Identifying patterns in amyotrophic lateral sclerosis progression from sparse longitudinal data

Answer ALS, Pooled Resource Open-Access ALS Clinical Trials Consortium, ALS/MND Natural History Consortium

Research output: Contribution to journalArticlepeer-review

Abstract

The clinical presentation of amyotrophic lateral sclerosis (ALS), a fatal neurodegenerative disease, varies widely across patients, making it challenging to determine if potential therapeutics slow progression. We sought to determine whether there were common patterns of disease progression that could aid in the design and analysis of clinical trials. We developed an approach based on a mixture of Gaussian processes to identify clusters of patients sharing similar disease progression patterns, modeling their average trajectories and the variability in each cluster. We show that ALS progression is frequently nonlinear, with periods of stable disease preceded or followed by rapid decline. We also show that our approach can be extended to Alzheimer’s and Parkinson’s diseases. Our results advance the characterization of disease progression of ALS and provide a flexible modeling approach that can be applied to other progressive diseases.

Original languageEnglish (US)
Pages (from-to)605-616
Number of pages12
JournalNature Computational Science
Volume2
Issue number9
DOIs
StatePublished - Sep 2022

Bibliographical note

Funding Information:
Data used in the preparation of this article were obtained from the PRO-ACT database, the ALS/MND Natural History Consortium, the Parkinson’s Progression Markers Initiative database and the ADNI database. This research includes the National Institute of Neurologic Disease and Stroke’s Archived Clinical Research data (Clinical Trial of Ceftriaxone in ALS, M. Cudkowicz, Massachusetts General Hospital) obtained from the NINDS Archived Clinical Research Datasets webpage. Additional information about the studies can be found in . The Answer ALS organization, ALS Finding a Cure and Packard Foundation supported the collection of the Answer ALS clinical dataset used in the manuscript. The Muscular Dystrophy Association contributed funding to the Emory ALS Clinic database that was included in this research. C.N.F. received funding from the Department of Veterans Affairs of Research and Development (IK2CX001595-02) and the Department of Defense (AL200156). K. Sachs received funding from the Muscular Dystrophy Association (award 574137). D.R. received funding from the NSF Gradate Research Fellowship Program (GRFP) and Siebel Scholars Fellowship. E.F. and D.R. received funding from Answer ALS, MIT–IBM Watson AI Lab (W1771646), the United States Army Medical Research Acquisition Activity (W81XWH-21-1-0245) and NIH (U54NS091046). T.M.H. received funding from the NIH/NINDS (K23NS099380). None of the organizations had any influence on the writing of the manuscript or the decision to submit it for publication.

Funding Information:
Data used in the preparation of this article were obtained from the PRO-ACT database, the ALS/MND Natural History Consortium, the Parkinson’s Progression Markers Initiative database and the ADNI database. This research includes the National Institute of Neurologic Disease and Stroke’s Archived Clinical Research data (Clinical Trial of Ceftriaxone in ALS, M. Cudkowicz, Massachusetts General Hospital) obtained from the NINDS Archived Clinical Research Datasets webpage. Additional information about the studies can be found in Supplementary Acknowledgements. The Answer ALS organization, ALS Finding a Cure and Packard Foundation supported the collection of the Answer ALS clinical dataset used in the manuscript. The Muscular Dystrophy Association contributed funding to the Emory ALS Clinic database that was included in this research. C.N.F. received funding from the Department of Veterans Affairs of Research and Development (IK2CX001595-02) and the Department of Defense (AL200156). K. Sachs received funding from the Muscular Dystrophy Association (award 574137). D.R. received funding from the NSF Gradate Research Fellowship Program (GRFP) and Siebel Scholars Fellowship. E.F. and D.R. received funding from Answer ALS, MIT–IBM Watson AI Lab (W1771646), the United States Army Medical Research Acquisition Activity (W81XWH-21-1-0245) and NIH (U54NS091046). T.M.H. received funding from the NIH/NINDS (K23NS099380). None of the organizations had any influence on the writing of the manuscript or the decision to submit it for publication.

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.

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