Implementation of total laparoscopic hysterectomy as day case surgery.

Elective surgeries within the National Health Service are frequently cancelled due to shortages of inpatient beds due to acute emergency admissions, and more recently, the COVID-19 pandemic. The aim of this quality improvement project was to initiate a day case hysterectomy pathway, prospectively collecting data on a group of selected motivated patients to assess its feasibility and safety. Interventions to maximise the chance of same day discharge included preoperative education and hydration, alterations in anaesthetic and surgical techniques and collaborative working between surgeons and recovery nurses to safely discharge patients. In change cycle 1, 93% of patients were discharged on the same day as surgery. In change cycle 2, 100% of patients were discharged on the same day as surgery. In a patient questionnaire, 90% of patients would recommend a day case hysterectomy to their friends or family. Day case hysterectomy was safely introduced to our unit, through leaders actively encouraging contributions and feedback throughout the initiation of the pathway from different components of the multidisciplinary team, from conception to roll out of the guideline for use by other gynaecological surgical teams within the trust.

Clin.iobio: A Collaborative Diagnostic Workflow to Enable Team-Based Precision Genomics.

The primary goal of precision genomics is the identification of causative genetic variants in targeted or whole-genome sequencing data. The ultimate clinical hope is that these findings lead to an efficacious change in treatment for the patient. In current clinical practice, these findings are typically returned by expert analysts as static, text-based reports. Ideally, these reports summarize the quality of the data obtained, integrate known gene-phenotype associations, follow allele segregation and affected status within the sequenced samples, and weigh computational evidence of pathogenicity. These findings are used to prioritize the variant(s) most likely to cause the given patient's phenotypes. In most diagnostic settings, a team of experts contribute to these reports, including bioinformaticians, clinicians, and genetic counselors, among others. However, these experts often do not have the necessary tools to review genomic findings, test genetic hypotheses, or query specific gene and variant information. Additionally, team members often rely on different tools and methods based on their given expertise, resulting in further difficulties in communicating and discussing genomic findings. Here, we present clin.iobio-a web-based solution to collaborative genomic analysis that enables diagnostic team members to focus on their area of expertise within the diagnostic process, while allowing them to easily review and contribute to all steps of the diagnostic process. Clin.iobio integrates tools from the popular iobio genomic visualization suite into a comprehensive diagnostic workflow, encompassing (1) genomic data quality review, (2) dynamic phenotype-driven gene prioritization, (3) variant prioritization using a comprehensive set of knowledge bases and annotations, (4) and an exportable findings summary. In conclusion, clin.iobio is a comprehensive solution to team-based precision genomics, the findings of which stand to inform genomic considerations in clinical practice.

Gene.iobio: an interactive web tool for versatile, clinically-driven variant interrogation and prioritization.

With increasing utilization of comprehensive genomic data to guide clinical care, anticipated to become the standard of care in many clinical settings, the practice of diagnostic medicine is undergoing a notable shift. However, the move from single-gene or panel-based genetic testing to exome and genome sequencing has not been matched by the development of tools to enable diagnosticians to interpret increasingly complex or uncertain genomic findings. Here, we present gene.iobio, a real-time, intuitive and interactive web application for clinically-driven variant interrogation and prioritization. We show gene.iobio is a novel and effective approach that significantly improves upon and reimagines existing methods. In a radical departure from existing methods that present variants and genomic data in text and table formats, gene.iobio provides an interactive, intuitive and visually-driven analysis environment. We demonstrate that adoption of gene.iobio in clinical and research settings empowers clinical care providers to interact directly with patient genomic data both for establishing clinical diagnoses and informing patient care, using sophisticated genomic analyses that previously were only accessible via complex command line tools.

Delayed miscarriage inside an infected decidual cast: a rare complication of the Depo medroxyprogesterone acetate injection.

Decidualisation of the endometrium is a progesterone-mediated reaction that naturally occurs during a woman's menstrual cycle. The hyperproliferated tissue is then usually dissolved and passed in a menstrual period. Occasionally, the natural dissolution does not happen, and the tissue maintains the shape of the endometrium, forming a decidual cast. These casts are known to be formed secondary to the use and/or cessation of various contraceptive methods. Here, we report a case of a patient presenting with passage of a decidual cast secondary to cessation of the Depo medroxyprogesterone acetate injection. This is the first reported case of the cast becoming infected, and also the first case of a decidual cast containing old products of conception.

gene.iobio: an interactive web tool for versatile, clinically-driven variant interrogation and prioritization.

