Genetic association study of dyslexia and ADHD candidate genes in a Spanish cohort: Implications of comorbid samples

Published: October 31, 2018Dyslexia and attention deficit hyperactivity disorder (ADHD) are two complex neuro-behaviorally disorders that co-occur more often than expected, so that reading disability has been linked to inattention symptoms. We examined 4 SNPs located on genes previously associated to dyslexia (KIAA0319, DCDC2, DYX1C1 and FOXP2) and 3 SNPs within genes related to ADHD (COMT, MAOA and DBH) in a cohort of Spanish children (N = 2078) that met the criteria of having one, both or none of these disorders (dyslexia and ADHD). We used a case-control approach comparing different groups of samples based on each individual diagnosis. In addition, we also performed a quantitative trait analysis with psychometric measures on the general population (N = 3357). The results indicated that the significance values for some markers change depending on the phenotypic groups compared and/or when considering pair-wise marker interactions. Furthermore, our quantitative trait study showed significant genetic associations with specific cognitive processes. These outcomes advocate the importance of establishing rigorous and homogeneous criteria for the diagnosis of cognitive disorders, as well as the relevance of considering cognitive endophenotypes.The work of MSM and MC was supported by CONSOLIDER-Ingenio- 2010_COEDUCA (CSD2008-00048). AMA, LB and AG-L’s work was supported by the Basque Department of Industry, Tourism and Trade (Etortek Program), Innovation Technology Department of Bizkaia and CIBERehd Network. MC was also supported by grants (PSI2015-67353-R), and Ayuda Centro de Excelencia Severo Ochoa SEV-2015-0490 from the MINECO, and by grant (ERC-2011-ADG-295362) from the European Research Council. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Regulation of the transcriptional program by DNA methylation during human αβ T-cell development

© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. Thymocyte differentiation is a complex process involving well-defined sequential developmental stages that ultimately result in the generation of mature T-cells. In this study, we analyzed DNA methylation and gene expression profiles at successive human thymus developmental stages. Gain and loss of methylation occurred during thymocyte differentiation, but DNA demethylation was much more frequent than de novo methylation and more strongly correlated with gene expression. These changes took place in CpG-poor regions and were closely associated with T-cell differentiation and TCR function. Up to 88 genes that encode transcriptional regulators, some of whose functions in T-cell development are as yet unknown, were differentially methylated during differentiation. Interestingly, no reversion of accumulated DNA methylation changes was observed as differentiation progressed, except in a very small subset of key genes (RAG1, RAG2, CD8A, PTCRA, etc.), indicating that methylation changes are mostly unique and irreversible events. Our study explores the contribution of DNA methylation to T-cell lymphopoiesis and provides a fine-scale map of differentially methylated regions associated with gene expression changes. These can lay the molecular foundations for a better interpretation of the regulatory networks driving human thymopoiesis.Plan Nacional de [I+D+I 2008–2011]; Instituto de Salud Carlos III [grant number PI12/02587]; Red Española de Investigación Renal (REDinREN) [grant number RD12/0021/0018 and RD12/0021/0021]; Spanish Ministry of Science and Innovation [grant number SAF2010- 15106 and PLE2009-0110]; European Union [Fondos FEDER]Peer Reviewe

Correction: Genetic association study of dyslexia and ADHD candidate genes in a Spanish cohort: Implications of comorbid samples (PLoS ONE (2018) 13:10 (e0206431) DOI: 10.1371/journal.pone.0206431)

Publisher Copyright: © 2018 Sánchez-Morán et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.There are errors in the Author Contributions. The correct contributions are: Conceptualization: AMA MC. Formal analysis: MSM AMA JAH MC LB AGL. Funding acquisition: MC AMA. Investigation: MSM JAD AE MTB LJF AMA MC. Methodology: MSM AMA JAH MC. Project administration: MC AMA. Supervision: AMA MC. Writing – original draft: MSM AMA. Writing – review and editing: MSM AMA MC

Correction: Genetic association study of dyslexia and ADHD candidate genes in a Spanish cohort: Implications of comorbid samples.

[This corrects the article DOI: 10.1371/journal.pone.0206431.]

Cross-sectional study of human coding- and non-coding RNAs in progressive stages of Helicobacter pylori infection

Helicobacter pylori infects 4.4 billion individuals worldwide and is considered the most important etiologic agent for peptic ulcers and gastric cancer. Individual response to H. pylori infection is complex and depends on complex interactions between host and environmental factors. The pathway towards gastric cancer is a sequence of events known as Correa's model of gastric carcinogenesis, a stepwise inflammatory process from normal mucosa to chronic-active gastritis, atrophy, metaplasia and gastric adenocarcinoma. This study examines gastric clinical specimens representing different steps of the Correa pathway with the aim of identifying the expression profiles of coding- and non-coding RNAs that may have a role in Correa's model of gastric carcinogenesis. We screened for differentially expressed genes in gastric biopsies by employing RNAseq, microarrays and qRT-PCR. Here we provide a detailed description of the experiments, methods and results generated. The datasets may help other scientists and clinicians to find new clues to the pathogenesis of H. pylori and the mechanisms of progression of the infection to more severe gastric diseases. Data is available via ArrayExpress. Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.1234933