Drug Repositioning for Alzheimer's Disease Based on Systematic 'omics' Data Mining

Exploring the new horizons of drug repurposing: A vital tool for turning hard work into smart work

Drug discovery and development are long and financially taxing processes. On an average it takes 12-15 years and costs 1.2 billion USD for successful drug discovery and approval for clinical use. Many lead molecules are not developed further and their potential is not tapped to the fullest due to lack of resources or time constraints. In order for a drug to be approved by FDA for clinical use, it must have excellent therapeutic potential in the desired area of target with minimal toxicities as supported by both pre-clinical and clinical studies. The targeted clinical evaluations fail to explore other potential therapeutic applications of the candidate drug. Drug repurposing or repositioning is a fast and relatively cheap alternative to the lengthy and expensive de novo drug discovery and development. Drug repositioning utilizes the already available clinical trials data for toxicity and adverse effects, at the same time explores the drug's therapeutic potential for a different disease. This review addresses recent developments and future scope of drug repositioning strategy.

Insights into Computational Drug Repurposing for Neurodegenerative Disease

Computational drug repurposing has the ability to remarkably reduce drug development time and cost in an era where these factors are prohibitively high. Several examples of successful repurposed drugs exist in fields such as oncology, diabetes, leprosy, inflammatory bowel disease, among others, however computational drug repurposing in neurodegenerative disease has presented several unique challenges stemming from the lack of validation methods and difficulty in studying heterogenous diseases of aging. Here, we examine existing approaches to computational drug repurposing, including molecular, clinical, and biophysical methods, and propose data sources and methods to advance computational drug repurposing in neurodegenerative disease using Alzheimer's disease as an example.

Using What We Already Have: Uncovering New Drug Repurposing Strategies in Existing Omics Data

The promise of drug repurposing is to accelerate the translation of knowledge to treatment of human disease, bypassing common challenges associated with drug development to be more time- and cost-efficient. Repurposing has an increased chance of success due to the previous validation of drug safety and allows for the incorporation of omics. Hypothesis-generating omics processes inform drug repurposing decision-making methods on drug efficacy and toxicity. This review summarizes drug repurposing strategies and methodologies in the context of the following omics fields: genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, phenomics, pregomics, and personomics. While each omics field has specific strengths and limitations, incorporating omics into the drug repurposing landscape is integral to its success.

Technology and Dementia: The Future is Now

BACKGROUND

Technology has multiple potential applications to dementia from diagnosis and assessment to care delivery and supporting ageing in place.

OBJECTIVES

To summarise key areas of technology development in dementia and identify future directions and implications.

METHOD

Members of the US Alzheimer's Association Technology Professional Interest Area involved in delivering the annual pre-conference summarised existing knowledge on current and future technology developments in dementia.

RESULTS

The main domains of technology development are as follows: (i) diagnosis, assessment and monitoring, (ii) maintenance of functioning, (iii) leisure and activity, (iv) caregiving and management.

CONCLUSIONS

The pace of technology development requires urgent policy, funding and practice change, away from a narrow medical approach, to a holistic model that facilitates future risk reduction and prevention strategies, enables earlier detection and supports implementation at scale for a meaningful and fulfilling life with dementia.

Review of Current Strategies for Delivering Alzheimer's Disease Drugs across the Blood-Brain Barrier

Effective therapy for Alzheimer’s disease is a major challenge in the pharmaceutical sciences. There are six FDA approved drugs (e.g., donepezil, memantine) that show some effectiveness; however, they only relieve symptoms. Two factors hamper research. First, the cause of Alzheimer’s disease is not fully understood. Second, the blood-brain barrier restricts drug efficacy. This review summarized current knowledge relevant to both of these factors. First, we reviewed the pathophysiology of Alzheimer’s disease. Next, we reviewed the structural and biological properties of the blood-brain barrier. We then described the most promising drug delivery systems that have been developed in recent years; these include polymeric nanoparticles, liposomes, metallic nanoparticles and cyclodextrins. Overall, we aim to provide ideas and clues to design effective drug delivery systems for penetrating the blood-brain barrier to treat Alzheimer’s disease.