With increasing utilization of comprehensive genomic data to guide clinical care, anticipated to become the standard of care in many clinical settings, the practice of diagnostic medicine is undergoing a notable shift. However, the move from single-gene or panel-based genetic testing to exome and genome sequencing has not been matched by the development of tools to enable diagnosticians to interpret increasingly complex genomic findings. A new paradigm has emerged, where genome-based tests are often evaluated by a large multi-disciplinary collaborative team, typically including a diagnostic pathologist, a bioinformatician, a genetic counselor, and often a subspeciality clinician. This team-based approach calls for new computational tools to allow every member of the clinical care provider team, at varying levels of genetic knowledge and diagnostic expertise, to quickly and easily analyze and interpret complex genomic data. Here, we present gene.iobio , a real-time, intuitive and interactive web application for clinically-driven variant interrogation and prioritization. We show gene.iobio is a novel and effective approach that significantly improves upon and reimagines existing methods. In a radical departure from existing methods that present variants and genomic data in text and table formats, gene.iobio provides an interactive, intuitive and visually-driven analysis environment. We demonstrate that adoption of gene.iobio in clinical and research settings empowers clinical care providers to interact directly with patient genomic data both for establishing clinical diagnoses and informing patient care, using sophisticated genomic analyses that previously were only accessible via complex command line tools.

Genepanel.iobio - an easy to use web tool for generating disease- and phenotype-associated gene lists.

When ordering genetic testing or triaging candidate variants in exome and genome sequencing studies, it is critical to generate and test a comprehensive list of candidate genes that succinctly describe the complete and objective phenotypic features of disease. Significant efforts have been made to curate gene:disease associations both in academic research and commercial genetic testing laboratory settings. However, many of these valuable resources exist as islands and must be used independently, generating static, single-resource gene:disease association lists. Here we describe genepanel.iobio (https://genepanel.iobio.io) an easy to use, free and open-source web tool for generating disease- and phenotype-associated gene lists from multiple gene:disease association resources, including the NCBI Genetic Testing Registry (GTR), Phenolyzer, and the Human Phenotype Ontology (HPO). We demonstrate the utility of genepanel.iobio by applying it to complex, rare and undiagnosed disease cases that had reached a diagnostic conclusion. We find that genepanel.iobio is able to correctly prioritize the gene containing the diagnostic variant in roughly half of these challenging cases. Importantly, each component resource contributed diagnostic value, showing the benefits of this aggregate approach. We expect genepanel.iobio will improve the ease and diagnostic value of generating gene:disease association lists for genetic test ordering and whole genome or exome sequencing variant prioritization.

Whole-genome analysis for effective clinical diagnosis and gene discovery in early infantile epileptic encephalopathy.

Early infantile epileptic encephalopathy (EIEE) is a devastating epilepsy syndrome with onset in the first months of life. Although mutations in more than 50 different genes are known to cause EIEE, current diagnostic yields with gene panel tests or whole-exome sequencing are below 60%. We applied whole-genome analysis (WGA) consisting of whole-genome sequencing and comprehensive variant discovery approaches to a cohort of 14 EIEE subjects for whom prior genetic tests had not yielded a diagnosis. We identified both de novo point and INDEL mutations and de novo structural rearrangements in known EIEE genes, as well as mutations in genes not previously associated with EIEE. The detection of a pathogenic or likely pathogenic mutation in all 14 subjects demonstrates the utility of WGA to reduce the time and costs of clinical diagnosis of EIEE. While exome sequencing may have detected 12 of the 14 causal mutations, 3 of the 12 patients received non-diagnostic exome panel tests prior to genome sequencing. Thus, given the continued decline of sequencing costs, our results support the use of WGA with comprehensive variant discovery as an efficient strategy for the clinical diagnosis of EIEE and other genetic conditions.

Rapid clinical diagnostic variant investigation of genomic patient sequencing data with iobio web tools.

INTRODUCTION: Computational analysis of genome or exome sequences may improve inherited disease diagnosis, but is costly and time-consuming. METHODS: We describe the use of iobio, a web-based tool suite for intuitive, real-time genome diagnostic analyses. RESULTS: We used iobio to identify the disease-causing variant in a patient with early infantile epileptic encephalopathy with prior nondiagnostic genetic testing. CONCLUSIONS: Iobio tools can be used by clinicians to rapidly identify disease-causing variants from genomic patient sequencing data.

Characterisation of chicken viperin.

