Research Approach

Enrollment

Answer ALS enrolled more than 1,100 participants in our landmark study, generating one of the largest collections of ALS data and biological samples ever shared openly with researchers worldwide. Although Answer ALS enrollment is currently closed, the rich, multi-omics data resource continues to grow through our Neuromine data portal.

We are actively adding new datasets from our partner ALS Research Collaborative (ARC) Study at the ALS Therapy Development Institute and from Champion Insights, a focused sub-study recruiting individuals with a higher incidence of ALS, including high-performance athletes, military personnel, and first responders. Together, these efforts ensure that scientists everywhere have access to an expanding, openly available foundation for discovery, driving progress toward treatments and a cure.

To learn more about the ALS Therapy Development Institute’s ARC Study: https://als.net/arc/

To learn more about Champion Insights: https://championinsights.org/

Data and Technology

In 2016, the Answer ALS team initiated the development of an innovative system designed to merge community data effectively and efficiently. This system integrates a wide range of information, including genomic data, clinical records, participant inputs, family medical histories, environmental data, and data from medical sensors like wearables.

Leveraging Advanced Technologies

Researchers using the Answer ALS dataset apply advanced data analytics and machine learning to uncover patterns and insights. This approach allows for more sensitive, specific, and efficient analyses as data volumes grow. By collaborating with community partners, Answer ALS ensures that data collection, processing, and secure storage stay ahead of our analytical capabilities.

Accessibility and Transparency in Data Analysis

To support transparency and accessibility, Answer ALS has made its data processing pipelines publicly available, including select workflows on the Galaxy platform. This platform supports both experienced bioinformaticians and experimental biologists, allowing them to execute computational analyses through a user-friendly graphical interface. Answer ALS is working to make its data processing pipelines more accessible by sharing them through platforms like GitHub and, where possible, Galaxy, an open source, web-based platform for data intensive biomedical research.

Impact and Collaboration

The data managed and analyzed by Answer ALS will underpin new clinical trials and assist in creating subgroups for more targeted drug discovery. It will also facilitate the identification of drug-responsive biomarkers and diagnostics. By sharing these insights, techniques, and processes, Answer ALS fosters a collaborative research ecosystem. The insights derived will not only generate testable hypotheses and new conceptual frameworks but also illuminate disease mechanisms and support novel therapeutic approaches.

Multi-Omics and Robotic Imaging for ALS Research

Genomics

We analyze the entire genome to understand the DNA sequences that underpin motor neuron function and disease progression. This foundational study helps us grasp the genetic basis of ALS.

Transcriptomics

By studying RNA transcripts through RNA-Seq, we track how genetic instructions are turned into RNA, revealing the active genetic information in motor neurons that influences ALS.

Epigenomics

Using ATAC-Seq, we explore how gene expression is regulated by environmental and lifestyle factors through changes in the epigenome, identifying key regulatory elements that contribute to ALS.

Proteomics

We employ SWATH-MS to study the full range of proteins produced by motor neurons, comparing protein expressions in ALS patients to those in healthy controls to identify disease-specific proteins.

Metabolomics

Through mass spectrometry, we analyze the metabolites in motor neurons to detect unique chemical fingerprints that differentiate ALS patients from healthy individuals, providing insights into the metabolic disruptions caused by ALS.

Robotic Imaging

Our use of automated robotic microscopy allows for the detailed tracking and analysis of live neurons, assessing changes over time to link cellular behavior with ALS progression. This dynamic imaging helps build predictive models of disease development and potential therapeutic responses.

Integrated Approach for Precision Medicine

By integrating data from genomics, transcriptomics, epigenomics, proteomics, metabolomics, and robotic imaging, Answer ALS offers a comprehensive view of ALS pathology. This approach deepens our understanding of the disease mechanisms and aids in identifying new targets for treatment, advancing towards personalized medicine strategies for ALS.

Induced Pluripotent Stem Cells (iPSCs) & Motor Neurons in Answer ALS Research

The Answer ALS Research Project has created nearly 1,000 unique stem cell lines from ALS patients and over 100 healthy controls. By transforming these iPSCs into brain and spinal cord cells, the project models ALS on a broad scale, facilitating a deeper understanding of the disease’s mechanisms across its various forms.

This extensive data collection serves as one of the most comprehensive repositories of chemical, clinical, genetic, and biological data in the history of ALS research. It forms the basis for defining patient subgroups, understanding disease pathways, and identifying potential new treatments and biomarkers.

Process Overview

Sample Collection and Processing: Blood samples from participants were anonymized and sent to Dr. Clive Svendsen’s laboratory at Cedars-Sinai. Here, peripheral blood mononuclear cells (PBMCs) have been reprogrammed into iPSCs.

Neuronal Differentiation: These iPSCs have been differentiated into motor neurons—the cell type primarily affected in ALS. This transformation is optimized to increase efficiency and yield, enabling the production of motor neurons at a rate suitable for large-scale analysis.

Scaling and Optimization: Traditionally, generating multiple iPSC and motor neuron lines is standard for laboratories. However, the Svendsen Lab has adapted to process dozens of samples simultaneously, significantly scaling up operations to meet the demands of the Answer ALS project.

Impact and Access

This work advances our understanding of ALS and supports ongoing big data and omics studies. Researchers interested in accessing these iPSC lines can find more information and order through Cedars-Sinai’s dedicated biomanufacturing page: Cedars-Sinai iPSC.

What is an iPSC?

Induced pluripotent stem cells, developed from adult blood cells, can differentiate into any cell type in the body. This technology, pioneered by Shinya Yamanaka in 2006, involves reprogramming adult cells by introducing specific transcription factors. iPSCs are invaluable for studying ALS as they allow for endless propagation and provide a personalized model to investigate the variability in disease progression among patients.