Scientists at Cedars-Sinai report they have developed a new resource to help identify new subtypes of amyotrophic lateral sclerosis (ALS). The web-based tool is part of a collaborative effort with more than 100 scientists called Answer ALS, which includes biological and clinical data from more than 1,000 ALS patients. The information is intended to help investigators across the globe better understand ALS, also known as Lou Gehrig’s disease.

Their findings are published in Nature Neurosciences in a paper titled, “Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines.”

“Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons, and longitudinal clinical and smartphone data from over 1,000 patients with ALS,” the researchers wrote. “This resource provides population-level biological and clinical data that may be employed to identify clinical–molecular–biochemical subtypes of ALS.”

“This is one of the largest resources for ALS samples in the world,” explained Clive Svendsen, PhD, executive director of the Cedars-Sinai Board of Governors Regenerative Medicine Institute, a co-author of the paper, and co-director of the Answer ALS program. “It’s a critical step forward in finding new treatments for a very complex disease that has really no effective treatments available.”

Discovering new subtypes of ALS can provide clues to how an individual may respond to treatment.

“We don’t think ALS is one disease,” said Svendsen, who is also a professor of biomedical sciences and medicine. “It’s very complex and we think there are different subtypes that can be targeted differently. We just need to uncover them.”

To successfully build the database, scientists first had to create a model of the disease that could be used to help study how ALS develops. Creating models of neurodegenerative diseases has been notoriously challenging because of the lack of reliable animal models or patient samples at early disease stages.

To overcome this issue, the investigators used iPSCs, which can be deployed to produce any type of cell in the body and at any stage of development. The team then converted these stem cells into the neurons of the spinal cord that die in ALS, essentially a personalized neural biopsy. These were then analyzed using the latest molecular techniques, which gave the team the ability to look for proteins that may have been affected in the disease.

“Proteomics is one of the most powerful tools we have to really look at the protein content of a cell, providing us insight into attractive treatment targets,” said Jennifer Van Eyk, PhD, professor of cardiology, biomedical sciences and pathology and laboratory medicine, and a study author who led the proteomics analysis.

“Creating this many iPS cell lines and generating neurons from them has never been done at this scale before,” said Sareen, who is also an associate professor of biomedical sciences. “We hope this platform will allow us to dive more deeply into the mechanisms leading to ALS. Furthermore, we can now provide these patient cells to the entire research community through our repository.”

All of the data is continually being collected and deposited into an online, open-source portal, where scientists can download all the data from every sample.

“This was a huge collaborative effort, and we hope the information we collected will help lead to the discovery of new molecular subtypes of ALS. With this knowledge we may at last be able to develop drugs targeted to these subtypes, laying the groundwork for new and improved therapies,” Svendsen said.

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