Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

Abstracting and Reasoning over Ship Trajectories and Web Data with the Simple Event Model (SEM)

Bridging the gap between low-level features and semantics is a problem commonly acknowledged in the Multimedia community. Event modeling can fill this gap by representing knowledge about the data at different level of abstraction. In this paper we present the Simple Event Model (SEM) and its application in a Maritime Safety and Security use case about Situational Awareness, where the data also come as low-level features (of ship trajectories). We show how we abstract over these low-level features, recognize simple behavior events using a Piecewise Linear Segmentation algorithm, and model the resulting events as instances of SEM. We aggregate web data from different sources, apply deduction rules, spatial proximity reasoning, and semantic web reasoning in SWI-Prolog to derive abstract events from the recognized simple events. The use case described in this paper comes from the Dutch Poseidon project

CD4+ T-cell counts and interleukin-8 and CCL-5 plasma concentrations discriminate disease severity in children with RSV infection

BACKGROUND: Current tools to predict the severity of respiratory syncytial virus (RSV) infection might be improved by including immunological parameters. We hypothesized that a combination of inflammatory markers would differentiate between severe and mild disease in RSV-infected children. METHODS: Blood and nasopharyngeal samples from 52 RSV-infected children were collected during acute infection and after recovery. Retrospectively, patients were categorized into three groups based on disease severity: mild (no supportive treatment), moderate (supplemental oxygen and/or nasogastric feeding), and severe (mechanical ventilation). Clinical data, number of flow-defined leukocyte subsets, and cytokine concentrations were compared. RESULTS: Children with severe RSV infection were characterized by young age; lymphocytopenia; increased interleukin (IL)-8, granulocyte colony-stimulating factor (G-CSF), and IL-6 concentrations; and decreased chemokine (C-C motif) ligand (CCL-5) concentrations in plasma. The combination of plasma levels of IL-8 and CCL-5, and CD4+ T-cell counts, with cutoff values of 67 pg/ml, 13 ng/ml, and 2.3 x 10(6)/ml, respectively, discriminated severe from mild RSV infection with 82% sensitivity and 96% specificity. CONCLUSION: This study demonstrates that the combination of CD4+ T-cell counts and IL-8 and CCL-5 plasma concentrations correlates with disease severity in RSV-infected children. In addition to clinical features, these immunological markers may be used to assess severity of RSV infection and guide clinical management

Life-prolonging treatment restrictions and outcomes in patients with cancer and COVID-19: an update from the Dutch Oncology COVID-19 Consortium

Aim of the study: The coronavirus disease 2019 (COVID-19) pandemic significantly impacted cancer care. In this study, clinical patient characteristics related to COVID-19 outcomes and advanced care planning, in terms of non-oncological treatment restrictions (e.g. do-not-resuscitate codes), were studied in patients with cancer and COVID-19. Methods: The Dutch Oncology COVID-19 Consortium registry was launched in March 2020 in 45 hospitals in the Netherlands, primarily to identify risk factors of a severe COVID-19 outcome in patients with cancer. Here, an updated analysis of the registry was performed, and treatment restrictions (e.g. do-not-intubate codes) were studied in relation to COVID-19 outcomes in patients with cancer. Oncological treatment restrictions were not taken into account. Results: Between 27th March 2020 and 4th February 2021, 1360 patients with cancer and COVID-19 were registered. Follow-up data of 830 patients could be validated for this analysis. Overall, 230 of 830 (27.7%) patients died of COVID-19, and 60% of the remaining 600 patients with resolved COVID-19 were admitted to the hospital. Patients with haematological malignancies or lung cancer had a higher risk of a fatal outcome than other solid tumours. No correlation between anticancer therapies and the risk of a fatal COVID-19 outcome was found. In terms of end-of-life communication, 50% of all patients had restrictions regarding life-prolonging treatment (e.g. do-not-intubate codes). Most identified patients with treatment restrictions had risk factors associated with fatal COVID-19 outcome. Conclusion: There was no evidence of a negative impact of anticancer therapies on COVID-19 outcomes. Timely end-of-life communication as part of advanced care planning could save patients from prolonged suffering and decrease burden in intensive care units. Early discussion of treatment restrictions should therefore be part of routine oncological care, especially during the COVID-19 pandemic