Unraveling Sex-Specific Alzheimer’s Factors with AI

A new study employs ‘Evolutionary Action Machine Learning’ (EAML) to explore sex-specific genes that contribute to Alzheimer’s Disease (AD). Researchers discovered 98 genes associated with AD, some of which were found to affect disease progression differently in men and women.

Alzheimer’s Disease (AD) is a complex neurodegenerative condition influenced by genetic and environmental factors. Recent research by Baylor College of Medicine and the Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital reveals sex-specific genes and molecular pathways associated with AD development. Using the Evolutionary Action Machine Learning (EAML) method, the study identifies 98 genes linked to AD. Fruit fly models validate the genes’ impact on neurodegeneration caused by tau and Aβ42 proteins. Separate analyses for males and females identify 157 and 127 AD-associated genes, respectively, with stronger connections to known AD genes. The findings suggest potential connections between AD and breast cancer. EAML’s predictive capability remains robust even with smaller sample sizes. The study highlights the importance of sex-specific analyses for personalized AD treatments.

Original article in NeuroSciencesNews

Author: Neurologica

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