Interactions of Selective Serotonin Reuptake Inhibitors with β-Amyloid

Treating Alzheimer's disease (AD) is a major challenge at the moment with no new drugs available to cure this devastating neurodegenerative disorder. In this regard, drug repurposing, which aims to determine novel therapeutic usage for drugs already approved by the regulatory agencies, is a pragmatic approach to discover novel treatment strategies. Selective serotonin reuptake inhibitors (SSRIs) are a known class of United States Food and Drug Administration approved drugs used in the treatment of depression. We investigated the ability of SSRIs fluvoxamine, fluoxetine, paroxetine, sertraline, and escitalopram on Aβ42 aggregation and fibrillogenesis. Remarkably, the aggregation kinetic experiments carried out demonstrate the anti-Aβ42 aggregation activity of SSRIs fluoxetine, paroxetine, and sertraline at all the tested concentrations (1, 10, 50, and 100 μM). Both fluoxetine and paroxetine were identified as the most promising SSRIs, showing 74.8 and 76% inhibition of Aβ42 aggregation at 100 μM. The transmission electron microscopy experiments and dot-blot study also demonstrate the ability of fluoxetine and paroxetine to prevent Aβ42 aggregation and fibrillogenesis, providing further evidence. Investigating the binding interactions of fluoxetine and paroxetine in the Aβ42 oligomer and fibril models derived from the solid-state NMR structure suggests that these SSRIs interact at a region close to the N-terminal (Lys16-Glu22) in the S-shaped cross-β-strand assembly and reduce Aβ42 fibrillogenesis. On the basis of this study, a pharmacophore model is proposed which shows that the minimum structural requirements to design novel Aβ42 aggregation inhibitors include the presence of one ionizable group, one hydrophobic group, two aromatic rings, and two hydrogen bond donor groups. These studies demonstrate that SSRIs have the potential to prevent Aβ42 aggregation by direct binding and could be beneficial to AD patients on SSRIs.

Niclosamide alleviates pulmonary fibrosis in vitro and in vivo by attenuation of epithelial-to-mesenchymal transition, matrix proteins & Wnt/β-catenin signaling: A drug repurposing study

Drug repurposing off late has been emerging as an inspiring alternative approach to conventional, exhaustive and arduous process of drug discovery. It is a process of identifying new therapeutic values for a drug already established for the treatment of a certain condition. Our current study is aimed at repurposing the old anti-helimenthic drug Niclosamide as an anti-fibrotic drug against pulmonary fibrosis (PF). PF is most common lethal interstitial lung disease hallmarked by deposition of extracelluar matrix and scarring of lung. Heterogenous nature, untimely diagnosis and lack of appropriate treatment options make PF an inexorable lung disorder. Prevailing void in PF treatment and drug repositioning strategy of drugs kindled our interest to demonstrate the anti-fibrotic activity of Niclosamide. Our study is aimed at investigating the anti-fibrotic potential of Niclosamide in TGF-β1 induced in vitro model of PF and 21-day model of Bleomycin induced PF in vivo respectively. Our study results showed that Niclosamide holds the potential to exert anti-fibrotic effect by hampering fibroblast migration, attenuating EMT, inhibiting fibrotic signaling and by regulating WNT/β-catenin signaling as evident from protein expression studies. Our study findings can give new directions to development of Niclosamide as an anti-fibrotic agent for treatment of pulmonary fibrosis.

Review of Drug Repositioning Approaches and Resources

Drug discovery is a time-consuming, high-investment, and high-risk process in traditional drug development. Drug repositioning has become a popular strategy in recent years. Different from traditional drug development strategies, the strategy is efficient, economical and riskless. There are usually three kinds of approaches: computational approaches, biological experimental approaches, and mixed approaches, all of which are widely used in drug repositioning. In this paper, we reviewed computational approaches and highlighted their characteristics to provide references for researchers to develop more powerful approaches. At the same time, the important findings obtained using these approaches are listed. Furthermore, we summarized 76 important resources about drug repositioning. Finally, challenges and opportunities in drug repositioning are discussed from multiple perspectives, including technology, commercial models, patents and investment.

Multimodal imaging-based therapeutic fingerprints for optimizing personalized interventions: Application to neurodegeneration

Personalized Medicine (PM) seeks to assist the patients according to their specific treatment needs and potential intervention responses. However, in the neurological context, this approach is limited by crucial methodological challenges, such as the requirement for an understanding of the causal disease mechanisms and the inability to predict the brain's response to therapeutic interventions. Here, we introduce and validate the concept of the personalized Therapeutic Intervention Fingerprint (pTIF), which predicts the effectiveness of potential interventions for controlling a patient's disease evolution. Each subject's pTIF can be inferred from multimodal longitudinal imaging (e.g. amyloid-β, metabolic and tau PET; vascular, functional and structural MRI). We studied an aging population (N = 331) comprising cognitively normal and neurodegenerative patients, longitudinally scanned using six different neuroimaging modalities. We found that the resulting pTIF vastly outperforms cognitive and clinical evaluations on predicting individual variability in gene expression (GE) profiles. Furthermore, after regrouping the patients according to their predicted primary single-target interventions, we observed that these pTIF-based subgroups present distinctively altered molecular pathway signatures, supporting the across-population identification of dissimilar pathological stages, in active correspondence with different therapeutic needs. The results further evidence the imprecision of using broad clinical categories for understanding individual molecular alterations and selecting appropriate therapeutic needs. To our knowledge, this is the first study highlighting the direct link between multifactorial brain dynamics, predicted treatment responses, and molecular alterations at the patient level. Inspired by the principles of PM, the proposed pTIF framework is a promising step towards biomarker-driven assisted therapeutic interventions, with additional important implications for selective enrollment of patients in clinical trials.

