The Hellenic type of nondeletional hereditary persistence of fetal hemoglobin results from a novel mutation (g.-109G>T) in the HBG2 gene promoter

Nondeletional hereditary persistence of fetal hemoglobin (nd-HPFH), a rare hereditary condition resulting in elevated levels of fetal hemoglobin (Hb F) in adults, is associated with promoter mutations in the human fetal globin (HBG1 and HBG2) genes. In this paper, we report a novel type of nd-HPFH due to a HBG2 gene promoter mutation (HBG2:g.-109G>T). This mutation, located at the 3′ end of the HBG2 distal CCAAT box, was initially identified in an adult female subject of Central Greek origin and results in elevated Hb F levels (4.1%) and significantly increased Gγ-globin chain production (79.2%). Family studies and DNA analysis revealed that the HBG2:g.-109G>T mutation is also found in the family members in compound heterozygosity with the HBG2:g.-158C>T single nucleotide polymorphism or the silent HBB:g.-101C>T β-thalassemia mutation, resulting in the latter case in significantly elevated Hb F levels (14.3%). Electrophoretic mobility shift analysis revealed that the HBG2:g.-109G>T mutation abolishes a transcription factor binding site, consistent with previous observations using DNA footprinting analysis, suggesting that guanine at position HBG2/1:g.-109 is critical for NF-E3 binding. These data suggest that the HBG2:g-109G>T mutation has a functional role in increasing HBG2 transcription and is responsible for the HPFH phenotype observed in our index cases

Genetics of Myasthenia Gravis: A Case-Control Association Study in the Hellenic Population

Myasthenia gravis (MG) is an heterogeneous autoimmune disease characterized by the production of autoantibodies against proteins of the postsynaptic membrane, in the neuromuscular junction. The contribution of genetic factors to MG susceptibility has been evaluated through family and twin studies however, the precise genetic background of the disease remains elusive. We conducted a case-control association study in 101 unrelated MG patients of Hellenic origin and 101 healthy volunteers in order to assess the involvement of common genetic variants in susceptibility to MG. We focused on three candidate genes which have been clearly associated with several autoimmune diseases, aiming to investigate their potential implication in MG pathogenesis. These are interferon regulatory factor 5 (IRF-5), TNFα-induced protein 3 (TNFAIP3), also known as A20, and interleukin-10 (IL-10), key molecules in the regulation of immune function. A statistical trend of association (P=0.068) between IL-10 promoter single nucleotide polymorphisms (SNPs) and the subgroups of early and late-onset MG patients was revealed. No statistically significant differences were observed in the rest of the variants examined. As far as we are aware, this is the first worldwide attempt to address the possible association between IRF-5 and TNFAIP3 common genetic variants and the genetic basis of MG

VariVis: a visualisation toolkit for variation databases

<p>Abstract</p> <p>Background</p> <p>With the completion of the Human Genome Project and recent advancements in mutation detection technologies, the volume of data available on genetic variations has risen considerably. These data are stored in online variation databases and provide important clues to the cause of diseases and potential side effects or resistance to drugs. However, the data presentation techniques employed by most of these databases make them difficult to use and understand.</p> <p>Results</p> <p>Here we present a visualisation toolkit that can be employed by online variation databases to generate graphical models of gene sequence with corresponding variations and their consequences. The VariVis software package can run on any web server capable of executing Perl CGI scripts and can interface with numerous Database Management Systems and "flat-file" data files. VariVis produces two easily understandable graphical depictions of any gene sequence and matches these with variant data. While developed with the goal of improving the utility of human variation databases, the VariVis package can be used in any variation database to enhance utilisation of, and access to, critical information.</p

Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach

We developed a series of interrelated locus-specific databases to store all published and unpublished genetic variation related to hemoglobinopathies and thalassemia and implemented microattribution to encourage submission of unpublished observations of genetic variation to these public repositories. A total of 1,941 unique genetic variants in 37 genes, encoding globins and other erythroid proteins, are currently documented in these databases, with reciprocal attribution of microcitations to data contributors. Our project provides the first example of implementing microattribution to incentivise submission of all known genetic variation in a defined system. It has demonstrably increased the reporting of human variants, leading to a comprehensive online resource for systematically describing human genetic variation in the globin genes and other genes contributing to hemoglobinopathies and thalassemias. The principles established here will serve as a model for other systems and for the analysis of other common and/or complex human genetic diseases

