42 research outputs found

    Whole genome identification of Mycobacterium tuberculosis vaccine candidates by comprehensive data mining and bioinformatic analyses

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    <p>Abstract</p> <p>Background</p> <p><it>Mycobacterium tuberculosis</it>, the causative agent of tuberculosis (TB), infects ~8 million annually culminating in ~2 million deaths. Moreover, about one third of the population is latently infected, 10% of which develop disease during lifetime. Current approved prophylactic TB vaccines (BCG and derivatives thereof) are of variable efficiency in adult protection against pulmonary TB (0%–80%), and directed essentially against early phase infection.</p> <p>Methods</p> <p>A genome-scale dataset was constructed by analyzing published data of: (1) global gene expression studies under conditions which simulate intra-macrophage stress, dormancy, persistence and/or reactivation; (2) cellular and humoral immunity, and vaccine potential. This information was compiled along with revised annotation/bioinformatic characterization of selected gene products and <it>in silico </it>mapping of T-cell epitopes. Protocols for scoring, ranking and prioritization of the antigens were developed and applied.</p> <p>Results</p> <p>Cross-matching of literature and <it>in silico</it>-derived data, in conjunction with the prioritization scheme and biological rationale, allowed for selection of 189 putative vaccine candidates from the entire genome. Within the 189 set, the relative distribution of antigens in 3 functional categories differs significantly from their distribution in the whole genome, with reduction in the Conserved hypothetical category (due to improved annotation) and enrichment in Lipid and in Virulence categories. Other prominent representatives in the 189 set are the PE/PPE proteins; iron sequestration, nitroreductases and proteases, all within the Intermediary metabolism and respiration category; ESX secretion systems, resuscitation promoting factors and lipoproteins, all within the Cell wall category. Application of a ranking scheme based on qualitative and quantitative scores, resulted in a list of 45 best-scoring antigens, of which: 74% belong to the dormancy/reactivation/resuscitation classes; 30% belong to the Cell wall category; 13% are classical vaccine candidates; 9% are categorized Conserved hypotheticals, all potentially very potent T-cell antigens.</p> <p>Conclusion</p> <p>The comprehensive literature and <it>in silico</it>-based analyses allowed for the selection of a repertoire of 189 vaccine candidates, out of the whole-genome 3989 ORF products. This repertoire, which was ranked to generate a list of 45 top-hits antigens, is a platform for selection of genes covering all stages of <it>M. tuberculosis </it>infection, to be incorporated in rBCG or subunit-based vaccines.</p

    Rare and low-frequency coding variants alter human adult height

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    Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    Giant cell tumor of the mandible

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    Paternal exposure to Agent Orange and spina bifida: A meta-analysis

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    The objective of this study is to conduct a meta-analysis of published and unpublished studies that examine the association between Agent Orange (AO) exposure and the risk of spina bifida. Relevant studies were identified through a computerized literature search of Medline and Embase from 1966 to 2008; a review of the reference list of retrieved articles and conference proceedings; and by contacting researchers for unpublished studies. Both fixed-effects and random-effects models were used to pool the results of individual studies. The Cochrane Q test and index of heterogeneity (I(2)) were used to evaluate heterogeneity, and a funnel plot and Egger's test were used to evaluate publication bias. Seven studies, including two Vietnamese and five non-Vietnamese studies, involving 330 cases and 134,884 non-cases were included in the meta-analysis. The overall relative risk (RR) for spina bifida associated with paternal exposure to AO was 2.02 (95% confidence interval [CI]: 1.48-2.74), with no statistical evidence of heterogeneity across studies. Non-Vietnamese studies showed a slightly higher summary RR (RR = 2.22; 95% CI: 1.38-3.56) than Vietnamese studies (RR = 1.92 95% CI: 1.29-2.86). When analyzed separately, the overall association was statistically significant for the three case-control studies (Summary Odds Ratio = 2.25, 95% CI: 1.31-3.86) and the cross sectional study (RR = 1.97, 95% CI: 1.31-2.96), but not for the three cohort studies (RR: 2.11; 95% CI: 0.78-5.73). Paternal exposure to AO appears to be associated with a statistically increased risk of spina bifida
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