Department
Biomedical Sciences
Document Type
Article
Publication Title
Bioinformatics
ISSN
1367-4803
Volume
35
Issue
1
DOI
10.1093/bioinformatics/bty537
First Page
95
Last Page
103
Publication Date
1-1-2019
Abstract
Motivation Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia. Results We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified. Availability and implementation Datasets and scripts for reproduction of results are available through: Https://nalab.stanford.edu/multiomics-pregnancy/.
Recommended Citation
Ghaemi, M. S.,
DiGiulio, D. B.,
Contrepois, K.,
Callahan, B.,
Ngo, T. T.,
Lee-Mcmullen, B.,
Lehallier, B.,
Robaczewska, A.,
McIlwain, D.,
Rosenberg-Hasson, Y.,
Wong, R. J.,
Quaintance, C.,
Culos, A.,
Stanley, N.,
Tanada, A.,
Tsai, A.,
Gaudilliere, D.,
Ganio, E.,
Han, X.,
Ando, K.,
McNeil, L.,
Tingle, M.,
Wise, P.,
Maric, I.,
Sirota, M.,
Wyss-Coray, T.,
Winn, V. D.,
Druzin, M. L.,
&
Gibbs, R. S.
(2019).
Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy.
Bioinformatics, 35(1), 95–103.
DOI: 10.1093/bioinformatics/bty537
https://scholarlycommons.pacific.edu/dugoni-facarticles/719
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
