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Stratification of amyotrophic lateral sclerosis patients: A crowdsourcing approach

Lookup NU author(s): Dr Jaume Bacardit, Dr Nicola Lazzarini

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© The Author(s) 2019. 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.


Publication metadata

Author(s): 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 ML, Li G, Mangravite L, Norman T, Wang L, Xiao J, Fang W-C, Peng J, Yang C, Chang H-J, Stolovitzky G, Alkallas R, Anghel C, Avril J, Bacardit J, Balser B, Balser J, Bar-Sinai Y, Ben-David N, Ben-Zion E, Bliss R, Cai J, Chernyshev A, Chiang J-H, Chicco D, Corriveau BAN, Dai J, Deshpande Y, Desplats E, Durgin JS, Espiritu SMG, Fan F, Fevrier P, Fridley BL, Godzik A, Golinska A, Gordon J, Graw S, Guo Y, Herpelinck T, Hopkins J, Huang B, Jacobsen J, Jahandideh S, Jeon J, Ji W, Jung K, Karanevich A, Koestler DC, Kozak M, Kurz C, Lalansingh C, Larrieu T, Lazzarini N, Lerner B, Lesinski W, Liang X, Lin X, Lowe J, Mackey L, Meier R, Min W, Mnich K, Nahmias V, Noel-Macdonnell J, O'donnell A, Paadre S, Park J, Polewko-Klim A, Raghavan R, Rudnicki W, Saghapour E, Salomond J-B, Sankaran K, Sendorek D, Sharan V, Shiah Y-J, Sirois J-K, Sumanaweera DN, Usset J, Vang YS, Vens C, Wadden D, Wang D, Wong WC, Xie X, Xu Z, Yang H-T, Yu X, Zhang H, Zhang L, Zhang S, Zhu S

Publication type: Article

Publication status: Published

Journal: Scientific Reports

Year: 2019

Volume: 9

Online publication date: 24/01/2019

Acceptance date: 26/11/2018

Date deposited: 18/02/2019

ISSN (electronic): 2045-2322

Publisher: Nature Publishing Group

URL: https://doi.org/10.1038/s41598-018-36873-4

DOI: 10.1038/s41598-018-36873-4

PubMed id: 30679616


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