Aripiprazole as a Candidate Treatment of COVID-19 Identified Through Genomic Analysis

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Abstract

Background: Antipsychotics modulate expression of inflammatory cytokines and inducible inflammatory enzymes. Elopiprazole (a phenylpiperazine antipsychotic drug in phase 1) has been characterized as a therapeutic drug to treat SARS-CoV-2 infection in a repurposing study. We aim to investigate the potential effects of aripiprazole (an FDA approved phenylpiperazine) on COVID-19-related immunological parameters.

Methods: Differential gene expression profiles of non-COVID-19 vs. COVID-19 RNA-Seq samples (CRA002390 project in GSA database) and drug-naïve patients with non-affective psychosis at baseline and after three months of aripiprazole treatment were identified. An integrative transcriptomic analyses of aripiprazole effects on differentially expressed genes in COVID-19 patients was performed.

Findings: 82 out the 377 genes (21.7%) with expression significantly altered by aripiprazole have also their expression altered in COVID-19 patients and in 93.9% of these genes their expression is reverted by aripiprazole. The number of common genes with expression altered in both analyses is significantly higher than expected (Fisher’s Exact Test, two tail; p value = 3.2e-11). 11 KEGG pathways were significantly enriched with genes with altered expression both in COVID-19 patients and aripiprazole medicated non-affective psychosis patients ( p adj<0.05). The most significant pathways were associated to immune responses and mechanisms of hyperinflammation-driven pathology (i.e.,“inflammatory bowel disease (IBD)” (the most significant pathway with a p adj of 0.00021), “Th1 and Th2 cell differentiation” and “B cell receptor signaling pathway”) that have been also associated with COVID19 clinical outcome.

Interpretation: This exploratory investigation may provide further support to the notion that a protective effect is exerted by aripiprazole (phenylpiperazine) by modulating the expression of genes that have shown to be altered in COVID-19 patients. Along with many ongoing studies and clinical trials, repurposing available medications could be of use in countering SARS-CoV-2 infection, but require further studies and trials.

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  1. SciScore for 10.1101/2020.12.05.20244590: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: Conforming to international standards for research ethics, this study was approved by the Cantabria Ethics Institutional Review Board (IRB).
    Consent: Patients meeting inclusion criteria for a first episode of psychosis (drug-naïve) and their families provided written informed consent to be included in the study.
    RandomizationAfter informed consent was signed, patients were included in a prospective, randomized, flexible-dose, open-label study (Crespo-Facorro et al., 2017; Mayoral Van-Son et al, 2020).
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Sequence files were aligned to the GRCh38 human reference genome (Gencode release 25) using the STAR aligner(Dobin et al., 2013; Harrow et al., 2012)
    STAR
    suggested: (STAR, RRID:SCR_015899)
    These data were analyzed with RaNA-Seq (Prieto & Barrios, 2019) cloud platform and differential expression genes were detected by means of DESeq2 (Love et al., 2014) cloud using a Wald test, a parametric fit type and setting an adjusted p-value cutoff of 0.01. 2.6 Statistical and bioinformatic Analysis: Statistical significance of differential expression co-occurrence between COVID and Aripiprazole studies was calculated with a Fisher Exact test.
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT02200588Enrolling by invitationLongitudinal Long-term Study (10 Years) of the Sample of Fir…
    NCT03481465Enrolling by invitationSearching for Early Biomarkers of Long-term Hepatic, Metabol…
    NCT03476473Enrolling by invitationEarly Detection of Respiratory Disorders in Psychosis


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.