Report on Prasad et al. (2021), Brain Disease Network Analysis to Elucidate the Neurological Manifestations of COVID-19

The twenty-first century has brought massive and sweeping changes in the field of neuroscience and the specializations that are under it. One of the most important concepts that have been established is how gene expression in the human neuron is altered by the physiologic and pathologic conditions that the human body is subjected to. The concept of gene expression dictating the cellular mechanisms is, in essence, genotype coding for the phenotype. This is true for pluripotent stem cells as much as it is true for cells that are in the terminal configuration and no longer undergo the cell cycle.

One of the timeliest applications for the role of changes in gene expression and its role in functional and structural changes in the brain is how the presence of certain proteins are more abundant in patients with neurologic manifestation of COVID-19 versus in normal controls. The work of Prasad et al. (2021) showed how certain proteins that are specific to the brain can develop protein-protein interaction with an identified 332 human genes and the other genes in their interaction network. This study gained insight from the work of Gordon, et al. (2020) which provided an interaction map for proteins that are involved in COVID-19 symptomatology to investigate drug repurposing for treatment.

The concept of brain-specific protein-protein interaction allowed for the establishment of the project that establishes the network for COVID-19 target genes. The project utilized the TissueNet v.2 database that generated 165,240 interactions. The TissueNet provided RNA-Seq and protein-based assay information that has been taken from the genotype-tissue expression project (GTEX) and correlated with the human protein atlas (HPA). Although certain protein-protein interactions are only at the theoretical, several experimentally validated protein interaction information were provided and this was compared with the 332 genes of humans that were documented to have COVID-19 interaction.

It is important to emphasize that identified genes may be in existence in the human brain in normal conditions and an increase or a decrease in their expression may be indicative of or contributory to the manifestation of the pathology. In this regard, other structures in the peripheral nervous system or outside of the nervous system may also express these genes but in a much more regulated manner or they may be expressed normally at a particular level in tissues outside of the human nervous system but the expression in the nervous system may indicate a disease-condition.

Furthermore, identification of the genes and their neighboring interaction, the protein-to-protein interaction that such relationships establish, and whether or not one part of the pair in the interaction or both are expressed aberrantly, serve the larger purpose of identifying existing brain-related disorders that have been reported in the past to harbor the combination of gene interaction.

For the research of Prasad et al. (2021) the Gene ORGANizer database was used and such database utilized the curated datasets from DisGeNET and human phenotype ontology (HPO). Evaluation of the specific disease-gene interaction was necessary to confirm the interaction that was established using the datasets. There were 2002 disease-gene interactions that were specific to the brain and these had 127 identifiable brain disorders. However, in the 2002 disease-gene interaction, only 653 genes were considered as valid for investigation for the 127 brain disorders. Among the 653 genes, 43 were the direct target of COVID-19. To specifically detect importance of the interactions, the COVID-19 target genes were divided into interaction and nearest neighbor groups, and labeled as modules. The modules have a specific pathway of involvement and these have a functional impact on the manifestation of COVID-19 as well as other diseases that it may be related to.

The modules underwent further analysis in terms of function and it was shown that Module-1 contributes to RNA splicing, mRNA processing, protein complex biogenesis and assembly. Moreover, the study of the regulatory elements and pathways related to apoptosis showed the role of Module-1 in proteolysis, ribosome pathway, spliceosome pathway, in Huntington’s disease pathway, and cancer pathways. Other conditions that were identified in the evaluation includes ataxia, dysarthria, spasticity, encephalopathy, coma, and delayed speech and language development among others.

In comparison, the analysis of Module-2 showed that the genes contribute to macromolecular complex assembly, negative regulation of gene expression, RNA transport, and localization. Moreover, they also have a contribution in spliceosome, ribosome, cell cycle, gliomas, pathways in cancer, and RIG-I like receptor signaling pathways. In terms of disease-condition, they have been documented in hydrocephalus, dementia, autism, muscular dystrophy, language impairment, and frontotemporal dementia.

