Pulmonary adverse drug event data in hypertension with implications on COVID-19 morbidity

Jaberi-Douraki, Majid; Meyer, Emma; Riviere, Jim E.; Gedara, Nuwan Indika Millagaha; Kawakami, Jessica; Wyckoff, Gerald J.; Xu, Xuan

doi:10.1038/s41598-021-92734-7

Cited by 5 publications

(5 citation statements)

References 34 publications

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“…We used VOSviewer software to analyze the association between the most productive authors and the most cited references to generate the network map and clusters visualization. Finally, we augmented qualitative text analysis using natural language processing (NLP) to investigate key characteristics and the pattern associations with nanotechnology and the top 10 cancer types [30,31]. Under the qualitative method, we mainly focus on qualitative text analysis or qualitative content analysis (e.g., thematic analysis).…”

Section: Methodsmentioning

confidence: 99%

Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification

Gedara

Delong

et al. 2021

Cancers

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This study presents a new way to investigate comprehensive trends in cancer nanotechnology research in different countries, institutions, and journals providing critical insights to prevention, diagnosis, and therapy. This paper applied the qualitative method of bibliometric analysis on cancer nanotechnology using the PubMed database during the years 2000–2021. Inspired by hybrid medical models and content-based and bibliometric features for machine learning models, our results show cancer nanotechnology studies have expanded exponentially since 2010. The highest production of articles in cancer nanotechnology is mainly from US institutions, with several countries, notably the USA, China, the UK, India, and Iran as concentrated focal points as centers of cancer nanotechnology research, especially in the last five years. The analysis shows the greatest overlap between nanotechnology and DNA, RNA, iron oxide or mesoporous silica, breast cancer, and cancer diagnosis and cancer treatment. Moreover, more than 50% of the information related to the keywords, authors, institutions, journals, and countries are considerably investigated in the form of publications from the top 100 journals. This study has the potential to provide past and current lines of research that can unmask comprehensive trends in cancer nanotechnology, key research topics, or the most productive countries and authors in the field.

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Section: Methodsmentioning

confidence: 99%

Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification

Gedara

Delong

et al. 2021

Cancers

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“…Unfortunately, the potential risk of drug-drug interactions is largely unknown since most studies on COVID-19 do not provide details on interactions between drugs used in the course of COVID-19 treatment and co-medications used for the management of other comorbidities in these patients 53 . Moreover, the use of some commonly used drugs in COVID patients may lead to an increased number of adverse pulmonary effects 54 . The current direction is to find suitable drugs that have a certain therapeutic effect and relatively few side effects.…”

Section: Discussionmentioning

confidence: 99%

Potential therapeutic targets for COVID-19 complicated with pulmonary hypertension: a bioinformatics and early validation study

Hou,

Jiang,

et al. 2024

Sci Rep

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Coronavirus disease (COVID-19) and pulmonary hypertension (PH) are closely correlated. However, the mechanism is still poorly understood. In this article, we analyzed the molecular action network driving the emergence of this event. Two datasets (GSE113439 and GSE147507) from the GEO database were used for the identification of differentially expressed genes (DEGs).Common DEGs were selected by VennDiagram and their enrichment in biological pathways was analyzed. Candidate gene biomarkers were selected using three different machine-learning algorithms (SVM-RFE, LASSO, RF).The diagnostic efficacy of these foundational genes was validated using independent datasets. Eventually, we validated molecular docking and medication prediction. We found 62 common DEGs, including several ones that could be enriched for Immune Response and Inflammation. Two DEGs (SELE and CCL20) could be identified by machine-learning algorithms. They performed well in diagnostic tests on independent datasets. In particular, we observed an upregulation of functions associated with the adaptive immune response, the leukocyte-lymphocyte-driven immunological response, and the proinflammatory response. Moreover, by ssGSEA, natural killer T cells, activated dendritic cells, activated CD4 T cells, neutrophils, and plasmacytoid dendritic cells were correlated with COVID-19 and PH, with SELE and CCL20 showing the strongest correlation with dendritic cells. Potential therapeutic compounds like FENRETI-NIDE, AFLATOXIN B1 and 1-nitropyrene were predicted. Further molecular docking and molecular dynamics simulations showed that 1-nitropyrene had the most stable binding with SELE and CCL20.The findings indicated that SELE and CCL20 were identified as novel diagnostic biomarkers for COVID-19 complicated with PH, and the target of these two key genes, FENRETI-NIDE and 1-nitropyrene, was predicted to be a potential therapeutic target, thus providing new insights into the prediction and treatment of COVID-19 complicated with PH in clinical practice.

