Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach

Kueffner, Robert; García-García, Javier, 1982-; Stolovitzky, Gustavo

doi:http://dx.doi.org/10.1038/s41598-018-36873-4

Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach

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Kueffner R, Zach N, Bronfeld M, Norel R, Atassi N, Balagurusamy V et al. Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach. Sci Rep. 2019; 9(1):690. DOI: 10.1038/s41598-018-36873-4

Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease where substantial heterogeneity in clinical presentation urgently requires a better stratification of patients for the development of drug trials and clinical care. In this study we explored stratification through a crowdsourcing approach, the DREAM Prize4Life ALS Stratification Challenge. Using data from >10,000 patients from ALS clinical trials and 1479 patients from community-based patient registers, more than 30 teams developed new approaches for machine learning and clustering, outperforming the best current predictions of disease outcome. We propose a new method to integrate and analyze patient clusters across methods, showing a clear pattern of consistent and clinically relevant sub-groups of patients that also enabled the reliable classification of new patients. Our analyses reveal novel insights in ALS and describe for the first time the potential of a crowdsourcing to uncover hidden patient sub-populations, and to accelerate disease understanding and therapeutic development.