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Machine learning suggests polygenic contribution to cognitive dysfunction in amyotrophic lateral sclerosis (ALS)
[article]
2019
medRxiv
pre-print
Amyotrophic lateral sclerosis (ALS) is a multi-system disorder characterized by progressive muscular weakness and, in addition, cognitive/behavioral dysfunction in nearly 50% of patients. The mechanisms underlying risk for cognitive dysfunction, however, remain elusive. Using sparse canonical correlation analysis (sCCA), an unsupervised machine-learning technique, we observed that 26 single nucleotide polymorphisms collectively associate with baseline cognitive performance in 330 ALS patients
doi:10.1101/2019.12.23.19014407
fatcat:xxf6px3bz5hgpgrkzh7iscygmm