The research team, led by the University of Birmingham and Keele University in the UK and the San Raffaele Scientific Institute in Italy, has demonstrated that fenofibrate and its active form (fenofibric acid) can significantly reduce SARS-COV-2 infection in human cells in the laboratory.
Importantly, reduction of infection was obtained using concentrations of the drug which are safe and achievable using the standard clinical dose of fenofibrate.
Fenofibrate, which is approved for use by most countries in the world including the US Food and Drug Administration (FDA) and the UK’s National Institute for Health and Care Excellence (NICE), is an oral drug currently used to treat conditions such as high levels of cholesterol and lipids (fatty substances) in the blood.
The team is now calling for clinical trials to test the drug in hospitalized COVID-19 patients, to be carried out in addition to two clinical trials also currently underway in such patients in research being led by the Hospital of the University of Pennsylvania in the US and Hebrew University of Jerusalem in Israel.
SARS-CoV-2, the virus that causes COVID-19, infects the host through an interaction between the Spike protein on the surface of the virus and the ACE2 receptor protein on host cells. In this study, responding to the global COVID-19 pandemic, the team tested a panel of already licensed drugs – including fenofibrate – to identify candidates that disrupt ACE2 and Spike interactions.
Having identified fenofibrate as a candidate, they then tested the efficacy of the drug in reducing infection in cells in the laboratory using the original strains of the SARS-CoV-2 virus isolated in 2020. They found fenofibrate reduced infection by up to 70%.
Corresponding author Dr. Farhat Khanim, of the University of Birmingham in the UK, explained: “The development of new more infectious SARS-CoV-2 variants has resulted in a rapid expansion in infection rates and deaths in several countries around the world, especially the UK, US and Europe. Whilst vaccine programs will hopefully reduce infection rates and virus spread in the longer term, there is still an urgent need to expand our arsenal of drugs to treat SARS-CoV-2-positive patients.”
Co-corresponding author Dr. Alan Richardson, of Keele University in the UK, added: “Whilst in some countries vaccination programs are progressing at speed, vaccine uptake rates are variable and for most low middle income countries, significant proportions of the population are unlikely to be vaccinated until 2022.
Furthermore, whilst vaccination has been shown to reduce infection rates and severity of disease, we are as yet unsure of the strength and duration of the response. Therapies are still urgently needed to manage COVID-19 patients who develop symptoms or require hospitalization.”
Co-author Dr. Elisa Vicenzi, of the San Raffaele Scientific Institute in Milan, Italy, said: “Our data indicates that fenofibrate may have the potential to reduce the severity of COVID-19 symptoms and also virus spread. Given that fenofibrate is an oral drug which is very cheap and available worldwide, together with its extensive history of clinical use and its good safety profile, our data has global implications – especially in low-middle income countries and in those individuals for whom vaccines are not recommended or suitable such as children, those with hyper-immune disorders and those using immune-suppressants.”
First author Dr. Scott Davies, also of the University of Birmingham, concluded: “We now urgently need further clinical studies to establish whether fenofibrate is a potential therapeutic agent to treat SARS-CoV-2 infection.”
The research, published today in Frontiers in Pharmacology, was also carried out in collaboration with the University of Copenhagen in Denmark and the University of Liverpool in the UK.
COVID–19 (Coronavirus Disease 2019) is an infectious virus outbreak which rapidly developed into a pandemic health crisis. The novel coronavirus (SARS-CoV–2/nCoV–19) is the causative agent of this disease.1 Several groups responded to the urgent need for effective therapeutics by leading systems-level efforts to identify drugs repurposable for COVID–19, through the lens of the virus-host protein interactome,2 and the interactomes of SARS-CoV–2-modulated host proteins3 and host proteins modulated by other human corona viruses such as SARS-CoV, MERS-CoV, HCoV–229E, and HCoV-NL63.4 Repurposing or finding alternate uses for approved drugs has proved to be a better strategy than de novo identification in terms of time and cost effectiveness.5–7
Discovery of therapeutic agents for infectious diseases in the past was largely serendipitous, and focused on screening and prioritizing drugs that target the viral system.8 Over the last few years, the focus has shifted towards computationally identifying drugs that could counter the virus attack A primary strategy is to repurpose drugs with the ability to revert the genes differentially expressed in the host upon viral infection to their normal levels; i.e. to revert the host transcriptional profile induced upon viral infection to its normal state.8
This “inverse genomic signature approach” involves identifying drugs that induce gene expression profiles negatively correlated with host-specific gene signatures induced by viral infection, and has been used to select candidates repurposable against influenza viruses and MERS-CoV.9–11 Availability of disease-associated and drug-induced transcriptomic profiles in online repositories such as NCBI GEO (Gene Expression Omnibus) and CMAP (Connectivity Map),12,13 allow these profiles to be compared using bioinformatics data analysis software suites such as the BaseSpace Correlation Engine.14
Changes in the host transcriptome induced by viral infection are also reflected in the host proteome, specifically as perturbations in the interaction networks of the host proteins. This complex network of protein-protein interactions (PPIs) called the ‘interactome’ has the potential to restrict viral replication in host cells, or conversely to be taken over by the virus for its replication.
