Identifying novel candidate compounds for therapeutic strategies in retinopathy of prematurity via computational drug-gene association analysis.

Purpose: Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness worldwide. Although interventions such as anti-VEGF and laser have high success rates in treating severe ROP, current treatment and preventative strategies still have their limitations. Thus, we aim to identify drugs and chemicals for ROP with comprehensive safety profiles and tolerability using a computational bioinformatics approach. Methods: We generated a list of genes associated with ROP to date by querying PubMed Gene which draws from animal models, human studies, and genomic studies in the NCBI database. Gene enrichment analysis was performed on the ROP gene list with the ToppGene program which draws from multiple drug-gene interaction databases to predict compounds with significant associations to the ROP gene list. Compounds with significant toxicities or without known clinical indications were filtered out from the final drug list. Results: The NCBI query identified 47 ROP genes with pharmacologic annotations present in ToppGene. Enrichment analysis revealed multiple drugs and chemical compounds related to the ROP gene list. The top ten most significant compounds associated with ROP include ascorbic acid, simvastatin, acetylcysteine, niacin, castor oil, penicillamine, curcumin, losartan, capsaicin, and metformin. Antioxidants, NSAIDs, antihypertensives, and anti-diabetics are the most common top drug classes derived from this analysis, and many of these compounds have potential to be readily repurposed for ROP as new prevention and treatment strategies. Conclusion: This bioinformatics analysis creates an unbiased approach for drug discovery by identifying compounds associated to the known genes and pathways of ROP. While predictions from bioinformatic studies require preclinical/clinical studies to validate their results, this technique could certainly guide future investigations for pathologies like ROP.

Using Advanced Bioinformatics Tools to Identify Novel Therapeutic Candidates for Proliferative Vitreoretinopathy.

Purpose: Proliferative vitreoretinopathy (PVR) is the dreaded cause of failure following retinal detachment repair; however, no cures or preventative therapies exist to date. The purpose of this study was to use bioinformatics tools to identify drugs or compounds that interact with biomarkers and pathways involved in PVR pathogenesis that could be eligible for further testing for the prevention and treatment of PVR. Methods: We queried PubMed to compile a comprehensive list of genes described in PVR to date from human studies, animal models, and genomic studies found in the National Center for Biotechnology Information database. Gene enrichment analysis was performed using ToppGene on PVR-related genes against drug-gene interaction databases to construct a pharmacome and estimate the statistical significance of overrepresented compounds. Compounds with no clinical indications were filtered out from the resulting drug lists. Results: Our query identified 34 unique genes associated with PVR. Out of 77,146 candidate drugs or compounds in the drug databases, our analysis revealed multiple drugs and compounds that have significant interactions with genes involved in PVR, including antiproliferatives, corticosteroids, cardiovascular agents, antioxidants, statins, and micronutrients. Top compounds, including curcumin, statins, and cardiovascular agents such as carvedilol and enalapril, have well-established safety profiles and potentially could be readily repurposed for PVR. Other significant compounds such as prednisone and methotrexate have shown promising results in ongoing clinical trials for PVR. Conclusions: This bioinformatics approach of studying drug-gene interactions can identify drugs that may affect genes and pathways implicated in PVR. Predicted bioinformatics studies require further validation by preclinical or clinical studies; however, this unbiased approach could identify potential candidates among existing drugs and compounds that could be repurposed for PVR and guide future investigations. Translational Relevance: Novel repurposable drug therapies for PVR can be found using advanced bioinformatics models.

Using Advanced Bioinformatics Tools to Identify Novel Therapeutic Candidates for Age-Related Macular Degeneration.

