Natural History studies are a type of clinical research that collect clinical health data and biological samples from people in real-world settings over time. These types of studies are crucial to advancing our understanding of amyotrophic lateral sclerosis (ALS), as the data and samples collected during Natural History studies provide researchers with the information they need to study how ALS develops and progresses. This can lead to faster diagnoses, more effective and targeted drug and treatment development, and future preventative treatments.

It is important to note that you can still join an interventional clinical trial even if you have joined an observational/natural history research study like the ARC Study or ALL ALS. Also, joining a natural history study does not exclude you from joining other natural history studies. We encourage participants, as they are able, to join multiple studies to help push research forward.

Among the longest-running natural history studies in ALS is the ALS Therapy Development Institute’s (ALS TDI) ALS Research Collaborative (ARC) study. Through the ARC Study, ALS TDI researchers partner with people with ALS and asymptomatic carriers of ALS-related genetic mutations from all over the world to gather comprehensive data, including whole genome sequencing, movement tracking, voice data, electronic health records, and survey data. However, ARC is not the only natural history study in ALS.

ALL ALS: “Access for ALL in ALS Consortium”

Another major study, launched in 2024, is ALL ALS. ALL ALS is a large U.S. consortium funded by the National Institutes of Health (NIH) that aims to create an expansive natural history study of ALS. It collects clinical, molecular, and digital data from people living with ALS, asymptomatic carriers of ALS-related genetic mutations, and control participants. 

Key features of the ALL ALS Consortium:

  • Study design: ALL ALS consists of two studies: ASSESS ALL ALS, which follows people living with ALS and people living without ALS (controls), and PREVENT ALL ALS, which follows people with genetic risk. The program aims to enroll over 2,000 participants across both studies by the end of 2026.
  • Geography/infrastructure: The consortium includes 36 Clinical Sites across the U.S. and Puerto Rico.. To expand accessibility, remote participation is available for all people living with ALS. 
  • Data & biospecimens: ALSFRS-R questionnaire, surveys (social determinants of health, environmental history, cognition, ALS impairment scale), slow vital capacity, speech assessments, handheld dynamometry, blood draws, and optional lumbar punctures.

Why it matters:
 ALS is a highly variable disease; onset and progression look different in everyone.  ALL ALS aims to collect and share data and samples to help researchers carry out critical research projects that will advance our understanding of ALS and develop more effective drugs and therapies. 

How ALS TDI Has Collaborated on ALL ALS

Dr. Fernando Vieira, CEO and Chief Scientific Officer at ALS TDI, and Alan Premasiri, Director of Clinical Research Operations at ALS TDI, worked with Dr. James Berry and the team at ALL ALS as they planned and outlined their study. They used insights and experience from the ARC Study to help plan and scale the program in a way that could be conducted around the country. 

Why Do We Need Multiple Natural History Studies in ALS

While studies like the ARC Study and ALL ALS may collect similar data, having multiple natural history studies in the same disease is important to ensure the reliability of future studies that utilize their data. Although the data is similar, it may be collected differently, meaning that people are rarely doing the same exact tasks twice, and having different methods allows researchers to test the pros and cons of different collection methods. In science, it is essential to be able to replicate the results of any study to make sure that the results are accurate. Even where these studies and datasets overlap, it can be important to have multiple sources of similar data available to researchers. When concluding an analysis of a large dataset, researchers can then run the same analysis on a different dataset and be even more confident in their conclusions if they achieve the same result. 

AMP ALS and the ALS Knowledge Portal

What is AMP ALS?
 AMP ALS (Accelerating Medicines Partnership for ALS) is part of a public-private partnership launched under the ACT for ALS Act (a U.S. law signed in late 2021). The goal is to accelerate the development of diagnostics, biomarkers, and therapies for ALS by improving collaboration, data sharing, and standardization among researchers, industry, regulators, and patient communities. The ALL ALS Consortium was created as part of the AMP ALS Initiative.

What is the ALS Knowledge Portal?
 The ALS Knowledge Portal is a central data storage and sharing platform that is managed by AMP ALS. The portal is designed to collect, harmonize, manage, and share clinical, molecular, biomarker, and other research data for ALS. It combines both new data (e.g.‑ the data collected through ALL ALS) with existing datasets to provide global access to researchers and support critical ALS research. 

  • The ALS Knowledge Portal currently includes over 5,000 files from 21 existing datasets.
  • These data are de‑identified, meaning that identifiable information, such as name, is removed from the data to protect the identities of research participants and prioritize secure data. 
  • The portal also supports features like cohort building and aims to make future data releases easier to integrate.

How These Programs Fit Together & Why It’s Important

  • Both the ARC Study and ALL ALS provide foundational data that feeds into ALS research. With large, well ‑curated, longitudinal natural history studies, researchers have enough high-quality data to support biomarker discovery, modeling disease trajectories, and improving trial designs.
  • By collecting and centralizing data through different portals, researchers aim to reduce duplicative data collection where possible, improve consistency, speed up discovery, and help in regulatory validation of biomarkers/outcome measures.
  • For people with ALS and those at risk of developing ALS, these efforts mean: earlier detection possibilities, a more precise understanding of how different ALS “types” progress, potentially more personalized therapies, and more efficient clinical trials.

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