J Biomed Sci. 2022 Sep 12;29(1):68. doi: 10.1186/s12929-022-00852-9.

ABSTRACT

The novel coronavirus disease (COVID-19) pandemic remains a global public health crisis, presenting a broad range of challenges. To help address some of the main problems, the scientific community has designed vaccines, diagnostic tools and therapeutics for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The rapid pace of technology development, especially with regard to vaccines, represents a stunning and historic scientific achievement. Nevertheless, many challenges remain to be overcome, such as improving vaccine and drug treatment efficacies for emergent mutant strains of SARS-CoV-2. Outbreaks of more infectious variants continue to diminish the utility of available vaccines and drugs. Thus, the effectiveness of vaccines and drugs against the most current variants is a primary consideration in the continual analyses of clinical data that supports updated regulatory decisions. The first two vaccines granted Emergency Use Authorizations (EUAs), BNT162b2 and mRNA-1273, still show more than 60% protection efficacy against the most widespread current SARS-CoV-2 variant, Omicron. This variant carries more than 30 mutations in the spike protein, which has largely abrogated the neutralizing effects of therapeutic antibodies. Fortunately, some neutralizing antibodies and antiviral COVID-19 drugs treatments have shown continued clinical benefits. In this review, we provide a framework for understanding the ongoing development efforts for different types of vaccines and therapeutics, including small molecule and antibody drugs. The ripple effects of newly emergent variants, including updates to vaccines and drug repurposing efforts, are summarized. In addition, we summarize the clinical trials supporting the development and distribution of vaccines, small molecule drugs, and therapeutic antibodies with broad-spectrum activity against SARS-CoV-2 strains.

PMID:36096815 | DOI:10.1186/s12929-022-00852-9

Chin J Integr Med. 2022 Sep 12. doi: 10.1007/s11655-022-3584-x. Online ahead of print.

ABSTRACT

Coalescence of traditional medicine Ayurveda and in silico technology is a rigor for supplementary development of future-ready effective traditional medicine. Ayurveda is a popular traditional medicine in South Asia, emanating worldwide for the treatment of metabolic disorders and chronic illness. Techniques of in silico biology are not much explored for the investigation of a variety of bioactive phytochemicals of Ayurvedic herbs. Drug repurposing, reverse pharmacology, and polypharmacology in Ayurveda are areas in silico explorations that are needed to understand the rich repertoire of herbs, minerals, herbo-minerals, and assorted Ayurvedic formulations. This review emphasizes exploring the concept of Ayurveda with in silico approaches and the need for Ayurinformatics studies. It also provides an overview of in silico studies done on phytoconstituents of some important Ayurvedic plants, the utility of in silico studies in Ayurvedic phytoconstituents/formulations, limitations/challenges, and prospects of in silico studies in Ayurveda. This article discusses the convergence of in silico work, especially in the least explored field of Ayurveda. The focused coalesce of these two domains could present a predictive combinatorial platform to enhance translational research magnitude. In nutshell, it could provide new insight into an Ayurvedic drug discovery involving an in silico approach that could not only alleviate the process of traditional medicine research but also enhance its effectiveness in addressing health care.

PMID:36094769 | DOI:10.1007/s11655-022-3584-x

Antimicrob Agents Chemother. 2022 Sep 12:e0100822. doi: 10.1128/aac.01008-22. Online ahead of print.

ABSTRACT

Human metapneumovirus (HMPV) is recognized as an important cause of pneumonia in infants, in the elderly, and in immunocompromised individuals worldwide. The absence of an antiviral treatment or vaccine strategy against HMPV infection creates a high burden on the global health care system. Drug repurposing has become increasingly attractive for the treatment of emerging and endemic diseases as it requires less research and development costs than traditional drug discovery. In this study, we developed an in vitro medium-throughput screening assay that allows for the identification of novel anti-HMPV drugs candidates. Out of ~2,400 compounds, we identified 11 candidates with a dose-dependent inhibitory activity against HMPV infection. Additionally, we further described the mode of action of five anti-HMPV candidates with low in vitro cytotoxicity. Two entry inhibitors, Evans Blue and aurintricarboxylic acid, and three post-entry inhibitors, mycophenolic acid, mycophenolate mofetil, and 2,3,4-trihydroxybenzaldehyde, were identified. Among them, the mycophenolic acid series displayed the highest levels of inhibition, due to the blockade of intracellular guanosine synthesis. Importantly, MPA has significant potential for drug repurposing as inhibitory levels are achieved below the approved human oral dose. Our drug-repurposing strategy proved to be useful for the rapid discovery of novel hit candidates to treat HMPV infection and provide promising novel templates for drug design.

