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
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 associate...
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Published in: | Heliyon Vol. 10; no. 6; p. e27043 |
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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. |
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AbstractList | 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. |
ArticleNumber | e27043 |
Author | Duong, Vinh Chi Nguyen, Thien Khac Nguyen, Nguyen Thanh Nguyen, Duong Thuy Phung, Huong Thanh Vo, Nam S. Tran, Trang Thi Ha Pham, Thang Luong Tran, Mai Hoang Vu, Giang Minh Hoang, Tham Hong |
Author_xml | – sequence: 1 givenname: Thien Khac orcidid: 0000-0003-1577-380X surname: Nguyen fullname: Nguyen, Thien Khac organization: GeneStory JSC, Hanoi, Viet Nam – sequence: 2 givenname: Giang Minh orcidid: 0000-0002-7934-9736 surname: Vu fullname: Vu, Giang Minh organization: Center for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam – sequence: 3 givenname: Vinh Chi orcidid: 0000-0001-5431-6500 surname: Duong fullname: Duong, Vinh Chi organization: Center for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam – sequence: 4 givenname: Thang Luong orcidid: 0000-0001-7600-7450 surname: Pham fullname: Pham, Thang Luong organization: GeneStory JSC, Hanoi, Viet Nam – sequence: 5 givenname: Nguyen Thanh surname: Nguyen fullname: Nguyen, Nguyen Thanh organization: GeneStory JSC, Hanoi, Viet Nam – sequence: 6 givenname: Trang Thi Ha surname: Tran fullname: Tran, Trang Thi Ha organization: Center for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam – sequence: 7 givenname: Mai Hoang surname: Tran fullname: Tran, Mai Hoang organization: Center for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam – sequence: 8 givenname: Duong Thuy surname: Nguyen fullname: Nguyen, Duong Thuy organization: Center for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam – sequence: 9 givenname: Nam S. orcidid: 0000-0002-5454-9176 surname: Vo fullname: Vo, Nam S. email: v.namvs@vinbigdata.org organization: Center for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam – sequence: 10 givenname: Huong Thanh orcidid: 0000-0002-7669-5983 surname: Phung fullname: Phung, Huong Thanh email: huongpt@hup.edu.vn organization: Faculty of Biotechnology, Hanoi University of Pharmacy, Hanoi, Viet Nam – sequence: 11 givenname: Tham Hong orcidid: 0000-0002-1592-237X surname: Hoang fullname: Hoang, Tham Hong email: v.thamhh@vinbigdata.org organization: Center for Biomedical Informatics, Vingroup Big Data Institute, Hanoi, Viet Nam |
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Keywords | Post-COVID-19 drugs Chronic diseases COVID-19 drugs Drug interactions Pharmacogenomics Vietnamese population |
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SubjectTerms | Chronic diseases Correspondence COVID-19 drugs Drug interactions Pharmacogenomics Post-COVID-19 drugs Vietnamese population |
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Title | 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 |
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