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.
Stratification of amyotrophic lateral sclerosis patients
A crowdsourcing approach
Kueffner, R., Zach, N., Bronfeld, M., Norel, R., Atassi, N., Balagurusamy, V., Di Camillo, B., Chio, A., Cudkowicz, M., Dillenberger, D., Garcia-Garcia, J., Hardiman, O., Hoff, B., Knight, J., Leitner, M. L., Li, G., Mangravite, L., Norman, T., Wang, L., ... Stolovitzky, G. (2019). Stratification of amyotrophic lateral sclerosis patients: A crowdsourcing approach. Scientific Reports, 9(1), 690. . https://doi.org/10.1038/s41598-018-36873-4