PMID:36094205 | DOI:10.1128/aac.01008-22

Curr Comput Aided Drug Des. 2022 Sep 9. doi: 10.2174/1573409918666220909094645. Online ahead of print.

ABSTRACT

The coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a serious global healthcare crisis, so there is an emergence of identifying efficacious therapeutic options. In a setting where there is an unavailability of definitive medication along with the constant eruption of vaccine-related controversies, the drug-repositioning approach seems to be an ideal step for the management of COVID-19 patients. Fluoroquinolones (FQs) are commonly prescribed antibiotics for the treatment of genitourinary tract and upper respiratory tract infections, including severe community-acquired pneumonia. Research over the years has postulated multifaceted implications of FQs in various pathological conditions. Previously, it has been reported that few, but not all FQs, possess strong antiviral activity with an unknown mechanism of action. Herein, an interesting perspective is discussed on repositioning possibilities of FQs for the SARS-CoV-2 infections based on the recent in silico evidential support. Noteworthy, FQs possess immunomodulatory and bactericidal activity which could be valuable for patients dealing with COVID-19 related complications. Conclusively, the current perspective could pave the way to initiate pre-clinical testing of FQs against several strains of SARS-CoV-2.

PMID:36093826 | DOI:10.2174/1573409918666220909094645

Front Cell Infect Microbiol. 2022 Aug 25;12:975931. doi: 10.3389/fcimb.2022.975931. eCollection 2022.

ABSTRACT

Chagas disease (CD), a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi, is an important public health problem mainly in Latin America, leading to approximately 12,000 annual deaths. Current etiological treatment for CD is limited to two nitro compounds, benznidazole (Bz) and nifurtimox (Nif), both presenting relevant limitations. Different approaches have been employed to establish more effective and safer schemes to treat T. cruzi infection, mostly based on drug repurposing and combination therapies. Amiodarone (AMD), an antiarrhythmic medicament of choice for patients with the chronic cardiac form of CD, is also recognized as a trypanocidal agent. Therefore, our aim is to investigate the combined treatment Bz + AMD on trypomastigote viability, control of T. cruzi intracellular form proliferation, and recovery of the infection-induced cytoskeleton alterations in cardiac cells. The combination of Bz + AMD did not improve the direct trypanocidal effect of AMD on the infective blood trypomastigote and replicative intracellular forms of the parasite. Otherwise, the treatment of T. cruzi-infected cardiac cells with Bz plus AMD attenuated the infection-triggered cytoskeleton damage of host cells and the cytotoxic effects of AMD. Thus, the combined treatment Bz + AMD may favor parasite control and hamper tissue damage.

PMID:36093188 | PMC:PMC9452897 | DOI:10.3389/fcimb.2022.975931

Front Pharmacol. 2022 Aug 25;13:970494. doi: 10.3389/fphar.2022.970494. eCollection 2022.

ABSTRACT

The worldwide outbreak of SARS-CoV-2 in early 2020 caused numerous deaths and unprecedented measures to control its spread. We employed our Computational Analysis of Novel Drug Opportunities (CANDO) multiscale therapeutic discovery, repurposing, and design platform to identify small molecule inhibitors of the virus to treat its resulting indication, COVID-19. Initially, few experimental studies existed on SARS-CoV-2, so we optimized our drug candidate prediction pipelines using results from two independent high-throughput screens against prevalent human coronaviruses. Ranked lists of candidate drugs were generated using our open source cando.py software based on viral protein inhibition and proteomic interaction similarity. For the former viral protein inhibition pipeline, we computed interaction scores between all compounds in the corresponding candidate library and eighteen SARS-CoV proteins using an interaction scoring protocol with extensive parameter optimization which was then applied to the SARS-CoV-2 proteome for prediction. For the latter similarity based pipeline, we computed interaction scores between all compounds and human protein structures in our libraries then used a consensus scoring approach to identify candidates with highly similar proteomic interaction signatures to multiple known anti-coronavirus actives. We published our ranked candidate lists at the very beginning of the COVID-19 pandemic. Since then, 51 of our 276 predictions have demonstrated anti-SARS-CoV-2 activity in published clinical and experimental studies. These results illustrate the ability of our platform to rapidly respond to emergent pathogens and provide greater evidence that treating compounds in a multitarget context more accurately describes their behavior in biological systems.

