114 research outputs found

    Detection and diversity of a putative novel heterogeneous polymorphic proline-glycine repeat (Pgr) protein in the footrot pathogen Dichelobacter nodosus

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    Dichelobacter nodosus, a Gram-negative anaerobic bacterium, is the essential causative agent of footrot in sheep. Currently, depending on the clinical presentation in the field, footrot is described as benign or virulent; D. nodosus strains have also been classified as benign or virulent, but this designation is not always consistent with clinical disease. The aim of this study was to determine the diversity of the pgr gene, which encodes a putative proline-glycine repeat protein (Pgr). The pgr gene was present in all 100 isolates of D. nodosus that were examined and, based on sequence analysis had two variants, pgrA and pgrB. In pgrA, there were two coding tandem repeat regions, R1 and R2: different strains had variable numbers of repeats within these regions. The R1 and R2 were absent from pgrB. Both variants were present in strains from Australia, Sweden and the UK, however, only pgrB was detected in isolates from Western Australia. The pgrA gene was detected in D. nodosus from tissue samples from two flocks in the UK with virulent footrot and only pgrB from a flock with no virulent or benign footrot for >10 years. Bioinformatic analysis of the putative PgrA protein indicated that it contained a collagen-like cell surface anchor motif. These results suggest that the pgr gene may be a useful molecular marker for epidemiological studies

    Two-dimensional enrichment analysis for mining high-level imaging genetic associations

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    Enrichment analysis has been widely applied in the genome-wide association studies (GWAS), where gene sets corresponding to biological pathways are examined for significant associations with a phenotype to help increase statistical power and improve biological interpretation. In this work, we expand the scope of enrichment analysis into brain imaging genetics, an emerging field that studies how genetic variation influences brain structure and function measured by neuroimaging quantitative traits (QT). Given the high dimensionality of both imaging and genetic data, we propose to study Imaging Genetic Enrichment Analysis (IGEA), a new enrichment analysis paradigm that jointly considers meaningful gene sets (GS) and brain circuits (BC) and examines whether any given GS-BC pair is enriched in a list of gene-QT findings. Using gene expression data from Allen Human Brain Atlas and imaging genetics data from Alzheimer's Disease Neuroimaging Initiative as test beds, we present an IGEA framework and conduct a proof-of-concept study. This empirical study identifies 12 significant high level two dimensional imaging genetics modules. Many of these modules are relevant to a variety of neurobiological pathways or neurodegenerative diseases, showing the promise of the proposal framework for providing insight into the mechanism of complex diseases

    People of the British Isles: preliminary analysis of genotypes and surnames in a UK control population

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    There is a great deal of interest in fine scale population structure in the UK, both as a signature of historical immigration events and because of the effect population structure may have on disease association studies. Although population structure appears to have a minor impact on the current generation of genome-wide association studies, it is likely to play a significant part in the next generation of studies designed to search for rare variants. A powerful way of detecting such structure is to control and document carefully the provenance of the samples involved. Here we describe the collection of a cohort of rural UK samples (The People of the British Isles), aimed at providing a well-characterised UK control population that can be used as a resource by the research community as well as providing fine scale genetic information on the British population. So far, some 4,000 samples have been collected, the majority of which fit the criteria of coming from a rural area and having all four grandparents from approximately the same area. Analysis of the first 3,865 samples that have been geocoded indicates that 75% have a mean distance between grandparental places of birth of 37.3km, and that about 70% of grandparental places of birth can be classed as rural. Preliminary genotyping of 1,057 samples demonstrates the value of these samples for investigating fine scale population structure within the UK, and shows how this can be enhanced by the use of surnames

    Towards the clinical implementation of pharmacogenetics in bipolar disorder.

