Evidence map›Paper›PMID 31285478›Full record

ArticleScientific reports2019

A reliable Epstein-Barr Virus classification based on phylogenomic and population analyses.

Louise Zanella, Ismael Riquelme, Kurt Buchegger, Michel Abanto, Carmen Ili, Priscilla Brebi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

46 citing papers in PubMed, 1 synthesis or guideline pooled it, 86 citations in OpenAlex.

  1. Estimating the global burden of Epstein-Barr virus-related cancers.Journal of cancer research and clinical oncology · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Louise ZanellaLaboratory of Integrative Biology (LIBi), Universidad de La Frontera, Temuco, Chile.
Ismael RiquelmeInstituto de Ciencias Biomédicas, Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Temuco, Chile.
Kurt BucheggerLaboratory of Integrative Biology (LIBi), Universidad de La Frontera, Temuco, Chile.
Michel AbantoScientific and Technological Bioresource Nucleus (BIOREN), Universidad de La Frontera, Temuco, Chile.
Carmen IliLaboratory of Integrative Biology (LIBi), Universidad de La Frontera, Temuco, Chile. carmen.ili@ufrontera.cl.
Priscilla BrebiLaboratory of Integrative Biology (LIBi), Universidad de La Frontera, Temuco, Chile. priscilla.brebi@ufrontera.cl.
Universidad de La Frontera · CLUniversidad Autónoma de Chile · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Epstein-Barr virus (EBV) infects more than 90% of the human population, playing a key role in the origin and progression of malignant and non-malignant diseases. Many attempts have been made to classify EBV according to clinical or epidemiological information; however, these classifications show frequent incongruences. For instance, they use a small subset of genes for sorting strains but fail to consider the enormous genomic variability and abundant recombinant regions present in the EBV genome. These could lead to diversity overestimation, alter the tree topology and misinterpret viral types when classified, therefore, a reliable EBV phylogenetic classification is needed to minimize recombination signals. Recombination events occur 2.5-times more often than mutation events, suggesting that recombination has a much stronger impact than mutation in EBV genomic diversity, detected within common ancestral node positions. The Hierarchical Bayesian Analysis of Population Structure (hierBAPS) resulted in the differentiation of 12 EBV populations showed seven monophyletic and five paraphyletic. The populations identified were related to geographic location, of which three populations (EBV-p1/Asia/GC, EBV-p2/Asia II/Tumors and EBV-p4/China/NPC) were related to tumor development. Therefore, we proposed a new consistent and non-simplistic EBV classification, beneficial in minimizing the recombination signal in the phylogeny reconstruction, investigating geography relationship and even infer associations to human diseases. These EBV classifications could also be useful in developing diagnostic applications or defining which strains need epidemiological surveillance.

Indexed as

Recombination, GeneticAsiaBayes TheoremChinaEpidemiological MonitoringEpstein-Barr Virus InfectionsGenetic VariationGenome, ViralGenomicsHerpesvirus 4, HumanHigh-Throughput Nucleotide SequencingHumansPhylogenyPhylogeographyWhole Genome Sequencing

Identifiers

PMID31285478
PMCPMC6614506
OpenAlexW2962209201

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.