PMID:36091793 | PMC:PMC9452636 | DOI:10.3389/fphar.2022.970494

Front Pharmacol. 2022 Aug 24;13:933655. doi: 10.3389/fphar.2022.933655. eCollection 2022.

ABSTRACT

Gliomas are the most common malignant brain tumors. High-grade gliomas, represented by glioblastoma multiforme (GBM), have a poor prognosis and are prone to recurrence. The standard treatment strategy is tumor removal combined with radiotherapy and chemotherapy, such as temozolomide (TMZ). However, even after conventional treatment, they still have a high recurrence rate, resulting in an increasing demand for effective anti-glioma drugs. Drug repurposing is a method of reusing drugs that have already been widely approved for new indication. It has the advantages of reduced research cost, safety, and increased efficiency. Disulfiram (DSF), originally approved for alcohol dependence, has been repurposed for adjuvant chemotherapy in glioma. This article reviews the drug repurposing method and the progress of research on disulfiram reuse for glioma treatment.

PMID:36091753 | PMC:PMC9448899 | DOI:10.3389/fphar.2022.933655

Biochem Biophys Rep. 2022 Aug 31;32:101334. doi: 10.1016/j.bbrep.2022.101334. eCollection 2022 Dec.

ABSTRACT

A major challenge in translating genomic variants of Tuberculosis (TB) into clinical implementation is to integrate the disease-associated variants and facilitate drug discovery through the concept of genomic-driven drug repurposing. Here, we utilized two established genomic databases, namely a Genome-Wide Association Study (GWAS) and a Phenome-Wide Association Study (PheWAS) to identify the genomic variants associated with TB disease and further utilize them for drug-targeted genes. We evaluated 3.425 genomic variants associated with TB disease which overlapped with 200 TB-associated genes. To prioritize the biological TB risk genes, we devised an in-silico pipeline and leveraged an established bioinformatics method based on six functional annotations (missense mutation, cis-eQTL, biological process, cellular component, molecular function, and KEGG molecular pathway analysis). Interestingly, based on the six functional annotations that we applied, we discovered that 14 biological TB risk genes are strongly linked to the deregulation of the biological TB risk genes. Hence, we demonstrated that 12 drug target genes overlapped with 40 drugs for other indications and further suggested that the drugs may be repurposed for the treatment of TB. We highlighted that CD44, CCR5, CXCR4, and C3 are highly promising proposed TB targets since they are connected to SELP and HLA-B, which are biological TB risk genes with high systemic scores on functional annotations. In sum, the current study shed light on the genomic variants involved in TB pathogenesis as the biological TB risk genes and provided empirical evidence that the genomics of TB may contribute to drug discovery.

PMID:36090591 | PMC:PMC9449755 | DOI:10.1016/j.bbrep.2022.101334

Infect Genet Evol. 2022 Sep 8:105361. doi: 10.1016/j.meegid.2022.105361. Online ahead of print.

NO ABSTRACT

PMID:36089457 | DOI:10.1016/j.meegid.2022.105361

J Infect. 2022 Sep 8:S0163-4453(22)00532-1. doi: 10.1016/j.jinf.2022.09.002. Online ahead of print.

NO ABSTRACT

PMID:36089103 | DOI:10.1016/j.jinf.2022.09.002

Curr Opin Chem Biol. 2022 Sep 7;71:102206. doi: 10.1016/j.cbpa.2022.102206. Online ahead of print.

ABSTRACT

Over the past decades, genome-wide association studies (GWAS) have led to a dramatic expansion of genetic variants implicated with human traits and diseases. These advances are expected to result in new drug targets but the identification of causal genes and the cell biology underlying human diseases from GWAS remains challenging. Here, we review protein interaction network-based methods to analyse GWAS data. These approaches can rank candidate drug targets at GWAS-associated loci or among interactors of disease genes without direct genetic support. These methods identify the cell biology affected in common across diseases, offering opportunities for drug repurposing, as well as be combined with expression data to identify focal tissues and cell types. Going forward, we expect that these methods will further improve from advances in the characterisation of context specific interaction networks and the joint analysis of rare and common genetic signals.

PMID:36087372 | DOI:10.1016/j.cbpa.2022.102206

Cell Discov. 2022 Sep 9;8(1):89. doi: 10.1038/s41421-022-00453-8.

