The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

A metagenomic viral discovery approach identifies potential zoonotic and novel mammalian viruses in Neoromicia bats within South Africa

Species within the Neoromicia bat genus are abundant and widely distributed in Africa. It is common for these insectivorous bats to roost in anthropogenic structures in urban regions. Additionally, Neoromicia capensis have previously been identified as potential hosts for Middle East respiratory syndrome (MERS)-related coronaviruses. This study aimed to ascertain the gastrointestinal virome of these bats, as viruses excreted in fecal material or which may be replicating in rectal or intestinal tissues have the greatest opportunities of coming into contact with other hosts. Samples were collected in five regions of South Africa over eight years. Initial virome composition was determined by viral metagenomic sequencing by pooling samples and enriching for viral particles. Libraries were sequenced on the Illumina MiSeq and NextSeq500 platforms, producing a combined 37 million reads. Bioinformatics analysis of the high throughput sequencing data detected the full genome of a novel species of the Circoviridae family, and also identified sequence data from the Adenoviridae, Coronaviridae, Herpesviridae, Parvoviridae, Papillomaviridae, Phenuiviridae, and Picornaviridae families. Metagenomic sequencing data was insufficient to determine the viral diversity of certain families due to the fragmented coverage of genomes and lack of suitable sequencing depth, as some viruses were detected from the analysis of reads-data only. Follow up conventional PCR assays targeting conserved gene regions for the Adenoviridae, Coronaviridae, and Herpesviridae families were used to confirm metagenomic data and generate additional sequences to determine genetic diversity. The complete coding genome of a MERS-related coronavirus was recovered with additional amplicon sequencing on the MiSeq platform. The new genome shared 97.2% overall nucleotide identity to a previous Neoromicia-associated MERS-related virus, also from South Africa. Conventional PCR analysis detected diverse adenovirus and herpesvirus sequences that were widespread throughout Neoromicia populations in South Africa. Furthermore, similar adenovirus sequences were detected within these populations throughout several years. With the exception of the coronaviruses, the study represents the first report of sequence data from several viral families within a Southern African insectivorous bat genus; highlighting the need for continued investigations in this regard.S1 File. Virome sequence data information from the Parvoviridae and Papillomaviridae families (with references and figures).S1 Table. Neoromicia samples collected to investigate the South African Neoromicia virome.S3 Table. Neoromicia samples pooled for molecular detection of selected viruses.S4 Table. Alpha- and Betacoronavirus genera hemi-nested RT-PCR primers.S5 Table. Pairwise similarities inferred from distance estimations of full length genomes of the Circoviridae family. Sequence similarities of viruses in the Circoviridae family inferred from estimated evolutionary divergence calculated from pairwise distances. Full genomes were aligned and trimmed to 1075 overlapping positions. All ambiguous positions were removed for each sequence pair. Analyses were conducted in MEGA7 [41].S6 Table. Pairwise similarities inferred from distance estimations of an L gene region between selected Bunyavirales. The table shows pairwise sequence similarities inferred from evolutionary divergence estimates of 249 positions of compared Bunyavirales. The number of base differences per site from between sequences were converted to percentage of similarities. Standard errors for distance estimates are shown above the diagonal. Codon positions included were 1±3 as well as noncoding. Ambiguous positions were removed for each sequence pair as per pairwise deletion. Estimates were analysed in MEGA7 [41].S7 Table. Pairwise similarities inferred from distance estimations of a 605bp conserved segment of the coronavirus RNA dependent RNA polymerase gene. The table shows pairwise sequence similarities inferred from evolutionary divergence estimates of 605 positions of compared coronaviruses. The number of base differences per site from between sequences were converted to percentage of similarities. The sequences from this study are highlighted in grey and closest similarities to sequences from other studies are indicated in bold. Standard errors for distance estimates are shown above the diagonal in grey text. Codon positions included were 1±3 as well as noncoding and ambiguous positions were removed for each sequence pair as per pairwise deletion. Estimates were analysed in MEGA 7 [41].S8 Table. Genome annotation of BtCoVNeo5038 with similarities to compared lineage C betacoronaviruses. The percentage similarities were inferred from pairwise distance estimates of the base pair and amino acid differences per site for each gene and of the overall genome. The estimates were calculated in MEGA7 [41] using pairwise deletion to treat gaps. All percentage similarities are given in comparison to BtCoVNeoV5038. Accession number of compared betacoronaviruses are listed in order: KC869678.4, KX574227, EF065505.1, EF065509.1, JX869059.2, KF958702.1, KF917527.1, and KJ477102.1.S9 Table. Pairwise similarities inferred from distance estimations between betacoronavirus full genomes. The table shows pairwise similarities inferred from evolutionary divergence estimates of betacoronavirus full genomes. The number of base differences per site between sequences were converted to percentage similarities. Within lineage similarities are indicated in shaded blocks. Standard errors for distance estimates are shown above the diagonal in grey text. Codon positions included were 1±3 as well as noncoding and ambiguous positions were removed for each sequence pair as per pairwise deletion. Estimates were analysed in MEGA 7 [41].S10 Table. Coronavirus strains and Genbank accession numbers of sequences used in the full genome phylogeny.This work was financially supported in part by the National Research Foundation (NRF) of South Africa: the South African Research Chair held by WMgrant no. 98339, as well as grant numbers 92524, 85756, and 91496. The opinions, findings and conclusions expressed are those of the authors alone, and the NRF accepts no liability in this regard for research supported. Additional support was obtained byWMfrom the Poliomyelitis Research Foundation (grant number: 12/14). The Research Trust of the National Health Laboratory Service and the Medical Research Council was awarded to JW. This research was partially supported by the Grant or Cooperative Agreement Number [5 NU2GGH001874-02-00], funded by the Centers for Disease Control and Prevention. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention or the Department of Health and Human Services. MG was supported by funding from the NRF's Innovation bursary award (grant UID: 79409), the Poliomyelitis Research Foundation (grant no. 13/48), and the postgraduate study abroad bursary program of the University of Pretoria, which funded a research visit to the Los Alamos National Laboratory in New Mexico.http://www.plosone.orgam2018Mammal Research InstituteMedical Virolog

