Selection for atrial fibrillation ablation: Importance of diastolic function grading

AbstractBackgroundPulmonary vein isolation (PVI) has become an accepted therapy for patients with atrial fibrillation (AF) and the indications have widened to include non-paroxysmal AF-patients. Maintenance of sinus rhythm after PVI can be adversely affected by clinical or echocardiographic parameters, which should be clearly identified.Methods and resultsAfter baseline clinical and echocardiographic evaluations, PVI was performed in patients with paroxysmal or non-paroxysmal AF. The follow-up strategy after PVI included: (1) clinical follow up, 12-lead electrocardiography (ECG) and 24-h ECG every 3 months, (2) trans-telephonic ECGs twice daily and when symptomatic (over 4 weeks) every 3 months, or (3) continuous monitoring via implanted devices. A recurrence was an atrial arrhythmia lasting >30s. All 340 PVI procedures of 229 patients were analyzed. On average, 1.5 PVI procedures per patient (range, 1–6 PVI) were performed. The mean age was 58±11 years (73% male) with 109 paroxysmal and 120 non-paroxysmal AF cases. Clinical follow-up with 12-lead ECGs, 24-h ECGs, trans-telephonic ECGs, and implanted devices was complete in 100%, 63%, 51%, and 16% of cases, respectively. The overall one-year recurrence rate of 59% (range, 24–82%) was dependent on grades of diastolic function (normal – dysfunction grade III) in a multivariable analysis model. Patients with normal diastolic function had the lowest recurrence rates of 24% and 49% after 1 and 3 years of follow-up, respectively (p<0.0001).ConclusionDiastolic function could serve as a simple summary predictor for AF recurrence, and would facilitate clinical decision-making in AF treatment

Comparative toxicity evaluation of targeted anticancer therapeutics in embryonic zebrafish and sea urchin models

Cancer drug resistance and poor selectivity towards cancer cells demand the constant search for new therapeutics. PI3K-Akt-mTOR and RAS-MAPK-ERK signaling pathways are key mechanisms involved in cell survival, proliferation, differentiation, and metabolism and their deregulation in cancer can promote development of therapy resistance. We investigated the effects of targeted inhibitors (wortmannin, GSK690693, AZD2014 and tipifarnib) towards these two pathways on early zebrafish and sea urchin development to assess their toxicity in normal, fast proliferating cells. PI3K inhibitor wortmannin and RAS inhibitor tipifarnib displayed highest toxicity while GSK690693, a pan-Akt kinase inhibitor, exhibited a less significant impact on embryo survival and development. Moreover, inhibition of the upstream part of the PI3K-Akt-mTOR pathway (wortmannin/GSK690693 co-treatment) produced a synergistic effect and impacted zebrafish embryo survival and development at much lower concentrations. Dual mTORC1/mTORC2 inhibitor AZD2014 showed no considerable effects on embryonic cells of zebrafish in concentrations substantially toxic in cancer cells. AZD2014 also caused the least prominent effects on sea urchin embryo development compared to other inhibitors. Significant toxicity of AZD2014 in human cancer cells, its capacity to sensitize resistant cancers, lower antiproliferative activity against human normal cell lines and fast proliferating embryonic cells could make this agent a promising candidate for anticancer therapy

Alternative activation of human macrophages enhances tissue factor expression and production of extracellular vesicles

Macrophages are versatile cells that can be polarized by the tissue environment to fulfill required needs. Proinflammatory polarization is associated with increased tissue degradation and propagation of inflammation whereas alternative polarization within a Th2 cytokine environment is associated with wound healing and angiogenesis. To understand if polarization of macrophages can lead to a procoagulant macrophage subset we polarized human monocyte derived macrophages to a proinflammatory and an alternative activation state. Alternative polarization with interleukin-4 and IL-13 led to a macrophage phenotype characterized by increased tissue factor (TF) production and release and by an increase in extracellular vesicle production. In addition, also TF activity was enhanced in extracellular vesicles of alternatively polarized macrophages. This TF induction was dependent on signal transducer and activator of transcription-6 signaling and poly ADP ribose polymerase activity. In contrast to monocytes, human macrophages did not show increased tissue factor expression upon stimulation with lipopolysaccharide and interferon-γ. Previous polarization to either a proinflammatory or an alternative activation subset does not change the subsequent stimulation of TF. The inability of proinflammatory activated macrophages to respond to lipopolysaccharide and interferon-γ with an increase in TF production seems to be due to an increase in TF promoter methylation and was reversible when treating these macrophages with a demethylation agent. In conclusion, we provide evidence that proinflammatory polarization of macrophages does not lead to enhanced procoagulatory function, whereas alternative polarization of macrophages leads to an increased expression of TF and increased production of TF bearing extracellular vesicles by these cells suggesting a procoagulatory phenotype of alternatively polarized macrophages

Proteomic Atlas of Atherosclerosis: The Contribution of Proteoglycans to Sex Differences, Plaque Phenotypes, and Outcomes

BACKGROUND: Using proteomics, we aimed to reveal molecular types of human atherosclerotic lesions and study their associations with histology, imaging, and cardiovascular outcomes. METHODS: Two hundred nineteen carotid endarterectomy samples were procured from 120 patients. A sequential protein extraction protocol was employed in conjunction with multiplexed, discovery proteomics. To focus on extracellular proteins, parallel reaction monitoring was employed for targeted proteomics. Proteomic signatures were integrated with bulk, single-cell, and spatial RNA-sequencing data, and validated in 200 patients from the Athero-Express Biobank study. RESULTS: This extensive proteomics analysis identified plaque inflammation and calcification signatures, which were inversely correlated and validated using targeted proteomics. The inflammation signature was characterized by the presence of neutrophil-derived proteins, such as S100A8/9 (calprotectin) and myeloperoxidase, whereas the calcification signature included fetuin-A, osteopontin, and gamma-carboxylated proteins. The proteomics data also revealed sex differences in atherosclerosis, with large-aggregating proteoglycans versican and aggrecan being more abundant in females and exhibiting an inverse correlation with estradiol levels. The integration of RNA-sequencing data attributed the inflammation signature predominantly to neutrophils and macrophages, and the calcification and sex signatures to smooth muscle cells, except for certain plasma proteins that were not expressed but retained in plaques, such as fetuin-A. Dimensionality reduction and machine learning techniques were applied to identify 4 distinct plaque phenotypes based on proteomics data. A protein signature of 4 key proteins (calponin, protein C, serpin H1, and versican) predicted future cardiovascular mortality with an area under the curve of 75% and 67.5% in the discovery and validation cohort, respectively, surpassing the prognostic performance of imaging and histology. CONCLUSIONS: Plaque proteomics redefined clinically relevant patient groups with distinct outcomes, identifying subgroups of male and female patients with elevated risk of future cardiovascular events

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe

Solving unsolved rare neurological diseases-a Solve-RD viewpoint.

Funder: Durch Princess Beatrix Muscle Fund Durch Speeren voor Spieren Muscle FundFunder: University of Tübingen Medical Faculty PATE programFunder: European Reference Network for Rare Neurological Diseases | 739510Funder: European Joint Program on Rare Diseases (EJP-RD COFUND-EJP) | 44140962

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

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock