Evidence map›Paper›PMID 35718768›Full record

ArticleBMC infectious diseases2022

Investigation of target sequencing of SARS-CoV-2 and immunogenic GWAS profiling in host cells of COVID-19 in Vietnam.

Tham H Hoang, Giang M Vu, Mai H Tran, Trang T H Tran, Quang D Le, Khanh V Tran, Tue T Nguyen, Lan T N Nguyen, Thinh H Tran, Van T Ta and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

5 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Review
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

11 authors at 3 institutions in 1 country.

Tham H HoangCenter for Biomedical Informatics, Vingroup Big Data Institute, 458 Minh Khai Street, Hai Ba Trung, Hanoi, Vietnam. v.thamhh@vinbigdata.org.
Giang M VuCenter for Biomedical Informatics, Vingroup Big Data Institute, 458 Minh Khai Street, Hai Ba Trung, Hanoi, Vietnam.
Mai H TranCenter for Biomedical Informatics, Vingroup Big Data Institute, 458 Minh Khai Street, Hai Ba Trung, Hanoi, Vietnam.
Trang T H TranCenter for Biomedical Informatics, Vingroup Big Data Institute, 458 Minh Khai Street, Hai Ba Trung, Hanoi, Vietnam.
Quang D LeHanoi University of Civil Engineering, 55 Giai Phong Street, Hai Ba Trung, Hanoi, Vietnam.
Khanh V TranHanoi Medical University, 1 Ton That Tung Street, Dong Da, Hanoi, Vietnam.
Tue T NguyenHanoi Medical University, 1 Ton That Tung Street, Dong Da, Hanoi, Vietnam.
Lan T N NguyenHanoi Medical University, 1 Ton That Tung Street, Dong Da, Hanoi, Vietnam.
Thinh H TranHanoi Medical University, 1 Ton That Tung Street, Dong Da, Hanoi, Vietnam.
Van T TaHanoi Medical University, 1 Ton That Tung Street, Dong Da, Hanoi, Vietnam.
Nam S VoCenter for Biomedical Informatics, Vingroup Big Data Institute, 458 Minh Khai Street, Hai Ba Trung, Hanoi, Vietnam.
Hanoi Medical University · VNHanoi University · VNVinUniversity · VN

Funding

QD-BKHCN 1539
6 · The paper itself

Abstract

backgroundA global pandemic has been declared for coronavirus disease 2019 (COVID-19), which has serious impacts on human health and healthcare systems in the affected areas, including Vietnam. None of the previous studies have a framework to provide summary statistics of the virus variants and assess the severity associated with virus proteins and host cells in COVID-19 patients in Vietnam.

methodIn this paper, we comprehensively investigated SARS-CoV-2 variants and immune responses in COVID-19 patients. We provided summary statistics of target sequences of SARS-CoV-2 in Vietnam and other countries for data scientists to use in downstream analysis for therapeutic targets. For host cells, we proposed a predictive model of the severity of COVID-19 based on public datasets of hospitalization status in Vietnam, incorporating a polygenic risk score. This score uses immunogenic SNP biomarkers as indicators of COVID-19 severity.

resultWe identified that the Delta variant of SARS-CoV-2 is most prevalent in southern areas of Vietnam and it is different from other areas in the world using various data sources. Our predictive models of COVID-19 severity had high accuracy (Random Forest AUC = 0.81, Elastic Net AUC = 0.7, and SVM AUC = 0.69) and showed that the use of polygenic risk scores increased the models' predictive capabilities.

conclusionWe provided a comprehensive analysis for COVID-19 severity in Vietnam. This investigation is not only helpful for COVID-19 treatment in therapeutic target studies, but also could influence further research on the disease progression and personalized clinical outcomes.

Indexed as

COVID-19COVID-19 Drug TreatmentGenome-Wide Association StudyHumansSARS-CoV-2VietnamCladeCOVID-19 severityPRSSARS-CoV-2Vietnam

Identifiers

PMID35718768
PMCPMC9206857
OpenAlexW4283118912

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.