A metagenomic viral discovery approach identifies potential zoonotic and novel mammalian viruses in <i>Neoromicia</i> bats within South Africa

<div><p>Species within the <i>Neoromicia</i> bat genus are abundant and widely distributed in Africa. It is common for these insectivorous bats to roost in anthropogenic structures in urban regions. Additionally, <i>Neoromicia capensis</i> have previously been identified as potential hosts for Middle East respiratory syndrome (MERS)-related coronaviruses. This study aimed to ascertain the gastrointestinal virome of these bats, as viruses excreted in fecal material or which may be replicating in rectal or intestinal tissues have the greatest opportunities of coming into contact with other hosts. Samples were collected in five regions of South Africa over eight years. Initial virome composition was determined by viral metagenomic sequencing by pooling samples and enriching for viral particles. Libraries were sequenced on the Illumina MiSeq and NextSeq500 platforms, producing a combined 37 million reads. Bioinformatics analysis of the high throughput sequencing data detected the full genome of a novel species of the <i>Circoviridae</i> family, and also identified sequence data from the <i>Adenoviridae</i>, <i>Coronaviridae</i>, <i>Herpesviridae</i>, <i>Parvoviridae</i>, <i>Papillomaviridae</i>, <i>Phenuiviridae</i>, and <i>Picornaviridae</i> families. Metagenomic sequencing data was insufficient to determine the viral diversity of certain families due to the fragmented coverage of genomes and lack of suitable sequencing depth, as some viruses were detected from the analysis of reads-data only. Follow up conventional PCR assays targeting conserved gene regions for the <i>Adenoviridae</i>, <i>Coronaviridae</i>, and <i>Herpesviridae</i> families were used to confirm metagenomic data and generate additional sequences to determine genetic diversity. The complete coding genome of a MERS-related coronavirus was recovered with additional amplicon sequencing on the MiSeq platform. The new genome shared 97.2% overall nucleotide identity to a previous <i>Neoromicia</i>-associated MERS-related virus, also from South Africa. Conventional PCR analysis detected diverse adenovirus and herpesvirus sequences that were widespread throughout <i>Neoromicia</i> populations in South Africa. Furthermore, similar adenovirus sequences were detected within these populations throughout several years. With the exception of the coronaviruses, the study represents the first report of sequence data from several viral families within a Southern African insectivorous bat genus; highlighting the need for continued investigations in this regard.</p></div

<i>Betacoronavirus</i> full genome phylogeny.

