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Repurposing current therapeutics for treating COVID-19: A vital role of prescription records data mining.

ABSTRACT: Since its outbreak in late 2019, the SARS-Cov-2 pandemic already infected over 3.7 million people and claimed more than 250,000 lives globally. At least 1?year may take for an approved vaccine to be in place, and meanwhile millions more could be infected, some with fatal outcome. Over thousand clinical trials with COVID-19 patients are already listed in ClinicalTrials.com, some of them for assessing the utility of therapeutics approved for other conditions. However, clinical trials take many months, and are typically done with small cohorts. A much faster and by far more efficient method for rapidly identifying approved therapeutics that can be repurposed for treating COVID-19 patients is data mining their past and current electronic health and prescription records for identifying drugs that may protect infected individuals from severe COVID-19 symptoms. Examples are discussed for applying health and prescription records for assessing the potential repurposing (repositioning) of angiotensin receptor blockers, estradiol, or antiandrogens for reducing COVID-19 morbidity and fatalities. Data mining of prescription records of COVID-19 patients will not cancel the need for conducting controlled clinical trials, but could substantially assist in trial design, drug choice, inclusion and exclusion criteria, and prioritization. This approach requires a strong commitment of health provides for open collaboration with the biomedical research community, as health provides are typically the sole owners of retrospective drug prescription records.

SUBMITTER: Gurwitz D

PROVIDER: S-EPMC7276810 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Repurposing current therapeutics for treating COVID-19: A vital role of prescription records data mining.

Gurwitz David D

Drug development research 20200518 7

Since its outbreak in late 2019, the SARS-Cov-2 pandemic already infected over 3.7 million people and claimed more than 250,000 lives globally. At least 1 year may take for an approved vaccine to be in place, and meanwhile millions more could be infected, some with fatal outcome. Over thousand clinical trials with COVID-19 patients are already listed in ClinicalTrials.com, some of them for assessing the utility of therapeutics approved for other conditions. However, clinical trials take many mon ...[more]

PMID: 32420637

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Project description:IntroductionTreatment of rheumatoid arthritis (RA) has advanced with the introduction of biological disease-modifying antirheumatic drugs. However, more than 20% of patients with RA still have moderate or severe disease activity. Hence, novel antirheumatic drugs are required. Recently, drug repurposing, a process of identifying new indications for existing drugs, has received great attention. Furthermore, a few reports have shown that antipsychotics are capable of affecting several cytokines that are also modulated by existing antirheumatic drugs. Therefore, we investigated the association between antipsychotics and RA by data mining using real-world data and bioinformatics databases.MethodsDisproportionality and sequence symmetry analyses were employed to identify the associations between the investigational drugs and RA using the US Food and Drug Administration Adverse Event Reporting System (2004-2016) and JMDC administrative claims database (January 2005-April 2017; JMDC Inc., Tokyo, Japan), respectively. The reporting odds ratio (ROR) and information component (IC) were used in the disproportionality analysis to indicate a signal. The adjusted sequence ratio (SR) was used in the sequence symmetry analysis to indicate a signal. The bioinformatics analysis suite, BaseSpace Correlation Engine (Illumina, CA, USA) was employed to explore the molecular mechanisms associated with the potential candidates identified by the drug-repurposing approach.ResultsA potential inverse association between the antipsychotic haloperidol and RA, which exhibited significant inverse signals with ROR, IC, and adjusted SR, was found. Furthermore, the results suggested that haloperidol may exert antirheumatic effects by modulating various signaling pathways, including cytokine and chemokine signaling, major histocompatibility complex class-II antigen presentation, and Toll-like receptor cascade pathways.ConclusionOur drug-repurposing approach using data mining techniques identified haloperidol as a potential antirheumatic drug candidate.

Project description:BackgroundThe pathogenesis of rheumatoid arthritis (RA) is complex. This study aimed to identify diagnostic biomarkers and transcriptional regulators that underlie RA based on bioinformatics analysis and experimental verification.Material and methodsWe applied weighted gene co-expression network analysis (WGCNA) to analyze dataset GSE55457 and obtained the key module most relevant to the RA phenotype. We then conducted gene function annotation, gene set enrichment analysis (GSEA) and immunocytes quantitative analysis (CIBERSORT). Moreover, the intersection of differentially expressed genes (DEGs) and genes within the key module were entered into the STRING database to construct an interaction network and to mine hub genes. We predicted microRNA (miRNA) using a web-based tool (miRDB). Finally, hub genes and vital miRNAs were validated with independent GEO datasets, RT-qPCR and Western blot.ResultsA total of 367 DEGs were characterized by differential expression analysis. The WGCNA method divided genes into 14 modules, and we focused on the turquoise module containing 845 genes. Gene function annotation and GSEA suggested that immune response and inflammatory signaling pathways are the molecular mechanisms behind RA. Nine hub genes were screened from the network and seven vital regulators were obtained using miRNA prediction. CIBERSORT analysis identified five cell types enriched in RA samples, which were closely related to the expression of hub genes. Through ROC curve and RT-qPCR validation, we confirmed five genes that were specific for RA, including CCL25, CXCL9, CXCL10, CXCL11, and CXCL13. Moreover, we selected a representative gene (CXCL10) for Western blot validation. Vital miRNAs verification showed that only the differences in has-miR-573 and has-miR-34a were statistically significant.ConclusionOur study reveals diagnostic genes and vital microRNAs highly related to RA, which could help improve our understanding of the molecular mechanisms underlying the disorder and provide theoretical support for the future exploration of innovative therapeutic approaches.

Dataset Information

Repurposing current therapeutics for treating COVID-19: A vital role of prescription records data mining.

Publications

Repurposing current therapeutics for treating COVID-19: A vital role of prescription records data mining.

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