Association of the rs3743205 variant of DYX1C1 with dyslexia in Chinese children

<p>Abstract</p> <p><b>Background</b></p> <p>Dyslexia is a learning disability that is characterized by difficulties in the acquisition of reading and spelling skills independent of intelligence, motivation or schooling. Studies of western populations have suggested that <it>DYX1C1 </it>is a candidate gene for dyslexia. In view of the different languages used in Caucasian and Chinese populations, it is therefore worthwhile to investigate whether there is an association of <it>DYX1C1 </it>in Chinese children with dyslexia.</p> <p>Method and Results</p> <p>Eight single nucleotide polymorphisms (SNPs) were genotyped from three hundred and ninety three individuals from 131 Chinese families with two which have been reported in the literature and six tag SNPs at <it>DYX1C1</it>. Analysis for allelic and haplotypic associations was performed with the UNPHASED program and multiple testing was corrected using false discovery rates. We replicated the previously reported association of rs3743205 in Chinese children with dyslexia (<it>p</it>_{<it>corrected </it>}= 0.0072). This SNP was also associated with rapid naming, phonological memory and orthographic skills in quantitative trait analysis.</p> <p>Conclusion</p> <p>Our findings suggest that <it>DYX1C1 </it>is associated with dyslexia in people of Chinese ethnicity in Hong Kong.</p

Interaction Between Pre- and Post-Migration Factors on Depressive Symptoms in New Migrants to Hong Kong from Mainland China

The goal of the current study is to examine the role of poor migration planning as a moderator for the effects of two post-migration factors, namely acculturation stress and quality of life, on symptoms of depression. Using a random sample of 347 Hong Kong new migrants from a 1-year longitudinal study, we used multiple regression analyses to examine both the direct and interaction effects of poorly planned migration, acculturation stress, and quality of life on depressive symptoms. Although poorly planned migration did not predict depressive symptoms at 1-year follow-up, it did exacerbate the detrimental effect of the two post-migration factors, namely high stress or low quality of life (both also measured at baseline) on depressive symptoms at this stage. Our results indicate that preventive measures must be developed for new immigrants in Hong Kong, especially for those who were not well prepared for migration

Adjusting a cancer mortality-prediction model for disease status-related eligibility criteria

<p>Abstract</p> <p>Background</p> <p>Volunteering participants in disease studies tend to be healthier than the general population partially due to specific enrollment criteria. Using modeling to accurately predict outcomes of cohort studies enrolling volunteers requires adjusting for the bias introduced in this way. Here we propose a new method to account for the effect of a specific form of healthy volunteer bias resulting from imposing disease status-related eligibility criteria, on disease-specific mortality, by explicitly modeling the length of the time interval between the moment when the subject becomes ineligible for the study, and the outcome.</p> <p>Methods</p> <p>Using survival time data from 1190 newly diagnosed lung cancer patients at MD Anderson Cancer Center, we model the time from clinical lung cancer diagnosis to death using an exponential distribution to approximate the length of this interval for a study where lung cancer death serves as the outcome. Incorporating this interval into our previously developed lung cancer risk model, we adjust for the effect of disease status-related eligibility criteria in predicting the number of lung cancer deaths in the control arm of CARET. The effect of the adjustment using the MD Anderson-derived approximation is compared to that based on SEER data.</p> <p>Results</p> <p>Using the adjustment developed in conjunction with our existing lung cancer model, we are able to accurately predict the number of lung cancer deaths observed in the control arm of CARET.</p> <p>Conclusions</p> <p>The resulting adjustment was accurate in predicting the lower rates of disease observed in the early years while still maintaining reasonable prediction ability in the later years of the trial. This method could be used to adjust for, or predict the duration and relative effect of any possible biases related to disease-specific eligibility criteria in modeling studies of volunteer-based cohorts.</p

Versatility of MicroRNA Biogenesis

MicroRNAs (miRNAs) are short single-stranded RNA molecules that regulate gene expression. MiRNAs originate from large primary (pri) and precursor (pre) transcripts that undergo various processing steps along their biogenesis pathway till they reach their mature and functional form. It is not clear, however, whether all miRNAs are processed similarly. Here we show that the ratio between pre-miRNA and mature miRNA forms varies between different miRNAs. Moreover, over-expression of several factors involved in miRNA biogenesis, including Exportin-5, Drosha, NF90a, NF45 and KSRP, displayed bidirectional effects on pre/mature miRNA ratios, suggesting their intricate biogenesis sensitivity. In an attempt to identify additional factors that might explain the versatility in miRNA biogenesis we have analyzed the contribution of two hnRNP family members, hnRNPH1 and hnRNPR. Knock-down or over-expression of these genes suggested that hnRNPR inhibits, whereas hnRNPH1 facilitates, miRNA processing. Overall, our results emphasize that miRNA biogenesis is versatile

