Target ALS
Target ALS
Accelerate your Amyotrophic Lateral Sclerosis (ALS) research with the Target ALS Data Collection – a comprehensive ecosystem of integrated, critical resources provided with minimal restrictions. Overcome common research barriers by accessing standardized, well-characterized components designed to fuel discovery:
- Natural History Study (Longitudinal Biofluids Core): Leverage unique longitudinal biofluids (CSF, blood, urine) paired with deep clinical, genomic, and functional data collected from a diverse, actively enrolling cohort of ALS participants and healthy controls.
- Postmortem Tissue Core: Explore human Central Nervous System (CNS) tissue linked to rich clinical, histological, and multi-omic data for direct investigation of human pathology.
- Stem Cell Core: Utilize patient-derived induced Pluripotent Stem Cell (iPSC) lines (representing familial, sporadic, and control cases, including isogenic lines) for disease modeling and therapeutic screening
Integrate insights across these unique resources – tissue, cells, and longitudinal fluid/clinical data – to investigate ALS mechanisms, discover and validate novel biomarkers, and drive the development of effective treatments.
Partner datasets
Target ALS
Amyotrophic Lateral Sclerosis (ALS)
Datasets
Target ALS
Data Collection Time Frame
2016-Present
Participants
225*
Geographical Coverage
International
Usage Examples
- Investigating ALS pathophysiology using human postmortem tissue, patient-derived cell models (iPSCs), and longitudinal biofluid analysis
- Discovering and validating diagnostic, prognostic, progression, and pharmacodynamic biomarkers in biofluids (CSF, blood, urine)
- Identifying and validating novel therapeutic targets using multi-omics data across different biological sample types
- Modeling disease mechanisms and testing therapeutic efficacy (including gene therapies) in human iPSC-derived cells
- Understanding ALS heterogeneity and progression patterns by integrating clinical, functional, genetic, and molecular data over time across diverse populations
- Correlating clinical phenotypes with neuropathology or molecular signatures.
Data Modalities
Genomics
- Whole Genome Sequencing (WGS - Short and Long Read)
- Gene Mutation Status
Transcriptomics
- Bulk RNA Sequencing (RNA Seq)
- Spatial Transcriptomics
Proteomics
- Targeted Proteomics
- Untargeted Proteomics
- Protein Biomarker Assays
Clinical Data
- Clinical Assessments / Scales
- Demographics
- Medical History
- Clinical Laboratory Tests
Biosamples
- Blood (incl. Plasma, Serum, PBMCs)
- Cerebrospinal Fluid (CSF)
- Urine
- Postmortem Tissue
Derived Cellular Models
- iPSC Lines (Patient, Control, Isogenic)
Pathology
- Quantitative Pathology Data
Functional Measures
- Digital Biomarkers
Biomarkers
- Fluid Biomarker Levels (e.g., NfL)
Other / Contextual
- Environmental and Occupational History Questionnaire