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Updated: Jun 29, 2026

Real-Time Fluorescent Measurement of Synaptic Functions in Models of Amyotrophic Lateral Sclerosis
Published on: July 16, 2021
Development of a high-throughput microarray-based resequencing system for neurological disorders and its application
Yuji Takahashi1, Naomi Seki, Hiroyuki Ishiura
1Department of Neurology, Graduate School of Medicine, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan.
Background:
Comprehensive resequencing of the causative and disease-related genes of neurodegenerative diseases is expected to enable (1) comprehensive mutational analysis of familial cases, (2) identification of sporadic cases with de novo or low-penetrant mutations, (3) identification of rare variants conferring disease susceptibility, and ultimately (4) better understanding of the molecular basis of these diseases.
Objective:
To develop a microarray-based high-throughput resequencing system for the causative and disease-related genes of amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases.
Design:
Validation of the system was conducted in terms of the signal-to-noise ratio, accuracy, and throughput. Comprehensive gene analysis was applied for patients with ALS. Subjects Ten patients with familial ALS, 35 patients with sporadic ALS, and 238 controls.
Results:
The system detected point mutations with 100% accuracy and completed the resequencing of 270 kilobase pairs in 3 working days with greater than 99.9% accuracy of base calls, or the determination of base(s) at each position. Analysis of patients with familial ALS revealed 2 SOD1 mutations. Analysis of the 35 patients with sporadic ALS revealed a previously known SOD1 mutation, S134N, a novel putative pathogenic DCTN1 mutation, R997W, and 9 novel variants including 4 nonsynonymous heterozygous variants consisting of 2 in ALS2, 1 in ANG, and 1 in VEGF that were not found in the controls.
Conclusion:
The DNA microarray-based resequencing system is a powerful tool for high-throughput comprehensive analysis of causative and disease-related genes. It can be used to detect mutations in familial and sporadic cases and to identify numerous novel variants potentially associated with genetic risks.
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