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“…Our previous work showed that quinapril and trandolapril were significantly different from other ACEI and ARB drug classes ( Jaberi-Douraki et al, 2021 ). Separating from its drug class was initially observed in Figure 2 when the PCA biplot was performed.…”

Section: Discussionmentioning

confidence: 99%

“…Different quantitative therapeutic efforts in drug repurposing or repositioning combined with adverse drug event (ADE) identification have led to more efficient therapies while improving the clinical course, lowering fatality, and decreasing cost burden ( Smith and Smith, 2021 ). The previous work focused on the incidence of pulmonary ADEs associated with ACEI and ARB use in patients with hypertension and other comorbidities ( Stafford et al, 2020 ; Jaberi-Douraki et al, 2021 ). The findings indicate that specific drugs—rather than entire classes—have higher incidences of pulmonary ADEs, which may have implications for treating patients diagnosed with COVID-19.…”

Section: Introductionmentioning

confidence: 99%

“…In our previous work, 13 different pulmonary ADEs were selected based on clinical importance, and as they were prevalent among the top reported symptoms in patients with COVID-19, to assess the related variation due to adverse event differences ( Stafford et al, 2020 ; Jaberi-Douraki et al, 2021 ). In the present work, we include 25 pulmonary, infectious diseases, or cardiac-associated ADEs.…”

Section: Introductionmentioning

confidence: 99%

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Data mining methodology for response to hypertension symptomology—application to COVID-19-related pharmacovigilance

Kawakami

Gedara

et al. 2021

eLife

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Background: Potential therapy and confounding factors including typical co‐administered medications, patient's disease states, disease prevalence, patient demographics, medical histories, and reasons for prescribing a drug often are incomplete, conflicting, missing, or uncharacterized in spontaneous adverse drug event (ADE) reporting systems. These missing or incomplete features can affect and limit the application of quantitative methods in pharmacovigilance for meta-analyses of data during randomized clinical trials.Methods: Data from patients with hypertension were retrieved and integrated from the FDA Adverse Event Reporting System. 134 antihypertensive drugs out of 1151 drugs were filtered and then evaluated using the Empirical Bayes Geometric Mean (EBGM) of the posterior distribution to build ADE-drug profiles with an emphasis on the pulmonary ADEs (pADE). Afterward, the Graphical Least Absolute Shrinkage and Selection Operator (GLASSO) captured drug associations based on pADEs by correcting hidden factors and confounder misclassification. Selected drugs were then compared using the Friedman test in drug classes and clusters obtained from GLASSO.Results: Following multiple filtering stages to exclude insignificant and noise-driven reports, we found that drugs from antihypertensives agents, urologicals, and antithrombotic agents (macitentan, bosentan, epoprostenol, selexipag, sildenafil, tadalafil, and beraprost) form a similar class with a significantly higher incidence of pADEs. Macitentan and bosentan were associates with 64% and 56% of pADEs, respectively. Because these two medications are prescribed in diseases affecting pulmonary function and may be likely to emerge among the highest reported pADEs, in fact, they serve to validate the methods utilized here. Conversely, doxazosin and rilmenidine were found to have the least pADEs in selected drugs from hypertension patients. Nifedipine and candesartan were also found by signal detection methods to form a drug cluster, shown by several studies an effective combination of these drugs on lowering blood pressure and appeared an improved side effect profile in comparison with single-agent monotherapy.Conclusions: We consider pADE profiles in multiple long-standing groups of therapeutics including antihypertensive agents, antithrombotic agents, beta-blocking agents, calcium channel blockers, or agents acting on the renin-angiotensin system, in patients with hypertension associated with high-risk for COVID-19. We found that several individual drugs have significant differences between their drug classes and compared to other drug classes. For instance, macitentan and bosentan from endothelin receptor antagonists show major concern while doxazosin and rilmenidine exhibited the least pADEs compared to the outcomes of other drugs. Using techniques in this study, we assessed and confirmed the hypothesis that drugs from the same drug class could have very different pADE profiles affecting outcomes in acute respiratory illness.Funding: GJW and MJD accepted funding from BioNexus KC for funding on this project, but BioNexus KC had no direct role in this article.

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Pulmonary adverse drug event data in hypertension with implications on COVID-19 morbidity

Cited by 5 publications

References 34 publications

Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification

Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification

Potential therapeutic targets for COVID-19 complicated with pulmonary hypertension: a bioinformatics and early validation study

Data mining methodology for response to hypertension symptomology—application to COVID-19-related pharmacovigilance

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