Gene family information facilitates variant interpretation and identification of disease-associated genes in neurodevelopmental disorders

Background Classifying pathogenicity of missense variants represents a major challenge in clinical practice during the diagnoses of rare and genetic heterogeneous neurodevelopmental disorders (NDDs). While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes belong to gene families. The use of gene family information for disease gene discovery and variant interpretation has not yet been investigated on a genome-wide scale. We empirically evaluate whether paralog-conserved or non-conserved sites in human gene families are important in NDDs. Methods Gene family information was collected from Ensembl. Paralog-conserved sites were defined based on paralog sequence alignments; 10,068 NDD patients and 2078 controls were statistically evaluated for de novo variant burden in gene families. Results We demonstrate that disease-associated missense variants are enriched at paralog-conserved sites across all disease groups and inheritance models tested. We developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in NDD patients of which 28 represent novel candidate genes for NDD which are brain expressed and under evolutionary constraint. Conclusion This study represents the first method to incorporate gene family information into a statistical framework to interpret variant data for NDDs and to discover new NDD-associated genes

Involvement of cell surface TG2 in the aggregation of K562 cells triggered by gluten

Gluten-induced aggregation of K562 cells represents an in vitro model reproducing the early steps occurring in the small bowel of celiac patients exposed to gliadin. Despite the clear involvement of TG2 in the activation of the antigen-presenting cells, it is not yet clear in which compartment it occurs. Herein we study the calcium-dependent aggregation of these cells, using either cell-permeable or cell-impermeable TG2 inhibitors. Gluten induces efficient aggregation when calcium is absent in the extracellular environment, while TG2 inhibitors do not restore the full aggregating potential of gluten in the presence of calcium. These findings suggest that TG2 activity is not essential in the cellular aggregation mechanism. We demonstrate that gluten contacts the cells and provokes their aggregation through a mechanism involving the A-gliadin peptide 31-43. This peptide also activates the cell surface associated extracellular TG2 in the absence of calcium. Using a bioinformatics approach, we identify the possible docking sites of this peptide on the open and closed TG2 structures. Peptide docks with the closed TG2 structure near to the GTP/GDP site, by establishing molecular interactions with the same amino acids involved in stabilization of GTP binding. We suggest that it may occur through the displacement of GTP, switching the TG2 structure from the closed to the active open conformation. Furthermore, docking analysis shows peptide binding with the β-sandwich domain of the closed TG2 structure, suggesting that this region could be responsible for the different aggregating effects of gluten shown in the presence or absence of calcium. We deduce from these data a possible mechanism of action by which gluten makes contact with the cell surface, which could have possible implications in the celiac disease onset

Cortical Thinning in Patients with Recent Onset Post-Traumatic Stress Disorder after a Single Prolonged Trauma Exposure

Most of magnetic resonance imaging (MRI) studies about post-traumatic stress disorder (PTSD) focused primarily on measuring of small brain structure volume or regional brain volume changes. There were rare reports investigating cortical thickness alterations in recent onset PTSD. Recent advances in computational analysis made it possible to measure cortical thickness in a fully automatic way, along with voxel-based morphometry (VBM) that enables an exploration of global structural changes throughout the brain by applying statistical parametric mapping (SPM) to high-resolution MRI. In this paper, Laplacian method was utilized to estimate cortical thickness after automatic segmentation of gray matter from MR images under SPM. Then thickness maps were analyzed by SPM8. Comparison between 10 survivors from a mining disaster with recent onset PTSD and 10 survivors without PTSD from the same trauma indicates cortical thinning in the left parietal lobe, right inferior frontal gyrus, and right parahippocampal gyrus. The regional cortical thickness of the right inferior frontal gyrus showed a significant negative correlation with the CAPS score in the patients with PTSD. Our study suggests that shape-related cortical thickness analysis may be more sensitive than volumetric analysis to subtle alteration at early stage of PTSD

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12- q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice