Evidence map›Paper›PMID 38509882›Full record

ArticleHeliyon2024

The therapeutic landscape for COVID-19 and post-COVID-19 medications from genetic profiling of the Vietnamese population and a predictive model of drug-drug interaction for comorbid COVID-19 patients.

Thien Khac Nguyen, Giang Minh Vu, Vinh Chi Duong, Thang Luong Pham, Nguyen Thanh Nguyen, Trang Thi Ha Tran, Mai Hoang Tran, Duong Thuy Nguyen, Nam S Vo, Huong Thanh Phung and 1 more

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

11 authors.

Thien Khac NguyenGeneStory JSC, Hanoi, Viet Nam.
Giang Minh VuCenter for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam.
Vinh Chi DuongCenter for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam.
Thang Luong PhamGeneStory JSC, Hanoi, Viet Nam.
Nguyen Thanh NguyenGeneStory JSC, Hanoi, Viet Nam.
Trang Thi Ha TranCenter for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam.
Mai Hoang TranCenter for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam.
Duong Thuy NguyenCenter for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam.
Nam S VoCenter for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam.
Huong Thanh PhungFaculty of Biotechnology, Hanoi University of Pharmacy, Hanoi, Viet Nam.
Tham Hong HoangCenter for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the raised awareness of the role of pharmacogenomic (PGx) in personalized medicines for COVID-19, data for COVID-19 drugs is extremely scarce and not even a publication on this topic for post-COVID-19 medications to date. In the current study, we investigated the genetic variations associated with COVID-19 and post-COVID-19 therapies by using whole genome sequencing data of the 1000 Vietnamese Genomes Project (1KVG) in comparison with other populations retrieved from the 1000 Genomes Project Phase 3 (1KGP3) and the Genome Aggregation Database (gnomAD). Moreover, we also evaluated the risk of drug interactions in comorbid COVID-19 and post-COVID-19 patients based on pharmacogenomic profiles of drugs using a computational approach. For COVID-19 therapies, variants related to the response of two causal treatment agents (tolicizumab and ritonavir) and antithrombotic drugs are common in the Vietnamese cohort. Regarding post-COVID-19, drugs for mental manipulations possess the highest number of clinical annotated variants carried by Vietnamese individuals. Among the superpopulations, East Asian populations shared the most similar genetic structure with the Vietnamese population, whereas the African population showed the most difference. Comorbid patients are at an increased drug-drug interaction (DDI) risk when suffering from COVID-19 and after recovering as well due to a large number of potential DDIs which have been identified. Our results presented the population-specific understanding of the pharmacogenomic aspect of COVID-19 and post-COVID-19 therapy to optimize therapeutic outcomes and promote personalized medicine strategy. We also partly clarified the higher risk in COVID-19 patients with underlying conditions by assessing the potential drug interactions.

Indexed as

Chronic diseasesCOVID-19 drugsDrug interactionsPharmacogenomicsPost-COVID-19 drugsVietnamese population

Identifiers

PMID38509882
PMCPMC10950508

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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.