We had previously presented the Host Protein Interactome (HoP Interactome) of 332 human proteins identified to interact with 27 SARS-CoV–2 viral proteins by Gordon et al.2,15. This interactome, consisting of 6,076 PPIs of the host proteins including 1,941 novel interactions predicted by HiPPIP, provided an integrated view on how host genes in various high throughput COVID–19 and SARS transcriptomic/proteomic studies are functionally linked.15 In this study, we identified drugs targeting the proteins in this interactome, and studied the correlation of the gene expression profiles induced by these drugs in various cell lines, with SARS/COVID-associated profiles observed in lung-derived (MRC5, Calu–3, NHBE and A549) cell lines, and in peripheral blood mononuclear cells (PBMCs) of SARS patients. Our work differs from previous efforts to identify drugs repurposable for COVID–192–4 in that it considers the host protein interactome, and includes computationally predicted novel interactors of the host proteins, which may lead to identification of drugs that were hitherto not prioritized.
Potentially Repurposable Drugs
We compared drug-induced versus SARS-associated differential expression using the BaseSpace Correlation Engine (previously called NextBio) (https://www.nextbio.com),16,17 to identify drugs for nCoV19. We compiled a list of 933 chemical compounds whose differential gene expression profile (drug versus no drug) were negatively correlated with at least one of the four SARS differential gene expression datasets (infected versus non-infected); the 4 SARS datasets we studied were: Calu–3 epithelial cells infected for 48 hours with SARS coronavirus versus mock infected cells (GSE17400), Calu–3 lung cells infected for 72 hours with SARS CoV Urbani versus mock infected cells (GSE37827), lung fibroblast MRC5 cells 24 hours post SARS coronavirus infection, high multiplicity of infection MOI versus mock infection (GSE56189) and peripheral blood mononuclear cells (PBMCs) from patients with SARS versus healthy subjects (GSE173918).
We also compiled a list of 381 chemical compounds with gene expression profiles negatively correlated with the profile induced in human bronchial epithelial (NHBE) and lung cancer (A549) cells infected with the SARS-CoV–2 strain USA-WA1/2020 (GSE14750719) Although in each case, there would be some genes that are differentially expressed in the same direction for both the drug and the disease (i.e., both cause some genes to overexpress, or both cause some genes to under express), the overall effect on the entire transcriptome would be an anti-correlation.
A correlation score is generated by NextBio based on the strength of the overlap between the drug and disease datasets. Statistical criteria such as correction for multiple hypothesis testing are applied and the correlated datasets are then ranked by statistical significance. A numerical score of 100 is assigned to the most significant result, and the scores of the other results are normalized with respect to this top-ranked result.
Next, we identified 1,130 drugs that target at least one protein in the HoP interactome using WebGestalt.20 We used the ‘redundancy reduction’ feature provided by WebGestalt to prioritize drugs with highly significant overlaps with the interactome, while also capturing all the unique target gene sets.
This feature used an affinity propagation algorithm which clusters sets of genes in the interactome targeted by specific drugs using Jaccard index as the similarity metric and identifies a ‘representative’ for each cluster (one drug and its targets), having the most significant p-value among all the gene sets in that cluster. This resulted in 209 drugs for further consideration. Given a class of drugs targeting the same set of proteins, this method ensures that only those individual drugs that target a statistically significant number of proteins in the interactome are prioritized for further analysis.
Fifty-six drugs were found in common to the above two analyses, i.e. these drugs not only targeted genes in the HoP interactome, but also induced gene expression profiles which are negatively correlated with that induced by SARS-CoV (Supplementary Table S1) and SARS-CoV–2 (Supplementary Table S2)..
Thirteen drugs showed negative correlation with both expression profiles. Twenty-four of the fifty six have supporting evidence for biological relevance through clinical trial data and published literature (Figure 1) (in the list below, three drugs—cyclosporine, sorafenib and tamoxifen—have multiple evidences, and are shown italicized after 1st occurrence):
Repurposable drugs for COVID-19: The network shows the drugs (green color nodes) that target the proteins in the CoV-HP interactome. Host proteins are shown as dark blue nodes, their known interactors are light blue and novel interactors are red.
- four drugs showed activity against SARS-CoV–2 in vitro (anisomycin, cyclosporine, sorafenib, tamoxifen)
- one chemical compound (nitric oxide) found here is already being tested against nCoV19 in clinical trials
- one drug (ramipril) belongs to the class of receptors targeted by nCoV19
- five drugs display antiviral activity in SARS or MERS infected cells line (cyclosporine, interferon alfacon–1, interferon alpha–2b, mycophenolic acid, resveratrol, sirolimus)
- three drugs (progesterone, quercetin, verapamil) are active against influenza viruses two drugs active against DNA viruses (sorafenib, daunorubicin, leflunomide), and
- eight drugs show activity against other RNA viruses (cerivastatin, clotrimazole, didanosine, fenofibrate, miglitol, paclitaxel, pioglitazone, tamoxifen, thioridazine)
8 drugs from our shortlist were independently identified or prioritized by other groups, namely: sirolimus (Zhou et al.4), leflunomide, quercetin and verapamil (Barabási et al.3), interferon alfa–2b, resveratrol, cyclosporine and mycophenolic acid (Li et al.21). Additionally, eight out of the 24 shortlisted drugs were also found among 127 broad-spectrum antiviral drugs active against 80 viruses (https://drugvirus.info/).
These are cyclosporine, leflunomide, mycophenolic acid, sirolimus, sorafenib, tamoxifen, anisomycin and verapamil.
reference link : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7336709/
More information: Frontiers in Pharmacology, DOI: 10.3389/fphar.2021.660490
