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Alzheimer's 2030: From Precision Genomics to Artificial Intelligence.

Valeria D'Argenio1,2, Rossella Tomaiuolo3,4, Silvia Bargeri5

  • 1Department of Human Sciences and Quality of Life Promotion, San Raffaele Open University, Via di Val Cannuta 247, 00166 Rome, Italy.

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Summary

Alzheimer's disease (AD) risk is influenced by genetics and gender. Precision medicine needs to integrate genetic data, sex, and gender factors for effective prevention and treatment strategies.

Keywords:
Alzheimer’s DiseaseGWASartificial intelligencedata treatmentdigital healthethicsgenderneurogenomics

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Area of Science:

  • Neuroscience
  • Genetics
  • Public Health

Background:

  • Alzheimer's disease (AD) poses a growing global health challenge, with prevalence and costs projected to double.
  • While lifestyle factors are important, genetics significantly contribute to late-onset AD (40-80% heritability).
  • Sex and gender are critical risk determinants, with women disproportionately affected due to biological and sociocultural influences.

Purpose of the Study:

  • To review the impact of genetic and gender-related factors on Alzheimer's disease risk.
  • To explore the utility of genome-wide association studies (GWASs) and genetic risk scores (GRS) for precision genomics in AD.
  • To examine the role of Artificial Intelligence (AI) and digital health in personalized AD prevention.

Main Methods:

  • Review of large-scale genome-wide association studies (GWASs).
  • Analysis of genetic risk scores (GRS) for precision genomics.
  • Exploration of Artificial Intelligence (AI) applications in multimodal big data analysis.

Main Results:

  • Genetic factors significantly contribute to Alzheimer's disease heritability.
  • Genome-wide association studies (GWASs) are advancing genetic risk prediction.
  • Sex and gender significantly modulate AD risk, necessitating tailored approaches.

Conclusions:

  • A precision medicine approach for Alzheimer's disease must incorporate genetic, sex, and gender information.
  • Integrating AI and digital health tools can enhance personalized prevention strategies.
  • Ethical considerations regarding data privacy are paramount in developing new AD interventions.