Polymeric synthetic nanoparticles for the induction of antigen-specific immunological tolerance

Current treatments to control pathological or unwanted immune responses often use broadly immunosuppressive drugs. New approaches to induce antigen-specific immunological tolerance that control both cellular and humoral immune responses are desirable. Here we describe the use of synthetic, biodegradable nanoparticles carrying either protein or peptide antigens and a tolerogenic immunomodulator, rapamycin, to induce durable and antigen-specific immune tolerance, even in the presence of potent Toll-like receptor agonists. Treatment with tolerogenic nanoparticles results in the inhibition of CD4+ and CD8+ T-cell activation, an increase in regulatory cells, durable B-cell tolerance resistant to multiple immunogenic challenges, and the inhibition of antigen-specific hypersensitivity reactions, relapsing experimental autoimmune encephalomyelitis, and antibody responses against coagulation factor VIII in hemophilia A mice, even in animals previously sensitized to antigen. Only encapsulated rapamycin, not the free form, could induce immunological tolerance. Tolerogenic nanoparticle therapy represents a potential novel approach for the treatment of allergies, autoimmune diseases, and prevention of antidrug antibodies against biologic therapies.Juvenile Diabetes Research Foundation Internationa

A fast and accurate method to detect allelic genomic imbalances underlying mosaic rearrangements using SNP array data

<p>Abstract</p> <p>Background</p> <p>Mosaicism for copy number and copy neutral chromosomal rearrangements has been recently identified as a relatively common source of genetic variation in the normal population. However its prevalence is poorly defined since it has been only studied systematically in one large-scale study and by using non optimal <it>ad-hoc </it>SNP array data analysis tools, uncovering rather large alterations (> 1 Mb) and affecting a high proportion of cells. Here we propose a novel methodology, Mosaic Alteration Detection-MAD, by providing a software tool that is effective for capturing previously described alterations as wells as new variants that are smaller in size and/or affecting a low percentage of cells.</p> <p>Results</p> <p>The developed method identified all previously known mosaic abnormalities reported in SNP array data obtained from controls, bladder cancer and HapMap individuals. In addition MAD tool was able to detect new mosaic variants not reported before that were smaller in size and with lower percentage of cells affected. The performance of the tool was analysed by studying simulated data for different scenarios. Our method showed high sensitivity and specificity for all assessed scenarios.</p> <p>Conclusions</p> <p>The tool presented here has the ability to identify mosaic abnormalities with high sensitivity and specificity. Our results confirm the lack of sensitivity of former methods by identifying new mosaic variants not reported in previously utilised datasets. Our work suggests that the prevalence of mosaic alterations could be higher than initially thought. The use of appropriate SNP array data analysis methods would help in defining the human genome mosaic map.</p

Mechanisms of ring chromosome formation, ring instability and clinical consequences

<p>Abstract</p> <p>Background</p> <p>The breakpoints and mechanisms of ring chromosome formation were studied and mapped in 14 patients.</p> <p>Methods</p> <p>Several techniques were performed such as genome-wide array, MLPA (Multiplex Ligation-Dependent Probe Amplification) and FISH (Fluorescent <it>in situ </it>Hybridization).</p> <p>Results</p> <p>The ring chromosomes of patients I to XIV were determined to be, respectively: r(3)(p26.1q29), r(4)(p16.3q35.2), r(10)(p15.3q26.2), r(10)(p15.3q26.13), r(13)(p13q31.1), r(13)(p13q34), r(14)(p13q32.33), r(15)(p13q26.2), r(18)(p11.32q22.2), r(18)(p11.32q21.33), r(18)(p11.21q23), r(22)(p13q13.33), r(22)(p13q13.2), and r(22)(p13q13.2). These rings were found to have been formed by different mechanisms, such as: breaks in both chromosome arms followed by end-to-end reunion (patients IV, VIII, IX, XI, XIII and XIV); a break in one chromosome arm followed by fusion with the subtelomeric region of the other (patients I and II); a break in one chromosome arm followed by fusion with the opposite telomeric region (patients III and X); fusion of two subtelomeric regions (patient VII); and telomere-telomere fusion (patient XII). Thus, the r(14) and one r(22) can be considered complete rings, since there was no loss of relevant genetic material. Two patients (V and VI) with r(13) showed duplication along with terminal deletion of 13q, one of them proved to be inverted, a mechanism known as inv-dup-del. Ring instability was detected by ring loss and secondary aberrations in all but three patients, who presented stable ring chromosomes (II, XIII and XIV).</p> <p>Conclusions</p> <p>We concluded that the clinical phenotype of patients with ring chromosomes may be related with different factors, including gene haploinsufficiency, gene duplications and ring instability. Epigenetic factors due to the circular architecture of ring chromosomes must also be considered, since even complete ring chromosomes can result in phenotypic alterations, as observed in our patients with complete r(14) and r(22).</p