ABSTRACT

Infection of human peripheral blood cells by SARS-CoV-2 has been debated because immune cells lack mRNA expression of both angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease type 2 (TMPRSS2). Herein we demonstrate that resting primary monocytes harbor abundant cytoplasmic ACE2 and TMPRSS2 protein and that circulating exosomes contain significant ACE2 protein. Upon ex vivo TLR4/7/8 stimulation, cytoplasmic ACE2 was quickly translocated to the monocyte cell surface independently of ACE2 transcription, while TMPRSS2 surface translocation occurred in conjunction with elevated mRNA expression. The rapid translocation of ACE2 to the monocyte cell surface was blocked by the endosomal trafficking inhibitor endosidin 2, suggesting that endosomal ACE2 could be derived from circulating ACE2-containing exosomes. TLR-stimulated monocytes concurrently expressing ACE2 and TMPRSS2 on the cell surface were efficiently infected by SARS-CoV-2, which was significantly mitigated by remdesivir, TMPRSS2 inhibitor camostat, and anti-ACE2 antibody. Mass cytometry showed that ACE2 surface translocation in peripheral myeloid cells from patients with severe COVID-19 correlated with its hyperactivation and PD-L1 expression. Collectively, TLR4/7/8-induced ACE2 translocation with TMPRSS2 expression makes circulating monocytes permissive to SARS-CoV-2 infection.

PMID:36085197 | DOI:10.1038/s41421-022-00453-8

Front Pharmacol. 2022 Aug 23;13:936758. doi: 10.3389/fphar.2022.936758. eCollection 2022.

ABSTRACT

Lung cancer is the leading cause of cancer deaths globally, and lung adenocarcinoma (LUAD) is the most common type of lung cancer. Gene dysregulation plays an essential role in the development of LUAD. Drug repositioning based on associations between drug target genes and LUAD target genes are useful to discover potential new drugs for the treatment of LUAD, while also reducing the monetary and time costs of new drug discovery and development. Here, we developed a pipeline based on machine learning to predict potential LUAD-related target genes through established graph attention networks (GATs). We then predicted potential drugs for the treatment of LUAD through gene coincidence-based and gene network distance-based methods. Using data from 535 LUAD tissue samples and 59 precancerous tissue samples from The Cancer Genome Atlas, 48,597 genes were identified and used for the prediction model building of the GAT. The GAT model achieved good predictive performance, with an area under the receiver operating characteristic curve of 0.90. 1,597 potential LUAD-related genes were identified from the GAT model. These LUAD-related genes were then used for drug repositioning. The gene overlap and network distance with the target genes were calculated for 3,070 drugs and 672 preclinical compounds approved by the US Food and Drug Administration. At which, bromoethylamine was predicted as a novel potential preclinical compound for the treatment of LUAD, and cimetidine and benzbromarone were predicted as potential therapeutic drugs for LUAD. The pipeline established in this study presents new approach for developing targeted therapies for LUAD.

PMID:36081949 | PMC:PMC9445420 | DOI:10.3389/fphar.2022.936758

Biomed Pharmacother. 2022 Sep 5;154:113663. doi: 10.1016/j.biopha.2022.113663. Online ahead of print.

ABSTRACT

The development of multidrug resistance (MDR) is one of the major challenges in the treatment of cancer which is caused by the overexpression of the ATP-binding cassette (ABC) transporters ABCB1 (P-glycoprotein) and/or ABCG2 (BCRP/MXR/ABCP) in cancer cells. These transporters are capable of reducing the efficacy of cytotoxic drugs by actively effluxing them out of cancer cells. Since there is currently no approved treatment for patients with multidrug-resistant tumors, the drug repurposing approach provides an alternative route to identify agents to reverse MDR mediated by ABCB1 and/or ABCG2 in multidrug-resistant cancer cells. WDR5-0103 is a histone H3 lysine 4 (H3K4) methyltransferase inhibitor that disrupts the interaction between the WD repeat-containing protein 5 (WDR5) and mixed-lineage leukemia (MLL) protein. In this study, the effect of WDR5-0103 on MDR mediated by ABCB1 and ABCG2 was determined. We found that in a concentration-dependent manner, WDR5-0103 could sensitize ABCB1- and ABCG2-overexpressing multidrug-resistant cancer cells to conventional cytotoxic drugs. Our results showed that WDR5-0103 reverses MDR and improves drug-induced apoptosis in multidrug-resistant cancer cells by inhibiting the drug-efflux function of ABCB1 and ABCG2, without altering the protein expression of ABCB1 or ABCG2. The potential sites of interactions of WDR5-0103 with the drug-binding pockets of ABCB1 and ABCG2 were predicted by molecular docking. In conclusion, the MDR reversal activity of WDR5-0103 demonstrated here indicates that it could be used in combination therapy to provide benefits to a subset of patients with tumor expressing high levels of ABCB1 or ABCG2.

