Alzheimer’s 2030: From Precision Genomics to Artificial Intelligence

Alzheimer's disease (AD) represents a critical global health challenge, with its prevalence and associated costs expected to double significantly by 2030 and 2050. While lifestyle interventions are crucial, sporadic late-onset AD has a substantial genetic component (40-80% heritability), though known variants limit the scope of traditional precision medicine. Crucially, sex and gender are significant risk determinants, with women accounting for two-thirds of cases due to a complex interplay of biological and sociocultural factors. This review focuses on the influence of genetic and gender-related factors, examining large-scale genome-wide association studies (GWASs) and their role in developing advanced genetic risk scores (GRS) for precision genomics. We also explore the potential of Artificial Intelligence (AI) for multimodal big data analysis and digital health tools to promote personalized prevention and emerging concerns about ethics, privacy and data treatment. The convergence of these findings underscores the urgent need for a genetic-, sex- and gender-informed precision-medicine approach to AD.

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Publication Details

Journal
Genes
Published
2026-02-12
DOI
https://doi.org/10.3390/genes17020233
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
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article

Alzheimer’s 2030: From Precision Genomics to Artificial Intelligence

Rossella Tomaiuolo, Giulia Maria Sancesario, Silvia Bargeri, Valeria D’Argenio
Genes
Genetic Associations and Epidemiology
article

Alzheimer’s 2030: From Precision Genomics to Artificial Intelligence

Rossella Tomaiuolo, Giulia Maria Sancesario, Silvia Bargeri, Valeria D’Argenio
article en

Abstract

Alzheimer's disease (AD) represents a critical global health challenge, with its prevalence and associated costs expected to double significantly by 2030 and 2050. While lifestyle interventions are crucial, sporadic late-onset AD has a substantial genetic component (40-80% heritability), though known variants limit the scope of traditional precision medicine. Crucially, sex and gender are significant risk determinants, with women accounting for two-thirds of cases due to a complex interplay of biological and sociocultural factors. This review focuses on the influence of genetic and gender-related factors, examining large-scale genome-wide association studies (GWASs) and their role in developing advanced genetic risk scores (GRS) for precision genomics. We also explore the potential of Artificial Intelligence (AI) for multimodal big data analysis and digital health tools to promote personalized prevention and emerging concerns about ethics, privacy and data treatment. The convergence of these findings underscores the urgent need for a genetic-, sex- and gender-informed precision-medicine approach to AD.

GenesVol. 17(2)
Vita-Salute San Raffaele University (IT), San Raffaele University of Rome (IT), Istituto Clinico Sant'Ambrogio (IT), IRCCS Ospedale Galeazzi - Sant'Ambrogio (IT), CEINGE Biotecnologie Avanzate Franco Salvatore (Italy) (IT), European Brain Research Institute (IT), Fondazione Santa Lucia (IT)
Gender equality
Openalex Percentile: Top 56%
Genetic Associations and Epidemiology
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Alzheimer’s 2030: From Precision Genomics to Artificial Intelligence — Rossella Tomaiuolo, Giulia Maria Sancesario, et al. · Genes (2026) | TGRS Research Map | TGRS