Module-3, on the other hand, also contain genes that have a role in RNA splicing, cell division, mRNA processing, spindle assembly, and nuclear division-related biological process. In terms of their pathway interaction, the module has a role in Notch signaling pathways, Toll-like receptor signaling pathways, and SNARE interaction in vesicular transport. The genes in this module have been reported in ataxia, sleep apnea, leukodystrophy, cerebral ataxia, and Joubert syndrome.

Interestingly, although some functions, pathways, and diseases overlap, the modules have specific conditions to themselves. In the case of Module-4, the involved function includes RNA processing, translational elongation, ncRNA processing, and in the viral infection cycle. The role in the viral infection cycle is much more contributory in terms of viruses triggering specific gene expression response. The pathways that they are involved in includes NOD-like receptor signaling pathways, Parkinson’s disease, Huntington’s disease, and Cytosolic DNA sensing pathways. Ataxia, spasticity, amyotrophic lateral sclerosis, chorea, and auditory neuropathy are among the diseases where the genes in the module have been reported.

Lastly, Module-5 showed that it plays a role in the regulation of transcription from RNA polymerase II promoter, chromatin modification, regulation of transcription, and in cellular protein catabolic process.  In terms of the pathways, it has shown involvement in the Wnt signaling pathways, viral reproduction, MAPK signaling pathway, neurotrophin signaling pathway, TGF-beta signaling pathway, and ErbB signaling pathway. Disease-conditions such as ataxia, myopathy, Chiari malformation, GAIT ataxia, limb ataxia, and febrile seizures have reported the presence of the genes in this module.

The research reports that early SARS-CoV-2 infection involved these modules such that the virus hijacks the cellular and extracellular interaction where these modules are involved in and utilize the genes for its own RNA synthesis. It may be hypothesized that, because the genes are associated with ataxia, spasticity, encephalopathy, and dementia, the patients who contract COVID-19 may have a higher risk of manifesting these clinical conditions. However, it must be emphasized that association is not correlation and that putative correlation is not necessarily causation.

The purpose of identifying gene expression and protein-protein interaction with their associated clinical manifestations is to enable drug repurposing for targeted treatment and to hamper the cytopathic changes caused by the virus and the immune response of the human body that is due to the presence of the virus. Evaluation of potential targets showed that FDA approved drugs, fulvestrant, tamoxifen, raloxifene, estradiol, ethinylestradiol may have potential for targeting the ESR1 gene, which is one of the five key genes that were identified as useable for drug repurposing. TP53 is also one of the five genes that were identified and the drugs that were candidates for repurposing to target this gene included anti-cancer drugs. Moreover, MYC gene was also detected and showed interaction with imatinib which is tyrosine-kinase inhibitor. The identified gene HSP90AA1 showed interaction with rifabutin, which is an antimicrobial drug for Mycobacterium avium-intracellulare.

The difficulty with utilizing the identified genes to determine the drugs for repurposing is not necessarily on whether the existing medications may genuinely work. The problem in this situation is deploying further studies to determine its efficacy based on empirical evidence and this has to be done at the level of the tissue culture that contains the SARS-CoV-2 virus. Future hurdles into the use of the identified drugs include animal testing to determine actual in-vivo performance and to have an idea on the effective dose based on in-vivo testing. Evaluation of the organs of those that underwent animal testing should be done using microscopy to establish a phenotype of the injury and to determine the effects of the repurposed drug visually as cellular changes pertaining to disease involvement. Animal testing may also be used as an early indicator of the effective dose that did not appear to have significant adverse effect to the animals who received the treatment. However, the adverse event should not be limited to documenting the number of animals who because of the drug. It is equally important to evaluate whether the internal organs of the animal subjects show inflammatory response, viremia, or drug- related toxicity that manifested as multi-organ failure. Success in the laboratory testing and animal testing may push the drug being repurposed to the actual phases of human clinical trials to determine how much the conceptual analysis will translate to an effective drug-repurposing protocol.

The role of gene expression in determining disease phenotype and finding the appropriate drug to treat the condition may be severely circuitous and may not necessarily lead to a functional treatment protocol. However, much of the options that can be provided for in the future, may it be related to COVID-19 treatment or other diseases, would not have been possible without the contribution of the exhaustive analytical processes that allowed establishing the interaction of genes and diseases to find a clinically significant solution.