PMID:36081287 | DOI:10.1016/j.biopha.2022.113663

Plants (Basel). 2022 Sep 2;11(17):2296. doi: 10.3390/plants11172296.

ABSTRACT

Zingiber officinale Roscoe (ginger) has long been used as an herbal medicine to treat various diseases, and its main sub-components, [6]-gingerol and [6]-shogaol, were also reported to have anti-inflammatory, anti-oxidant, and anti-tumor effects. However, their effects on various types of pain and their underlying mechanisms of action have not been clearly analyzed and understood yet. Thus, in this review, by analyzing 16 studies that used Z. officinale, [6]-gingerol, and [6]-shogaol on mechanical, spontaneous and thermal pain, their effects and mechanisms of action have been analyzed. Pain was induced by either nerve injury or chemical injections in rodents. Nine studies analyzed the analgesic effect of Z. officinale, and four and three studies focused on [6]-gingerol and [6]-shogaol, respectively. Seven papers have demonstrated the underlying mechanism of action of their analgesic effects. Studies have focused on the spinal cord and one on the dorsal root ganglion (DRG) neurons. Involvement and change in the function of serotonergic receptors (5-HT1A, B, D, and 5A), transient receptor potential vanilloid 1 (TRPV1), N-methyl-D-aspartate (NMDA) receptors, phosphorylated extracellular signal-regulated kinase 1/2 (pERK1/2), histone deacetylase 1 (HDAC1), voltage-gated sodium channel 1.8 (Nav1.8), substance P (SP), and sciatic nerve's morphology have been observed.

PMID:36079679 | DOI:10.3390/plants11172296

Int J Mol Sci. 2022 Aug 26;23(17):9666. doi: 10.3390/ijms23179666.

ABSTRACT

Identifying drug-target interactions is a crucial step in discovering novel drugs and for drug repositioning. Network-based methods have shown great potential thanks to the straightforward integration of information from different sources and the possibility of extracting novel information from the graph topology. However, despite recent advances, there is still an urgent need for efficient and robust prediction methods. Here, we present SimSpread, a novel method that combines network-based inference with chemical similarity. This method employs a tripartite drug-drug-target network constructed from protein-ligand interaction annotations and drug-drug chemical similarity on which a resource-spreading algorithm predicts potential biological targets for both known or failed drugs and novel compounds. We describe small molecules as vectors of similarity indices to other compounds, thereby providing a flexible means to explore diverse molecular representations. We show that our proposed method achieves high prediction performance through multiple cross-validation and time-split validation procedures over a series of datasets. In addition, we demonstrate that our method performed a balanced exploration of both chemical ligand space (scaffold hopping) and biological target space (target hopping). Our results suggest robust and balanced performance, and our method may be useful for predicting drug targets, virtual screening, and drug repositioning.

PMID:36077062 | DOI:10.3390/ijms23179666

Brain Res. 2022 Sep 5:148073. doi: 10.1016/j.brainres.2022.148073. Online ahead of print.

ABSTRACT

More than 30% of individuals with epilepsy are refractory to currently available drugs, highlighting the urgent need to develop novel candidate drugs. Accumulating evidence implicates the key role of ferroptosis in the pathophysiology of epileptic seizuresand its potential as a new drug target. Drug repurposing is a promising strategy for the rapid generation of new candidate drugs from the market drugs with new therapeutic indications, such as the best-selling drug thalidomide. Herein, we reported the discovery of Seratrodast, a market drug of thromboxane A2 receptor antagonist as a new ferroptosis inhibitor (IC50: 4.5 μmol·L-1). Seratrodast could reduce lipid ROS production, regulate the system xc-/glutathione (GSH)/glutathione peroxidase 4 (GPX4) axis, and inhibit JNK phosphorylation and p53 expression. In addition, Seratrodast elevated GXP4 expression and decreased JNK phosphorylation in pentylenetetrazole-induced seizures in mice. Seratrodast increased the latency of seizures and reduced seizure duration in pentylenetetrazole-induced seizures. Our results suggest Seratrodast might be either a ferroptosis inhibitor or a novel lead compound for further optimization of novel drug discovery.