Application of Ferulic Acid for Alzheimer's Disease: Combination of Text Mining and Experimental Validation

Alzheimer's disease (AD) is an increasing concern in human health. Despite significant research, highly effective drugs to treat AD are lacking. The present study describes the text mining process to identify drug candidates from a traditional Chinese medicine (TCM) database, along with associated protein target mechanisms. We carried out text mining to identify literatures that referenced both AD and TCM and focused on identifying compounds and protein targets of interest. After targeting one potential TCM candidate, corresponding protein-protein interaction (PPI) networks were assembled in STRING to decipher the most possible mechanism of action. This was followed by validation using Western blot and co-immunoprecipitation in an AD cell model. The text mining strategy using a vast amount of AD-related literature and the TCM database identified curcumin, whose major component was ferulic acid (FA). This was used as a key candidate compound for further study. Using the top calculated interaction score in STRING, BACE1 and MMP2 were implicated in the activity of FA in AD. Exposure of SHSY5Y-APP cells to FA resulted in the decrease in expression levels of BACE-1 and APP, while the expression of MMP-2 and MMP-9 increased in a dose-dependent manner. This suggests that FA induced BACE1 and MMP2 pathways maybe novel potential mechanisms involved in AD. The text mining of literature and TCM database related to AD suggested FA as a promising TCM ingredient for the treatment of AD. Potential mechanisms interconnected and integrated with Aβ aggregation inhibition and extracellular matrix remodeling underlying the activity of FA were identified using in vitro studies.

PregOMICS-Leveraging systems biology and bioinformatics for drug repurposing in maternal-child health

Obstetric diseases remain underserved and understudied. Drug repurposing-utilization of a drug whose use is accepted in one condition for a different condition-could represent a rapid and low-cost way to identify new therapies that are known to be safe. In diseases of pregnancy, the known safety profile is a strong additional incentive. We describe the techniques and steps used in the use of 'omics data for drug repurposing. We illustrate these techniques using case studies of published drug repurposing projects. We provide a set of available databases with low barriers to entry which investigators can use to perform their own projects. The promise of 'omics techniques is unbiased screening, either of all drug targets or of all patients using particular drugs to find which are likely to alter disease risk or progression. However, we caution that reproducibility across the underlying studies, and thus the drugs suggested for repurposing, can be poor. We suggest that improved nosology, for example correlating patient clinical conditions with placental pathology, could yield more robust associations. We conclude that 'omics-driven drug repurposing represents a potential fruitful path to discover new, safe treatments of obstetric diseases.

Pulmonary arterial hypertension - progress in understanding the disease and prioritizing strategies for drug development

Pulmonary arterial hypertension (PAH), at one time a largely overlooked disease, is now the subject of intense study in many academic and biotech groups. The availability of new treatments has increased awareness of the condition. This in turn has driven a change in the demographics of PAH, with an increase in the mean age at diagnosis. The diagnosis of PAH in more elderly patients has highlighted the need for careful phenotyping of patients and for further studies to understand how best to manage pulmonary hypertension associated with, for example, left heart disease. The breadth and depth of expertise focused on unravelling the molecular pathology of PAH has yielded novel insights, including the role of growth factors, inflammation and metabolic remodelling. The description of the genetic architecture of PAH is accelerating in parallel, with novel variants, such as those reported in potassium two-pore domain channel subfamily K member 3 (KCNK3), adding to the list of more established mutations in genes associated with bone morphogenetic protein receptor type 2 (BMPR2) signalling. These insights have supported a paradigm shift in treatment strategies away from simply addressing the imbalance of vasoactive mediators observed in PAH towards tackling more directly the structural remodelling of the pulmonary vasculature. Here, we summarize the changing clinical and molecular landscape of PAH. We highlight novel drug therapies that are in various stages of clinical development, targeting for example cell proliferation, metabolic, inflammatory/immune and BMPR2 dysfunction, and the challenges around developing these treatments. We argue that advances in the treatment of PAH will come through deep molecular phenotyping with the integration of clinical, genomic, transcriptomic, proteomic and metabolomic information in large populations of patients through international collaboration. This approach provides the best opportunity for identifying key signalling pathways, both as potential drug targets and as biomarkers for patient selection. The expectation is that together these will enable the prioritization of potential therapies in development and the evolution of personalized medicine for PAH.