Genomic and Proteomic Biomarker Discovery in Neurological Disease

Technology for high-throughout scanning of the human genome and its encoded proteins have rapidly developed to allow systematic analyses of human disease. Application of these technologies is becoming an increasingly effective approach for identifying the biological basis of genetically complex neurological diseases. This review will highlight significant findings resulting from the use of a multitude of genomic and proteomic technologies toward biomarker discovery in neurological disorders. Though substantial discoveries have been made, there is clearly significant promise and potential remaining to be fully realized through increasing use of and further development of -omic technologies

Device-specific Outcomes Following Endovascular Aortic Aneurysm Repair

AbstractObjectiveTo compare aneurysm morphology, initial outcomes and mid-term results in patients receiving Talent or Zenith grafts for elective endovascular aneurysm repair (EVR).MethodsOver a 6-year time period ending in 2007, 286 patients underwent elective EVR of infra-renal abdominal aortic aneurysms using Talent or Zenith devices. Patient demographics, aneurysm morphology and initial outcomes (primary-assisted technical success rates, 30-day limb occlusion, re-intervention and mortality) were compared using chi-squared tests or Student's t-tests. Kaplan–Meier curves were calculated to compare cumulative rates of freedom from type I or III endoleak, re-intervention, endograft patency and overall survival over mid-term follow-up.ResultsAdverse aneurysm morphology was more common in patients receiving Zenith stent grafts, with a greater proportion of shorter neck lengths (<10mm, 12.9% vs 0%; p≤0.001) and severe neck angulation (>60°, 25.0% vs 10.3%; p=0.002). Equivalent primary-assisted technical success rates were achieved with both Talent and Zenith grafts (94.0% vs 96.1%; p=0.41). A significant number of adjunctive procedures were required in both groups to obtain a proximal endograft seal, with relatively more procedures performed in the Talent group (28.6% vs 12.4%; p=0.003). Early outcomes were similar for 30-day re-intervention (5.3% vs 3.9%; p=0.91), 30-day limb occlusion (1.5% vs 2.6%; p=0.51), 30-day morbidity (6.8% vs 11.8%; p=0.15) and 30-day mortality (4.5% vs 3.9%; p=0.80).The cumulative incidence of freedom from re-intervention was 88.3±2.9%, 86.1±3.3% and 84.1±3.9% at 1, 2 and 3 years respectively. There were no significant differences between Talent and Zenith groups for re-intervention, type I or III endoleak or limb occlusion rates over the same time period. Overall patient survival was 88.4±2.85% at 1 year, 83.7±4.0% at 2 years and 78.9±5.5% at 3 years.ConclusionsEquivalent primary-assisted technical success rates can be achieved using either Talent or Zenith endografts for endovascular aneurysm repair, but operating teams should be prepared to perform additional adjunctive procedures to obtain a primary proximal seal with either stent. The Zenith endograft performed well in the context of less favourable pre-operative aneurysm morphology. Both Talent and Zenith endografts appeared equally durable in the medium term

Brans-Dicke model constrained from Big Bang nucleosynthesis and magnitude redshift relations of Supernovae

The Brans-Dicke model with a variable cosmological term ($BD\Lambda$) has been investigated with use of the coupling constant of $\omega=10^4$. Parameters inherent in this model are constrained from comparison between Big Bang nucleosynthesis and the observed abundances. Furthermore, the magnitude redshift ($m-z$) relations are studied for $BD\Lambda$ with and without another constant cosmological term in a flat universe. Observational data of Type Ia Supernovae are used in the redshift range of $0.01<z<2$. It is found that our model with energy density of the constant cosmological term with the value of 0.7 can explain the SNIa observations, though the model parameters are insensitive to the $m-z$ relation.Comment: Submitted to A&A, 4 pages, 3 figure

High-content siRNA screening of the kinome identifies kinases involved in Alzheimer's disease-related tau hyperphosphorylation