PMID:36075466 | DOI:10.1016/j.brainres.2022.148073

Biochem Pharmacol. 2022 Sep 5:115239. doi: 10.1016/j.bcp.2022.115239. Online ahead of print.

ABSTRACT

Ferroptosis, first coined in 2012, is an iron-dependent regulated cell death (RCD) characterized by the accumulation of lipid peroxides to toxic levels. This mechanism is currently being evaluated as a target for a variety of diseases offering new opportunities for drug design and development. Recent reports uncovered acyl-CoA synthetase long-chain 4 (ACSL4) as a critical contributor to ferroptosis execution. Therefore, ACSL4 inhibitors are emerging as attractive anti-ferroptotic agents. Herein, we developed a robust screening cascade with orthogonal biophysical and biochemical techniques to identify original human ACSL4 inhibitors. By screening an FDA-approved drug library, we were able to identify and validate new inhibitors with micromolar-range activity against ACSL4. With an IC50 of 280 nM against hACSL4, antifungal agent sertaconazole is to our knowledge, the most potent ACSL4 inhibitor identified so far. In addition, sertaconazole significantly reduced lipid peroxidation and ferroptosis in human differentiated dopaminergic neurons (Lund human mesencephalic LUHMES cells), demonstrating that it is a valuable chemical tool for further investigating the role of ACSL4 in ferroptosis. This study highlights phenethyl-imidazole scaffold as a novel and promising starting point for the development of anti-ferroptotic agents targeting ACSL4.

PMID:36075462 | DOI:10.1016/j.bcp.2022.115239

J Enzyme Inhib Med Chem. 2022 Dec;37(1):2478-2488. doi: 10.1080/14756366.2022.2121393.

ABSTRACT

The mitochondrial isoforms VA/VB of metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1) are involved in metabolic processes, such as de novo lipogenesis and fatty acid biosynthesis. We review the drug design landscape for obtaining CA VA/VB-selective/effective inhibitors, starting from the clinical observations that CA inhibitory drugs, such as the antiepileptics topiramate and zonisamide, or the diuretic acetazolamide induce a significant weight loss. The main approaches for designing such compounds consisted in drug repurposing of already known CA inhibitors (CAIs); screening of synthetic/natural products libraries both in the classical and virtual modes, and de novo drug design using the tail approach. A number of such studies allowed the identification of lead compounds diverse from sulphonamides, such as tropolones, phenols, polyphenols, flavones, glycosides, fludarabine, lenvatinib, rufinamide, etc., for which the binding mode to the enzyme is not always well understood. Classical drug design studies of sulphonamides, sulfamates and sulfamides afforded low nanomolar mitochondrial CA-selective inhibitors, but detailed antiobesity studies were poorly performed with most of them. A breakthrough in the field may be constituted by the design of hybrids incorporating CAIs and other antiobesity chemotypes.

PMID:36073149 | DOI:10.1080/14756366.2022.2121393

Front Med (Lausanne). 2022 Aug 22;9:931860. doi: 10.3389/fmed.2022.931860. eCollection 2022.

ABSTRACT

Diseases originate at the molecular-genetic layer, manifest through altered biochemical homeostasis, and develop symptoms later. Hence, symptomatic diagnosis is inadequate to explain the underlying molecular-genetic abnormality and individual genomic disparities. The current trends include molecular-genetic information relying on algorithms to recognize the disease subtypes through gene expressions. Despite their disposition toward disease-specific heterogeneity and cross-disease homogeneity, a gap still exists in describing the extent of homogeneity within the heterogeneous subpopulation of different diseases. They are limited to obtaining the holistic sense of the whole genome-based diagnosis resulting in inaccurate diagnosis and subsequent management. Addressing those ambiguities, our proposed framework, ReDisX, introduces a unique classification system for the patients based on their genomic signatures. In this study, it is a scalable machine learning algorithm deployed to re-categorize the patients with rheumatoid arthritis and coronary artery disease. It reveals heterogeneous subpopulations within a disease and homogenous subpopulations across different diseases. Besides, it identifies granzyme B (GZMB) as a subpopulation-differentiation marker that plausibly serves as a prominent indicator for GZMB-targeted drug repurposing. The ReDisX framework offers a novel strategy to redefine disease diagnosis through characterizing personalized genomic signatures. It may rejuvenate the landscape of precision and personalized diagnosis and a clue to drug repurposing.

PMID:36072953 | PMC:PMC9441882 | DOI:10.3389/fmed.2022.931860