Mild dyserythropoiesis and beta-like globin gene expression imbalance due to the loss of histone chaperone ASF1B

The expression of the human β-like globin genes follows a well-orchestrated developmental pattern, undergoing two essential switches, the first one during the first weeks of gestation (ε to γ), and the second one during the perinatal period (γ to β). The γ- to β-globin gene switching mechanism includes suppression of fetal (γ-globin, HbF) and activation of adult (β-globin, HbA) globin gene transcription. In hereditary persistence of fetal hemoglobin (HPFH), the γ-globin suppression mechanism is impaired leaving these individuals with unusual elevated levels of fetal hemoglobin (HbF) in adulthood. Recently, the transcription factors KLF1 and BCL11A have been established as master regulators of the γ- to β-globin switch. Previously, a genomic variant in the KLF1 gene, identified by linkage analysis performed on twenty-seven members of a Maltese family, was found to be associated with HPFH. However, variation in the levels of HbF among family members, and those from other reported families carrying genetic variants in KLF1, suggests additional contributors to globin switching. ASF1B was downregulated in the family members with HPFH. Here, we investigate the role of ASF1B in γ- to β-globin switching and erythropoiesis in vivo. Mouse-human interspecies ASF1B protein identity is 91.6%. By means of knockdown functional assays in human primary erythroid cultures and analysis of the erythroid lineage in Asf1b knockout mice, we provide evidence that ASF1B is a novel contributor to steady-state erythroid differentiation, and while its loss affects the balance of globin expression, it has no major role in hemoglobin switching

Cataloging Coding Sequence Variations in Human Genome Databases

BACKGROUND: With the recent growth of information on sequence variations in the human genome, predictions regarding the functional effects and relevance to disease phenotypes of coding sequence variations are becoming increasingly important. The aims of this study were to catalog protein-coding sequence variations (CVs) occurring in genetic variation databases and to use bioinformatic programs to analyze CVs. In addition, we aim to provide insight into the functionality of the reference databases. METHODOLOGY AND FINDINGS: To catalog CVs on a genome-wide scale with regard to protein function and disease, we investigated three representative databases; the Human Gene Mutation Database (HGMD), the Single Nucleotide Polymorphisms database (dbSNP), and the Haplotype Map (HapMap). Using these three databases, we analyzed CVs at the protein function level with bioinformatic programs. We proposed a combinatorial approach using the Support Vector Machine (SVM) to increase the performance of the prediction programs. By cataloging the coding sequence variations using these databases, we found that 4.36% of CVs from HGMD are concurrently registered in dbSNP (8.11% of CVs from dbSNP are concurrent in HGMD). The pattern of substitutions and functional consequences predicted by three bioinformatic programs was significantly different among concurrent CVs, and CVs occurring solely in HGMD or in dbSNP. The experimental results showed that the proposed SVM combination noticeably outperformed the individual prediction programs. CONCLUSIONS: This is the first study to compare human sequence variations in HGMD, dbSNP and HapMap at the genome-wide level. We found that a significant proportion of CVs in HGMD and dbSNP overlap, and we emphasize the need to use caution when interpreting the phenotypic relevance of these concurrent CVs. Combining bioinformatic programs can be helpful in predicting the functional consequences of CVs because it improved the performance of functional predictions

RD-Connect: An Integrated Platform Connecting Databases, Registries, Biobanks and Clinical Bioinformatics for Rare Disease Research

Research into rare diseases is typically fragmented by data type and disease. Individual efforts often have poor interoperability and do not systematically connect data across clinical phenotype, genomic data, biomaterial availability, and research/trial data sets. Such data must be linked at both an individual-patient and whole-cohort level to enable researchers to gain a complete view of their disease and patient population of interest. Data access and authorization procedures are required to allow researchers in multiple institutions to securely compare results and gain new insights. Funded by the European Union’s Seventh Framework Programme under the International Rare Diseases Research Consortium (IRDiRC), RD-Connect is a global infrastructure project initiated in November 2012 that links genomic data with registries, biobanks, and clinical bioinformatics tools to produce a central research resource for rare diseases