Evidence map›Paper›PMID 29310750›Full record

ArticleMicrobial genomics2018

Integrating patient and whole-genome sequencing data to provide insights into the epidemiology of seasonal influenza A(H3N2) viruses.

Emily J Goldstein, William T Harvey, Gavin S Wilkie, Samantha J Shepherd, Alasdair R MacLean, Pablo R Murcia, Rory N Gunson

Abstract read
In one paragraph

Article in Microbial genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

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  11. Randomly primed, strand-switching, MinION-based sequencing for the detection and characterization of cultured RNA viruses.Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · 2021
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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

7 authors.

Emily J Goldstein1​West of Scotland Specialist Virology Centre, NHS Greater Glasgow and Clyde, Glasgow, UK.
William T Harvey2​Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, UK.
Gavin S Wilkie3​Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK.
Samantha J Shepherd1​West of Scotland Specialist Virology Centre, NHS Greater Glasgow and Clyde, Glasgow, UK.
Alasdair R MacLean1​West of Scotland Specialist Virology Centre, NHS Greater Glasgow and Clyde, Glasgow, UK.
Pablo R Murcia3​Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK.
Rory N Gunson1​West of Scotland Specialist Virology Centre, NHS Greater Glasgow and Clyde, Glasgow, UK.

Funding

Medical Research Council MC_UU_12014/9
6 · The paper itself

Abstract

Genetic surveillance of seasonal influenza is largely focused on sequencing of the haemagglutinin gene. Consequently, our understanding of the contribution of the remaining seven gene segments to the evolution and epidemiological dynamics of seasonal influenza is relatively limited. The increased availability of next-generation sequencing technologies allows rapid and economic whole-genome sequencing (WGS) of influenza virus. Here, 150 influenza A(H3N2) positive clinical specimens with linked epidemiological data, from the 2014/15 season in Scotland, were sequenced directly using both Sanger sequencing of the HA1 region and WGS using the Illumina MiSeq platform. Sequences generated by the two methods were highly correlated, and WGS provided on average >90 % whole genome coverage. As reported in other European countries during 2014/15, all strains belonged to genetic group 3C, with subgroup 3C.2a predominating. Multiple inter-subgroup reassortants were identified, including three 3C.3 viruses descended from a single reassortment event, which had persisted in the population. Cases of severe acute respiratory illness were significantly clustered on phylogenies of multiple gene segments indicating potential genetic factors warranting further investigation. Severe cases were also more likely to be associated with reassortant viruses and to occur later in the season. These results suggest that WGS provides an opportunity to develop our understanding of the relationship between the influenza genome and disease severity and the epidemiological consequences of within-subtype reassortment. Therefore, increased levels of WGS, linked to clinical and epidemiological data, could improve influenza surveillance.

Indexed as

Epidemiological MonitoringGenome, ViralSentinel SurveillanceComputational BiologyHemagglutinins, ViralHigh-Throughput Nucleotide SequencingHumansInfluenza A Virus, H3N2 SubtypeInfluenza, HumanLectinsLogistic ModelsPhylogenyReassortant VirusesScotlandSeasonsWhole Genome Sequencinghemagglutinin IHemagglutinins, ViralLectinsA(H3N2)disease severityinfluenzareassortmentsurveillancewhole-genome sequencing

Identifiers

PMID29310750
PMCPMC5857367

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Registered trials

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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.