ZFIN: enhancements and updates to the zebrafish model organism database

ZFIN, the Zebrafish Model Organism Database, http://zfin.org, serves as the central repository and web-based resource for zebrafish genetic, genomic, phenotypic and developmental data. ZFIN manually curates comprehensive data for zebrafish genes, phenotypes, genotypes, gene expression, antibodies, anatomical structures and publications. A wide-ranging collection of web-based search forms and tools facilitates access to integrated views of these data promoting analysis and scientific discovery. Data represented in ZFIN are derived from three primary sources: curation of zebrafish publications, individual research laboratories and collaborations with bioinformatics organizations. Data formats include text, images and graphical representations. ZFIN is a dynamic resource with data added daily as part of our ongoing curation process. Software updates are frequent. Here, we describe recent additions to ZFIN including (i) enhanced access to images, (ii) genomic features, (iii) genome browser, (iv) transcripts, (v) antibodies and (vi) a community wiki for protocols and antibodies

The Zebrafish Information Network: the zebrafish model organism database provides expanded support for genotypes and phenotypes

The Zebrafish Information Network (ZFIN, http://zfin.org), the model organism database for zebrafish, provides the central location for curated zebrafish genetic, genomic and developmental data. Extensive data integration of mutant phenotypes, genes, expression patterns, sequences, genetic markers, morpholinos, map positions, publications and community resources facilitates the use of the zebrafish as a model for studying gene function, development, behavior and disease. Access to ZFIN data is provided via web-based query forms and through bulk data files. ZFIN is the definitive source for zebrafish gene and allele nomenclature, the zebrafish anatomical ontology (AO) and for zebrafish gene ontology (GO) annotations. ZFIN plays an active role in the development of cross-species ontologies such as the phenotypic quality ontology (PATO) and the gene ontology (GO). Recent enhancements to ZFIN include (i) a new home page and navigation bar, (ii) expanded support for genotypes and phenotypes, (iii) comprehensive phenotype annotations based on anatomical, phenotypic quality and gene ontologies, (iv) a BLAST server tightly integrated with the ZFIN database via ZFIN-specific datasets, (v) a global site search and (vi) help with hands-on resources

A systematic review and meta-analysis of gene therapy in animal models of cerebral glioma:why did promise not translate to human therapy?

BACKGROUND: The development of therapeutics is often characterized by promising animal research that fails to translate into clinical efficacy; this holds for the development of gene therapy in glioma. We tested the hypothesis that this is because of limitations in the internal and external validity of studies reporting the use of gene therapy in experimental glioma. METHOD: We systematically identified studies testing gene therapy in rodent glioma models by searching three online databases. The number of animals treated and median survival were extracted and studies graded using a quality checklist. We calculated median survival ratios and used random effects meta‐analysis to estimate efficacy. We explored effects of study design and quality and searched for evidence of publication bias. RESULTS: We identified 193 publications using gene therapy in experimental glioma, including 6,366 animals. Overall, gene therapy improved median survival by a factor of 1.60 (95% CI 1.53–1.67). Study quality was low and the type of gene therapy did not account for differences in outcome. Study design characteristics accounted for a significant proportion of between‐study heterogeneity. We observed similar findings in a data subset limited to the most common gene therapy. CONCLUSION: As the dysregulation of key molecular pathways is characteristic of gliomas, gene therapy remains a promising treatment for glioma. Nevertheless, we have identified areas for improvement in conduct and reporting of studies, and we provide a basis for sample size calculations. Further work should focus on genes of interest in paradigms recapitulating human disease. This might improve the translation of such therapies into the clinic

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics

Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium

Evaluating the pathogenicity of a variant is challenging given the plethora of types of genetic evidence that laboratories consider. Deciding how to weigh each type of evidence is difficult, and standards have been needed. In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published guidelines for the assessment of variants in genes associated with Mendelian diseases. Nine molecular diagnostic laboratories involved in the Clinical Sequencing Exploratory Research (CSER) consortium piloted these guidelines on 99 variants spanning all categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign). Nine variants were distributed to all laboratories, and the remaining 90 were evaluated by three laboratories. The laboratories classified each variant by using both the laboratory's own method and the ACMG-AMP criteria. The agreement between the two methods used within laboratories was high (K-alpha = 0.91) with 79% concordance. However, there was only 34% concordance for either classification system across laboratories. After consensus discussions and detailed review of the ACMG-AMP criteria, concordance increased to 71%. Causes of initial discordance in ACMG-AMP classifications were identified, and recommendations on clarification and increased specification of the ACMG-AMP criteria were made. In summary, although an initial pilot of the ACMG-AMP guidelines did not lead to increased concordance in variant interpretation, comparing variant interpretations to identify differences and having a common framework to facilitate resolution of those differences were beneficial for improving agreement, allowing iterative movement toward increased reporting consistency for variants in genes associated with monogenic disease