Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research.
16S harmonization
DREAM challenge
crowdsourced
machine learning
microbiome
predictive modeling
preterm birth
vaginal microbiome
Journal
Cell reports. Medicine
ISSN: 2666-3791
Titre abrégé: Cell Rep Med
Pays: United States
ID NLM: 101766894
Informations de publication
Date de publication:
21 Dec 2023
21 Dec 2023
Historique:
received:
28
03
2023
revised:
15
09
2023
accepted:
01
12
2023
medline:
23
12
2023
pubmed:
23
12
2023
entrez:
22
12
2023
Statut:
aheadofprint
Résumé
Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource models to predict (1) preterm birth (PTB; <37 weeks) or (2) early preterm birth (ePTB; <32 weeks) from 9 vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from public raw data via phylogenetic harmonization. The predictive models are validated on two independent unpublished datasets representing 331 samples from 148 pregnant individuals. The top-performing models (among 148 and 121 submissions from 318 teams) achieve area under the receiver operator characteristic (AUROC) curve scores of 0.69 and 0.87 predicting PTB and ePTB, respectively. Alpha diversity, VALENCIA community state types, and composition are important features in the top-performing models, most of which are tree-based methods. This work is a model for translation of microbiome data into clinically relevant predictive models and to better understand preterm birth.
Identifiants
pubmed: 38134931
pii: S2666-3791(23)00567-0
doi: 10.1016/j.xcrm.2023.101350
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
101350Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interests S.V.L. is a board member at, holds stock in, and consults for Siolta Therapeutics. She also consults for the Atria Academy of Science and Medicine and for Sanofi. J.C.C. is co-founder of PrecisionProfile and OncoRx Insights. N.Aghaeepour. is a member of the scientific advisory boards of January AI, Parallel Bio, Celine Therapeutics, and WellSim Biomedical Technologies and is a paid consultant for Mara BioSystems. J.G. and M.S. have filed a patent related to the phylotype generation process.