<p>Abstract</p> <p>Background</p> <p>Neurofibrillary tangles (NFT), a cardinal neuropathological feature of Alzheimer's disease (AD) that is highly correlated with synaptic loss and dementia severity, appear to be partly attributable to increased phosphorylation of the microtubule stabilizing protein tau at certain AD-related residues. Identifying the kinases involved in the pathologic phosphorylation of tau may provide targets at which to aim new AD-modifying treatments.</p> <p>Results</p> <p>We report results from a screen of 572 kinases in the human genome for effects on tau hyperphosphorylation using a loss of function, high-throughput RNAi approach. We confirm effects of three kinases from this screen, the eukaryotic translation initiation factor 2 α kinase 2 (EIF2AK2), the dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 1A (DYRK1A), and the A-kinase anchor protein 13 (AKAP13) on tau phosphorylation at the 12E8 epitope (serine 262/serine 356). We provide evidence that EIF2AK2 effects may result from effects on tau protein expression, whereas DYRK1A and AKAP13 are likely more specifically involved in tau phosphorylation pathways.</p> <p>Conclusions</p> <p>These findings identify novel kinases that phosphorylate tau protein and provide a valuable reference data set describing the kinases involved in phosphorylating tau at an AD-relevant epitope.</p

Insights into the molecular determinants involved in cap recognition by the vaccinia virus D10 decapping enzyme

Decapping enzymes are required for the removal of the 5′-end m7GpppN cap of mRNAs to allow their decay in cells. While many cap-binding proteins recognize the cap structure via the stacking of the methylated guanosine ring between two aromatic residues, the precise mechanism of cap recognition by decapping enzymes has yet to be determined. In order to get insights into the interaction of decapping enzymes with the cap structure, we studied the vaccinia virus D10 decapping enzyme as a model to investigate the important features for substrate recognition by the enzyme. We demonstrate that a number of chemically modified purines can competitively inhibit the decapping reaction, highlighting the molecular features of the cap structure that are required for recognition by the enzyme, such as the nature of the moiety at positions 2 and 6 of the guanine base. A 3D structural model of the D10 protein was generated which suggests amino acids implicated in cap binding. Consequently, we expressed 17 mutant proteins with amino acid substitutions in the active site of D10 and found that eight are critical for the decapping activity. These data underscore the functional features involved in the non-canonical cap-recognition by the vaccinia virus D10 decapping enzyme

Direct observation of procedural skills (DOPS) assessment in diagnostic gastroscopy: nationwide evidence of validity and competency development during training.

Background: Validated competency assessment tools and the data supporting milestone development during gastroscopy training are lacking. We aimed to assess the validity of the formative direct observation of procedural skills (DOPS) assessment tool in diagnostic gastroscopy and study competency development using DOPS. Methods: This was a prospective multicentre (N = 275) analysis of formative gastroscopy DOPS assessments. Internal structure validity was tested using exploratory factor analysis and reliability estimated using generalisability theory. Item and global DOPS scores were stratified by lifetime procedure count to define learning curves, using a threshold determined from receiver operator characteristics (ROC) analysis. Multivariable binary logistic regression analysis was performed to identify independent predictors of DOPS competence. Results: In total, 10086 DOPS were submitted for 987 trainees. Exploratory factor analysis identified three distinct item groupings, representing 'pre-procedure', 'technical', and 'post-procedure non-technical' skills. From generalisability analyses, sources of variance in overall DOPS scores included trainee ability (31%), assessor stringency (8%), assessor subjectivity (18%), and trainee case-to-case variation (43%). The combination of three assessments from three assessors was sufficient to achieve the reliability threshold of 0.70. On ROC analysis, a mean score of 3.9 provided optimal sensitivity and specificity for determining competency. This threshold was attained in the order of 'pre-procedure' (100-124 procedures), 'technical' (150-174 procedures), 'post-procedure non-technical' skills (200-224 procedures), and global competency (225-249 procedures). Higher lifetime procedure count, DOPS count, surgical trainees and assessors, higher trainee seniority, and lower case difficulty were significant multivariable predictors of DOPS competence. Conclusion: This study establishes milestones for competency acquisition during gastroscopy training and provides validity and reliability evidence to support gastroscopy DOPS as a competency assessment tool

New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background

<p>Abstract</p> <p>Background</p> <p>Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis</p> <p>Results</p> <p>Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase -480 C/T; endothelial nitric oxide synthase 690 C/T and glu298asp; vitamin K-dependent coagulation factor seven arg353glu, glycoprotein Ia/IIa 873 G/A and E-selectin ser128arg.</p> <p>Conclusion</p> <p>This study provides an alternative and reliable method to approach complex diseases. Indeed, the application of a novel artificial intelligence-based method offers a new insight into genetic markers of sporadic ALS pointing out the existence of a strong genetic background.</p