was examined in a case-control study of renal cell carcinoma (RCC). Comprehensive analysis of variation across the ALAD gene was assessed using a tagging SNP approach among 987 cases and 1298 controls. Occupational lead exposure was estimated using questionnaire-based exposure assessment and expert review. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression. RESULTS: The adjusted risk associated with the ALAD variant rs8177796(CT/TT) was increased (OR = 1.35, 95%CI = 1.05-1.73, p-value = 0.02) when compared to the major allele, regardless of lead exposure. Joint effects of lead and ALAD rs2761016 suggest an increased RCC risk for the homozygous wild-type and heterozygous alleles ((GG)OR = 2.68, 95%CI = 1.17-6.12, p = 0.01; (GA)OR = 1.79, 95%CI = 1.06-3.04 with an interaction approaching significance (p(int) = 0.06). No significant modification in RCC risk was observed for the functional variant rs1800435(K68N). Haplotype analysis identified a region associated with risk supporting tagging SNP results. CONCLUSION: A common genetic variation in ALAD may alter the risk of RCC overall, and among individuals occupationally exposed to lead. Further work in larger exposed populations is warranted to determine if ALAD modifies RCC risk associated with lead exposure

    Analysis of SNPs and Haplotypes in Vitamin D Pathway Genes and Renal Cancer Risk

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    In the kidney vitamin D is converted to its active form. Since vitamin D exerts its activity through binding to the nuclear vitamin D receptor (VDR), most genetic studies have primarily focused on variation within this gene. Therefore, analysis of genetic variation in VDR and other vitamin D pathway genes may provide insight into the role of vitamin D in renal cell carcinoma (RCC) etiology. RCC cases (N = 777) and controls (N = 1,035) were genotyped to investigate the relationship between RCC risk and variation in eight target genes. Minimum-p-value permutation (Min-P) tests were used to identify genes associated with risk. A three single nucleotide polymorphism (SNP) sliding window was used to identify chromosomal regions with a False Discovery Rate of <10%, where subsequently, haplotype relative risks were computed in Haplostats. Min-P values showed that VDR (p-value = 0.02) and retinoid-X-receptor-alpha (RXRA) (p-value = 0.10) were associated with RCC risk. Within VDR, three haplotypes across two chromosomal regions of interest were identified. The first region, located within intron 2, contained two haplotypes that increased RCC risk by approximately 25%. The second region included a haplotype (rs2239179, rs12717991) across intron 4 that increased risk among participants with the TC (OR = 1.31, 95% CI = 1.09–1.57) haplotype compared to participants with the common haplotype, TT. Across RXRA, one haplotype located 3′ of the coding sequence (rs748964, rs3118523), increased RCC risk 35% among individuals with the variant haplotype compared to those with the most common haplotype. This study comprehensively evaluated genetic variation across eight vitamin D pathway genes in relation to RCC risk. We found increased risk associated with VDR and RXRA. Replication studies are warranted to confirm these findings

    Stable carbon and nitrogen isotope enrichment in primate tissues

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    Isotopic studies of wild primates have used a wide range of tissues to infer diet and model the foraging ecologies of extinct species. The use of mismatched tissues for such comparisons can be problematic because differences in amino acid compositions can lead to small isotopic differences between tissues. Additionally, physiological and dietary differences among primate species could lead to variable offsets between apatite carbonate and collagen. To improve our understanding of the isotopic chemistry of primates, we explored the apparent enrichment (ε*) between bone collagen and muscle, collagen and fur or hair keratin, muscle and keratin, and collagen and bone carbonate across the primate order. We found that the mean ε* values of proteinaceous tissues were small (≤1‰), and uncorrelated with body size or phylogenetic relatedness. Additionally, ε* values did not vary by habitat, sex, age, or manner of death. The mean ε* value between bone carbonate and collagen (5.6 ± 1.2‰) was consistent with values reported for omnivorous mammals consuming monoisotopic diets. These primate-specific apparent enrichment values will be a valuable tool for cross-species comparisons. Additionally, they will facilitate dietary comparisons between living and fossil primates

    Large-Scale Pathway-Based Analysis of Bladder Cancer Genome-Wide Association Data from Five Studies of European Background

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    Pathway analysis of genome-wide association studies (GWAS) offer a unique opportunity to collectively evaluate genetic variants with effects that are too small to be detected individually. We applied a pathway analysis to a bladder cancer GWAS containing data from 3,532 cases and 5,120 controls of European background (n = 5 studies). Thirteen hundred and ninety-nine pathways were drawn from five publicly available resources (Biocarta, Kegg, NCI-PID, HumanCyc, and Reactome), and we constructed 22 additional candidate pathways previously hypothesized to be related to bladder cancer. In total, 1421 pathways, 5647 genes and ∼90,000 SNPs were included in our study. Logistic regression model adjusting for age, sex, study, DNA source, and smoking status was used to assess the marginal trend effect of SNPs on bladder cancer risk. Two complementary pathway-based methods (gene-set enrichment analysis [GSEA], and adapted rank-truncated product [ARTP]) were used to assess the enrichment of association signals within each pathway. Eighteen pathways were detected by either GSEA or ARTP at P≤0.01. To minimize false positives, we used the I2 statistic to identify SNPs displaying heterogeneous effects across the five studies. After removing these SNPs, seven pathways (‘Aromatic amine metabolism’ [PGSEA = 0.0100, PARTP = 0.0020], ‘NAD biosynthesis’ [PGSEA = 0.0018, PARTP = 0.0086], ‘NAD salvage’ [PARTP = 0.0068], ‘Clathrin derived vesicle budding’ [PARTP = 0.0018], ‘Lysosome vesicle biogenesis’ [PGSEA = 0.0023, PARTP<0.00012], ’Retrograde neurotrophin signaling’ [PGSEA = 0.00840], and ‘Mitotic metaphase/anaphase transition’ [PGSEA = 0.0040]) remained. These pathways seem to belong to three fundamental cellular processes (metabolic detoxification, mitosis, and clathrin-mediated vesicles). Identification of the aromatic amine metabolism pathway provides support for the ability of this approach to identify pathways with established relevance to bladder carcinogenesis
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