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Artificial intelligence for dementia genetics and omics.

Conceicao Bettencourt1,2, Nathan Skene3,4, Sara Bandres-Ciga5

  • 1Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|August 22, 2023
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) offers new ways to analyze complex genetics and omics data for Alzheimer's disease and other dementias. AI helps tackle key challenges in dementia research, improving precision medicine approaches.

Keywords:
artificial intelligence, biomarkerspathology, causality, dementia, disease pathways, etiology, genetics, machine learning, omics, risk factors

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Area of Science:

  • Neuroscience
  • Genetics
  • Bioinformatics

Background:

  • Genetics and omics studies are crucial for understanding Alzheimer's disease (AD) and dementia subtypes.
  • Key challenges remain in dementia research, including missing heritability, identifying subtype-specific omics signatures, and discovering novel biomarkers.
  • Understanding the causal role of risk factors and the biological impact of genetic variations is essential.

Purpose of the Study:

  • To review the challenges in dementia genetics and omics research.
  • To explore the application of artificial intelligence (AI) and machine learning (ML) in addressing these challenges.
  • To highlight the potential of AI for advancing precision dementia medicine.

Main Methods:

  • Review of current challenges in dementia genetics and omics.
  • Exploration of AI and ML methodologies for analyzing high-dimensional data.
  • Discussion of best practices, limitations, and future directions for AI in dementia research.

Main Results:

  • AI and ML provide powerful tools to address critical challenges in dementia genetics and omics.
  • AI can uncover novel patterns and improve biomarker discovery for dementia subtypes.
  • The integration of AI with multidisciplinary research and diverse cohorts is key.

Conclusions:

  • AI approaches significantly enhance the interrogation of genetics and omics data for precision dementia medicine.
  • Addressing limitations and fostering collaborative, diverse research are vital for realizing AI's full potential.
  • AI-driven insights can accelerate the development of targeted therapies for dementia.