The identification of immune pathways that protect against pathogens may lead to novel molecular therapies for both livestock and human health. Interferon (IFN) is a major response pathway that stimulates multiple genes targeted towards reducing virus. Viperin is one such interferon stimulated gene (ISG) that helps protect mammals from virus and may be critical to protecting chickens in the same way. In chickens, ISGs are not generally well characterised and viperin, in concert with other ISGs, may be important in protecting against virus. Here we identify chicken viperin (ch-viperin) and show that ch-viperin is upregulated in response to viral signature molecules. We further show that viperin is upregulated in response to virus infection in vivo. This data will benefit investigators targeting the antiviral pathways in the chicken.

Tangram: a comprehensive toolbox for mobile element insertion detection.

BACKGROUND: Mobile elements (MEs) constitute greater than 50% of the human genome as a result of repeated insertion events during human genome evolution. Although most of these elements are now fixed in the population, some MEs, including ALU, L1, SVA and HERV-K elements, are still actively duplicating. Mobile element insertions (MEIs) have been associated with human genetic disorders, including Crohn's disease, hemophilia, and various types of cancer, motivating the need for accurate MEI detection methods. To comprehensively identify and accurately characterize these variants in whole genome next-generation sequencing (NGS) data, a computationally efficient detection and genotyping method is required. Current computational tools are unable to call MEI polymorphisms with sufficiently high sensitivity and specificity, or call individual genotypes with sufficiently high accuracy. RESULTS: Here we report Tangram, a computationally efficient MEI detection program that integrates read-pair (RP) and split-read (SR) mapping signals to detect MEI events. By utilizing SR mapping in its primary detection module, a feature unique to this software, Tangram is able to pinpoint MEI breakpoints with single-nucleotide precision. To understand the role of MEI events in disease, it is essential to produce accurate individual genotypes in clinical samples. Tangram is able to determine sample genotypes with very high accuracy. Using simulations and experimental datasets, we demonstrate that Tangram has superior sensitivity, specificity, breakpoint resolution and genotyping accuracy, when compared to other, recently developed MEI detection methods. CONCLUSIONS: Tangram serves as the primary MEI detection tool in the 1000 Genomes Project, and is implemented as a highly portable, memory-efficient, easy-to-use C++ computer program, built under an open-source development model.

Characterisation of chicken ZAP.

Emerging pathogenic viruses, such as avian influenza (AI), represent a serious threat to the poultry industry and human health. The development of novel therapeutics to protect against these viruses is critical and necessitates understanding the host immune mechanisms to find new pathways for protection against virus infection. Interferon (IFN) is a major antiviral arm of the immune system and is generally the first line of defence against virus. The multiple genes orchestrated by IFN upregulation are not well characterised in chickens due to a lack of reagents and research efforts. Here we have identified chicken ZAP (chZAP), an IFN stimulated gene (ISG), that has antiviral properties in human models, and show that chZAP is upregulated in response to PAMPs. Moreover, we show that chZAP is upregulated in vivo following particular viral infections. This data will benefit further studies that aim to understand antiviral response pathways in the chicken.

MOSAIK: a hash-based algorithm for accurate next-generation sequencing short-read mapping.

MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery. All variant discovery benefits from an accurate description of the read placement confidence. To this end, MOSAIK uses a neural-network based training scheme to provide well-calibrated mapping quality scores, demonstrated by a correlation coefficient between MOSAIK assigned and actual mapping qualities greater than 0.98. In order to ensure that studies of any genome are supported, a training pipeline is provided to ensure optimal mapping quality scores for the genome under investigation. MOSAIK is multi-threaded, open source, and incorporated into our command and pipeline launcher system GKNO (http://gkno.me).

The functional spectrum of low-frequency coding variation.

BACKGROUND: Rare coding variants constitute an important class of human genetic variation, but are underrepresented in current databases that are based on small population samples. Recent studies show that variants altering amino acid sequence and protein function are enriched at low variant allele frequency, 2 to 5%, but because of insufficient sample size it is not clear if the same trend holds for rare variants below 1% allele frequency. RESULTS: The 1000 Genomes Exon Pilot Project has collected deep-coverage exon-capture data in roughly 1,000 human genes, for nearly 700 samples. Although medical whole-exome projects are currently afoot, this is still the deepest reported sampling of a large number of human genes with next-generation technologies. According to the goals of the 1000 Genomes Project, we created effective informatics pipelines to process and analyze the data, and discovered 12,758 exonic SNPs, 70% of them novel, and 74% below 1% allele frequency in the seven population samples we examined. Our analysis confirms that coding variants below 1% allele frequency show increased population-specificity and are enriched for functional variants. CONCLUSIONS: This study represents a large step toward detecting and interpreting low frequency coding variation, clearly lays out technical steps for effective analysis of DNA capture data, and articulates functional and population properties of this important class of genetic variation.