Explaining predictions for drug repositioning with biological knowledge graphs is a challenging problem. Graph completion methods using symbolic reasoning predict drug treatments and associated rules to generate evidence representing the therapeutic basis of the drug. Yet the vast amounts of generated paths that are biologically irrelevant or not mechanistically meaningful within the context of disease biology can limit utility. We use a reinforcement learning based knowledge graph completion model combined with an automatic filtering approach that produces the most relevant rules and biological paths explaining the predicted drug’s therapeutic connection to the disease. In this work we validate the approach against preclinical experimental data for Fragile X syndrome demonstrating strong correlation between automatically extracted paths and experimentally derived transcriptional changes of selected genes and pathways of drug predictions Sulindac and Ibudilast. Additionally, we show it reduces the number of generated paths in two case studies, 85% for Cystic fibrosis and 95% for Parkinson’s disease.

Background: The hippocampus mediates the acquisition of spatial memory, but the memory trace is eventually transferred to the cortex. We have investigated transcriptional activation of pathways related to cognitive function in the cortex of the aged mouse by analyzing gene expression following water maze training. Results: We identified genes that were differentially responsive in aged mice with accurate spatial performance during probe trials or repeated swimming sessions, relative to home cage conditions. Effective learners exhibited significantly greater activation of several pathways, such as the mitogen-activated protein kinase and insulin receptor signaling pathways, relative to swimmers. The genes encoding activity-related cytoskeletal protein (Arc) and brain-derived neurotrophic factor (BDNF) were upregulated in proficient learners, relative to swimmers and home cage controls, while the gene encoding Rho GTPase activating protein 32 (GRIT) was downregulated. We explored the regulation of Arc, BDNF, and GRIT expression in greater morphological detail using in situ hybridization. Recall during probe trials enhanced Arc expression across multiple cortical regions involved in the cognitive component of water maze learning, while BDNF expression was more homogeneously upregulated across cortical regions involved in the associational and sensorimotor aspects of water maze training. In contrast, levels of GRIT expression were uniformly reduced across all cortical regions examined. Conclusions: These results suggest that cortical gene transcription is responsive to learning in aged mice that exhibit behavioral proficiency, and support a distributed hypothesis of memory storage across multiple cortical compartments.

Sporadic Alzheimer’s disease (sAD) represents a serious and growing worldwide economic and healthcare burden. Almost 95% of current AD patients are associated with sAD as opposed to patients presenting with well-characterized genetic mutations that lead to AD predisposition, i.e., familial AD (fAD). Presently, the use of transgenic (Tg) animals overexpressing human versions of these causative fAD genes represents the dominant research model for AD therapeutic development. As significant differences in etiology exist between sAD and fAD, it is perhaps more appropriate to develop novel, more sAD-reminiscent experimental models that would expedite the discovery of effective therapies for the majority of AD patients. Here we present the oDGal mouse model, a novel model of sAD that displays a range of AD-like pathologies as well as multiple cognitive deficits reminiscent of AD symptomology. Hippocampal cognitive impairment and pathology were delayed with N-acetyl-cysteine (NaC) treatment, which strongly suggests that reactive oxygen species (ROS) are the drivers of downstream pathologies such as elevated amyloid beta and hyperphosphorylated tau. These features demonstrate a desired pathophenotype that distinguishes our model from current transgenic rodent AD models. A preclinical model that presents a phenotype of non-genetic AD-like pathologies and cognitive deficits would benefit the sAD field, particularly when translating therapeutics from the preclinical to the clinical phase.

Fragile X syndrome is a neurodevelopmental disorder caused by silencing of the fragile X messenger ribonucleotide gene. Patients display a wide spectrum of symptoms ranging from intellectual and learning disabilities to behavioural challenges including autism spectrum disorder. In addition to this, patients also display a diversity of symptoms due to mosaicism. These factors make fragile X syndrome a difficult syndrome to manage and suggest that a single targeted therapeutic approach cannot address all the symptoms. To this end, we utilized Healx’s data-driven drug discovery platform to identify a treatment strategy to address the wide range of diverse symptoms among patients. Computational methods identified the combination of ibudilast and gaboxadol as a treatment for several pathophysiological targets that could potentially reverse multiple symptoms associated with fragile X syndrome. Ibudilast is an approved broad-spectrum phosphodiesterase inhibitor, selective against both phosphodiesterase 4 and phosphodiesterase 10, and has demonstrated to have several beneficial effects in the brain. Gaboxadol is a GABA_A receptor agonist, selective against the delta subunit, which has previously displayed encouraging results in a fragile X syndrome clinical trial. Alterations in GABA and cyclic adenosine monophosphate metabolism have long since been associated with the pathophysiology of fragile X syndrome; however, targeting both pathways simultaneously has never been investigated. Both drugs have a good safety and tolerability profile in the clinic making them attractive candidates for repurposing. We set out to explore whether the combination of ibudilast and gaboxadol could demonstrate therapeutic efficacy in a fragile X syndrome mouse model. We found that daily treatment with ibudilast significantly enhanced the ability of fragile X syndrome mice to perform a number of different cognitive assays while gaboxadol treatment improved behaviours such as hyperactivity, aggression, stereotypy and anxiety. Importantly, when ibudilast and gaboxadol were co-administered, the cognitive deficits as well as the aforementioned behaviours were rescued. Moreover, this combination treatment showed no evidence of tolerance, and no adverse effects were reported following chronic dosing. This work demonstrates for the first time that by targeting multiple pathways, with a combination treatment, we were able to rescue more phenotypes in a fragile X syndrome mouse model than either ibudilast or gaboxadol could achieve as monotherapies. This combination treatment approach holds promise for addressing the wide spectrum of diverse symptoms in this heterogeneous patient population and may have therapeutic potential for idiopathic autism.