Deriving a mutation index of carcinogenicity using protein structure and protein interfaces

With the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/

Surface Chemistry of Perfluoropolyethers and Hydrogenated Analogs: Are Studies of Model Compounds Useful?

We have studied adsorption, desorption, and decomposition of ethers on Ru(001), an atomically-smooth metal surface. We have compared diethers with monoethers, and fluorinated ethers with hydrogenated ethers. The number of ether linkages does not strongly influence adsorption bond strength, nor the extent of decomposition. Fluorination does weaken the adsorption bond strength and prevents decomposition. These studies suggest that the surface properties of monomeric ethers can be used to predict properties of oligomeric, and perhaps even polymeric, ethers

Does Hepatitis C Virus Infection Increase Risk for Stroke? A Population-Based Cohort Study

BACKGROUND: The relationship between hepatitis C virus infection and risk of stroke remains inconsistent. This study evaluates the risk of stroke in association with chronic hepatitis C infection in a longitudinal population-based cohort. METHODS: We identified 4,094 adults newly diagnosed with hepatitis C infection in 2002-2004 from the Taiwan National Health Insurance Research Database. Comparison group consisted of 16,376 adults without hepatitis C infection randomly selected from the same dataset, frequency matched by age and sex. Events of stroke from 2002-2008 were ascertained from medical claims (International Classification of Diseases, Ninth Revision, Clinical Modification, ICD-9-CM, codes 430-438). Multivariate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for potential associated factors including HCV infection, age, sex, low-income status, urbanization, cessation of cigarette smoking, alcohol-related illness, obesity, history of chronic diseases and medication use. FINDINGS: During 96,752 person-years of follow-up, there were 1981 newly diagnosed stroke cases. The HRs of stroke associated with medical conditions such as hypertension, diabetes and heart disease were 1.48 (95% CI 1.33 to 1.65), 1.23 (95% CI 1.11 to 1.36) and 1.17 (95% CI 1.06 to 1.30), respectively, after adjustment for covariates. The cumulative risk of stroke for people with hepatitis C and without hepatitis C infections was 2.5% and 1.9%, respectively (p<0.0001). Compared with people without hepatitis C infection, the adjusted HR of stroke was 1.27 (95% CI 1.14 to 1.41) for people with hepatitis C infection. CONCLUSION: Chronic hepatitis C infection increases stroke risk and should be considered an important and independent risk factor

Zigzag Turning Preference of Freely Crawling Cells

The coordinated motion of a cell is fundamental to many important biological processes such as development, wound healing, and phagocytosis. For eukaryotic cells, such as amoebae or animal cells, the cell motility is based on crawling and involves a complex set of internal biochemical events. A recent study reported very interesting crawling behavior of single cell amoeba: in the absence of an external cue, free amoebae move randomly with a noisy, yet, discernible sequence of ‘run-and-turns’ analogous to the ‘run-and-tumbles’ of swimming bacteria. Interestingly, amoeboid trajectories favor zigzag turns. In other words, the cells bias their crawling by making a turn in the opposite direction to a previous turn. This property enhances the long range directional persistence of the moving trajectories. This study proposes that such a zigzag crawling behavior can be a general property of any crawling cells by demonstrating that 1) microglia, which are the immune cells of the brain, and 2) a simple rule-based model cell, which incorporates the actual biochemistry and mechanics behind cell crawling, both exhibit similar type of crawling behavior. Almost all legged animals walk by alternating their feet. Similarly, all crawling cells appear to move forward by alternating the direction of their movement, even though the regularity and degree of zigzag preference vary from one type to the other

Common and Distant Structural Characteristics of Feruloyl Esterase Families from Aspergillus oryzae

Background: Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed. Methodology/Principal Findings: The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations. Conclusions/Significance: Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods. © 2012 Udatha et al.published_or_final_versio