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    BackgroundBipolar disorder (BD) is a psychiatric illness defined by pathological alterations between the mood states of mania and depression, causing disability, imposing healthcare costs and elevating the risk of suicide. Although effective treatments for BD exist, variability in outcomes leads to a large number of treatment failures, typically followed by a trial and error process of medication switches that can take years. Pharmacogenetic testing (PGT), by tailoring drug choice to an individual, may personalize and expedite treatment so as to identify more rapidly medications well suited to individual BD patients.DiscussionA number of associations have been made in BD between medication response phenotypes and specific genetic markers. However, to date clinical adoption of PGT has been limited, often citing questions that must be answered before it can be widely utilized. These include: What are the requirements of supporting evidence? How large is a clinically relevant effect? What degree of specificity and sensitivity are required? Does a given marker influence decision making and have clinical utility? In many cases, the answers to these questions remain unknown, and ultimately, the question of whether PGT is valid and useful must be determined empirically. Towards this aim, we have reviewed the literature and selected drug-genotype associations with the strongest evidence for utility in BD.SummaryBased upon these findings, we propose a preliminary panel for use in PGT, and a method by which the results of a PGT panel can be integrated for clinical interpretation. Finally, we argue that based on the sufficiency of accumulated evidence, PGT implementation studies are now warranted. We propose and discuss the design for a randomized clinical trial to test the use of PGT in the treatment of BD

    Evidence For Genetic Heterogeneity Between Clinical Subtypes of Bipolar Disorder

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    We performed a genome-wide association study of 6447 bipolar disorder (BD) cases and 12 639 controls from the International Cohort Collection for Bipolar Disorder (ICCBD). Meta-analysis was performed with prior results from the Psychiatric Genomics Consortium Bipolar Group for a combined sample of 13 902 cases and 19 279 controls. We identified eight genome-wide significant, associated regions, including a novel associated region on chromosome 10 (rs10884920; P = 3.28 × 10 − 8) that includes the brain-enriched cytoskeleton protein adducin 3 (ADD3), a non-coding RNA, and a neuropeptide-specific aminopeptidase P (XPNPEP1). Our large sample size allowed us to test the heritability and genetic correlation of BD subtypes and investigate their genetic overlap with schizophrenia (SCZ) and major depressive disorder. We found a significant difference in heritability of the two most common forms of BD (BD I h2 = 0.35; BD II h2 = 0.25; P = 0.02) with a genetic correlation between BD I and BD II of 0.78,compared with a genetic correlation of 0.97 when BD cohorts containing both types were compared. In addition, we demonstrated a significantly greater load of polygenic risk alleles for SCZ and BD in patients with BD I compared with patients with BD II, and a greater load of SCZ risk alleles in the bipolar type of schizoaffective disorder (SAB) compared with both other BD subtypes. These results point to a partial difference in genetic architecture of BD subtypes, and are suggestive of a molecular correlate for the clinical division of BD into subtypes

    zCall: a rare variant caller for array-based genotyping

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    Summary: zCall is a variant caller specifically designed for calling rare single-nucleotide polymorphisms from array-based technology. This caller is implemented as a post-processing step after a default calling algorithm has been applied. The algorithm uses the intensity profile of the common allele homozygote cluster to define the location of the other two genotype clusters. We demonstrate improved detection of rare alleles when applying zCall to samples that have both Illumina Infinium HumanExome BeadChip and exome sequencing data available

    The Irish DNA Atlas: Revealing Fine-Scale Population Structure and History within Ireland

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    The extent of population structure within Ireland is largely unknown, as is the impact of historical migrations. Here we illustrate fine-scale genetic structure across Ireland that follows geographic boundaries and present evidence of admixture events into Ireland. Utilising the ‘Irish DNA Atlas’, a cohort (n = 194) of Irish individuals with four generations of ancestry linked to specific regions in Ireland, in combination with 2,039 individuals from the Peoples of the British Isles dataset, we show that the Irish population can be divided in 10 distinct geographically stratified genetic clusters; seven of ‘Gaelic’ Irish ancestry, and three of shared Irish-British ancestry. In addition we observe a major genetic barrier to the north of Ireland in Ulster. Using a reference of 6,760 European individuals and two ancient Irish genomes, we demonstrate high levels of North-West French-like and West Norwegian-like ancestry within Ireland. We show that that our ‘Gaelic’ Irish clusters present homogenous levels of ancient Irish ancestries. We additionally detect admixture events that provide evidence of Norse-Viking gene flow into Ireland, and reflect the Ulster Plantations. Our work informs both on Irish history, as well as the study of Mendelian and complex disease genetics involving populations of Irish ancestry

    Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

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    Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies
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