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Basic Science and Pathogenesis.

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Artificial Intelligence and Machine Learning tools combined with genetic data identify new Alzheimer's disease (AD) drug targets. This approach revealed EPHX2 as a key target and identified existing drugs that may reduce AD incidence.

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Area of Science:

  • Genomics
  • Pharmacogenomics
  • Computational Biology

Background:

  • High-throughput sequencing has generated vast genetic data for Alzheimer's disease (AD), but translating these findings into treatments remains a challenge.
  • Lack of effective Artificial Intelligence (AI) and Machine Learning (ML) tools hinders the application of genetic discoveries in clinical practice.

Purpose of the Study:

  • To develop and apply AI/ML approaches, Mendelian randomization (MR), and integrated genomic data to identify druggable targets for AD.
  • To validate potential therapeutic targets and repurpose existing drugs for AD treatment.

Main Methods:

  • Utilized AI/ML, MR, and large-scale genetic/functional genomic data from eQTL and pQTL datasets across multiple brain regions.
  • Analyzed genome-wide association studies (GWAS) data from 275,540 AD cases and 1.55 million controls.
  • Employed AI-assisted drugome-wide association studies on ~80 million electronic health records to identify repurposable drugs.

Main Results:

  • Identified approximately 30 druggable genes with significant MR evidence, including epoxide hydrolase 2 (EPHX2) as a key anti-inflammatory target.
  • Validated EPHX2's protective role in AD through experimental studies in iPSC-derived neurons, showing reduced ptau181 and improved cognition in a mouse model with an EPHX2 inhibitor (EC5026).
  • Discovered 12 drugs, such as trazodone and baclofen, associated with reduced AD incidence in 111,680 mild cognitive impairment patients.

Conclusions:

  • AI/ML technologies integrating genetic and real-world patient data are effective in identifying therapeutic targets and medicines for AD.
  • Further functional and clinical validation in diverse populations is necessary for candidate targets and drugs.