Purpose: Age-related macular degeneration (AMD) is the most common cause of aging-related blindness in the developing world. Although medications can slow progressive wet AMD, currently, no drugs to treat dry-AMD are available. We use a systems or in silico biology analysis to identify chemicals and drugs approved by the Food and Drug Administration for other indications that can be used to treat and prevent AMD. Methods: We queried National Center for Biotechnology Information to identify genes associated with AMD, wet AMD, dry AMD, intermediate AMD, and geographic atrophy to date. We combined genes from various AMD subtypes to reflect distinct stages of disease. Enrichment analysis using the ToppGene platform predicted molecules that can influence AMD genes. Compounds without clinical indications or with deleterious effects were manually filtered. Results: We identified several drug/chemical classes that can affect multiple genes involved in AMD. The drugs predicted from this analysis include antidiabetics, lipid-lowering agents, and antioxidants, which could theoretically be repurposed for AMD. Metformin was identified as the drug with the strongest association with wet AMD genes and is among the top candidates in all dry AMD subtypes. Curcumin, statins, and antioxidants are also among the top drugs correlating with AMD-risk genes. Conclusions: We use a systematic computational process to discover potential therapeutic targets for AMD. Our systematic and unbiased approach can be used to guide targeted preclinical/clinical studies for AMD and other ocular diseases. Translational Relevance: Advanced bioinformatics models identify novel chemicals and approved drug candidates that can be efficacious for different subtypes of AMD.

Mitoautophagy: A Unique Self-Destructive Path Mitochondria of Upper Motor Neurons With TDP-43 Pathology Take, Very Early in ALS.

Mitochondrial dysfunction is one of the converging paths for many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), and TDP-43 pathology is the most common proteinopathy detected in ALS and ALS/Frontotemporal lobar degeneration (ALS/FTLD). We recently identified mitochondrial problems in corticospinal motor neurons (CSMN) and in Betz cells of patients with TDP-43 pathology. However, the timing and the extent of mitochondrial defects, and their mode of degeneration have not been revealed. Because it is important to reveal when problems first begin to emerge and whether they are shared or unique, we investigated the health and integrity of mitochondria in CSMN of prpTDP-43A315T, PFN1G118V, and hSOD1G93A mice at P15 (post-natal day 15)-a very early age in mice without any sign of cellular degeneration.Utilization of immuno-coupled electron microscopy for a detailed surveillance of mitochondria in CSMN and other non-CSMN cells revealed presence of a novel self-destructive path of mitochondrial degeneration, which we named mitoautophagy. Mitoauthopgy is different from mitophagy, as it does not require autophagosome-mediated degradation. In contrast, in this novel path, mitochondria can clear themselves independently. We find that even at this early age, all diseased CSMN begin to display mitochondrial defects, whereas mitochondria in non-CSMN cells are healthy. Our findings not only reveal mitoautophagy as a novel path of mitochondrial clearance that occurs prior to neuronal vulnerability, but it also highlights that it is present mainly in the upper motor neurons of prpTDP-43A315T and PFN1G118V mice, which mimic many aspects of the disease in patients with TDP-43 pathology.

MCP1-CCR2 and neuroinflammation in the ALS motor cortex with TDP-43 pathology.

BACKGROUND: The involvement of non-neuronal cells and the cells of innate immunity has been attributed to the initiation and progression of ALS. TDP-43 pathology is observed in a broad spectrum of ALS cases and is one of the most commonly shared pathologies. The potential involvement of the neuroimmune axis in the motor cortex of ALS patients with TDP-43 pathology needs to be revealed. This information is vital for building effective treatment strategies. METHODS: We investigated the presence of astrogliosis and microgliosis in the motor cortex of ALS patients with TDP-43 pathology. prpTDP-43A315T-UeGFP mice, corticospinal motor neuron (CSMN) reporter line with TDP-43 pathology, are utilized to reveal the timing and extent of neuroimmune interactions and the involvement of non-neuronal cells to neurodegeneration. Electron microscopy and immunolabeling techniques are used to mark and monitor cells of interest. RESULTS: We detected both activated astrocytes and microglia, especially rod-like microglia, in the motor cortex of patients and TDP-43 mouse model. Besides, CCR2+ TMEM119- infiltrating monocytes were detected as they penetrate the brain parenchyma. Interestingly, Betz cells, which normally do not express MCP1, were marked with high levels of MCP1 expression when diseased. CONCLUSIONS: There is an early contribution of a neuroinflammatory response for upper motor neuron (UMN) degeneration with respect to TDP-43 pathology, and MCP1-CCR2 signaling is important for the recognition of diseased upper motor neurons by infiltrating monocytes. The findings are conserved among species and are observed in both ALS and ALS-FTLD patients.