TY - JOUR
T1 - Identification of Therapeutic Targets for Amyotrophic Lateral Sclerosis Using PandaOmics – An AI-Enabled Biological Target Discovery Platform
AU - Pun, Frank W.
AU - Liu, Bonnie Hei Man
AU - Long, Xi
AU - Leung, Hoi Wing
AU - Leung, Geoffrey Ho Duen
AU - Mewborne, Quinlan T.
AU - Gao, Junli
AU - Shneyderman, Anastasia
AU - Ozerov, Ivan V.
AU - Wang, Ju
AU - Ren, Feng
AU - Aliper, Alexander
AU - Bischof, Evelyne
AU - Izumchenko, Evgeny
AU - Guan, Xiaoming
AU - Zhang, Ke
AU - Lu, Bai
AU - Rothstein, Jeffrey D.
AU - Cudkowicz, Merit E.
AU - Zhavoronkov, Alex
N1 - Publisher Copyright:
Copyright © 2022 Pun, Liu, Long, Leung, Leung, Mewborne, Gao, Shneyderman, Ozerov, Wang, Ren, Aliper, Bischof, Izumchenko, Guan, Zhang, Lu, Rothstein, Cudkowicz and Zhavoronkov.
PY - 2022/6/28
Y1 - 2022/6/28
N2 - 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.
AB - 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.
KW - artificial intelligence
KW - multi-omics
KW - target discovery
KW - target novelty
KW - time machine
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UR - http://www.scopus.com/inward/citedby.url?scp=85133895189&partnerID=8YFLogxK
U2 - 10.3389/fnagi.2022.914017
DO - 10.3389/fnagi.2022.914017
M3 - Article
AN - SCOPUS:85133895189
SN - 1663-4365
VL - 14
JO - Frontiers in Aging Neuroscience
JF - Frontiers in Aging Neuroscience
M1 - 914017
ER -