1. Academic Validation
  2. Repurposing ibudilast to mitigate Alzheimer's disease by targeting inflammation

Repurposing ibudilast to mitigate Alzheimer's disease by targeting inflammation

  • Brain. 2022 Apr 12;awac136. doi: 10.1093/brain/awac136.
Giovanni Oliveros 1 Charles H Wallace 1 Osama Chaudry 2 Qiao Liu 3 Yue Qiu 4 Lei Xie 3 4 5 6 Patricia Rockwell 1 2 Maria E Figueiredo-Pereira 1 2 Peter A Serrano 1 7
Affiliations

Affiliations

  • 1 Program in Biochemistry, The Graduate Center, CUNY, 365 5th Ave, New York, NY 10016, USA.
  • 2 Department of Biological Sciences, Hunter College, 695 Park Ave, New York, NY 10065, USA.
  • 3 Department of Computer Science, Hunter College, 695 Park Ave, New York, NY 10065, USA.
  • 4 Program in Biology, The Graduate Center, CUNY, 365 5th Ave, New York, NY 10016, USA.
  • 5 Program in Computer Science and Biochemistry, The Graduate Center, 365 5th Ave, New York NY 10016, USA.
  • 6 Department of Psychology, Hunter College, 695 Park Ave, New York, NY 10065, USA.
  • 7 Helen and Robert Appel Alzheimer's disease Research Institute, Feil Family Brain & Mind Research Institute, Weill Cornell Medicine, Cornell University, 411 E 69th St, New York, NY 10021, USA.
Abstract

Alzheimer's disease is a multifactorial disease that exhibits cognitive deficits, neuronal loss, amyloid plaques, neurofibrillary tangles and neuroinflammation in the brain. Hence, a multi-target drug would improve treatment efficacy. We applied a new multi-scale predictive modeling framework that integrates machine learning with biophysics and systems pharmacology to screen drugs for Alzheimer's disease using patient's tissue samples. Our predictive modeling framework identified ibudilast as a drug with repurposing potential to treat Alzheimer's disease. Ibudilast is a multi-target drug, as it is a phosphodiesterase inhibitor and Toll-like Receptor 4 (TLR4) antagonist. In addition, we predict that ibudilast inhibits off-target kinases (e.g. IRAK1 and GSG2). In Japan and Other Asian countries, ibudilast is approved for treating asthma and stroke due to its anti-inflammatory potential. Based on these previous studies and on our predictions, we tested for the first time the efficacy of ibudilast in Fisher transgenic 344-AD rats. This transgenic rat model is unique as it exhibits hippocampal-dependent spatial learning and memory deficits, and Alzheimer's disease pathology including hippocampal amyloid plaques, tau paired-helical filaments, neuronal loss and microgliosis, in a progressive age-dependent manner that mimics the pathology observed in Alzheimer's disease patients. Following long-term treatment with ibudilast, transgenic rats were evaluated at 11 months of age for spatial memory performance and Alzheimer's disease pathology. We demonstrate that ibudilast-treatment of transgenic rats mitigated hippocampal-dependent spatial memory deficits, as well as hippocampal (hilar subregion) amyloid plaque and tau paired-helical filament load, and microgliosis compared to untreated transgenic rat. Neuronal density analyzed across all hippocampal regions was similar in ibudilast-treated transgenic compared to untreated transgenic rats. Interestingly, RNA Sequencing analysis of hippocampal tissue showed that ibudilast-treatment affects gene expression levels of the TLR and ubiquitin/Proteasome pathways differentially in male and female transgenic rats. Based on the TLR4 signaling pathway, our RNAsequencing data suggest that ibudilast-treatment inhibits IRAK1 activity by increasing expression of its negative regulator IRAK3, and/or by altering TRAF6 and Other TLR-related ubiquitin Ligase and conjugase levels. Our results support that ibudilast can serve as a repurposed drug that targets multiple pathways including TLR signaling and the ubiquitin/Proteasome pathway to reduce cognitive deficits and pathology relevant to Alzheimer's disease.

Keywords

TLR and ubiquitin-proteasome pathways; drug repurposing; machine learning; polypharmacology; systems pharmacology.

Figures
Products