Unlocking New Therapeutic Targets for ALS with AI-Enabled Platform

Published on June 28, 2022

Imagine you have a treasure map, but instead of X marking the spot, it’s AI technology pointing out potential targets for treating a devastating neurodegenerative disease. That’s exactly what researchers did with PandaOmics, an AI-driven platform, to identify therapeutic candidates for amyotrophic lateral sclerosis (ALS). By analyzing expression profiles of CNS samples and iPSC-derived motor neurons, they discovered 17 high-confidence and 11 novel targets. These findings open up new opportunities for intervening in ALS and shedding light on its pathophysiology. Not only that, but the study also tested some proposed targets in a Drosophila model and found 8 previously unknown genes that could potentially rescue eye neurodegeneration. The dysregulated pathways identified from the data give insight into different stages of disease development. With AI speeding up the discovery process, scientists are definitely onto something big! To learn more about this groundbreaking research and dive deeper into the science behind it, check out the article on ALS.AI.

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease with ill-defined pathogenesis, calling for urgent developments of new therapeutic regimens. Herein, we applied PandaOmics, an AI-driven target discovery platform, to analyze the expression profiles of central nervous system (CNS) samples (237 cases; 91 controls) from public datasets, and direct iPSC-derived motor neurons (diMNs) (135 cases; 31 controls) from Answer ALS. Seventeen high-confidence and eleven novel therapeutic targets were identified and will be released onto ALS.AI (http://als.ai/). Among the proposed targets screened in the c9ALS Drosophila model, we verified 8 unreported genes (KCNB2, KCNS3, ADRA2B, NR3C1, P2RY14, PPP3CB, PTPRC, and RARA) whose suppression strongly rescues eye neurodegeneration. Dysregulated pathways identified from CNS and diMN data characterize different stages of disease development. Altogether, our study provides new insights into ALS pathophysiology and demonstrates how AI speeds up the target discovery process, and opens up new opportunities for therapeutic interventions.

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