A new study shows artificial intelligence (AI) analysis of blood samples can predict and explain disease progression.
Scientists behind the work claim this could help inform more appropriate and effective treatments for patients.
An AI algorithm was used to analyse the blood and post-mortem brain samples of 1969 patients with Alzheimer’s and Huntington’s diseases. The goal was to find molecular patterns specific to these diseases.
The algorithm was able to detect how these patients’ genes expressed themselves in unique ways over decades.
It is claimed that this offers the first long-term view of molecular changes underlying neurodegeneration – an important accomplishment because neurodegenerative diseases develop over years.
Previous studies of neurodegeneration often used static or “snapshot” data, and are therefore limited in how much they can reveal about the typically slow progression of disease.
This study aimed to uncover the chronological information contained in large-scale data by covering decades of disease progression, revealing how changes in gene expression over that time are related to changes in the patient’s condition.
Furthermore, the blood test detected 85-90% of the top predictive molecular pathways that the test of post-mortem brain data did, showing a striking similarity between molecular alterations in both the brain and peripheral body.
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