A machine-learning program has revealed the genes that are responsible for the sex-specific variations in Alzheimer’s progression.
Alzheimer’s (AD) disease is a neurodegenerative disorder with both genetic and environmental causes. The female brain atrophy and cognitive decline is faster than the male counterpart, while male mortality rates are higher. Researchers at Baylor College of Medicine and Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital discovered sex specific genes and molecular pathway that contributed to the progression of the condition. The study was published by Nature Communications.
We have developed a machine-learning program that uses a computationally advanced predictive metric, called the evolutionary action score (EA), as a feature, to identify genetic factors which influence AD risk in both males and women,\” said Dr. Olivier Lichtarge. This approach allows us to exploit a large amount of evolutionary data quickly, allowing us to probe smaller cohorts with greater accuracy and identify genes that are involved in sex specific differences in AD.
EAML is a computational ensemble that uses nine machine-learning algorithms to assess the impact of nonsynonymous coding variations, which are defined as DNA mutations affecting the structure and function resulting in a protein. It also estimates the deleterious effects of these variants on biological processes by using the evolutionary action score (EA).
Source:
https://medicalxpress.com/news/2023-05-machine-learning-reveals-genes-responsible-sex-specific.html