<p><b>A)</b> The full genome phylogeny of 4 lineages (A-D) of the genus <i>Betacoronavirus</i> constructed using BEAST software with the GTR substitution model using invariant sites and gamma distribution. The MCMC chain was set to 15,000,000 generations sampled every 1500 steps, with a 10% burn-in of the first generated trees and displayed as a radial tree in Figtree. The lineages are indicated with clipart images of host species. Also displayed are the averaged pairwise similarities between lineages as well as highlighted similarities between human coronaviruses and related viruses identified in bats (and other animals). <b>B)</b> Close-up of the external nodes of the lineage B phylogeny to show relative distances of human and civet SARS-CoV strains and SARS-related <i>Rhinolophus</i> strains (WIV1, Rp3, Rm1 and HKU3). <b>C)</b> Close-up of the lineage C external nodes depicting the human and camel MERS strains with the bat MERS-related viruses (BtCoVNeo5038 from this study is indicated with a star). Sequence abbreviations and GenBank accession numbers are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194527#pone.0194527.s011" target="_blank">S10 Table</a>.</p

Novel <i>Neoromicia</i> picornavirus.

<p><b>A)</b> Overview of the confirmed picornavirus contig alignment positions in reference to a typical picornavirus genome. The dark grey contig (1077bp) of the P1/P2 region was used to construct a Bayesian phylogeny. <b>B)</b> The maximum clade credibility tree constructed in BEAST v1.8 used the GTR plus invariant sites and gamma distribution substitution model. The genera are indicated on the right side of the sequence names (with GenBank accession numbers); the <i>Neoromicia</i> picornavirus from this study is indicated with a black circle. Posterior probability values of less than 50% were omitted.</p

Conserved sequences of identified <i>Neoromicia</i> coronaviruses.

<p><b>A)</b> Region of the coronavirus ORF1ab (within the RdRp gene) targeted with the molecular detection assay. <b>B)</b> The coronavirus phylogenetic tree generated using the 605bp region was constructed in BEAST v1.8 using the GTR plus invariant sites and gamma distribution substitution model. The MCMC chain was set to 20,000,000 generations, sampled every 2000 steps, with a 10% burn-in of the first generated trees. Coronavirus genera and <i>Betacoronavirus</i> lineages are indicated on the right side of the sequences. GenBank accession numbers are shown with each sequence and coronaviruses detected in this study are indicated with a black circle. Posterior probability values of less than 50% were omitted.</p

<i>Phenuiviridae</i> sequence identified from the <i>Neoromicia</i> virome.

<p><b>A)</b> Alignment of the <i>Phenuiviridae</i> contig in reference to a typical L segment gene. <b>B)</b> The phylogenetic tree was constructed with a 267 bp region of the bunyavirus L genome segment using BEAST v1.8 with the GTR substitution model plus invariant sites. Relevant genera are shown on the right and GenBank accession numbers of each sequence are provided; the novel <i>Neoromicia</i> bunyavirus sequence from this study is indicated with a black circle. SFTSV = Severe fever with thrombocytopenia syndrome virus.</p

Strategies for sample pooling and data analysis workflows.

<p><b>A)</b> The workflow depicts the sample pooling strategies utilized in the study. Faecal and rectal samples were primarily pooled for initial viral metagenomic sample processing. Subsequently, remaining sample material (faecal homogenates, rectum, or intestine) available for individual bats were pooled according to species and location to associate selected viral families with specific species. A further step was implemented to determine specific host individuals harbouring coronaviruses in order to clarify exact sampling locations. <b>B)</b> Bioinformatics data analysis of Illumina reads with a developed workflow in CLC genomic workbench that trims data for quality, removes adaptors and depletes host reads based on set mapping parameters. Remaining reads were taxonomically assigned with BLASTn and MEGAN v6. <b>C)</b> Shows the BLASTn assignments of reads according to virus genome types: ssRNA, ssDNA and dsDNA viruses.</p