Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy
| Autor: | Ghaemi, Mohammad Sajjad, DiGiulio, Daniel B, Contrepois, Kévin, Callahan, Benjamin, Ngo, Thuy T M, Lee-McMullen, Brittany, Lehallier, Benoit, Robaczewska, Anna, Mcilwain, David, Rosenberg-Hasson, Yael, Wong, Ronald J, Quaintance, Cecele, Culos, Anthony, Stanley, Natalie, Tanada, Athena, Tsai, Amy, Gaudilliere, Dyani, Ganio, Edward, Han, Xiaoyuan, Ando, Kazuo, McNeil, Leslie, Tingle, Martha, Wise, Paul, Maric, Ivana, Sirota, Marina, Wyss-Coray, Tony, Winn, Virginia D, Druzin, Maurice L, Gibbs, Ronald, Darmstadt, Gary L, Lewis, David B, Partovi Nia, Vahid, Agard, Bruno, Tibshirani, Robert, Nolan, Garry, Snyder, Michael P, Relman, David A, Quake, Stephen R, Shaw, Gary M, Stevenson, David K, Angst, Martin S, Gaudilliere, Brice, Aghaeepour, Nima |
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| Přispěvatelé: | Wren, Jonathan |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Pediatric
Proteome Bioinformatics Contraception/Reproduction Systems Biology Microbiota Computational Biology Reproductive health and childbirth Perinatal Period - Conditions Originating in Perinatal Period Biological Sciences Low Birth Weight and Health of the Newborn Original Papers Mathematical Sciences Good Health and Well Being Preterm Pregnancy Information and Computing Sciences Infant Mortality Metabolome Humans Female Transcriptome Biotechnology |
| Zdroj: | Bioinformatics Bioinformatics (Oxford, England), vol 35, iss 1 |
| ISSN: | 1367-4811 1367-4803 |
| Popis: | 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/. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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